Author: Neville Li <neville@spotify.com>
Closes#1006 from nevillelyh/gh/SPARK-2067 and squashes the following commits:
9ee64cf [Neville Li] [SPARK-2067] use relative path for Spark logo in UI
Adding a paragraph clarifying a weird behavior in RangePartitioner.
See also #549.
Author: Reynold Xin <rxin@apache.org>
Closes#1012 from rxin/partitioner-doc and squashes the following commits:
6f0109e [Reynold Xin] SPARK-1628 follow up: Improve RangePartitioner's documentation.
JIRA: https://issues.apache.org/jira/browse/SPARK-1628
Added `hashCode` in HashPartitioner, RangePartitioner, PythonPartitioner and PageRankUtils.CustomPartitioner.
Author: zsxwing <zsxwing@gmail.com>
Closes#549 from zsxwing/SPARK-1628 and squashes the following commits:
2620936 [zsxwing] SPARK-1628: Add missing hashCode methods in Partitioner subclasses
Author: Neville Li <neville@spotify.com>
Closes#992 from nevillelyh/master and squashes the following commits:
3011739 [Neville Li] [SPARK-2056] Set RDD name to input path
The current implementation reads one key with the next hash code as it finishes reading the keys with the current hash code, which may cause it to miss some matches of the next key. This can cause operations like join to give the wrong result when reduce tasks spill to disk and there are hash collisions, as values won't be matched together. This PR fixes it by not reading in that next key, using a peeking iterator instead.
Author: Matei Zaharia <matei@databricks.com>
Closes#986 from mateiz/spark-2043 and squashes the following commits:
0959514 [Matei Zaharia] Added unit test for having many hash collisions
892debb [Matei Zaharia] SPARK-2043: don't read a key with the next hash code in ExternalAppendOnlyMap, instead use a buffered iterator to only read values with the current hash code.
DAGScheduler supports pluggable clock like what TaskSetManager does.
Author: CrazyJvm <crazyjvm@gmail.com>
Closes#976 from CrazyJvm/clock and squashes the following commits:
6779a4c [CrazyJvm] Use pluggable clock in DAGSheduler
https://issues.apache.org/jira/browse/SPARK-1677
For compatibility with older versions of Spark it would be nice to have an option `spark.hadoop.validateOutputSpecs` (default true) for the user to disable the output directory existence checking
Author: CodingCat <zhunansjtu@gmail.com>
Closes#947 from CodingCat/SPARK-1677 and squashes the following commits:
7930f83 [CodingCat] miao
c0c0e03 [CodingCat] bug fix and doc update
5318562 [CodingCat] bug fix
13219b5 [CodingCat] allow user to disable output dir existence checking
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#974 from ueshin/issues/SPARK-2029 and squashes the following commits:
e19e8f4 [Takuya UESHIN] Bump version number to 1.1.0-SNAPSHOT.
In Hadoop trunk (currently Hadoop 3.0.0), the deprecated
FSDataOutputStream#sync() method has been removed. Instead, we should
call FSDataOutputStream#hflush, which does the same thing as the
deprecated method used to do.
Author: Colin McCabe <cmccabe@cloudera.com>
Closes#898 from cmccabe/SPARK-1518 and squashes the following commits:
752b9d7 [Colin McCabe] FileLogger: Fix compile against Hadoop trunk
I'd like to use randomSplit through the Java API, and would like to add a convenience wrapper for this method to JavaRDD. This is fairly trivial. (In fact, is the intent that JavaRDD not wrap every RDD method? and that sometimes users should just use JavaRDD.wrapRDD()?)
Along the way, I added tests for it, and also touched up the Java API test style and behavior. This is maybe the more useful part of this small change.
Author: Sean Owen <sowen@cloudera.com>
Author: Xiangrui Meng <meng@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Xiangrui Meng <meng@databricks.com>
Closes#919 from srowen/SPARK-1973 and squashes the following commits:
148cb7b [Sean Owen] Some final Java test polish, while we are at it
1fc3f3e [Xiangrui Meng] more cleaning on Java 8 tests
9ebc57f [Sean Owen] Use accumulator instead of temp files to test foreach
5efb0be [Sean Owen] Add Java randomSplit, and unit tests (including for sample)
5dcc158 [Sean Owen] Simplified Java 8 test with new language features, and fixed the name of MLB's greatest team
91a1769 [Sean Owen] Touch up minor style issues in existing Java API suite test
RDD.zip() will throw an exception if it finds partition sizes are not the same.
Author: Kan Zhang <kzhang@apache.org>
Closes#944 from kanzhang/SPARK-1817 and squashes the following commits:
c073848 [Kan Zhang] [SPARK-1817] Cosmetic updates
524c670 [Kan Zhang] [SPARK-1817] RDD.zip() should verify partition sizes for each partition
The update to Mesos 0.18 caused some deprecation warnings in the build. The change to the non-deprecated version is straightforward as it emulates what the Mesos driver does with the deprecated method anyway (c5aa1dd221/src/sched/sched.cpp (L1354))
Author: Sean Owen <sowen@cloudera.com>
Closes#920 from srowen/SPARK-1806 and squashes the following commits:
8d76b6a [Sean Owen] Use non-deprecated methods in Mesos 0.18
I also corrected some errors made in the previous HLL count approximate API, including relativeSD wasn't really a measure for error (and we used it to test error bounds in test results).
Author: Reynold Xin <rxin@apache.org>
Closes#897 from rxin/hll and squashes the following commits:
4d83f41 [Reynold Xin] New error bound and non-randomness.
f154ea0 [Reynold Xin] Added a comment on the value bound for testing.
e367527 [Reynold Xin] One more round of code review.
41e649a [Reynold Xin] Update final mima list.
9e320c8 [Reynold Xin] Incorporate code review feedback.
e110d70 [Reynold Xin] Merge branch 'master' into hll
354deb8 [Reynold Xin] Added comment on the Mima exclude rules.
acaa524 [Reynold Xin] Added the right exclude rules in MimaExcludes.
6555bfe [Reynold Xin] Added a default method and re-arranged MimaExcludes.
1db1522 [Reynold Xin] Excluded util.SerializableHyperLogLog from MIMA check.
9221b27 [Reynold Xin] Merge branch 'master' into hll
88cfe77 [Reynold Xin] Updated documentation and restored the old incorrect API to maintain API compatibility.
1294be6 [Reynold Xin] Updated HLL+.
e7786cb [Reynold Xin] Merge branch 'master' into hll
c0ef0c2 [Reynold Xin] SPARK-1941: Update streamlib to 2.7.0 and use HyperLogLogPlus instead of HyperLogLog.
This PR adds support for specifying custom storage levels for the vertices and edges of a graph. This enables GraphX to handle graphs larger than memory size by specifying MEMORY_AND_DISK and then repartitioning the graph to use many small partitions, each of which does fit in memory. Spark will then automatically load partitions from disk as needed.
The user specifies the desired vertex and edge storage levels when building the graph by passing them to the graph constructor. These are then stored in the `targetStorageLevel` attribute of the VertexRDD and EdgeRDD respectively. Whenever GraphX needs to cache a VertexRDD or EdgeRDD (because it plans to use it more than once, for example), it uses the specified target storage level. Also, when the user calls `Graph#cache()`, the vertices and edges are persisted using their target storage levels.
In order to facilitate propagating the target storage levels across VertexRDD and EdgeRDD operations, we remove raw calls to the constructors and instead introduce the `withPartitionsRDD` and `withTargetStorageLevel` methods.
I tested this change by running PageRank and triangle count on a severely memory-constrained cluster (1 executor with 300 MB of memory, and a 1 GB graph). Before this PR, these algorithms used to fail with OutOfMemoryErrors. With this PR, and using the DISK_ONLY storage level, they succeed.
Author: Ankur Dave <ankurdave@gmail.com>
Closes#946 from ankurdave/SPARK-1991 and squashes the following commits:
ce17d95 [Ankur Dave] Move pickStorageLevel to StorageLevel.fromString
ccaf06f [Ankur Dave] Shadow members in withXYZ() methods rather than using underscores
c34abc0 [Ankur Dave] Exclude all of GraphX from compatibility checks vs. 1.0.0
c5ca068 [Ankur Dave] Revert "Exclude all of GraphX from binary compatibility checks"
34bcefb [Ankur Dave] Exclude all of GraphX from binary compatibility checks
6fdd137 [Ankur Dave] [SPARK-1991] Support custom storage levels for vertices and edges
When we need to read a compressed block, we will first create a compress stream instance(LZF or Snappy) and use it to wrap that block.
Let's say a reducer task need to read 1000 local shuffle blocks, it will first prepare to read that 1000 blocks, which means create 1000 compression stream instance to wrap them. But the initialization of compression instance will allocate some memory and when we have many compression instance at the same time, it is a problem.
Actually reducer reads the shuffle blocks one by one, so we can do the compression instance initialization lazily.
Author: Wenchen Fan(Cloud) <cloud0fan@gmail.com>
Closes#860 from cloud-fan/fix-compress and squashes the following commits:
0924a6b [Wenchen Fan(Cloud)] rename 'doWork' into 'getIterator'
07f32c2 [Wenchen Fan(Cloud)] move the LazyProxyIterator to dataDeserialize
d80c426 [Wenchen Fan(Cloud)] remove empty lines in short class
2c8adb2 [Wenchen Fan(Cloud)] add inline comment
8ebff77 [Wenchen Fan(Cloud)] fix compress memory issue during reduce
stop resetting spark.driver.port in unit tests (scala, java and python).
Author: Syed Hashmi <shashmi@cloudera.com>
Author: CodingCat <zhunansjtu@gmail.com>
Closes#943 from syedhashmi/master and squashes the following commits:
885f210 [Syed Hashmi] Removing unnecessary file (created by mergetool)
b8bd4b5 [Syed Hashmi] Merge remote-tracking branch 'upstream/master'
b895e59 [Syed Hashmi] Revert "[SPARK-1784] Add a new partitioner"
57b6587 [Syed Hashmi] Revert "[SPARK-1784] Add a balanced partitioner"
1574769 [Syed Hashmi] [SPARK-1942] Stop clearing spark.driver.port in unit tests
4354836 [Syed Hashmi] Revert "SPARK-1686: keep schedule() calling in the main thread"
fd36542 [Syed Hashmi] [SPARK-1784] Add a balanced partitioner
6668015 [CodingCat] SPARK-1686: keep schedule() calling in the main thread
4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
Author: witgo <witgo@qq.com>
Closes#786 from witgo/maven_plugin and squashes the following commits:
5de86a2 [witgo] Merge branch 'master' of https://github.com/apache/spark into maven_plugin
c35ef73 [witgo] Improve maven plugin configuration
This patch simply ports over the Scala implementation of RDD#take(), which reads the first partition at the driver, then decides how many more partitions it needs to read and will possibly start a real job if it's more than 1. (Note that SparkContext#runJob(allowLocal=true) only runs the job locally if there's 1 partition selected and no parent stages.)
Author: Aaron Davidson <aaron@databricks.com>
Closes#922 from aarondav/take and squashes the following commits:
fa06df9 [Aaron Davidson] SPARK-1839: PySpark RDD#take() shouldn't always read from driver
`Properties#load()` doesn't close the InputStream, but it'd be closed after being GC'd anyway...
Also changed file.getName to file, because getName only shows the filename. This will show the full (possibly relative) path, which is less confusing if it's not found.
Author: Aaron Davidson <aaron@databricks.com>
Closes#914 from aarondav/tiny and squashes the following commits:
db9d072 [Aaron Davidson] Super minor: Close inputStream in SparkSubmitArguments
Author: Chen Chao <crazyjvm@gmail.com>
Closes#928 from CrazyJvm/patch-8 and squashes the following commits:
144328b [Chen Chao] correct tiny comment error
https://issues.apache.org/jira/browse/SPARK-1901
Author: Zhen Peng <zhenpeng01@baidu.com>
Closes#854 from zhpengg/bugfix-worker-kills-executor and squashes the following commits:
21d380b [Zhen Peng] add some error messages
506cea6 [Zhen Peng] add some docs for killProcess()
a0b9860 [Zhen Peng] [SPARK-1901] worker should make sure executor has exited before updating executor's info
bugfix worker DriverStateChanged state should match DriverState.FAILED
Author: lianhuiwang <lianhuiwang09@gmail.com>
Closes#864 from lianhuiwang/master and squashes the following commits:
480ce94 [lianhuiwang] address aarondav comments
f2b5970 [lianhuiwang] bugfix worker DriverStateChanged state should match DriverState.FAILED
`var cachedPeers: Seq[BlockManagerId] = null` is used in `def replicate(blockId: BlockId, data: ByteBuffer, level: StorageLevel)` without proper protection.
There are two place will call `replicate(blockId, bytesAfterPut, level)`
* 17f3075bc4/core/src/main/scala/org/apache/spark/storage/BlockManager.scala (L644) runs in `connectionManager.futureExecContext`
* 17f3075bc4/core/src/main/scala/org/apache/spark/storage/BlockManager.scala (L752) `doPut` runs in `connectionManager.handleMessageExecutor`. `org.apache.spark.storage.BlockManagerWorker` calls `blockManager.putBytes` in `connectionManager.handleMessageExecutor`.
As they run in different `Executor`s, this is a race condition which may cause the memory pointed by `cachedPeers` is not correct even if `cachedPeers != null`.
The race condition of `onReceiveCallback` is that it's set in `BlockManagerWorker` but read in a different thread in `ConnectionManager.handleMessageExecutor`.
Author: zsxwing <zsxwing@gmail.com>
Closes#887 from zsxwing/SPARK-1932 and squashes the following commits:
524f69c [zsxwing] SPARK-1932: Fix race conditions in onReceiveCallback and cachedPeers
https://issues.apache.org/jira/browse/SPARK-1933
Author: Reynold Xin <rxin@apache.org>
Closes#888 from rxin/addfile and squashes the following commits:
8c402a3 [Reynold Xin] Updated comment.
ff6c162 [Reynold Xin] SPARK-1933: Throw a more meaningful exception when a directory is passed to addJar/addFile.
DAGScheduler does not handle local task OOM properly, and will wait for the job result forever.
Author: Zhen Peng <zhenpeng01@baidu.com>
Closes#883 from zhpengg/bugfix-dag-scheduler-oom and squashes the following commits:
76f7eda [Zhen Peng] remove redundant memory allocations
aa63161 [Zhen Peng] SPARK-1929 DAGScheduler suspended by local task OOM
Self explanatory.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#878 from pwendell/java-constructor and squashes the following commits:
2cc1605 [Patrick Wendell] HOTFIX: Add no-arg SparkContext constructor in Java
Author: Zhen Peng <zhenpeng01@baidu.com>
Closes#827 from zhpengg/bugfix-executor-id-not-found and squashes the following commits:
cd8bb65 [Zhen Peng] bugfix: check executor id existence when executor exit
If I run the following on a YARN cluster
```
bin/spark-submit sheep.py --master yarn-client
```
it fails because of a mismatch in paths: `spark-submit` thinks that `sheep.py` resides on HDFS, and balks when it can't find the file there. A natural workaround is to add the `file:` prefix to the file:
```
bin/spark-submit file:/path/to/sheep.py --master yarn-client
```
However, this also fails. This time it is because python does not understand URI schemes.
This PR fixes this by automatically resolving all paths passed as command line argument to `spark-submit` properly. This has the added benefit of keeping file and jar paths consistent across different cluster modes. For python, we strip the URI scheme before we actually try to run it.
Much of the code is originally written by @mengxr. Tested on YARN cluster. More tests pending.
Author: Andrew Or <andrewor14@gmail.com>
Closes#853 from andrewor14/submit-paths and squashes the following commits:
0bb097a [Andrew Or] Format path correctly before adding it to PYTHONPATH
323b45c [Andrew Or] Include --py-files on PYTHONPATH for pyspark shell
3c36587 [Andrew Or] Improve error messages (minor)
854aa6a [Andrew Or] Guard against NPE if user gives pathological paths
6638a6b [Andrew Or] Fix spark-shell jar paths after #849 went in
3bb0359 [Andrew Or] Update more comments (minor)
2a1f8a0 [Andrew Or] Update comments (minor)
6af2c77 [Andrew Or] Merge branch 'master' of github.com:apache/spark into submit-paths
a68c4d1 [Andrew Or] Handle Windows python file path correctly
427a250 [Andrew Or] Resolve paths properly for Windows
a591a4a [Andrew Or] Update tests for resolving URIs
6c8621c [Andrew Or] Move resolveURIs to Utils
db8255e [Andrew Or] Merge branch 'master' of github.com:apache/spark into submit-paths
f542dce [Andrew Or] Fix outdated tests
691c4ce [Andrew Or] Ignore special primary resource names
5342ac7 [Andrew Or] Add missing space in error message
02f77f3 [Andrew Or] Resolve command line arguments to spark-submit properly
Due to perhaps zombie processes on Jenkins, it seems that at least 10
Spark ports are in use. It also doesn't matter that the port increases
when used, it could in fact go down -- the only part that matters is
that it selects a different port rather than failing to bind.
Changed test to match this.
Thanks to @andrewor14 for helping diagnose this.
Author: Aaron Davidson <aaron@databricks.com>
Closes#857 from aarondav/tiny and squashes the following commits:
c199ec8 [Aaron Davidson] Fix UISuite unit test that fails under Jenkins contention
Sent secondary jars to distributed cache of all containers and add the cached jars to classpath before executors start. Tested on a YARN cluster (CDH-5.0).
`spark-submit --jars` also works in standalone server and `yarn-client`. Thanks for @andrewor14 for testing!
I removed "Doesn't work for drivers in standalone mode with "cluster" deploy mode." from `spark-submit`'s help message, though we haven't tested mesos yet.
CC: @dbtsai @sryza
Author: Xiangrui Meng <meng@databricks.com>
Closes#848 from mengxr/yarn-classpath and squashes the following commits:
23e7df4 [Xiangrui Meng] rename spark.jar to __spark__.jar and app.jar to __app__.jar to avoid confliction apped $CWD/ and $CWD/* to the classpath remove unused methods
a40f6ed [Xiangrui Meng] standalone -> cluster
65e04ad [Xiangrui Meng] update spark-submit help message and add a comment for yarn-client
11e5354 [Xiangrui Meng] minor changes
3e7e1c4 [Xiangrui Meng] use sparkConf instead of hadoop conf
dc3c825 [Xiangrui Meng] add secondary jars to classpath in yarn
It was in the wrong package
Author: Andrew Or <andrewor14@gmail.com>
Closes#839 from andrewor14/jdbc-suite and squashes the following commits:
f948c5a [Andrew Or] cache -> cache()
b215279 [Andrew Or] Move JdbcRDDSuite to the correct package
Updated version of #821
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Ghidireac <bogdang@u448a5b0a73d45358d94a.ant.amazon.com>
Closes#835 from tdas/SPARK-1877 and squashes the following commits:
f346f71 [Tathagata Das] Addressed Patrick's comments.
fee0c5d [Ghidireac] SPARK-1877: ClassNotFoundException when loading RDD with serialized objects
scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such.
Author: Aaron Davidson <aaron@databricks.com>
Closes#832 from aarondav/i-love-u and squashes the following commits:
9f1200f [Aaron Davidson] SPARK-1689: Spark application should die when removed by Master
See https://issues.apache.org/jira/browse/SPARK-1879 -- builds with Hadoop2 and Hive ran out of PermGen space in spark-shell, when those things added up with the Scala compiler.
Note that users can still override it by setting their own Java options with this change. Their options will come later in the command string than the -XX:MaxPermSize=128m.
Author: Matei Zaharia <matei@databricks.com>
Closes#823 from mateiz/spark-1879 and squashes the following commits:
6bc0ee8 [Matei Zaharia] Increase MaxPermSize to 128m since some of our builds have lots of classes
- Look for JARs in the right place
- Launch examples the same way as on Unix
- Load datanucleus JARs if they exist
- Don't attempt to parse local paths as URIs in SparkSubmit, since paths with C:\ are not valid URIs
- Also fixed POM exclusion rules for datanucleus (it wasn't properly excluding it, whereas SBT was)
Author: Matei Zaharia <matei@databricks.com>
Closes#819 from mateiz/win-fixes and squashes the following commits:
d558f96 [Matei Zaharia] Fix comment
228577b [Matei Zaharia] Review comments
d3b71c7 [Matei Zaharia] Properly exclude datanucleus files in Maven assembly
144af84 [Matei Zaharia] Update Windows scripts to match latest binary package layout
Just a small change. I think it's good not to scare people who are using the old options.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#810 from pwendell/warnings and squashes the following commits:
cb8a311 [Patrick Wendell] Make deprecation warning less severe
**Problem.** For `bin/pyspark`, there is currently no other way to specify Spark configuration properties other than through `SPARK_JAVA_OPTS` in `conf/spark-env.sh`. However, this mechanism is supposedly deprecated. Instead, it needs to pick up configurations explicitly specified in `conf/spark-defaults.conf`.
**Solution.** Have `bin/pyspark` invoke `bin/spark-submit`, like all of its counterparts in Scala land (i.e. `bin/spark-shell`, `bin/run-example`). This has the additional benefit of making the invocation of all the user facing Spark scripts consistent.
**Details.** `bin/pyspark` inherently handles two cases: (1) running python applications and (2) running the python shell. For (1), Spark submit already handles running python applications. For cases in which `bin/pyspark` is given a python file, we can simply call pass the file directly to Spark submit and let it handle the rest.
For case (2), `bin/pyspark` starts a python process as before, which launches the JVM as a sub-process. The existing code already provides a code path to do this. All we needed to change is to use `bin/spark-submit` instead of `spark-class` to launch the JVM. This requires modifications to Spark submit to handle the pyspark shell as a special case.
This has been tested locally (OSX and Windows 7), on a standalone cluster, and on a YARN cluster. Running IPython also works as before, except now it takes in Spark submit arguments too.
Author: Andrew Or <andrewor14@gmail.com>
Closes#799 from andrewor14/pyspark-submit and squashes the following commits:
bf37e36 [Andrew Or] Minor changes
01066fa [Andrew Or] bin/pyspark for Windows
c8cb3bf [Andrew Or] Handle perverse app names (with escaped quotes)
1866f85 [Andrew Or] Windows is not cooperating
456d844 [Andrew Or] Guard against shlex hanging if PYSPARK_SUBMIT_ARGS is not set
7eebda8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-submit
b7ba0d8 [Andrew Or] Address a few comments (minor)
06eb138 [Andrew Or] Use shlex instead of writing our own parser
05879fa [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-submit
a823661 [Andrew Or] Fix --die-on-broken-pipe not propagated properly
6fba412 [Andrew Or] Deal with quotes + address various comments
fe4c8a7 [Andrew Or] Update --help for bin/pyspark
afe47bf [Andrew Or] Fix spark shell
f04aaa4 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-submit
a371d26 [Andrew Or] Route bin/pyspark through Spark submit
Author: Michael Armbrust <michael@databricks.com>
Closes#808 from marmbrus/confClasspath and squashes the following commits:
4c31d57 [Michael Armbrust] Look in spark conf instead of system properties when propagating configuration to executors.
This causes an unrecoverable error for applications that are running for longer
than 7 days that have jars added to the SparkContext, as the jars are cleaned up
even though the application is still running.
Author: Aaron Davidson <aaron@databricks.com>
Closes#800 from aarondav/shitty-defaults and squashes the following commits:
a573fbb [Aaron Davidson] SPARK-1860: Do not cleanup application work/ directories by default
Author: Huajian Mao <huajianmao@gmail.com>
Closes#798 from huajianmao/patch-1 and squashes the following commits:
208a454 [Huajian Mao] A typo in Task
1b515af [Huajian Mao] A typo in the message
This is a few changes based on the original patch by @scrapcodes.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#785 from pwendell/package-docs and squashes the following commits:
c32b731 [Patrick Wendell] Changes based on Prashant's patch
c0463d3 [Prashant Sharma] added eof new line
ce8bf73 [Prashant Sharma] Added eof new line to all files.
4c35f2e [Prashant Sharma] SPARK-1563 Add package-info.java and package.scala files for all packages that appear in docs
Author: Patrick Wendell <pwendell@gmail.com>
Closes#784 from pwendell/group-by-key and squashes the following commits:
9b4505f [Patrick Wendell] Small fix
6347924 [Patrick Wendell] Documentation: Encourage use of reduceByKey instead of groupByKey.
Running SparkPi example gave this error.
```
Pi is roughly 3.14374
14/05/14 18:16:19 ERROR Utils: Uncaught exception in thread SparkListenerBus
scala.runtime.NonLocalReturnControl$mcV$sp
```
This is due to the catch-all in the SparkListenerBus, which logged control throwable used by scala system
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#783 from tdas/controlexception-fix and squashes the following commits:
a466c8d [Tathagata Das] Ignored control exceptions when logging all exceptions.
Author: andrewor14 <andrewor14@gmail.com>
Closes#780 from andrewor14/submit-typo and squashes the following commits:
e70e057 [andrewor14] propertes -> properties
After having been invited to make the change in 6bee01dd04 (commitcomment-6284165) by @witgo.
Author: Jacek Laskowski <jacek@japila.pl>
Closes#748 from jaceklaskowski/sparkenv-string-interpolation and squashes the following commits:
be6ebac [Jacek Laskowski] String interpolation + some other small changes
This is nicer than relying on new SparkContext(new SparkConf())
Author: Patrick Wendell <pwendell@gmail.com>
Closes#774 from pwendell/spark-context and squashes the following commits:
ef9f12f [Patrick Wendell] SPARK-1833 - Have an empty SparkContext constructor.
As "99 ms" up to 99 ms
As "0.1 s" from 0.1 s up to 0.9 s
https://issues.apache.org/jira/browse/SPARK-1829
Compare the first image to the second here: http://imgur.com/RaLEsSZ,7VTlgfo#0
Author: Andrew Ash <andrew@andrewash.com>
Closes#768 from ash211/spark-1829 and squashes the following commits:
1c15b8e [Andrew Ash] SPARK-1829 Format sub-second durations more appropriately
If the intended behavior was that uncaught exceptions thrown in functions being run by the Akka scheduler would end up being handled by the default uncaught exception handler set in Executor, and if that behavior is, in fact, correct, then this is a way to accomplish that. I'm not certain, though, that we shouldn't be doing something different to handle uncaught exceptions from some of these scheduled functions.
In any event, this PR covers all of the cases I comment on in [SPARK-1620](https://issues.apache.org/jira/browse/SPARK-1620).
Author: Mark Hamstra <markhamstra@gmail.com>
Closes#622 from markhamstra/SPARK-1620 and squashes the following commits:
071d193 [Mark Hamstra] refactored post-SPARK-1772
1a6a35e [Mark Hamstra] another style fix
d30eb94 [Mark Hamstra] scalastyle
3573ecd [Mark Hamstra] Use wrapped try/catch in Utils.tryOrExit
8fc0439 [Mark Hamstra] Make functions run by the Akka scheduler use Executor's UncaughtExceptionHandler
This PR replaces the Schedulable data structures in Pool.scala with thread-safe ones from java. Note that Scala's `with SynchronizedBuffer` trait is soon to be deprecated in 2.11 because it is ["inherently unreliable"](http://www.scala-lang.org/api/2.11.0/index.html#scala.collection.mutable.SynchronizedBuffer). We should slowly drift away from `SynchronizedBuffer` in other places too.
Note that this PR introduces an API-breaking change; `sc.getAllPools` now returns an Array rather than an ArrayBuffer. This is because we want this method to return an immutable copy rather than one may potentially confuse the user if they try to modify the copy, which takes no effect on the original data structure.
Author: Andrew Or <andrewor14@gmail.com>
Closes#762 from andrewor14/pool-npe and squashes the following commits:
383e739 [Andrew Or] JavaConverters -> JavaConversions
3f32981 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pool-npe
769be19 [Andrew Or] Assorted minor changes
2189247 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pool-npe
05ad9e9 [Andrew Or] Fix test - contains is not the same as containsKey
0921ea0 [Andrew Or] var -> val
07d720c [Andrew Or] Synchronize Schedulable data structures
...loper api
Author: Koert Kuipers <koert@tresata.com>
Closes#764 from koertkuipers/feat-rdd-developerapi and squashes the following commits:
8516dd2 [Koert Kuipers] SPARK-1801. expose InterruptibleIterator and TaskKilledException in developer api
Add the implementation for ApproximateCountDistinct to SparkSql. We use the HyperLogLog algorithm implemented in stream-lib, and do the count in two phases: 1) counting the number of distinct elements in each partitions, and 2) merge the HyperLogLog results from different partitions.
A simple serializer and test cases are added as well.
Author: larvaboy <larvaboy@gmail.com>
Closes#737 from larvaboy/master and squashes the following commits:
bd8ef3f [larvaboy] Add support of user-provided standard deviation to ApproxCountDistinct.
9ba8360 [larvaboy] Fix alignment and null handling issues.
95b4067 [larvaboy] Add a test case for count distinct and approximate count distinct.
f57917d [larvaboy] Add the parser for the approximate count.
a2d5d10 [larvaboy] Add ApproximateCountDistinct aggregates and functions.
7ad273a [larvaboy] Add SparkSql serializer for HyperLogLog.
1d9aacf [larvaboy] Fix a minor typo in the toString method of the Count case class.
653542b [larvaboy] Fix a couple of minor typos.
This change adds a new partitioner which allows users
to specify # of keys per partition.
Author: Syed Hashmi <shashmi@cloudera.com>
Closes#721 from syedhashmi/master and squashes the following commits:
4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
JIRA issue: [SPARK-1527](https://issues.apache.org/jira/browse/SPARK-1527)
getName() only gets the last component of the file path. When deleting test-generated directories,
we should pass the generated directory's absolute path to DiskBlockManager.
Author: Ye Xianjin <advancedxy@gmail.com>
This patch had conflicts when merged, resolved by
Committer: Patrick Wendell <pwendell@gmail.com>
Closes#436 from advancedxy/SPARK-1527 and squashes the following commits:
4678bab [Ye Xianjin] change rootDir*.getname to rootDir*.getAbsolutePath so the temporary directories are deleted when the test is finished.
The solution is to wrap a try / catch / log around the posting of each event to each listener.
Author: Andrew Or <andrewor14@gmail.com>
Closes#759 from andrewor14/listener-die and squashes the following commits:
aee5107 [Andrew Or] Merge branch 'master' of github.com:apache/spark into listener-die
370939f [Andrew Or] Remove two layers of indirection
422d278 [Andrew Or] Explicitly throw an exception instead of 1 / 0
0df0e2a [Andrew Or] Try/catch and log exceptions when posting events
This patch checks top-level closure arguments to `ClosureCleaner.clean` for `return` statements and raises an exception if it finds any. This is mainly a user-friendliness addition, since programs with return statements in closure arguments will currently fail upon RDD actions with a less-than-intuitive error message.
Author: William Benton <willb@redhat.com>
Closes#717 from willb/spark-571 and squashes the following commits:
c41eb7d [William Benton] Another test case for SPARK-571
30c42f4 [William Benton] Stylistic cleanups
559b16b [William Benton] Stylistic cleanups from review
de13b79 [William Benton] Style fixes
295b6a5 [William Benton] Forbid return statements in closure arguments.
b017c47 [William Benton] Added a test for SPARK-571
Author: Sandy Ryza <sandy@cloudera.com>
Closes#753 from sryza/sandy-spark-1815 and squashes the following commits:
957a8ac [Sandy Ryza] SPARK-1815. SparkContext should not be marked DeveloperApi
What they really mean is SPARK_DAEMON_***JAVA***_OPTS
Author: Andrew Or <andrewor14@gmail.com>
Closes#751 from andrewor14/spark-daemon-opts and squashes the following commits:
70c41f9 [Andrew Or] SPARK_DAEMON_OPTS -> SPARK_DAEMON_JAVA_OPTS
Author: Andrew Ash <andrew@andrewash.com>
Closes#743 from ash211/patch-4 and squashes the following commits:
c959f3b [Andrew Ash] Typo: resond -> respond
This seems strictly better, and I think it's justified only the grounds of
clean-up. It might also fix issues with path conversions, but I haven't
yet isolated any instance of that happening.
/cc @srowen @tdas
Author: Patrick Wendell <pwendell@gmail.com>
Closes#749 from pwendell/broadcast-cleanup and squashes the following commits:
d6d54f2 [Patrick Wendell] SPARK-1623: Use File objects instead of string's in HTTPBroadcast
This was changed, but in fact, it's used for things other than tests.
So I've changed it back.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#747 from pwendell/executor-env and squashes the following commits:
36a60a5 [Patrick Wendell] Rename testExecutorEnvs --> executorEnvs.
Three issues related to temp files that tests generate – these should be touched up for hygiene but are not urgent.
Modules have a log4j.properties which directs the unit-test.log output file to a directory like `[module]/target/unit-test.log`. But this ends up creating `[module]/[module]/target/unit-test.log` instead of former.
The `work/` directory is not deleted by "mvn clean", in the parent and in modules. Neither is the `checkpoint/` directory created under the various external modules.
Many tests create a temp directory, which is not usually deleted. This can be largely resolved by calling `deleteOnExit()` at creation and trying to call `Utils.deleteRecursively` consistently to clean up, sometimes in an `@After` method.
_If anyone seconds the motion, I can create a more significant change that introduces a new test trait along the lines of `LocalSparkContext`, which provides management of temp directories for subclasses to take advantage of._
Author: Sean Owen <sowen@cloudera.com>
Closes#732 from srowen/SPARK-1798 and squashes the following commits:
5af578e [Sean Owen] Try to consistently delete test temp dirs and files, and set deleteOnExit() for each
b21b356 [Sean Owen] Remove work/ and checkpoint/ dirs with mvn clean
bdd0f41 [Sean Owen] Remove duplicate module dir in log4j.properties output path for tests
Enabled Mesos (0.18.1) dependency with shaded protobuf
Why is this needed?
Avoids any protobuf version collision between Mesos and any other
dependency in Spark e.g. Hadoop HDFS 2.2+ or 1.0.4.
Ticket: https://issues.apache.org/jira/browse/SPARK-1806
* Should close https://issues.apache.org/jira/browse/SPARK-1433
Author berngp
Author: Bernardo Gomez Palacio <bernardo.gomezpalacio@gmail.com>
Closes#741 from berngp/feature/SPARK-1806 and squashes the following commits:
5d70646 [Bernardo Gomez Palacio] SPARK-1806: Upgrade Mesos dependency to 0.18.1
The main issue this patch fixes is [SPARK-1772](https://issues.apache.org/jira/browse/SPARK-1772), in which Executors may not die when fatal exceptions (e.g., OOM) are thrown. This patch causes Executors to delegate to the ExecutorUncaughtExceptionHandler when a fatal exception is thrown.
This patch also continues the fight in the neverending war against `case t: Throwable =>`, by only catching Exceptions in many places, and adding a wrapper for Threads and Runnables to make sure any uncaught exceptions are at least printed to the logs.
It also turns out that it is unlikely that the IndestructibleActorSystem actually works, given testing ([here](https://gist.github.com/aarondav/ca1f0cdcd50727f89c0d)). The uncaughtExceptionHandler is not called from the places that we expected it would be.
[SPARK-1620](https://issues.apache.org/jira/browse/SPARK-1620) deals with part of this issue, but refactoring our Actor Systems to ensure that exceptions are dealt with properly is a much bigger change, outside the scope of this PR.
Author: Aaron Davidson <aaron@databricks.com>
Closes#715 from aarondav/throwable and squashes the following commits:
f9b9bfe [Aaron Davidson] Remove other redundant 'throw e'
e937a0a [Aaron Davidson] Address Prashant and Matei's comments
1867867 [Aaron Davidson] [RFC] SPARK-1772 Stop catching Throwable, let Executors die
This patch adds better balancing when performing a repartition of an
RDD. Previously the elements in the RDD were hash partitioned, meaning
if the RDD was skewed certain partitions would end up being very large.
This commit adds load balancing of elements across the repartitioned
RDD splits. The load balancing is not perfect: a given output partition
can have up to N more elements than the average if there are N input
partitions. However, some randomization is used to minimize the
probabiliy that this happens.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#727 from pwendell/load-balance and squashes the following commits:
f9da752 [Patrick Wendell] Response to Matei's feedback
acfa46a [Patrick Wendell] SPARK-1770: Load balance elements when repartitioning.
Author: witgo <witgo@qq.com>
Closes#728 from witgo/scala_home and squashes the following commits:
cdfd8be [witgo] Merge branch 'master' of https://github.com/apache/spark into scala_home
fac094a [witgo] remove outdated runtime Information scala home
SparkSubmit ignores `--jars` for YARN client. This is a bug.
This PR also automatically adds the application jar to `spark.jar`. Previously, when running as yarn-client, you must specify the jar additionally through `--files` (because `--jars` didn't work). Now you don't have to explicitly specify it through either.
Tested on a YARN cluster.
Author: Andrew Or <andrewor14@gmail.com>
Closes#710 from andrewor14/yarn-jars and squashes the following commits:
35d1928 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-jars
c27bf6c [Andrew Or] For yarn-cluster and python, do not add primaryResource to spark.jar
c92c5bf [Andrew Or] Minor cleanups
269f9f3 [Andrew Or] Fix format
013d840 [Andrew Or] Fix tests
1407474 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-jars
3bb75e8 [Andrew Or] Allow SparkSubmit --jars to take effect in yarn-client mode
TL;DR is there is a bit of JAR hell trouble with Netty, that can be mostly resolved and will resolve a test failure.
I hit the error described at http://apache-spark-user-list.1001560.n3.nabble.com/SparkContext-startup-time-out-td1753.html while running FlumeStreamingSuite, and have for a short while (is it just me?)
velvia notes:
"I have found a workaround. If you add akka 2.2.4 to your dependencies, then everything works, probably because akka 2.2.4 brings in newer version of Jetty."
There are at least 3 versions of Netty in play in the build:
- the new Flume 1.4.0 dependency brings in io.netty:netty:3.4.0.Final, and that is the immediate problem
- the custom version of akka 2.2.3 depends on io.netty:netty:3.6.6.
- but, Spark Core directly uses io.netty:netty-all:4.0.17.Final
The POMs try to exclude other versions of netty, but are excluding org.jboss.netty:netty, when in fact older versions of io.netty:netty (not netty-all) are also an issue.
The org.jboss.netty:netty excludes are largely unnecessary. I replaced many of them with io.netty:netty exclusions until everything agreed on io.netty:netty-all:4.0.17.Final.
But this didn't work, since Akka 2.2.3 doesn't work with Netty 4.x. Down-grading to 3.6.6.Final across the board made some Spark code not compile.
If the build *keeps* io.netty:netty:3.6.6.Final as well, everything seems to work. Part of the reason seems to be that Netty 3.x used the old `org.jboss.netty` packages. This is less than ideal, but is no worse than the current situation.
So this PR resolves the issue and improves the JAR hell, even if it leaves the existing theoretical Netty 3-vs-4 conflict:
- Remove org.jboss.netty excludes where possible, for clarity; they're not needed except with Hadoop artifacts
- Add io.netty:netty excludes where needed -- except, let akka keep its io.netty:netty
- Change a bit of test code that actually depended on Netty 3.x, to use 4.x equivalent
- Update SBT build accordingly
A better change would be to update Akka far enough such that it agrees on Netty 4.x, but I don't know if that's feasible.
Author: Sean Owen <sowen@cloudera.com>
Closes#723 from srowen/SPARK-1789 and squashes the following commits:
43661b7 [Sean Owen] Update and add Netty excludes to prevent some JAR conflicts that cause test issues
Tolerate empty strings in PythonRDD
Author: Kan Zhang <kzhang@apache.org>
Closes#644 from kanzhang/SPARK-1690 and squashes the following commits:
c62ad33 [Kan Zhang] Adding Python doctest
473ec4b [Kan Zhang] [SPARK-1690] Tolerating empty elements when saving Python RDD to text files
This fixes https://issues.apache.org/jira/browse/SPARK-1731 by adding the Python includes to the PYTHONPATH before depickling the broadcast values
@airhorns
Author: Bouke van der Bijl <boukevanderbijl@gmail.com>
Closes#656 from bouk/python-includes-before-broadcast and squashes the following commits:
7b0dfe4 [Bouke van der Bijl] Add Python includes to path before depickling broadcast values
This pull request contains a rebased patch from @heathermiller (https://github.com/heathermiller/spark/pull/1) to add ClassTags on Serializer and types that depend on it (Broadcast and AccumulableCollection). Putting these in the public API signatures now will allow us to use Scala Pickling for serialization down the line without breaking binary compatibility.
One question remaining is whether we also want them on Accumulator -- Accumulator is passed as part of a bigger Task or TaskResult object via the closure serializer so it doesn't seem super useful to add the ClassTag there. Broadcast and AccumulableCollection in contrast were being serialized directly.
CC @rxin, @pwendell, @heathermiller
Author: Matei Zaharia <matei@databricks.com>
Closes#700 from mateiz/spark-1708 and squashes the following commits:
1a3d8b0 [Matei Zaharia] Use fake ClassTag in Java
3b449ed [Matei Zaharia] test fix
2209a27 [Matei Zaharia] Code style fixes
9d48830 [Matei Zaharia] Add a ClassTag on Serializer and things that depend on it
https://issues.apache.org/jira/browse/SPARK-1686
moved from original JIRA (by @markhamstra):
In deploy.master.Master, the completeRecovery method is the last thing to be called when a standalone Master is recovering from failure. It is responsible for resetting some state, relaunching drivers, and eventually resuming its scheduling duties.
There are currently four places in Master.scala where completeRecovery is called. Three of them are from within the actor's receive method, and aren't problems. The last starts from within receive when the ElectedLeader message is received, but the actual completeRecovery() call is made from the Akka scheduler. That means that it will execute on a different scheduler thread, and Master itself will end up running (i.e., schedule() ) from that Akka scheduler thread.
In this PR, I added a new master message TriggerSchedule to trigger the "local" call of schedule() in the scheduler thread
Author: CodingCat <zhunansjtu@gmail.com>
Closes#639 from CodingCat/SPARK-1686 and squashes the following commits:
81bb4ca [CodingCat] rename variable
69e0a2a [CodingCat] style fix
36a2ac0 [CodingCat] address Aaron's comments
ec9b7bb [CodingCat] address the comments
02b37ca [CodingCat] keep schedule() calling in the main thread
Looks like this change was accidentally committed here: 06b15baab2
but the change does not show up in the PR itself (#704).
Other than not intending to go in with that PR, this also broke the test JavaAPISuite.repartition.
Author: Aaron Davidson <aaron@databricks.com>
Closes#716 from aarondav/shufflerand and squashes the following commits:
b1cf70b [Aaron Davidson] SPARK-1770: Revert accidental(?) fix
Removing a block through the blockmanager gave a scary warning messages in the driver.
```
2014-05-08 20:16:19,172 WARN BlockManagerMasterActor: Got unknown message: true
2014-05-08 20:16:19,172 WARN BlockManagerMasterActor: Got unknown message: true
2014-05-08 20:16:19,172 WARN BlockManagerMasterActor: Got unknown message: true
```
This is because the [BlockManagerSlaveActor](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala#L44) would send back an acknowledgement ("true"). But the BlockManagerMasterActor would have sent the RemoveBlock message as a send, not as ask(), so would reject the receiver "true" as a unknown message.
@pwendell
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#708 from tdas/bm-fix and squashes the following commits:
ed4ef15 [Tathagata Das] Converted bang to ask to avoid scary warning when a block is removed.
This was used in the past to have a cache of deserialized ShuffleMapTasks, but that's been removed, so there's no need for a lock. It slows down Spark when task descriptions are large, e.g. due to large lineage graphs or local variables.
Author: Sandeep <sandeep@techaddict.me>
Closes#707 from techaddict/SPARK-1775 and squashes the following commits:
18d8ebf [Sandeep] SPARK-1775: Unneeded lock in ShuffleMapTask.deserializeInfo This was used in the past to have a cache of deserialized ShuffleMapTasks, but that's been removed, so there's no need for a lock. It slows down Spark when task descriptions are large, e.g. due to large lineage graphs or local variables.
Gives a nicely formatted message to the user when `run-example` is run to
tell them to use `spark-submit`.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#704 from pwendell/examples and squashes the following commits:
1996ee8 [Patrick Wendell] Feedback form Andrew
3eb7803 [Patrick Wendell] Suggestions from TD
2474668 [Patrick Wendell] SPARK-1565 (Addendum): Replace `run-example` with `spark-submit`.
Right now, SparkSubmit ignores the `--name` flag for both yarn-client and yarn-cluster. This is a bug.
In client mode, SparkSubmit treats `--name` as a [cluster config](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L170) and does not propagate this to SparkContext.
In cluster mode, SparkSubmit passes this flag to `org.apache.spark.deploy.yarn.Client`, which only uses it for the [YARN ResourceManager](https://github.com/apache/spark/blob/master/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala#L80), but does not propagate this to SparkContext.
This PR ensures that `spark.app.name` is always set if SparkSubmit receives the `--name` flag, which is what the usage promises. This makes it possible for applications to start a SparkContext with an empty conf `val sc = new SparkContext(new SparkConf)`, and inherit the app name from SparkSubmit.
Tested both modes on a YARN cluster.
Author: Andrew Or <andrewor14@gmail.com>
Closes#699 from andrewor14/yarn-app-name and squashes the following commits:
98f6a79 [Andrew Or] Fix tests
dea932f [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-app-name
c86d9ca [Andrew Or] Respect SparkSubmit --name on YARN
It makes little sense to start a TaskContext that is interrupted. Indeed, I searched for all use cases of it and didn't find a single instance in which `interrupted` is true on construction.
This was inspired by reviewing #640, which adds an additional `@volatile var completed` that is similar. These are not the most urgent changes, but I wanted to push them out before I forget.
Author: Andrew Or <andrewor14@gmail.com>
Closes#675 from andrewor14/task-context and squashes the following commits:
9575e02 [Andrew Or] Add space
69455d1 [Andrew Or] Merge branch 'master' of github.com:apache/spark into task-context
c471490 [Andrew Or] Oops, removed one flag too many. Adding it back.
85311f8 [Andrew Or] Move interrupted flag from TaskContext constructor
Commit for initial feedback, basically I am curious if we should prompt user for providing args esp. when its mandatory. And can we skip if they are not ?
Also few other things that did not work like
`bin/spark-submit examples/target/scala-2.10/spark-examples-1.0.0-SNAPSHOT-hadoop1.0.4.jar --class org.apache.spark.examples.SparkALS --arg 100 500 10 5 2`
Not all the args get passed properly, may be I have messed up something will try to sort it out hopefully.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#552 from ScrapCodes/SPARK-1565/update-examples and squashes the following commits:
669dd23 [Prashant Sharma] Review comments
2727e70 [Prashant Sharma] SPARK-1565, update examples to be used with spark-submit script.
When at least one of the following conditions is true, PySpark cannot be loaded:
1. PYTHONPATH is not set
2. PYTHONPATH does not contain the python directory (or jar, in the case of YARN)
3. The jar does not contain pyspark files (YARN)
4. The jar does not contain py4j files (YARN)
However, we currently throw the same random `java.io.EOFException` for all of the above cases, when trying to read from the python daemon's output. This message is super unhelpful.
This PR includes the python stderr and the PYTHONPATH in the exception propagated to the driver. Now, the exception message looks something like:
```
Error from python worker:
: No module named pyspark
PYTHONPATH was:
/path/to/spark/python:/path/to/some/jar
java.io.EOFException
<stack trace>
```
whereas before it was just
```
java.io.EOFException
<stack trace>
```
Author: Andrew Or <andrewor14@gmail.com>
Closes#603 from andrewor14/pyspark-exception and squashes the following commits:
10d65d3 [Andrew Or] Throwable -> Exception, worker -> daemon
862d1d7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
a5ed798 [Andrew Or] Use block string and interpolation instead of var (minor)
cc09c45 [Andrew Or] Account for the fact that the python daemon may not have terminated yet
444f019 [Andrew Or] Use the new RedirectThread + include system PYTHONPATH
aab00ae [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
0cc2402 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
783efe2 [Andrew Or] Make python daemon stderr indentation consistent
9524172 [Andrew Or] Avoid potential NPE / error stream contention + Move things around
29f9688 [Andrew Or] Add back original exception type
e92d36b [Andrew Or] Include python worker stderr in the exception propagated to the driver
7c69360 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
cdbc185 [Andrew Or] Fix python attribute not found exception when PYTHONPATH is not set
dcc0353 [Andrew Or] Check both python and system environment variables for PYTHONPATH
6c09c21 [Andrew Or] Validate PYTHONPATH and PySpark modules before starting python workers
Happy to open a jira ticket if you'd like to track one there.
Author: Andrew Ash <andrew@andrewash.com>
Closes#678 from ash211/SecurityManagerLogging and squashes the following commits:
2aa0b7a [Andrew Ash] Nicer logging for SecurityManager startup
This patch includes several cleanups to PythonRDD, focused around fixing [SPARK-1579](https://issues.apache.org/jira/browse/SPARK-1579) cleanly. Listed in order of approximate importance:
- The Python daemon waits for Spark to close the socket before exiting,
in order to avoid causing spurious IOExceptions in Spark's
`PythonRDD::WriterThread`.
- Removes the Python Monitor Thread, which polled for task cancellations
in order to kill the Python worker. Instead, we do this in the
onCompleteCallback, since this is guaranteed to be called during
cancellation.
- Adds a "completed" variable to TaskContext to avoid the issue noted in
[SPARK-1019](https://issues.apache.org/jira/browse/SPARK-1019), where onCompleteCallbacks may be execution-order dependent.
Along with this, I removed the "context.interrupted = true" flag in
the onCompleteCallback.
- Extracts PythonRDD::WriterThread to its own class.
Since this patch provides an alternative solution to [SPARK-1019](https://issues.apache.org/jira/browse/SPARK-1019), I did test it with
```
sc.textFile("latlon.tsv").take(5)
```
many times without error.
Additionally, in order to test the unswallowed exceptions, I performed
```
sc.textFile("s3n://<big file>").count()
```
and cut my internet during execution. Prior to this patch, we got the "stdin writer exited early" message, which was unhelpful. Now, we get the SocketExceptions propagated through Spark to the user and get proper (though unsuccessful) task retries.
Author: Aaron Davidson <aaron@databricks.com>
Closes#640 from aarondav/pyspark-io and squashes the following commits:
b391ff8 [Aaron Davidson] Detect "clean socket shutdowns" and stop waiting on the socket
c0c49da [Aaron Davidson] SPARK-1579: Clean up PythonRDD and avoid swallowing IOExceptions
... that do not change schema
Author: Kan Zhang <kzhang@apache.org>
Closes#448 from kanzhang/SPARK-1460 and squashes the following commits:
111e388 [Kan Zhang] silence MiMa errors in EdgeRDD and VertexRDD
91dc787 [Kan Zhang] Taking into account newly added Ordering param
79ed52a [Kan Zhang] [SPARK-1460] Returning SchemaRDD on Set operations that do not change schema
Author: Patrick Wendell <pwendell@gmail.com>
Closes#676 from pwendell/worker-opts and squashes the following commits:
54456c4 [Patrick Wendell] SPARK-1746: Support setting SPARK_JAVA_OPTS on executors for backwards compatibility
This PR updates spark-submit to allow submitting Python scripts (currently only with deploy-mode=client, but that's all that was supported before) and updates the PySpark code to properly find various paths, etc. One significant change is that we assume we can always find the Python files either from the Spark assembly JAR (which will happen with the Maven assembly build in make-distribution.sh) or from SPARK_HOME (which will exist in local mode even if you use sbt assembly, and should be enough for testing). This means we no longer need a weird hack to modify the environment for YARN.
This patch also updates the Python worker manager to run python with -u, which means unbuffered output (send it to our logs right away instead of waiting a while after stuff was written); this should simplify debugging.
In addition, it fixes https://issues.apache.org/jira/browse/SPARK-1709, setting the main class from a JAR's Main-Class attribute if not specified by the user, and fixes a few help strings and style issues in spark-submit.
In the future we may want to make the `pyspark` shell use spark-submit as well, but it seems unnecessary for 1.0.
Author: Matei Zaharia <matei@databricks.com>
Closes#664 from mateiz/py-submit and squashes the following commits:
15e9669 [Matei Zaharia] Fix some uses of path.separator property
051278c [Matei Zaharia] Small style fixes
0afe886 [Matei Zaharia] Add license headers
4650412 [Matei Zaharia] Add pyFiles to PYTHONPATH in executors, remove old YARN stuff, add tests
15f8e1e [Matei Zaharia] Set PYTHONPATH in PythonWorkerFactory in case it wasn't set from outside
47c0655 [Matei Zaharia] More work to make spark-submit work with Python:
d4375bd [Matei Zaharia] Clean up description of spark-submit args a bit and add Python ones
... java.lang.ClassNotFoundException: org.apache.spark.broadcast.TorrentBroadcastFactory
Author: witgo <witgo@qq.com>
Closes#665 from witgo/SPARK-1734 and squashes the following commits:
cacf238 [witgo] SPARK-1734: spark-submit throws an exception: Exception in thread "main" java.lang.ClassNotFoundException: org.apache.spark.broadcast.TorrentBroadcastFactory
See https://issues.apache.org/jira/browse/SPARK-1685 for a more complete description, but in essence: If the Worker or AppClient actor restarts before successfully registering with Master, multiple retryTimers will be running, which will lead to less than the full number of registration retries being attempted before the new actor is forced to give up.
Author: Mark Hamstra <markhamstra@gmail.com>
Closes#602 from markhamstra/SPARK-1685 and squashes the following commits:
11cc088 [Mark Hamstra] retryTimer -> registrationRetryTimer
69c348c [Mark Hamstra] Cancel retryTimer on restart of Worker or AppClient
Modify wrong comment of function addWithoutResize.
Author: ArcherShao <ArcherShao@users.noreply.github.com>
Closes#667 from ArcherShao/patch-3 and squashes the following commits:
a607358 [ArcherShao] Update OpenHashSet.scala
Hopefully this can go into 1.0, as a few people on the user list have asked for this.
Author: Andrew Or <andrewor14@gmail.com>
Closes#648 from andrewor14/expose-listeners and squashes the following commits:
e45e1ef [Andrew Or] Add missing colons (minor)
350d643 [Andrew Or] Expose SparkListeners and relevant classes as DeveloperApi
Author: Sandy Ryza <sandy@cloudera.com>
Closes#657 from sryza/sandy-spark-1728 and squashes the following commits:
4751443 [Sandy Ryza] SPARK-1728. JavaRDDLike.mapPartitionsWithIndex requires ClassTag
This is because Mesos calls it with a different environment or something, the result is that the Spark jar is missing and it can't load classes.
This fixes http://apache-spark-user-list.1001560.n3.nabble.com/java-lang-ClassNotFoundException-spark-on-mesos-td3510.html
I have no idea whether this is the right fix, I can only confirm that it fixes the issue for us.
The `registered` method is called from mesos (765ff9bc2a/src/java/jni/org_apache_mesos_MesosExecutorDriver.cpp)
I am unsure which commit caused this regression
Author: Bouke van der Bijl <boukevanderbijl@gmail.com>
Closes#620 from bouk/mesos-classloader-fix and squashes the following commits:
c13eae0 [Bouke van der Bijl] Use getContextOrSparkClassLoader in SparkEnv and CompressionCodec
See related discussion at https://github.com/apache/spark/pull/468
This PR may still overstep what you have in mind, but let me put it on the table to start. Besides fixing the issue, it has one substantive change, and that is to manage Hadoop-specific things only in Hadoop-related profiles. This does _not_ remove `yarn.version`.
- Moves the YARN and Hadoop profiles together in pom.xml. Sorry that this makes the diff a little hard to grok but the changes are only as follows.
- Removes `hadoop.major.version`
- Introduce `hadoop-2.2` and `hadoop-2.3` profiles to control Hadoop-specific changes:
- like the protobuf version issue - this was only 'solved' now by enabling YARN for 2.2+, which is really an orthogonal issue
- like the jets3t version issue now
- Hadoop profiles set an appropriate default `hadoop.version`, that can be overridden
- _(YARN profiles in the parent now only exist to add the sub-module)_
- Fixes the jets3t dependency issue
- and makes it a runtime dependency
- and centralizes config of this guy in the parent pom
- Updates build docs
- Updates SBT build too
- and fixes a regex problem along the way
Author: Sean Owen <sowen@cloudera.com>
Closes#629 from srowen/SPARK-1556 and squashes the following commits:
c3fa967 [Sean Owen] Fix hadoop-2.4 profile typo in doc
a2105fd [Sean Owen] Add hadoop-2.4 profile and don't set hadoop.version in profiles
274f4f9 [Sean Owen] Make jets3t a runtime dependency, and bring its exclusion up into parent config
bbed826 [Sean Owen] Use jets3t 0.9.0 for Hadoop 2.3+ (and correct similar regex issue in SBT build)
f21f356 [Sean Owen] Build changes to set up for jets3t fix
Catching the InvocationTargetException, printing getTargetException.
Author: Sandeep <sandeep@techaddict.me>
Closes#630 from techaddict/SPARK-1710 and squashes the following commits:
834d79b [Sandeep] changes from srowen suggestions
109d604 [Sandeep] SPARK-1710: spark-submit should print better errors than "InvocationTargetException"
For consideration. This was proposed in related discussion: https://github.com/apache/spark/pull/569
Author: Sean Owen <sowen@cloudera.com>
Closes#635 from srowen/SPARK-1629.2 and squashes the following commits:
a442b98 [Sean Owen] Depend on commons lang3 (already used by tachyon) as it's used in ReplSuite, and return to use lang3 utility in Utils.scala
Previously, we indicated disconnected(), which keeps the application in a limbo state where it has no executors but thinks it will get them soon.
This is a bug fix that hopefully can be included in 1.0.
Author: Aaron Davidson <aaron@databricks.com>
Closes#605 from aarondav/appremoved and squashes the following commits:
bea02a2 [Aaron Davidson] SPARK-1689 AppClient should indicate app is dead() when removed
Should lookup `shutdownDeleteTachyonPaths` instead of `shutdownDeletePaths`. Together with a minor style clean up: `find {...}.isDefined` to `exists {...}`.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#575 from liancheng/tachyonFix and squashes the following commits:
deb8f31 [Cheng Lian] Fixed logical error in when cleanup Tachyon files and minor style cleanup
Move the doAs in Executor higher up so that we only have 1 ugi and aren't leaking filesystems.
Fix spark on yarn to work when the cluster is running as user "yarn" but the clients are launched as the user and want to read/write to hdfs as the user.
Note this hasn't been fully tested yet. Need to test in standalone mode.
Putting this up for people to look at and possibly test. I don't have access to a mesos cluster.
This is alternative to https://github.com/apache/spark/pull/607
Author: Thomas Graves <tgraves@apache.org>
Closes#621 from tgravescs/SPARK-1676 and squashes the following commits:
244d55a [Thomas Graves] fix line length
44163d4 [Thomas Graves] Rework
9398853 [Thomas Graves] change to have doAs in executor higher up.
This will ensure that sockets do not build up over the course of a job, and that cancellation successfully cleans up sockets.
Tested in standalone mode. More file descriptors spawn than expected (around 1000ish rather than the expected 8ish) but they do not pile up between runs, or as high as before (where they went up to around 5k).
Author: Aaron Davidson <aaron@databricks.com>
Closes#623 from aarondav/pyspark2 and squashes the following commits:
0ca13bb [Aaron Davidson] SPARK-1700: Close socket file descriptors on task completion
Author: wangfei <wangfei_hello@126.com>
Closes#613 from scwf/masterIndex and squashes the following commits:
1463056 [wangfei] delete no use var: masterIndex
Modifications to Spark core are limited to exposing functionality to test files + minor style fixes.
(728 / 769 lines are from tests)
Author: Andrew Or <andrewor14@gmail.com>
Closes#591 from andrewor14/event-log-tests and squashes the following commits:
2883837 [Andrew Or] Merge branch 'master' of github.com:apache/spark into event-log-tests
c3afcea [Andrew Or] Compromise
2d5daf8 [Andrew Or] Use temp directory provided by the OS rather than /tmp
2b52151 [Andrew Or] Remove unnecessary file delete + add a comment
62010fd [Andrew Or] More cleanup (renaming variables, updating comments etc)
ad2beff [Andrew Or] Clean up EventLoggingListenerSuite + modify a few comments
862e752 [Andrew Or] Merge branch 'master' of github.com:apache/spark into event-log-tests
e0ba2f8 [Andrew Or] Fix test failures caused by race condition in processing/mutating events
b990453 [Andrew Or] ReplayListenerBus suite - tests do not all pass yet
ab66a84 [Andrew Or] Tests for FileLogger + delete file after tests
187bb25 [Andrew Or] Formatting and renaming variables
769336f [Andrew Or] Merge branch 'master' of github.com:apache/spark into event-log-tests
5d38ffe [Andrew Or] Clean up EventLoggingListenerSuite + add comments
e12f4b1 [Andrew Or] Preliminary tests for EventLoggingListener (need major cleanup)
Author: witgo <witgo@qq.com>
Closes#581 from witgo/SPARK-1659 and squashes the following commits:
0b2cf98 [witgo] Delete spark-submit obsolete usage: "--arg ARG"
...OS_WINDOWS`
Author: witgo <witgo@qq.com>
Closes#569 from witgo/SPARK-1629 and squashes the following commits:
31520eb [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1629
fcaafd7 [witgo] merge mastet
49e248e [witgo] Fix SPARK-1629: Spark should inline use of commons-lang `SystemUtils.IS_OS_WINDOWS`
This reopens https://github.com/apache/incubator-spark/pull/640 against the new repo
Author: Sandy Ryza <sandy@cloudera.com>
Closes#30 from sryza/sandy-spark-1004 and squashes the following commits:
89889d4 [Sandy Ryza] Move unzipping py4j to the generate-resources phase so that it gets included in the jar the first time
5165a02 [Sandy Ryza] Fix docs
fd0df79 [Sandy Ryza] PySpark on YARN
In XORShiftRandom.scala, use val "million" instead of constant "1e6.toInt".
Delete vals that never used in other files.
Author: WangTao <barneystinson@aliyun.com>
Closes#565 from WangTaoTheTonic/master and squashes the following commits:
17cacfc [WangTao] Handle the unused assignment, method parameters and symbol inspected by Intellij IDEA
37b4090 [WangTao] Handle the vals that never used
Args for worker rather than master
Author: Chen Chao <crazyjvm@gmail.com>
Closes#587 from CrazyJvm/patch-6 and squashes the following commits:
b54b89f [Chen Chao] Args for worker rather than master
Author: witgo <witgo@qq.com>
Closes#423 from witgo/zipWithIndex and squashes the following commits:
039ec04 [witgo] Merge branch 'master' of https://github.com/apache/spark into zipWithIndex
24d74c9 [witgo] review commit
763a5e4 [witgo] Merge branch 'master' of https://github.com/apache/spark into zipWithIndex
59747d1 [witgo] review commit
7bf4d06 [witgo] Merge branch 'master' of https://github.com/apache/spark into zipWithIndex
daa8f84 [witgo] review commit
4070613 [witgo] Merge branch 'master' of https://github.com/apache/spark into zipWithIndex
18e6c97 [witgo] java api zipWithIndex test
11e2e7f [witgo] add zipWithIndex zipWithUniqueId methods to java api
This adds minimal setting of event log directory/files permissions. To have a secure environment the user must manually create the top level event log directory and set permissions up. We can add logic to do that automatically later if we want.
Author: Thomas Graves <tgraves@apache.org>
Closes#538 from tgravescs/SPARK-1557 and squashes the following commits:
e471d8e [Thomas Graves] rework
d8b6620 [Thomas Graves] update use of octal
3ca9b79 [Thomas Graves] Updated based on comments
5a09709 [Thomas Graves] add in missing import
3150ed6 [Thomas Graves] SPARK-1557 Set permissions on event log files/directories
This is a straightforward fix.
Author: Patrick Wendell <pwendell@gmail.com>
This patch had conflicts when merged, resolved by
Committer: Patrick Wendell <pwendell@gmail.com>
Closes#578 from pwendell/spark-submit-yarn and squashes the following commits:
96027c7 [Patrick Wendell] Test fixes
b5be173 [Patrick Wendell] Review feedback
4ac9cac [Patrick Wendell] SPARK-1652: spark-submit for yarn prints warnings even though calling as expected
Deals with two issues:
1. Spark shell didn't correctly pass quoted arguments to spark-submit.
```./bin/spark-shell --driver-java-options "-Dfoo=f -Dbar=b"```
2. Spark submit used deprecated environment variables (SPARK_CLASSPATH)
which triggered warnings. Now we use new, more narrowly scoped,
variables.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#576 from pwendell/spark-submit and squashes the following commits:
67004c9 [Patrick Wendell] SPARK-1654 and SPARK-1653: Fixes in spark-submit.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#579 from pwendell/spark-submit-yarn-2 and squashes the following commits:
05e1b11 [Patrick Wendell] Small fix
d2a40ad [Patrick Wendell] SPARK-1652: Spark submit should fail gracefully if YARN support not enabled
This includes some minor code clean-up as well. The main change is that small files are not memory mapped. There is a nicer way to write that code block using Scala's `Try` but to make it easy to back port and as simple as possible, I opted for the more explicit but less pretty format.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#43 from pwendell/block-iter-logging and squashes the following commits:
1cff512 [Patrick Wendell] Small issue from merge.
49f6c269 [Patrick Wendell] Merge remote-tracking branch 'apache/master' into block-iter-logging
4943351 [Patrick Wendell] Added a test and feedback on mateis review
a637a18 [Patrick Wendell] Review feedback and adding rewind() when reading byte buffers.
b76b95f [Patrick Wendell] Review feedback
4e1514e [Patrick Wendell] Don't memory map for small files
d238b88 [Patrick Wendell] Some logging and clean-up
This modifies spark-submit to do something more like the Hadoop `jar`
command. Now we have the following syntax:
./bin/spark-submit [options] user.jar [user options]
Author: Patrick Wendell <pwendell@gmail.com>
Closes#563 from pwendell/spark-submit and squashes the following commits:
32241fc [Patrick Wendell] Review feedback
3adfb69 [Patrick Wendell] Small fix
bc48139 [Patrick Wendell] SPARK-1606: Infer user application arguments instead of requiring --arg.
We may want to evolve these in the future to add things like SSDs, so let's mark them as experimental for now. Long-term the right solution might be some kind of builder. The stable API should be the existing StorageLevel constants.
Author: Sandeep <sandeep@techaddict.me>
Closes#551 from techaddict/SPARK-1467 and squashes the following commits:
6bdda24 [Sandeep] SPARK-1467: Make StorageLevel.apply() factory methods as Developer Api's We may want to evolve these in the future to add things like SSDs, so let's mark them as experimental for now. Long-term the right solution might be some kind of builder. The stable API should be the existing StorageLevel constants.
...ap
Author: Sandy Ryza <sandy@cloudera.com>
Closes#559 from sryza/sandy-spark-1632 and squashes the following commits:
a6cd352 [Sandy Ryza] Only compute hashes once
04e3884 [Sandy Ryza] SPARK-1632. Remove unnecessary boxing in compares in ExternalAppendOnlyMap
https://spark-project.atlassian.net/browse/SPARK-1235
In the current implementation, the running job will hang if the DAGScheduler crashes for some reason (eventProcessActor throws exception in receive() )
The reason is that the actor will automatically restart when the exception is thrown during the running but is not captured properly (Akka behaviour), and the JobWaiters are still waiting there for the completion of the tasks
In this patch, I refactored the DAGScheduler with Akka and manage the eventProcessActor with supervisor, so that upon the failure of a eventProcessActor, the supervisor will terminate the EventProcessActor and close the SparkContext
thanks for @kayousterhout and @markhamstra to give the hints in JIRA
Author: CodingCat <zhunansjtu@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>
Author: Nan Zhu <CodingCat@users.noreply.github.com>
Closes#186 from CodingCat/SPARK-1235 and squashes the following commits:
a7fb0ee [CodingCat] throw Exception on failure of creating DAG
124d82d [CodingCat] blocking the constructor until event actor is ready
baf2d38 [CodingCat] fix the issue brought by non-blocking actorOf
35c886a [CodingCat] fix bug
82d08b3 [CodingCat] calling actorOf on system to ensure it is blocking
310a579 [CodingCat] style fix
cd02d9a [Nan Zhu] small fix
561cfbc [CodingCat] recover doCheckpoint
c048d0e [CodingCat] call submitWaitingStages for every event
a9eea039 [CodingCat] address Matei's comments
ac878ab [CodingCat] typo fix
5d1636a [CodingCat] re-trigger the test.....
9dfb033 [CodingCat] remove unnecessary changes
a7a2a97 [CodingCat] add StageCancelled message
fdf3b17 [CodingCat] just to retrigger the test......
089bc2f [CodingCat] address andrew's comments
228f4b0 [CodingCat] address comments from Mark
b68c1c7 [CodingCat] refactor DAGScheduler with Akka
810efd8 [Xiangrui Meng] akka solution
It seems that the val "startTime" and "endTime" is never used, so delete them.
Author: WangTao <barneystinson@aliyun.com>
Closes#553 from WangTaoTheTonic/master and squashes the following commits:
4fcb639 [WangTao] Delete the val that never used
It registers more Scala classes, including things like Ranges that we had to register manually before. See https://github.com/twitter/chill/releases for Chill's change log.
Author: Matei Zaharia <matei@databricks.com>
Closes#543 from mateiz/chill-0.3.6 and squashes the following commits:
a1dc5e0 [Matei Zaharia] Upgrade Chill to 0.3.6 and remove our special registration of Ranges
This simplifies the shell a bunch and passes all arguments through to spark-submit.
There is a tiny incompatibility from 0.9.1 which is that you can't put `-c` _or_ `--cores`, only `--cores`. However, spark-submit will give a good error message in this case, I don't think many people used this, and it's a trivial change for users.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#542 from pwendell/spark-shell and squashes the following commits:
9eb3e6f [Patrick Wendell] Updating Spark docs
b552459 [Patrick Wendell] Andrew's feedback
97720fa [Patrick Wendell] Review feedback
aa2900b [Patrick Wendell] SPARK-1619 Launch spark-shell with spark-submit
Oopsie in #504.
Author: Aaron Davidson <aaron@databricks.com>
Closes#527 from aarondav/stop and squashes the following commits:
8d1446a [Aaron Davidson] Call correct stop().
1617: These changes expose the receiver state (active or inactive) and last error in the UI
1618: If the socket receiver cannot connect in the first attempt, it should try to restart after a delay. That was broken, as the thread that restarts (hence, stops) the receiver waited on Thread.join on itself!
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#540 from tdas/streaming-ui-fix and squashes the following commits:
e469434 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into streaming-ui-fix
dbddf75 [Tathagata Das] Style fix.
66df1a5 [Tathagata Das] Merge remote-tracking branch 'apache/master' into streaming-ui-fix
ad98bc9 [Tathagata Das] Refactored streaming listener to use ReceiverInfo.
d7f849c [Tathagata Das] Revert "Moved BatchInfo from streaming.scheduler to streaming.ui"
5c80919 [Tathagata Das] Moved BatchInfo from streaming.scheduler to streaming.ui
da244f6 [Tathagata Das] Fixed socket receiver as well as made receiver state and error visible in the streamign UI.
Unfortunately, this is not exhaustive - particularly hive tests still fail due to path issues.
Author: Mridul Muralidharan <mridulm80@apache.org>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#505 from mridulm/windows_fixes and squashes the following commits:
ef12283 [Mridul Muralidharan] Move to org.apache.commons.lang3 for StringEscapeUtils. Earlier version was buggy appparently
cdae406 [Mridul Muralidharan] Remove leaked changes from > 2G fix branch
3267f4b [Mridul Muralidharan] Fix build failures
35b277a [Mridul Muralidharan] Fix Scalastyle failures
bc69d14 [Mridul Muralidharan] Change from hardcoded path separator
10c4d78 [Mridul Muralidharan] Use explicit encoding while using getBytes
1337abd [Mridul Muralidharan] fix classpath while running in windows
* Additions to the PySpark API to cancel jobs
* Monitor Thread in PythonRDD to kill Python workers if a task is interrupted
Author: Ahir Reddy <ahirreddy@gmail.com>
Closes#541 from ahirreddy/python-cancel and squashes the following commits:
dfdf447 [Ahir Reddy] Changed success -> completed and made logging message clearer
6c860ab [Ahir Reddy] PR Comments
4b4100a [Ahir Reddy] Success flag
adba6ed [Ahir Reddy] Destroy python workers
27a2f8f [Ahir Reddy] Start the writer thread...
d422f7b [Ahir Reddy] Remove unnecesssary vals
adda337 [Ahir Reddy] Busy wait on the ocntext.interrupted flag, and then kill the python worker
d9e472f [Ahir Reddy] Revert "removed unnecessary vals"
5b9cae5 [Ahir Reddy] removed unnecessary vals
07b54d9 [Ahir Reddy] Fix canceling unit test
8ae9681 [Ahir Reddy] Don't interrupt worker
7722342 [Ahir Reddy] Monitor Thread for python workers
db04e16 [Ahir Reddy] Added canceling api to PySpark
Original poster is @zsxwing, who reported this bug in #516.
Much of SparkListenerSuite relies on LiveListenerBus's `waitUntilEmpty()` method. As the name suggests, this waits until the event queue is empty. However, the following race condition could happen:
(1) We dequeue an event
(2) The queue is empty, we return true (even though the event has not been processed)
(3) The test asserts something assuming that all listeners have finished executing (and fails)
(4) The listeners receive and process the event
This PR makes (1) and (4) atomic by synchronizing around it. To do that, however, we must avoid using `eventQueue.take`, which is blocking and will cause a deadlock if we synchronize around it. As a workaround, we use the non-blocking `eventQueue.poll` + a semaphore to provide the same semantics.
This has been a possible race condition for a long time, but for some reason we've never run into it.
Author: Andrew Or <andrewor14@gmail.com>
Closes#544 from andrewor14/stage-info-test-fix and squashes the following commits:
3cbe40c [Andrew Or] Merge github.com:apache/spark into stage-info-test-fix
56dbbcb [Andrew Or] Check if event is actually added before releasing semaphore
eb486ae [Andrew Or] Synchronize accesses to the LiveListenerBus' event queue
This allows the view acls set by the user to be enforced by the history server. It also fixes filters being applied properly.
Author: Thomas Graves <tgraves@apache.org>
Closes#509 from tgravescs/SPARK-1489 and squashes the following commits:
869c186 [Thomas Graves] change to either acls enabled or disabled
0d8333c [Thomas Graves] Add history ui policy to allow acls to either use application set, history server force acls on, or off
65148b5 [Thomas Graves] SPARK-1489 Fix the HistoryServer view acls
The raw input data is stored as blocks in BlockManagers. Earlier they were cleared by cleaner ttl. Now since streaming does not require cleaner TTL to be set, the block would not get cleared. This increases up the Spark's memory usage, which is not even accounted and shown in the Spark storage UI. It may cause the data blocks to spill over to disk, which eventually slows down the receiving of data (persisting to memory become bottlenecked by writing to disk).
The solution in this PR is to automatically remove those blocks. The mechanism to keep track of which BlockRDDs (which has presents the raw data blocks as a RDD) can be safely cleared already exists. Just use it to explicitly remove blocks from BlockRDDs.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#512 from tdas/block-rdd-unpersist and squashes the following commits:
d25e610 [Tathagata Das] Merge remote-tracking branch 'apache/master' into block-rdd-unpersist
5f46d69 [Tathagata Das] Merge remote-tracking branch 'apache/master' into block-rdd-unpersist
2c320cd [Tathagata Das] Updated configuration with spark.streaming.unpersist setting.
2d4b2fd [Tathagata Das] Automatically removed input blocks
copying form previous pull request https://github.com/apache/spark/pull/462
Its probably better to let the underlying language implementation take care of the default . This was easier to do with python as the default value for seed in random and numpy random is None.
In Scala/Java side it might mean propagating an Option or null(oh no!) down the chain until where the Random is constructed. But, looks like the convention in some other methods was to use System.nanoTime. So, followed that convention.
Conflict with overloaded method in sql.SchemaRDD.sample which also defines default params.
sample(fraction, withReplacement=false, seed=math.random)
Scala does not allow more than one overloaded to have default params. I believe the author intended to override the RDD.sample method and not overload it. So, changed it.
If backward compatible is important, 3 new method can be introduced (without default params) like this
sample(fraction)
sample(fraction, withReplacement)
sample(fraction, withReplacement, seed)
Added some tests for the scala RDD takeSample method.
Author: Arun Ramakrishnan <smartnut007@gmail.com>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#477 from smartnut007/master and squashes the following commits:
07bb06e [Arun Ramakrishnan] SPARK-1438 fixing more space formatting issues
b9ebfe2 [Arun Ramakrishnan] SPARK-1438 removing redundant import of random in python rddsampler
8d05b1a [Arun Ramakrishnan] SPARK-1438 RDD . Replace System.nanoTime with a Random generated number. python: use a separate instance of Random instead of seeding language api global Random instance.
69619c6 [Arun Ramakrishnan] SPARK-1438 fix spacing issue
0c247db [Arun Ramakrishnan] SPARK-1438 RDD language apis to support optional seed in RDD methods sample/takeSample
As reported in https://spark-project.atlassian.net/browse/SPARK-1104
By @pwendell: "Sometimes due to large shuffles executors will take a long time shutting down. In particular this can happen if large numbers of shuffle files are around (this will be alleviated by SPARK-1103, but nonetheless...).
The symptom is you have DEAD workers sitting around in the UI and the existing workers keep trying to re-register but can't because they've been assumed dead."
In this patch, I add lines in the handler of InterruptedException in workerThread of executorRunner, so that the process.destroy() and process.waitFor() can only block the workerThread instead of blocking the worker Actor...
---------
analysis: process.destroy() is a blocking method, i.e. it only returns when all shutdownHook threads return...so calling it in Worker thread will make Worker block for a long while....
about what will happen on the shutdown hooks when the JVM process is killed: http://www.tutorialspoint.com/java/lang/runtime_addshutdownhook.htm
Author: CodingCat <zhunansjtu@gmail.com>
Closes#35 from CodingCat/SPARK-1104 and squashes the following commits:
85767da [CodingCat] add null checking and remove unnecessary killProce
3107aeb [CodingCat] address Aaron's comments
eb615ba [CodingCat] kill the process when the error happens
0accf2f [CodingCat] set process to null after killed it
1d511c8 [CodingCat] kill Process in workerThread
Here I've added the ability for the History server to login from a kerberos keytab file so that the history server can be run as a super user and stay up for along period of time while reading the history files from HDFS.
Author: Thomas Graves <tgraves@apache.org>
Closes#513 from tgravescs/SPARK-1490 and squashes the following commits:
e204a99 [Thomas Graves] remove extra logging
5418daa [Thomas Graves] fix typo in config
0076b99 [Thomas Graves] Update docs
4d76545 [Thomas Graves] SPARK-1490 Add kerberos support to the HistoryServer
JIRA: https://issues.apache.org/jira/browse/SPARK-1611
Author: zsxwing <zsxwing@gmail.com>
Closes#534 from zsxwing/SPARK-1611 and squashes the following commits:
96af089 [zsxwing] SPARK-1611: Fix incorrect initialization order in AppendOnlyMap
This should go into 1.0 since it would return wrong data when the bug happens (which is pretty likely if cancellation is used). Test case attached.
1. Do not put partially executed partitions into cache (in task killing).
2. Iterator returned by CacheManager#getOrCompute was not an InterruptibleIterator, and was thus leading to uninterruptible jobs.
Thanks @aarondav and @ahirreddy for reporting and helping debug.
Author: Reynold Xin <rxin@apache.org>
Closes#521 from rxin/kill and squashes the following commits:
401033f [Reynold Xin] Merge branch 'master' of https://git-wip-us.apache.org/repos/asf/spark into kill
7a7bdd2 [Reynold Xin] Add a new line in the end of JobCancellationSuite.scala.
35cd9f7 [Reynold Xin] Fixed a bug that partially executed partitions can be put into cache (in task killing).
mvn test fails (intermittently) due to thread leak - since scalatest runs all tests in same vm.
Author: Mridul Muralidharan <mridulm80@apache.org>
Closes#504 from mridulm/resource_leak_fixes and squashes the following commits:
a5d10d0 [Mridul Muralidharan] Prevent thread leaks while running tests : cleanup all threads when SparkContext.stop is invoked. Causes tests to fail
7b5e19c [Mridul Muralidharan] Prevent NPE while running tests
JIRA: https://issues.apache.org/jira/browse/SPARK-1589
Author: zsxwing <zsxwing@gmail.com>
Closes#508 from zsxwing/SPARK-1589 and squashes the following commits:
570c67a [zsxwing] SPARK-1589: Fix the incorrect compare
Also adds a unit test.
Author: Aaron Davidson <aaron@databricks.com>
Closes#522 from aarondav/cancel2 and squashes the following commits:
565c253 [Aaron Davidson] Update Java api for setJobGroup with interruptOnCancel
65b33d8 [Aaron Davidson] Add unit test for Thread interruption on cancellation
The two modified tests may fail if the race condition does not bid in our favor...
Author: Andrew Or <andrewor14@gmail.com>
Closes#516 from andrewor14/stage-info-test-fix and squashes the following commits:
b4b6100 [Andrew Or] Add/replace missing waitUntilEmpty() calls to listener bus
In https://issues.apache.org/jira/browse/SPARK-1540 we'd like to look at Spark's API to see if we can take advantage of Comparable keys in more places, which will make external spilling more efficient. This PR is a first step towards that that shows how to pass an Ordering when available and still continue functioning otherwise. It does this using a new implicit parameter with a default value of null.
The API is currently only in Scala -- in Java we'd have to add new versions of mapToPair and such that take a Comparator, or a new method to add a "type hint" to an RDD. We can address those later though.
Unfortunately requiring all keys to be Comparable would not work without requiring RDDs in general to contain only Comparable types. The reason is that methods such as distinct() and intersection() do a shuffle, but should be usable on RDDs of any type. So ordering will have to remain an optimization for the types that can be ordered. I think this isn't a horrible outcome though because one of the nice things about Spark's API is that it works on objects of *any* type, without requiring you to specify a schema or implement Writable or stuff like that.
Author: Matei Zaharia <matei@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@apache.org>
Closes#487 from mateiz/ordered-keys and squashes the following commits:
bd565f6 [Matei Zaharia] Pass an Ordering to only one version of groupBy because the Scala language spec doesn't allow having an optional parameter on all of them (this was only compiling in Scala 2.10 due to a bug).
4629965 [Matei Zaharia] Add tests for other versions of groupBy
3beae85 [Matei Zaharia] Added a test for implicit orderings
80b7a3b [Matei Zaharia] Add an optional Ordering parameter to PairRDDFunctions.
Sometimes executor threads are blocked waiting for IO or monitors, and the current implementation of job cancellation may never recover these threads. By simply invoking Thread.interrupt() during cancellation, we can often safely unblock the threads and use them for subsequent work.
Note that this feature must remain optional for now because of a bug in HDFS where Thread.interrupt() may cause nodes to be marked as permanently dead (as the InterruptedException is reinterpreted as an IOException during communication with some node).
Author: Aaron Davidson <aaron@databricks.com>
Closes#498 from aarondav/cancel and squashes the following commits:
e52b829 [Aaron Davidson] Don't use job.properties when null
82f78bb [Aaron Davidson] Update DAGSchedulerSuite
b67f472 [Aaron Davidson] Add comment on why interruptOnCancel is in setJobGroup
4cb9fd6 [Aaron Davidson] SPARK-1582 Invoke Thread.interrupt() when cancelling jobs
This is related to SPARK-1459 / PR #375. Without this fix,
FileLogger.createLogDir() may try to create the log dir on
HDFS, while createWriter() will try to open the log file on
the local file system, leading to interesting errors and
confusion.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#450 from vanzin/event-file-2 and squashes the following commits:
592cdb3 [Marcelo Vanzin] Honor default fs name when initializing event logger.
Previously, the behavior was that if the parent RDD threw any exception other than IOException or FileNotFoundException (which is quite possible for Hadoop input sources), the entire Executor would crash, because the default thread a uncaught exception handler calls System.exit().
This patch avoids two related issues:
1. Always catch exceptions in this reader thread.
2. Don't mask readerException when Python throws an EOFError
after worker.shutdownOutput() is called.
Author: Aaron Davidson <aaron@databricks.com>
Closes#486 from aarondav/pyspark and squashes the following commits:
fbb11e9 [Aaron Davidson] Make sure FileNotFoundExceptions are handled same as before
b9acb3e [Aaron Davidson] SPARK-1572 Don't kill Executor if PythonRDD fails while computing parent
JIRA: https://issues.apache.org/jira/browse/SPARK-1583
Does anyone know why using `java.util.HashMap` rather than `mutable.HashMap`? Some methods of `java.util.HashMap` are not generics and compiler can not help us find similar problems.
Author: zsxwing <zsxwing@gmail.com>
Closes#500 from zsxwing/SPARK-1583 and squashes the following commits:
7bfd74d [zsxwing] SPARK-1583: Fix a bug that using java.util.HashMap by mistake
Even if users use `--arg`, `SparkSubmit` still uses `--args` for child args internally, which triggers a warning message that may confuse users:
~~~
--args is deprecated. Use --arg instead.
~~~
@sryza Does it look good to you?
Author: Xiangrui Meng <meng@databricks.com>
Closes#485 from mengxr/submit-arg and squashes the following commits:
5e1b9fe [Xiangrui Meng] update test
cebbeb7 [Xiangrui Meng] use --arg instead of --args in SparkSubmit to avoid warning messages
**Bug**: After the following command `sc.parallelize(1 to 1000).persist.map(_ + 1).count()` is run, the the persisted RDD is missing from the storage tab of the SparkUI.
**Cause**: The command creates two RDDs in one stage, a `ParallelCollectionRDD` and a `MappedRDD`. However, the existing StageInfo only keeps the RDDInfo of the last RDD associated with the stage (`MappedRDD`), and so all RDD information regarding the first RDD (`ParallelCollectionRDD`) is discarded. In this case, we persist the first RDD, but the StorageTab doesn't know about this RDD because it is not encoded in the StageInfo.
**Fix**: Record information of all RDDs in StageInfo, instead of just the last RDD (i.e. `stage.rdd`). Since stage boundaries are marked by shuffle dependencies, the solution is to traverse the last RDD's dependency tree, visiting only ancestor RDDs related through a sequence of narrow dependencies.
---
This PR also moves RDDInfo to its own file, includes a few style fixes, and adds a unit test for constructing StageInfos.
Author: Andrew Or <andrewor14@gmail.com>
Closes#469 from andrewor14/storage-ui-fix and squashes the following commits:
07fc7f0 [Andrew Or] Add back comment that was accidentally removed (minor)
5d799fe [Andrew Or] Add comment to justify testing of getNarrowAncestors with cycles
9d0e2b8 [Andrew Or] Hide details of getNarrowAncestors from outsiders
d2bac8a [Andrew Or] Deal with cycles in RDD dependency graph + add extensive tests
2acb177 [Andrew Or] Move getNarrowAncestors to RDD.scala
bfe83f0 [Andrew Or] Backtrace RDD dependency tree to find all RDDs that belong to a Stage
In particular when the HADOOP_CONF_DIR is not not specified.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#488 from pwendell/hadoop-cleanup and squashes the following commits:
fe95f13 [Patrick Wendell] Changes based on Andrew's feeback
18d09c1 [Patrick Wendell] Review comments from Andrew
17929cc [Patrick Wendell] Assorted clean-up for Spark-on-YARN.
**Bug**: In the existing history server, there is a `spark.history.updateInterval` seconds delay before application logs show up on the UI.
**Cause**: This is because the following events happen in this order: (1) The background thread that checks for logs starts, but realizes the server has not yet bound and so waits for N seconds, (2) server binds, (3) N seconds later the background thread finds that the server has finally bound to a port, and so finally checks for application logs.
**Fix**: This PR forces the log checking thread to start immediately after binding. It also documents two relevant environment variables that are currently missing.
Author: Andrew Or <andrewor14@gmail.com>
Closes#441 from andrewor14/history-server-fix and squashes the following commits:
b2eb46e [Andrew Or] Document SPARK_PUBLIC_DNS and SPARK_HISTORY_OPTS for the history server
e8d1fbc [Andrew Or] Eliminate delay between binding and checking for logs
Changed the Pyrolite dependency to a build which targets Java 6.
Author: Ahir Reddy <ahirreddy@gmail.com>
Closes#479 from ahirreddy/java6-pyrolite and squashes the following commits:
8ea25d3 [Ahir Reddy] Updated maven build to use java 6 compatible pyrolite
dabc703 [Ahir Reddy] Updated Pyrolite dependency to be Java 6 compatible
as the original PR was merged before this mistake is found....fix here,
Sorry about that @pwendell, @andrewor14, I will be more careful next time
Author: CodingCat <zhunansjtu@gmail.com>
Closes#474 from CodingCat/hotfix_1399 and squashes the following commits:
f3a8ba9 [CodingCat] move outdated comments
A simple change, mostly had to change a bunch of example code.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#438 from pwendell/jar-of-class and squashes the following commits:
aa010ff [Patrick Wendell] SPARK-1496: Have jarOfClass return Option[String]
...g file.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#375 from vanzin/event-file and squashes the following commits:
f673029 [Marcelo Vanzin] [SPARK-1459] Use local path (and not complete URL) when opening local log file.
... so that we don't follow an unspoken set of forbidden rules for adding **@AlphaComponent**, **@DeveloperApi**, and **@Experimental** annotations in the code.
In addition, this PR
(1) removes unnecessary `:: * ::` tags,
(2) adds missing `:: * ::` tags, and
(3) removes annotations for internal APIs.
Author: Andrew Or <andrewor14@gmail.com>
Closes#470 from andrewor14/annotations-fix and squashes the following commits:
92a7f42 [Andrew Or] Document + fix annotation usages
I used the sbt-unidoc plugin (https://github.com/sbt/sbt-unidoc) to create a unified Scaladoc of our public packages, and generate Javadocs as well. One limitation is that I haven't found an easy way to exclude packages in the Javadoc; there is a SBT task that identifies Java sources to run javadoc on, but it's been very difficult to modify it from outside to change what is set in the unidoc package. Some SBT-savvy people should help with this. The Javadoc site also lacks package-level descriptions and things like that, so we may want to look into that. We may decide not to post these right now if it's too limited compared to the Scala one.
Example of the built doc site: http://people.csail.mit.edu/matei/spark-unified-docs/
Author: Matei Zaharia <matei@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Patrick Wendell <pwendell@gmail.com>
Closes#457 from mateiz/better-docs and squashes the following commits:
a63d4a3 [Matei Zaharia] Skip Java/Scala API docs for Python package
5ea1f43 [Matei Zaharia] Fix links to Java classes in Java guide, fix some JS for scrolling to anchors on page load
f05abc0 [Matei Zaharia] Don't include java.lang package names
995e992 [Matei Zaharia] Skip internal packages and class names with $ in JavaDoc
a14a93c [Matei Zaharia] typo
76ce64d [Matei Zaharia] Add groups to Javadoc index page, and a first package-info.java
ed6f994 [Matei Zaharia] Generate JavaDoc as well, add titles, update doc site to use unified docs
acb993d [Matei Zaharia] Add Unidoc plugin for the projects we want Unidoced
The current Network Receiver API makes it slightly complicated to right a new receiver as one needs to create an instance of BlockGenerator as shown in SocketReceiver
https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala#L51
Exposing the BlockGenerator interface has made it harder to improve the receiving process. The API of NetworkReceiver (which was not a very stable API anyways) needs to be change if we are to ensure future stability.
Additionally, the functions like streamingContext.socketStream that create input streams, return DStream objects. That makes it hard to expose functionality (say, rate limits) unique to input dstreams. They should return InputDStream or NetworkInputDStream. This is still not yet implemented.
This PR is blocked on the graceful shutdown PR #247
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#300 from tdas/network-receiver-api and squashes the following commits:
ea27b38 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into network-receiver-api
3a4777c [Tathagata Das] Renamed NetworkInputDStream to ReceiverInputDStream, and ActorReceiver related stuff.
838dd39 [Tathagata Das] Added more events to the StreamingListener to report errors and stopped receivers.
a75c7a6 [Tathagata Das] Address some PR comments and fixed other issues.
91bfa72 [Tathagata Das] Fixed bugs.
8533094 [Tathagata Das] Scala style fixes.
028bde6 [Tathagata Das] Further refactored receiver to allow restarting of a receiver.
43f5290 [Tathagata Das] Made functions that create input streams return InputDStream and NetworkInputDStream, for both Scala and Java.
2c94579 [Tathagata Das] Fixed graceful shutdown by removing interrupts on receiving thread.
9e37a0b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into network-receiver-api
3223e95 [Tathagata Das] Refactored the code that runs the NetworkReceiver into further classes and traits to make them more testable.
a36cc48 [Tathagata Das] Refactored the NetworkReceiver API for future stability.
https://issues.apache.org/jira/browse/SPARK-1399
refactor StageTable a bit to support additional column for failed stage
Author: CodingCat <zhunansjtu@gmail.com>
Author: Nan Zhu <CodingCat@users.noreply.github.com>
Closes#421 from CodingCat/SPARK-1399 and squashes the following commits:
2caba36 [CodingCat] remove dummy tag
77cf305 [CodingCat] create dummy element to wrap columns
3989ce2 [CodingCat] address Aaron's comments
18fc09f [Nan Zhu] fix compile error
00ea30a [Nan Zhu] address Kay's comments
16ac83d [CodingCat] set a default value of failureReason
35df3df [CodingCat] address andrew's comments
06d21a4 [CodingCat] address andrew's comments
25a6db6 [CodingCat] style fix
dc8856d [CodingCat] show stage failure reason in UI
SPARK-1386 changed RDDPage to RddPage but didn't change the filename. I tried sbt/sbt publish-local. Inside the spark-core jar, the unit name is RDDPage.class and hence I got the following error:
~~~
[error] (run-main) java.lang.NoClassDefFoundError: org/apache/spark/ui/storage/RddPage
java.lang.NoClassDefFoundError: org/apache/spark/ui/storage/RddPage
at org.apache.spark.ui.SparkUI.initialize(SparkUI.scala:59)
at org.apache.spark.ui.SparkUI.<init>(SparkUI.scala:52)
at org.apache.spark.ui.SparkUI.<init>(SparkUI.scala:42)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:215)
at MovieLensALS$.main(MovieLensALS.scala:38)
at MovieLensALS.main(MovieLensALS.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
Caused by: java.lang.ClassNotFoundException: org.apache.spark.ui.storage.RddPage
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
at org.apache.spark.ui.SparkUI.initialize(SparkUI.scala:59)
at org.apache.spark.ui.SparkUI.<init>(SparkUI.scala:52)
at org.apache.spark.ui.SparkUI.<init>(SparkUI.scala:42)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:215)
at MovieLensALS$.main(MovieLensALS.scala:38)
at MovieLensALS.main(MovieLensALS.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
~~~
This can be fixed after renaming RddPage to RDDPage, or renaming RDDPage.scala to RddPage.scala. I chose the former since the name `RDD` is common in Spark code.
Author: Xiangrui Meng <meng@databricks.com>
Closes#454 from mengxr/rddpage-fix and squashes the following commits:
f75e544 [Xiangrui Meng] rename RddPage to RDDPage
#446 faced a connection refused exception from these tests, causing them to timeout and fail after a long time. For now, let's disable these tests.
(We recently disabled the corresponding test in streaming in 7863ecca35. These tests are very similar).
Author: Andrew Or <andrewor14@gmail.com>
Closes#466 from andrewor14/ignore-ui-tests and squashes the following commits:
6f5a362 [Andrew Or] Ignore org.apache.spark.ui.UISuite tests
Over time as we've added more deployment modes, this have gotten a bit unwieldy with user-facing configuration options in Spark. Going forward we'll advise all users to run `spark-submit` to launch applications. This is a WIP patch but it makes the following improvements:
1. Improved `spark-env.sh.template` which was missing a lot of things users now set in that file.
2. Removes the shipping of SPARK_CLASSPATH, SPARK_JAVA_OPTS, and SPARK_LIBRARY_PATH to the executors on the cluster. This was an ugly hack. Instead it introduces config variables spark.executor.extraJavaOpts, spark.executor.extraLibraryPath, and spark.executor.extraClassPath.
3. Adds ability to set these same variables for the driver using `spark-submit`.
4. Allows you to load system properties from a `spark-defaults.conf` file when running `spark-submit`. This will allow setting both SparkConf options and other system properties utilized by `spark-submit`.
5. Made `SPARK_LOCAL_IP` an environment variable rather than a SparkConf property. This is more consistent with it being set on each node.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#299 from pwendell/config-cleanup and squashes the following commits:
127f301 [Patrick Wendell] Improvements to testing
a006464 [Patrick Wendell] Moving properties file template.
b4b496c [Patrick Wendell] spark-defaults.properties -> spark-defaults.conf
0086939 [Patrick Wendell] Minor style fixes
af09e3e [Patrick Wendell] Mention config file in docs and clean-up docs
b16e6a2 [Patrick Wendell] Cleanup of spark-submit script and Scala quick start guide
af0adf7 [Patrick Wendell] Automatically add user jar
a56b125 [Patrick Wendell] Responses to Tom's review
d50c388 [Patrick Wendell] Merge remote-tracking branch 'apache/master' into config-cleanup
a762901 [Patrick Wendell] Fixing test failures
ffa00fe [Patrick Wendell] Review feedback
fda0301 [Patrick Wendell] Note
308f1f6 [Patrick Wendell] Properly escape quotes and other clean-up for YARN
e83cd8f [Patrick Wendell] Changes to allow re-use of test applications
be42f35 [Patrick Wendell] Handle case where SPARK_HOME is not set
c2a2909 [Patrick Wendell] Test compile fixes
4ee6f9d [Patrick Wendell] Making YARN doc changes consistent
afc9ed8 [Patrick Wendell] Cleaning up line limits and two compile errors.
b08893b [Patrick Wendell] Additional improvements.
ace4ead [Patrick Wendell] Responses to review feedback.
b72d183 [Patrick Wendell] Review feedback for spark env file
46555c1 [Patrick Wendell] Review feedback and import clean-ups
437aed1 [Patrick Wendell] Small fix
761ebcd [Patrick Wendell] Library path and classpath for drivers
7cc70e4 [Patrick Wendell] Clean up terminology inside of spark-env script
5b0ba8e [Patrick Wendell] Don't ship executor envs
84cc5e5 [Patrick Wendell] Small clean-up
1f75238 [Patrick Wendell] SPARK_JAVA_OPTS --> SPARK_MASTER_OPTS for master settings
4982331 [Patrick Wendell] Remove SPARK_LIBRARY_PATH
6eaf7d0 [Patrick Wendell] executorJavaOpts
0faa3b6 [Patrick Wendell] Stash of adding config options in submit script and YARN
ac2d65e [Patrick Wendell] Change spark.local.dir -> SPARK_LOCAL_DIRS
This gets rid of a warning when compiling core (since we were depending on a deprecated interface with a non-deprecated function). I also tested with javac, and this does the right thing when compiling java code.
Author: Michael Armbrust <michael@databricks.com>
Closes#452 from marmbrus/scalaDeprecation and squashes the following commits:
f628b4d [Michael Armbrust] Use scala deprecation instead of java.
...AsNewAPIHadoopDataset
`writer.close` should be put in the `finally` block to avoid potential resource leaks.
JIRA: https://issues.apache.org/jira/browse/SPARK-1482
Author: zsxwing <zsxwing@gmail.com>
Closes#400 from zsxwing/SPARK-1482 and squashes the following commits:
06b197a [zsxwing] SPARK-1482: Fix potential resource leaks in saveAsHadoopDataset and saveAsNewAPIHadoopDataset
This doesn't require creating new Ordering objects per row. Additionally, [view bounds are going to be deprecated](https://issues.scala-lang.org/browse/SI-7629), so we should get rid of them while APIs are still flexible.
Author: Michael Armbrust <michael@databricks.com>
Closes#410 from marmbrus/viewBounds and squashes the following commits:
c574221 [Michael Armbrust] fix example.
812008e [Michael Armbrust] Update Java API.
1b9b85c [Michael Armbrust] Update scala doc.
35798a8 [Michael Armbrust] Remove view bounds on Ordered in favor of a context bound on Ordering.
https://issues.apache.org/jira/browse/SPARK-1483
From the original JIRA: " The parameter name is part of the public API in Scala and Python, since you can pass named parameters to a method, so we should name it to this more descriptive term. Everywhere else we refer to "splits" as partitions." - @mateiz
Author: CodingCat <zhunansjtu@gmail.com>
Closes#430 from CodingCat/SPARK-1483 and squashes the following commits:
4b60541 [CodingCat] deprecate defaultMinSplits
ba2c663 [CodingCat] Rename minSplits to minPartitions in public APIs
This only works for the three paths defined in the environment
(SPARK_JAR, SPARK_YARN_APP_JAR and SPARK_LOG4J_CONF).
Tested by running SparkPi with local: and file: URIs against Yarn cluster (no "upload" shows up in logs in the local case).
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#303 from vanzin/yarn-local and squashes the following commits:
82219c1 [Marcelo Vanzin] [SPARK-1395] Allow "local:" URIs to work on Yarn.
It is very confusing when your code throws an exception, but the only stack trace show is in the DAGScheduler. This is a simple patch to include the stack trace for the actual failure in the error message. Suggestions on formatting welcome.
Before:
```
scala> sc.parallelize(1 :: Nil).map(_ => sys.error("Ahh!")).collect()
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0:3 failed 1 times (most recent failure: Exception failure in TID 3 on host localhost: java.lang.RuntimeException: Ahh!)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1055)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1039)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1037)
...
```
After:
```
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0:3 failed 1 times, most recent failure: Exception failure in TID 3 on host localhost: java.lang.RuntimeException: Ahh!
scala.sys.package$.error(package.scala:27)
$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:13)
$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:13)
scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
scala.collection.Iterator$class.foreach(Iterator.scala:727)
scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
scala.collection.AbstractIterator.to(Iterator.scala:1157)
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
org.apache.spark.rdd.RDD$$anonfun$6.apply(RDD.scala:676)
org.apache.spark.rdd.RDD$$anonfun$6.apply(RDD.scala:676)
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1048)
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1048)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:110)
org.apache.spark.scheduler.Task.run(Task.scala:50)
org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:211)
org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:46)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:176)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:744)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1055)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1039)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1037)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1037)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:614)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:614)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:614)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:143)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
```
Author: Michael Armbrust <michael@databricks.com>
Closes#409 from marmbrus/stacktraces and squashes the following commits:
3e4eb65 [Michael Armbrust] indent. include header for driver stack trace.
018b06b [Michael Armbrust] Include stack trace for exceptions in user code.
Author: Kan Zhang <kzhang@apache.org>
Closes#401 from kanzhang/fix-1475 and squashes the following commits:
c6058bd [Kan Zhang] Fixing a race condition in event listener unit test
JIRA issue:[SPARK-1511](https://issues.apache.org/jira/browse/SPARK-1511)
TestUtils.createCompiledClass method use renameTo() to move files which fails when the src and dest files are in different disks or partitions. This pr uses Files.move() instead. The move method will try to use renameTo() and then fall back to copy() and delete(). I think this should handle this issue.
I didn't found a test suite for this file, so I add file existence detection after file moving.
Author: Ye Xianjin <advancedxy@gmail.com>
Closes#427 from advancedxy/SPARK-1511 and squashes the following commits:
a2b97c7 [Ye Xianjin] Based on @srowen's comment, assert file existence.
6f95550 [Ye Xianjin] use Files.move instead of renameTo to handle the src and dest files are in different disks or partitions.
... nicer error messages
There are two improvements to Scheduler Mode:
1. Made the built in ones case insensitive (fair/FAIR, fifo/FIFO).
2. If an invalid mode is given we should print a better error message.
Author: Sandeep <sandeep@techaddict.me>
Closes#388 from techaddict/1469 and squashes the following commits:
a31bbd5 [Sandeep] SPARK-1469: Scheduler mode should accept lower-case definitions and have nicer error messages There are two improvements to Scheduler Mode: 1. Made the built in ones case insensitive (fair/FAIR, fifo/FIFO). 2. If an invalid mode is given we should print a better error message.
Author: Holden Karau <holden@pigscanfly.ca>
Closes#18 from holdenk/addkfoldcrossvalidation and squashes the following commits:
208db9b [Holden Karau] Fix a bad space
e84f2fc [Holden Karau] Fix the test, we should be looking at the second element instead
6ddbf05 [Holden Karau] swap training and validation order
7157ae9 [Holden Karau] CR feedback
90896c7 [Holden Karau] New line
150889c [Holden Karau] Fix up error messages in the MLUtilsSuite
2cb90b3 [Holden Karau] Fix the names in kFold
c702a96 [Holden Karau] Fix imports in MLUtils
e187e35 [Holden Karau] Move { up to same line as whenExecuting(random) in RandomSamplerSuite.scala
c5b723f [Holden Karau] clean up
7ebe4d5 [Holden Karau] CR feedback, remove unecessary learners (came back during merge mistake) and insert an empty line
bb5fa56 [Holden Karau] extra line sadness
163c5b1 [Holden Karau] code review feedback 1.to -> 1 to and folds -> numFolds
5a33f1d [Holden Karau] Code review follow up.
e8741a7 [Holden Karau] CR feedback
b78804e [Holden Karau] Remove cross validation [TODO in another pull request]
91eae64 [Holden Karau] Consolidate things in mlutils
264502a [Holden Karau] Add a test for the bug that was found with BernoulliSampler not copying the complement param
dd0b737 [Holden Karau] Wrap long lines (oops)
c0b7fa4 [Holden Karau] Switch FoldedRDD to use BernoulliSampler and PartitionwiseSampledRDD
08f8e4d [Holden Karau] Fix BernoulliSampler to respect complement
a751ec6 [Holden Karau] Add k-fold cross validation to MLLib
This is not an issue with the driver UI, but when you fire
up the history server, there's currently no way to go back to
the app listing page without editing the browser's location
field (since the logo's link points to the root of the
application's own UI - i.e. the "stages" tab).
The change just points the logo link to "/", which is the app
listing for the history server, and the stages tab for the
driver's UI.
Tested with both history server and live driver.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#408 from vanzin/web-ui-root and squashes the following commits:
1b60cb6 [Marcelo Vanzin] Make "spark logo" link refer to "/".
An initial API that exposes SparkSQL functionality in PySpark. A PythonRDD composed of dictionaries, with string keys and primitive values (boolean, float, int, long, string) can be converted into a SchemaRDD that supports sql queries.
```
from pyspark.context import SQLContext
sqlCtx = SQLContext(sc)
rdd = sc.parallelize([{"field1" : 1, "field2" : "row1"}, {"field1" : 2, "field2": "row2"}, {"field1" : 3, "field2": "row3"}])
srdd = sqlCtx.applySchema(rdd)
sqlCtx.registerRDDAsTable(srdd, "table1")
srdd2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1")
srdd2.collect()
```
The last line yields ```[{"f1" : 1, "f2" : "row1"}, {"f1" : 2, "f2": "row2"}, {"f1" : 3, "f2": "row3"}]```
Author: Ahir Reddy <ahirreddy@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#363 from ahirreddy/pysql and squashes the following commits:
0294497 [Ahir Reddy] Updated log4j properties to supress Hive Warns
307d6e0 [Ahir Reddy] Style fix
6f7b8f6 [Ahir Reddy] Temporary fix MIMA checker. Since we now assemble Spark jar with Hive, we don't want to check the interfaces of all of our hive dependencies
3ef074a [Ahir Reddy] Updated documentation because classes moved to sql.py
29245bf [Ahir Reddy] Cache underlying SchemaRDD instead of generating and caching PythonRDD
f2312c7 [Ahir Reddy] Moved everything into sql.py
a19afe4 [Ahir Reddy] Doc fixes
6d658ba [Ahir Reddy] Remove the metastore directory created by the HiveContext tests in SparkSQL
521ff6d [Ahir Reddy] Trying to get spark to build with hive
ab95eba [Ahir Reddy] Set SPARK_HIVE=true on jenkins
ded03e7 [Ahir Reddy] Added doc test for HiveContext
22de1d4 [Ahir Reddy] Fixed maven pyrolite dependency
e4da06c [Ahir Reddy] Display message if hive is not built into spark
227a0be [Michael Armbrust] Update API links. Fix Hive example.
58e2aa9 [Michael Armbrust] Build Docs for pyspark SQL Api. Minor fixes.
4285340 [Michael Armbrust] Fix building of Hive API Docs.
38a92b0 [Michael Armbrust] Add note to future non-python developers about python docs.
337b201 [Ahir Reddy] Changed com.clearspring.analytics stream version from 2.4.0 to 2.5.1 to match SBT build, and added pyrolite to maven build
40491c9 [Ahir Reddy] PR Changes + Method Visibility
1836944 [Michael Armbrust] Fix comments.
e00980f [Michael Armbrust] First draft of python sql programming guide.
b0192d3 [Ahir Reddy] Added Long, Double and Boolean as usable types + unit test
f98a422 [Ahir Reddy] HiveContexts
79621cf [Ahir Reddy] cleaning up cruft
b406ba0 [Ahir Reddy] doctest formatting
20936a5 [Ahir Reddy] Added tests and documentation
e4d21b4 [Ahir Reddy] Added pyrolite dependency
79f739d [Ahir Reddy] added more tests
7515ba0 [Ahir Reddy] added more tests :)
d26ec5e [Ahir Reddy] added test
e9f5b8d [Ahir Reddy] adding tests
906d180 [Ahir Reddy] added todo explaining cost of creating Row object in python
251f99d [Ahir Reddy] for now only allow dictionaries as input
09b9980 [Ahir Reddy] made jrdd explicitly lazy
c608947 [Ahir Reddy] SchemaRDD now has all RDD operations
725c91e [Ahir Reddy] awesome row objects
55d1c76 [Ahir Reddy] return row objects
4fe1319 [Ahir Reddy] output dictionaries correctly
be079de [Ahir Reddy] returning dictionaries works
cd5f79f [Ahir Reddy] Switched to using Scala SQLContext
e948bd9 [Ahir Reddy] yippie
4886052 [Ahir Reddy] even better
c0fb1c6 [Ahir Reddy] more working
043ca85 [Ahir Reddy] working
5496f9f [Ahir Reddy] doesn't crash
b8b904b [Ahir Reddy] Added schema rdd class
67ba875 [Ahir Reddy] java to python, and python to java
bcc0f23 [Ahir Reddy] Java to python
ab6025d [Ahir Reddy] compiling
For your consideration: scalac currently notes a number of feature warnings during compilation:
```
[warn] there were 65 feature warning(s); re-run with -feature for details
```
Warnings are like:
```
[warn] /Users/srowen/Documents/spark/core/src/main/scala/org/apache/spark/SparkContext.scala:1261: implicit conversion method rddToPairRDDFunctions should be enabled
[warn] by making the implicit value scala.language.implicitConversions visible.
[warn] This can be achieved by adding the import clause 'import scala.language.implicitConversions'
[warn] or by setting the compiler option -language:implicitConversions.
[warn] See the Scala docs for value scala.language.implicitConversions for a discussion
[warn] why the feature should be explicitly enabled.
[warn] implicit def rddToPairRDDFunctions[K: ClassTag, V: ClassTag](rdd: RDD[(K, V)]) =
[warn] ^
```
scalac is suggesting that it's just best practice to explicitly enable certain language features by importing them where used.
This PR simply adds the imports it suggests (and squashes one other Java warning along the way). This leaves just deprecation warnings in the build.
Author: Sean Owen <sowen@cloudera.com>
Closes#404 from srowen/SPARK-1488 and squashes the following commits:
8598980 [Sean Owen] Quiet scalac warnings about language features by explicitly importing language features.
39bc831 [Sean Owen] Enable -feature in scalac to emit language feature warnings
JIRA issue [here](https://issues.apache.org/jira/browse/SPARK-1415).
New Hadoop API of `InputFormat` does not provide the `minSplits` parameter, which makes the API incompatible between `HadoopRDD` and `NewHadoopRDD`. The PR is for constructing compatible APIs.
Though `minSplits` is deprecated by New Hadoop API, we think it is better to make APIs compatible here.
**Note** that `minSplits` in `wholeTextFiles` could only be treated as a *suggestion*, the real number of splits may not be greater than `minSplits` due to `isSplitable()=false`.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#376 from yinxusen/hadoop-min-split and squashes the following commits:
76417f6 [Xusen Yin] refine comments
c10af60 [Xusen Yin] refine comments and rewrite new class for wholeTextFile
766d05b [Xusen Yin] refine Java API and comments
4875755 [Xusen Yin] add minSplits for WholeTextFiles
The Spark codebase is a bit fast-and-loose when accessing classloaders and this has caused a few bugs to surface in master.
This patch defines some utility methods for accessing classloaders. This makes the intention when accessing a classloader much more explicit in the code and fixes a few cases where the wrong one was chosen.
case (a) -> We want the classloader that loaded Spark
case (b) -> We want the context class loader, or if not present, we want (a)
This patch provides a better fix for SPARK-1403 (https://issues.apache.org/jira/browse/SPARK-1403) than the current work around, which it reverts. It also fixes a previously unreported bug that the `./spark-submit` script did not work for running with `local` master. It didn't work because the executor classloader did not properly delegate to the context class loader (if it is defined) and in local mode the context class loader is set by the `./spark-submit` script. A unit test is added for that case.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#398 from pwendell/class-loaders and squashes the following commits:
b4a1a58 [Patrick Wendell] Minor clean up
14f1272 [Patrick Wendell] SPARK-1480: Clean up use of classloaders
[SPARK-1403] I investigated why spark 0.9.0 loads fine on mesos while spark 1.0.0 fails. What I found was that in SparkEnv.scala, while creating the SparkEnv object, the current thread's classloader is null. But in 0.9.0, at the same place, it is set to org.apache.spark.repl.ExecutorClassLoader . I saw that 7edbea41b4 moved it to it current place. I moved it back and saw that 1.0.0 started working fine on mesos.
I just created a minimal patch that allows me to run spark on mesos correctly. It seems like SecurityManager's creation needs to be taken into account for a correct fix. Also moving the creation of the serializer out of SparkEnv might be a part of the right solution. PTAL.
Author: Bharath Bhushan <manku.timma@outlook.com>
Closes#322 from manku-timma/spark-1403 and squashes the following commits:
606c2b9 [Bharath Bhushan] Merge remote-tracking branch 'upstream/master' into spark-1403
ec8f870 [Bharath Bhushan] revert the logger change for java 6 compatibility as PR 334 is doing it
728beca [Bharath Bhushan] Merge remote-tracking branch 'upstream/master' into spark-1403
044027d [Bharath Bhushan] fix compile error
6f260a4 [Bharath Bhushan] Merge remote-tracking branch 'upstream/master' into spark-1403
b3a053f [Bharath Bhushan] Merge remote-tracking branch 'upstream/master' into spark-1403
04b9662 [Bharath Bhushan] add missing line
4803c19 [Bharath Bhushan] Merge remote-tracking branch 'upstream/master' into spark-1403
f3c9a14 [Bharath Bhushan] Merge remote-tracking branch 'upstream/master' into spark-1403
42d3d6a [Bharath Bhushan] used code fragment from @ueshin to fix the problem in a better way
89109d7 [Bharath Bhushan] move the class loader creation back to where it was in 0.9.0
This PR is self-explanatory.
Author: Andrew Or <andrewor14@gmail.com>
Closes#381 from andrewor14/master and squashes the following commits:
3e8dde2 [Andrew Or] Fix comments for #204
When debugging Spark Streaming applications it is necessary to monitor certain metrics that are not shown in the Spark application UI. For example, what is average processing time of batches? What is the scheduling delay? Is the system able to process as fast as it is receiving data? How many records I am receiving through my receivers?
While the StreamingListener interface introduced in the 0.9 provided some of this information, it could only be accessed programmatically. A UI that shows information specific to the streaming applications is necessary for easier debugging. This PR introduces such a UI. It shows various statistics related to the streaming application. Here is a screenshot of the UI running on my local machine.
http://i.imgur.com/1ooDGhm.png
This UI is integrated into the Spark UI running at 4040.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Andrew Or <andrewor14@gmail.com>
Closes#290 from tdas/streaming-web-ui and squashes the following commits:
fc73ca5 [Tathagata Das] Merge pull request #9 from andrewor14/ui-refactor
642dd88 [Andrew Or] Merge SparkUISuite.scala into UISuite.scala
eb30517 [Andrew Or] Merge github.com:apache/spark into ui-refactor
f4f4cbe [Tathagata Das] More minor fixes.
34bb364 [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
252c566 [Tathagata Das] Merge pull request #8 from andrewor14/ui-refactor
e038b4b [Tathagata Das] Addressed Patrick's comments.
125a054 [Andrew Or] Disable serving static resources with gzip
90feb8d [Andrew Or] Address Patrick's comments
89dae36 [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
72fe256 [Tathagata Das] Merge pull request #6 from andrewor14/ui-refactor
2fc09c8 [Tathagata Das] Added binary check exclusions
aa396d4 [Andrew Or] Rename tabs and pages (No more IndexPage.scala)
f8e1053 [Tathagata Das] Added Spark and Streaming UI unit tests.
caa5e05 [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
585cd65 [Tathagata Das] Merge pull request #5 from andrewor14/ui-refactor
914b8ff [Tathagata Das] Moved utils functions to UIUtils.
548c98c [Andrew Or] Wide refactoring of WebUI, UITab, and UIPage (see commit message)
6de06b0 [Tathagata Das] Merge remote-tracking branch 'apache/master' into streaming-web-ui
ee6543f [Tathagata Das] Minor changes based on Andrew's comments.
fa760fe [Tathagata Das] Fixed long line.
1c0bcef [Tathagata Das] Refactored streaming UI into two files.
1af239b [Tathagata Das] Changed streaming UI to attach itself as a tab with the Spark UI.
827e81a [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
168fe86 [Tathagata Das] Merge pull request #2 from andrewor14/ui-refactor
3e986f8 [Tathagata Das] Merge remote-tracking branch 'apache/master' into streaming-web-ui
c78c92d [Andrew Or] Remove outdated comment
8f7323b [Andrew Or] End of file new lines, indentation, and imports (minor)
0d61ee8 [Andrew Or] Merge branch 'streaming-web-ui' of github.com:tdas/spark into ui-refactor
9a48fa1 [Andrew Or] Allow adding tabs to SparkUI dynamically + add example
61358e3 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into streaming-web-ui
53be2c5 [Tathagata Das] Minor style updates.
ed25dfc [Andrew Or] Generalize SparkUI header to display tabs dynamically
a37ad4f [Andrew Or] Comments, imports and formatting (minor)
cd000b0 [Andrew Or] Merge github.com:apache/spark into ui-refactor
7d57444 [Andrew Or] Refactoring the UI interface to add flexibility
aef4dd5 [Tathagata Das] Added Apache licenses.
db27bad [Tathagata Das] Added last batch processing time to StreamingUI.
4d86e98 [Tathagata Das] Added basic stats to the StreamingUI and refactored the UI to a Page to make it easier to transition to using SparkUI later.
93f1c69 [Tathagata Das] Added network receiver information to the Streaming UI.
56cc7fb [Tathagata Das] First cut implementation of Streaming UI.
(This is for discussion at this point -- I'm not suggesting this should be committed.)
This is what removing fastutil looks like. Much of it is straightforward, like using `java.io` buffered stream classes, and Guava for murmurhash3.
Uses of the `FastByteArrayOutputStream` were a little trickier. In only one case though do I think the change to use `java.io` actually entails an extra array copy.
The rest is using `OpenHashMap` and `OpenHashSet`. These are now written in terms of more scala-like operations.
`OpenHashMap` is where I made three non-trivial changes to make it work, and they need review:
- It is no longer private
- The key must be a `ClassTag`
- Unless a lot of other code changes, the key type can't enforce being a supertype of `Null`
It all works and tests pass, and I think there is reason to believe it's OK from a speed perspective.
But what about those last changes?
Author: Sean Owen <sowen@cloudera.com>
Closes#266 from srowen/SPARK-1057-alternate and squashes the following commits:
2601129 [Sean Owen] Fix Map return type error not previously caught
ec65502 [Sean Owen] Updates from matei's review
00bc81e [Sean Owen] Remove use of fastutil and replace with use of java.io, spark.util and Guava classes
Make coalesce test deterministic by setting pre-defined seeds. (Saw random failures in other PRs.)
Author: Xiangrui Meng <meng@databricks.com>
Closes#387 from mengxr/fix-random and squashes the following commits:
59bc16f [Xiangrui Meng] make coalesce test deterministic in RDDSuite
Author: Thomas Graves <tgraves@apache.org>
Closes#344 from tgravescs/SPARK-1417 and squashes the following commits:
c450b5f [Thomas Graves] fix test
e1c1d7e [Thomas Graves] add missing $ to appUIAddress
e982ddb [Thomas Graves] use appUIHostPort in appUIAddress
0803ec2 [Thomas Graves] Review comment updates - remove extra newline, simplify assert in test
658a8ec [Thomas Graves] Add a appUIHostPort routine
0614208 [Thomas Graves] Fix test
2a6b1b7 [Thomas Graves] SPARK-1417: Spark on Yarn - spark UI link from resourcemanager is broken
1. Adds a separate endpoint for the killing logic that is outside of a page.
2. Narrows the scope of the killingEnabled tracking.
3. Some style improvements.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#386 from pwendell/kill-link and squashes the following commits:
8efe02b [Patrick Wendell] Improvements to task killing in the UI.
Author: Sundeep Narravula <sundeepn@superduel.local>
Author: Sundeep Narravula <sundeepn@dhcpx-204-110.corp.yahoo.com>
Closes#246 from sundeepn/uikilljob and squashes the following commits:
5fdd0e2 [Sundeep Narravula] Fix test string
f6fdff1 [Sundeep Narravula] Format fix; reduced line size to less than 100 chars
d1daeb9 [Sundeep Narravula] Incorporating review comments.
8d97923 [Sundeep Narravula] Ability to kill jobs thru the UI. This behavior can be turned on be settings the following variable: spark.ui.killEnabled=true (default=false) Adding DAGScheduler event StageCancelled and corresponding handlers. Added cancellation reason to handlers.
stack these together in a commit else they show up chunk by chunk in different commits.
Author: Sandeep <sandeep@techaddict.me>
Closes#380 from techaddict/white_space and squashes the following commits:
b58f294 [Sandeep] Remove Unnecessary Whitespace's
The new feature of event logging, introduced in #42, allows the user to persist the details of his/her Spark application to storage, and later replay these events to reconstruct an after-the-fact SparkUI.
Currently, however, a persisted UI can only be rendered through the standalone Master. This greatly limits the use case of this new feature as many people also run Spark on Yarn / Mesos.
This PR introduces a new entity called the HistoryServer, which, given a log directory, keeps track of all completed applications independently of a Spark Master. Unlike Master, the HistoryServer needs not be running while the application is still running. It is relatively light-weight in that it only maintains static information of applications and performs no scheduling.
To quickly test it out, generate event logs with ```spark.eventLog.enabled=true``` and run ```sbin/start-history-server.sh <log-dir-path>```. Your HistoryServer awaits on port 18080.
Comments and feedback are most welcome.
---
A few other changes introduced in this PR include refactoring the WebUI interface, which is beginning to have a lot of duplicate code now that we have added more functionality to it. Two new SparkListenerEvents have been introduced (SparkListenerApplicationStart/End) to keep track of application name and start/finish times. This PR also clarifies the semantics of the ReplayListenerBus introduced in #42.
A potential TODO in the future (not part of this PR) is to render live applications in addition to just completed applications. This is useful when applications fail, a condition that our current HistoryServer does not handle unless the user manually signals application completion (by creating the APPLICATION_COMPLETION file). Handling live applications becomes significantly more challenging, however, because it is now necessary to render the same SparkUI multiple times. To avoid reading the entire log every time, which is inefficient, we must handle reading the log from where we previously left off, but this becomes fairly complicated because we must deal with the arbitrary behavior of each input stream.
Author: Andrew Or <andrewor14@gmail.com>
Closes#204 from andrewor14/master and squashes the following commits:
7b7234c [Andrew Or] Finished -> Completed
b158d98 [Andrew Or] Address Patrick's comments
69d1b41 [Andrew Or] Do not block on posting SparkListenerApplicationEnd
19d5dd0 [Andrew Or] Merge github.com:apache/spark
f7f5bf0 [Andrew Or] Make history server's web UI port a Spark configuration
2dfb494 [Andrew Or] Decouple checking for application completion from replaying
d02dbaa [Andrew Or] Expose Spark version and include it in event logs
2282300 [Andrew Or] Add documentation for the HistoryServer
567474a [Andrew Or] Merge github.com:apache/spark
6edf052 [Andrew Or] Merge github.com:apache/spark
19e1fb4 [Andrew Or] Address Thomas' comments
248cb3d [Andrew Or] Limit number of live applications + add configurability
a3598de [Andrew Or] Do not close file system with ReplayBus + fix bind address
bc46fc8 [Andrew Or] Merge github.com:apache/spark
e2f4ff9 [Andrew Or] Merge github.com:apache/spark
050419e [Andrew Or] Merge github.com:apache/spark
81b568b [Andrew Or] Fix strange error messages...
0670743 [Andrew Or] Decouple page rendering from loading files from disk
1b2f391 [Andrew Or] Minor changes
a9eae7e [Andrew Or] Merge branch 'master' of github.com:apache/spark
d5154da [Andrew Or] Styling and comments
5dbfbb4 [Andrew Or] Merge branch 'master' of github.com:apache/spark
60bc6d5 [Andrew Or] First complete implementation of HistoryServer (only for finished apps)
7584418 [Andrew Or] Report application start/end times to HistoryServer
8aac163 [Andrew Or] Add basic application table
c086bd5 [Andrew Or] Add HistoryServer and scripts ++ Refactor WebUI interface
Author: witgo <witgo@qq.com>
Closes#325 from witgo/SPARK-1413 and squashes the following commits:
e57cd8e [witgo] use scala reflection to access and call the SLF4JBridgeHandler methods
45c8f40 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
5e35d87 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
0d5f819 [witgo] review commit
45e5b70 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
fa69dcf [witgo] Merge branch 'master' into SPARK-1413
3c98dc4 [witgo] Merge branch 'master' into SPARK-1413
38160cb [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
ba09bcd [witgo] remove set the parquet log level
a63d574 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
5231ecd [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
3feb635 [witgo] parquet logger use parent handler
fa00d5d [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
8bb6ffd [witgo] enableLogForwarding note fix
edd9630 [witgo] move to
f447f50 [witgo] merging master
5ad52bd [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1413
76670c1 [witgo] review commit
70f3c64 [witgo] Fix SPARK-1413
[SPARK-729](https://spark-project.atlassian.net/browse/SPARK-729) concerns when free variables in closure arguments to transformations are captured. Currently, it is possible for closures to get the environment in which they are serialized (not the environment in which they are created). There are a few possible approaches to solving this problem and this PR will discuss some of them. The approach I took has the advantage of being simple, obviously correct, and minimally-invasive, but it preserves something that has been bothering me about Spark's closure handling, so I'd like to discuss an alternative and get some feedback on whether or not it is worth pursuing.
## What I did
The basic approach I took depends on the work I did for #143, and so this PR is based atop that. Specifically: #143 modifies `ClosureCleaner.clean` to preemptively determine whether or not closures are serializable immediately upon closure cleaning (rather than waiting for an job involving that closure to be scheduled). Thus non-serializable closure exceptions will be triggered by the line defining the closure rather than triggered where the closure is used.
Since the easiest way to determine whether or not a closure is serializable is to attempt to serialize it, the code in #143 is creating a serialized closure as part of `ClosureCleaner.clean`. `clean` currently modifies its argument, but the method in `SparkContext` that wraps it to return a value (a reference to the modified-in-place argument). This branch modifies `ClosureCleaner.clean` so that it returns a value: if it is cleaning a serializable closure, it returns the result of deserializing its serialized argument; therefore it is returning a closure with an environment captured at cleaning time. `SparkContext.clean` then returns the result of `ClosureCleaner.clean`, rather than a reference to its modified-in-place argument.
I've added tests for this behavior (777a1bc). The pull request as it stands, given the changes in #143, is nearly trivial. There is some overhead from deserializing the closure, but it is minimal and the benefit of obvious operational correctness (vs. a more sophisticated but harder-to-validate transformation in `ClosureCleaner`) seems pretty important. I think this is a fine way to solve this problem, but it's not perfect.
## What we might want to do
The thing that has been bothering me about Spark's handling of closures is that it seems like we should be able to statically ensure that cleaning and serialization happen exactly once for a given closure. If we serialize a closure in order to determine whether or not it is serializable, we should be able to hang on to the generated byte buffer and use it instead of re-serializing the closure later. By replacing closures with instances of a sum type that encodes whether or not a closure has been cleaned or serialized, we could handle clean, to-be-cleaned, and serialized closures separately with case matches. Here's a somewhat-concrete sketch (taken from my git stash) of what this might look like:
```scala
package org.apache.spark.util
import java.nio.ByteBuffer
import scala.reflect.ClassManifest
sealed abstract class ClosureBox[T] { def func: T }
final case class RawClosure[T](func: T) extends ClosureBox[T] {}
final case class CleanedClosure[T](func: T) extends ClosureBox[T] {}
final case class SerializedClosure[T](func: T, bytebuf: ByteBuffer) extends ClosureBox[T] {}
object ClosureBoxImplicits {
implicit def closureBoxFromFunc[T <: AnyRef](fun: T) = new RawClosure[T](fun)
}
```
With these types declared, we'd be able to change `ClosureCleaner.clean` to take a `ClosureBox[T=>U]` (possibly generated by implicit conversion) and return a `ClosureBox[T=>U]` (either a `CleanedClosure[T=>U]` or a `SerializedClosure[T=>U]`, depending on whether or not serializability-checking was enabled) instead of a `T=>U`. A case match could thus short-circuit cleaning or serializing closures that had already been cleaned or serialized (both in `ClosureCleaner` and in the closure serializer). Cleaned-and-serialized closures would be represented by a boxed tuple of the original closure and a serialized copy (complete with an environment quiesced at transformation time). Additional implicit conversions could convert from `ClosureBox` instances to the underlying function type where appropriate. Tracking this sort of state in the type system seems like the right thing to do to me.
### Why we might not want to do that
_It's pretty invasive._ Every function type used by every `RDD` subclass would have to change to reflect that they expected a `ClosureBox[T=>U]` instead of a `T=>U`. This obscures what's going on and is not a little ugly. Although I really like the idea of using the type system to enforce the clean-or-serialize once discipline, it might not be worth adding another layer of types (even if we could hide some of the extra boilerplate with judicious application of implicit conversions).
_It statically guarantees a property whose absence is unlikely to cause any serious problems as it stands._ It appears that all closures are currently dynamically cleaned once and it's not obvious that repeated closure-cleaning is likely to be a problem in the future. Furthermore, serializing closures is relatively cheap, so doing it once to check for serialization and once again to actually ship them across the wire doesn't seem like a big deal.
Taken together, these seem like a high price to pay for statically guaranteeing that closures are operated upon only once.
## Other possibilities
I felt like the serialize-and-deserialize approach was best due to its obvious simplicity. But it would be possible to do a more sophisticated transformation within `ClosureCleaner.clean`. It might also be possible for `clean` to modify its argument in a way so that whether or not a given closure had been cleaned would be apparent upon inspection; this would buy us some of the operational benefits of the `ClosureBox` approach but not the static cleanliness.
I'm interested in any feedback or discussion on whether or not the problems with the type-based approach indeed outweigh the advantage, as well as of approaches to this issue and to closure handling in general.
Author: William Benton <willb@redhat.com>
Closes#189 from willb/spark-729 and squashes the following commits:
f4cafa0 [William Benton] Stylistic changes and cleanups
b3d9c86 [William Benton] Fixed style issues in tests
9b56ce0 [William Benton] Added array-element capture test
97e9d91 [William Benton] Split closure-serializability failure tests
12ef6e3 [William Benton] Skip proactive closure capture for runJob
8ee3ee7 [William Benton] Predictable closure environment capture
12c63a7 [William Benton] Added tests for variable capture in closures
d6e8dd6 [William Benton] Don't check serializability of DStream transforms.
4ecf841 [William Benton] Make proactive serializability checking optional.
d8df3db [William Benton] Adds proactive closure-serializablilty checking
21b4b06 [William Benton] Test cases for SPARK-897.
d5947b3 [William Benton] Ensure assertions in Graph.apply are asserted.
Author: Kan Zhang <kzhang@apache.org>
Closes#366 from kanzhang/SPARK-1407 and squashes the following commits:
cd0629f [Kan Zhang] code refactoring and adding test
b073ee6 [Kan Zhang] SPARK-1407 drain event queue before stopping event logger
This patch marks some existing classes as private[spark] and adds two types of API annotations:
- `EXPERIMENTAL API` = experimental user-facing module
- `DEVELOPER API - UNSTABLE` = developer-facing API that might change
There is some discussion of the different mechanisms for doing this here:
https://issues.apache.org/jira/browse/SPARK-1081
I was pretty aggressive with marking things private. Keep in mind that if we want to open something up in the future we can, but we can never reduce visibility.
A few notes here:
- In the past we've been inconsistent with the visiblity of the X-RDD classes. This patch marks them private whenever there is an existing function in RDD that can directly creat them (e.g. CoalescedRDD and rdd.coalesce()). One trade-off here is users can't subclass them.
- Noted that compression and serialization formats don't have to be wire compatible across versions.
- Compression codecs and serialization formats are semi-private as users typically don't instantiate them directly.
- Metrics sources are made private - user only interacts with them through Spark's reflection
Author: Patrick Wendell <pwendell@gmail.com>
Author: Andrew Or <andrewor14@gmail.com>
Closes#274 from pwendell/private-apis and squashes the following commits:
44179e4 [Patrick Wendell] Merge remote-tracking branch 'apache-github/master' into private-apis
042c803 [Patrick Wendell] spark.annotations -> spark.annotation
bfe7b52 [Patrick Wendell] Adding experimental for approximate counts
8d0c873 [Patrick Wendell] Warning in SparkEnv
99b223a [Patrick Wendell] Cleaning up annotations
e849f64 [Patrick Wendell] Merge pull request #2 from andrewor14/annotations
982a473 [Andrew Or] Generalize jQuery matching for non Spark-core API docs
a01c076 [Patrick Wendell] Merge pull request #1 from andrewor14/annotations
c1bcb41 [Andrew Or] DeveloperAPI -> DeveloperApi
0d48908 [Andrew Or] Comments and new lines (minor)
f3954e0 [Andrew Or] Add identifier tags in comments to work around scaladocs bug
99192ef [Andrew Or] Dynamically add badges based on annotations
824011b [Andrew Or] Add support for injecting arbitrary JavaScript to API docs
037755c [Patrick Wendell] Some changes after working with andrew or
f7d124f [Patrick Wendell] Small fixes
c318b24 [Patrick Wendell] Use CSS styles
e4c76b9 [Patrick Wendell] Logging
f390b13 [Patrick Wendell] Better visibility for workaround constructors
d6b0afd [Patrick Wendell] Small chang to existing constructor
403ba52 [Patrick Wendell] Style fix
870a7ba [Patrick Wendell] Work around for SI-8479
7fb13b2 [Patrick Wendell] Changes to UnionRDD and EmptyRDD
4a9e90c [Patrick Wendell] EXPERIMENTAL API --> EXPERIMENTAL
c581dce [Patrick Wendell] Changes after building against Shark.
8452309 [Patrick Wendell] Style fixes
1ed27d2 [Patrick Wendell] Formatting and coloring of badges
cd7a465 [Patrick Wendell] Code review feedback
2f706f1 [Patrick Wendell] Don't use floats
542a736 [Patrick Wendell] Small fixes
cf23ec6 [Patrick Wendell] Marking GraphX as alpha
d86818e [Patrick Wendell] Another naming change
5a76ed6 [Patrick Wendell] More visiblity clean-up
42c1f09 [Patrick Wendell] Using better labels
9d48cbf [Patrick Wendell] Initial pass
I still need to do a small bit of re-factoring [mostly the one Java file I'll switch it back to a Scala file and use it in both the close loaders], but comments on other things I should do would be great.
Author: Holden Karau <holden@pigscanfly.ca>
Closes#217 from holdenk/spark-939-allow-user-jars-to-take-precedence-over-spark-jars and squashes the following commits:
cf0cac9 [Holden Karau] Fix the executorclassloader
1955232 [Holden Karau] Fix long line in TestUtils
8f89965 [Holden Karau] Fix tests for new class name
7546549 [Holden Karau] CR feedback, merge some of the testutils methods down, rename the classloader
644719f [Holden Karau] User the class generator for the repl class loader tests too
f0b7114 [Holden Karau] Fix the core/src/test/scala/org/apache/spark/executor/ExecutorURLClassLoaderSuite.scala tests
204b199 [Holden Karau] Fix the generated classes
9f68f10 [Holden Karau] Start rewriting the ExecutorURLClassLoaderSuite to not use the hard coded classes
858aba2 [Holden Karau] Remove a bunch of test junk
261aaee [Holden Karau] simplify executorurlclassloader a bit
7a7bf5f [Holden Karau] CR feedback
d4ae848 [Holden Karau] rewrite component into scala
aa95083 [Holden Karau] CR feedback
7752594 [Holden Karau] re-add https comment
a0ef85a [Holden Karau] Fix style issues
125ea7f [Holden Karau] Easier to just remove those files, we don't need them
bb8d179 [Holden Karau] Fix issues with the repl class loader
241b03d [Holden Karau] fix my rat excludes
a343350 [Holden Karau] Update rat-excludes and remove a useless file
d90d217 [Holden Karau] Fix fall back with custom class loader and add a test for it
4919bf9 [Holden Karau] Fix parent calling class loader issue
8a67302 [Holden Karau] Test are good
9e2d236 [Holden Karau] It works comrade
691ee00 [Holden Karau] It works ish
dc4fe44 [Holden Karau] Does not depend on being in my home directory
47046ff [Holden Karau] Remove bad import'
22d83cb [Holden Karau] Add a test suite for the executor url class loader suite
7ef4628 [Holden Karau] Clean up
792d961 [Holden Karau] Almost works
16aecd1 [Holden Karau] Doesn't quite work
8d2241e [Holden Karau] Adda FakeClass for testing ClassLoader precedence options
648b559 [Holden Karau] Both class loaders compile. Now for testing
e1d9f71 [Holden Karau] One loader workers.
Author: Holden Karau <holden@pigscanfly.ca>
Closes#242 from holdenk/spark-1320-cogroupandgroupshouldpassiterator and squashes the following commits:
f289536 [Holden Karau] Fix bad merge, should have been Iterable rather than Iterator
77048f8 [Holden Karau] Fix merge up to master
d3fe909 [Holden Karau] use toSeq instead
7a092a3 [Holden Karau] switch resultitr to resultiterable
eb06216 [Holden Karau] maybe I should have had a coffee first. use correct import for guava iterables
c5075aa [Holden Karau] If guava 14 had iterables
2d06e10 [Holden Karau] Fix Java 8 cogroup tests for the new API
11e730c [Holden Karau] Fix streaming tests
66b583d [Holden Karau] Fix the core test suite to compile
4ed579b [Holden Karau] Refactor from iterator to iterable
d052c07 [Holden Karau] Python tests now pass with iterator pandas
3bcd81d [Holden Karau] Revert "Try and make pickling list iterators work"
cd1e81c [Holden Karau] Try and make pickling list iterators work
c60233a [Holden Karau] Start investigating moving to iterators for python API like the Java/Scala one. tl;dr: We will have to write our own iterator since the default one doesn't pickle well
88a5cef [Holden Karau] Fix cogroup test in JavaAPISuite for streaming
a5ee714 [Holden Karau] oops, was checking wrong iterator
e687f21 [Holden Karau] Fix groupbykey test in JavaAPISuite of streaming
ec8cc3e [Holden Karau] Fix test issues\!
4b0eeb9 [Holden Karau] Switch cast in PairDStreamFunctions
fa395c9 [Holden Karau] Revert "Add a join based on the problem in SVD"
ec99e32 [Holden Karau] Revert "Revert this but for now put things in list pandas"
b692868 [Holden Karau] Revert
7e533f7 [Holden Karau] Fix the bug
8a5153a [Holden Karau] Revert me, but we have some stuff to debug
b4e86a9 [Holden Karau] Add a join based on the problem in SVD
c4510e2 [Holden Karau] Revert this but for now put things in list pandas
b4e0b1d [Holden Karau] Fix style issues
71e8b9f [Holden Karau] I really need to stop calling size on iterators, it is the path of sadness.
b1ae51a [Holden Karau] Fix some of the types in the streaming JavaAPI suite. Probably still needs more work
37888ec [Holden Karau] core/tests now pass
249abde [Holden Karau] org.apache.spark.rdd.PairRDDFunctionsSuite passes
6698186 [Holden Karau] Revert "I think this might be a bad rabbit hole. Started work to make CoGroupedRDD use iterator and then went crazy"
fe992fe [Holden Karau] hmmm try and fix up basic operation suite
172705c [Holden Karau] Fix Java API suite
caafa63 [Holden Karau] I think this might be a bad rabbit hole. Started work to make CoGroupedRDD use iterator and then went crazy
88b3329 [Holden Karau] Fix groupbykey to actually give back an iterator
4991af6 [Holden Karau] Fix some tests
be50246 [Holden Karau] Calling size on an iterator is not so good if we want to use it after
687ffbc [Holden Karau] This is the it compiles point of replacing Seq with Iterator and JList with JIterator in the groupby and cogroup signatures
Mesos 0.13.0 was released 6 months ago.
Upgrade Mesos dependency to 0.17.0
Author: Sandeep <sandeep@techaddict.me>
Closes#355 from techaddict/mesos_update and squashes the following commits:
f1abeee [Sandeep] SPARK-1433: Upgrade Mesos dependency to 0.17.0 Mesos 0.13.0 was released 6 months ago. Upgrade Mesos dependency to 0.17.0
[I wanted to post this for folks to comment but it depends on (and thus includes the changes in) a currently outstanding PR, #305. You can look at just the second commit: 93f08baf73 to see just the changes relevant to this PR]
Previously, when stages fail or get cancelled, the SparkListener is only notified
indirectly through the SparkListenerJobEnd, where we sometimes pass in a single
stage that failed. This worked before job cancellation, because jobs would only fail
due to a single stage failure. However, with job cancellation, multiple running stages
can fail when a job gets cancelled. Right now, this is not handled correctly, which
results in stages that get stuck in the “Running Stages” window in the UI even
though they’re dead.
This PR changes the SparkListenerStageCompleted event to a SparkListenerStageEnded
event, and uses this event to tell SparkListeners when stages fail in addition to when
they complete successfully. This change is NOT publicly backward compatible for two
reasons. First, it changes the SparkListener interface. We could alternately add a new event,
SparkListenerStageFailed, and keep the existing SparkListenerStageCompleted. However,
this is less consistent with the listener events for tasks / jobs ending, and will result in some
code duplication for listeners (because failed and completed stages are handled in similar
ways). Note that I haven’t finished updating the JSON code to correctly handle the new event
because I’m waiting for feedback on whether this is a good or bad idea (hence the “WIP”).
It is also not backwards compatible because it changes the publicly visible JobWaiter.jobFailed()
method to no longer include a stage that caused the failure. I think this change should definitely
stay, because with cancellation (as described above), a failure isn’t necessarily caused by a
single stage.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#309 from kayousterhout/stage_cancellation and squashes the following commits:
5533ecd [Kay Ousterhout] Fixes in response to Mark's review
320c7c7 [Kay Ousterhout] Notify SparkListeners when stages fail or are cancelled.
Author: Kan Zhang <kzhang@apache.org>
Closes#318 from kanzhang/SPARK-1348 and squashes the following commits:
e625a5f [Kan Zhang] reverting the changes to startJettyServer()
7a8084e [Kan Zhang] SPARK-1348 binding Master, Worker, and App Web UI to all interfaces
Previously, when jobs were cancelled, not all of the state in the
DAGScheduler was cleaned up, leading to a slow memory leak in the
DAGScheduler. As we expose easier ways to cancel jobs, it's more
important to fix these issues.
This commit also fixes a second and less serious problem, which is that
previously, when a stage failed, not all of the appropriate stages
were cancelled. See the "failure of stage used by two jobs" test
for an example of this. This just meant that extra work was done, and is
not a correctness problem.
This commit adds 3 tests. “run shuffle with map stage failure” is
a new test to more thoroughly test this functionality, and passes on
both the old and new versions of the code. “trivial job
cancellation” fails on the old code because all state wasn’t cleaned
up correctly when jobs were cancelled (we didn’t remove the job from
resultStageToJob). “failure of stage used by two jobs” fails on the
old code because taskScheduler.cancelTasks wasn’t called for one of
the stages (see test comments).
This should be checked in before #246, which makes it easier to
cancel stages / jobs.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#305 from kayousterhout/incremental_abort_fix and squashes the following commits:
f33d844 [Kay Ousterhout] Mark review comments
9217080 [Kay Ousterhout] Properly cleanup DAGScheduler on job cancellation.
This PR allows Spark to automatically cleanup metadata and data related to persisted RDDs, shuffles and broadcast variables when the corresponding RDDs, shuffles and broadcast variables fall out of scope from the driver program. This is still a work in progress as broadcast cleanup has not been implemented.
**Implementation Details**
A new class `ContextCleaner` is responsible cleaning all the state. It is instantiated as part of a `SparkContext`. RDD and ShuffleDependency classes have overridden `finalize()` function that gets called whenever their instances go out of scope. The `finalize()` function enqueues the object’s identifier (i.e. RDD ID, shuffle ID, etc.) with the `ContextCleaner`, which is a very short and cheap operation and should not significantly affect the garbage collection mechanism. The `ContextCleaner`, on a different thread, performs the cleanup, whose details are given below.
*RDD cleanup:*
`ContextCleaner` calls `RDD.unpersist()` is used to cleanup persisted RDDs. Regarding metadata, the DAGScheduler automatically cleans up all metadata related to a RDD after all jobs have completed. Only the `SparkContext.persistentRDDs` keeps strong references to persisted RDDs. The `TimeStampedHashMap` used for that has been replaced by `TimeStampedWeakValueHashMap` that keeps only weak references to the RDDs, allowing them to be garbage collected.
*Shuffle cleanup:*
New BlockManager message `RemoveShuffle(<shuffle ID>)` asks the `BlockManagerMaster` and currently active `BlockManager`s to delete all the disk blocks related to the shuffle ID. `ContextCleaner` cleans up shuffle data using this message and also cleans up the metadata in the `MapOutputTracker` of the driver. The `MapOutputTracker` at the workers, that caches the shuffle metadata, maintains a `BoundedHashMap` to limit the shuffle information it caches. Refetching the shuffle information from the driver is not too costly.
*Broadcast cleanup:*
To be done. [This PR](https://github.com/apache/incubator-spark/pull/543/) adds mechanism for explicit cleanup of broadcast variables. `Broadcast.finalize()` will enqueue its own ID with ContextCleaner and the PRs mechanism will be used to unpersist the Broadcast data.
*Other cleanup:*
`ShuffleMapTask` and `ResultTask` caches tasks and used TTL based cleanup (using `TimeStampedHashMap`), so nothing got cleaned up if TTL was not set. Instead, they now use `BoundedHashMap` to keep a limited number of map output information. Cost of repopulating the cache if necessary is very small.
**Current state of implementation**
Implemented RDD and shuffle cleanup. Things left to be done are.
- Cleaning up for broadcast variable still to be done.
- Automatic cleaning up keys with empty weak refs as values in `TimeStampedWeakValueHashMap`
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Andrew Or <andrewor14@gmail.com>
Author: Roman Pastukhov <ignatich@mail.ru>
Closes#126 from tdas/state-cleanup and squashes the following commits:
61b8d6e [Tathagata Das] Fixed issue with Tachyon + new BlockManager methods.
f489fdc [Tathagata Das] Merge remote-tracking branch 'apache/master' into state-cleanup
d25a86e [Tathagata Das] Fixed stupid typo.
cff023c [Tathagata Das] Fixed issues based on Andrew's comments.
4d05314 [Tathagata Das] Scala style fix.
2b95b5e [Tathagata Das] Added more documentation on Broadcast implementations, specially which blocks are told about to the driver. Also, fixed Broadcast API to hide destroy functionality.
41c9ece [Tathagata Das] Added more unit tests for BlockManager, DiskBlockManager, and ContextCleaner.
6222697 [Tathagata Das] Fixed bug and adding unit test for removeBroadcast in BlockManagerSuite.
104a89a [Tathagata Das] Fixed failing BroadcastSuite unit tests by introducing blocking for removeShuffle and removeBroadcast in BlockManager*
a430f06 [Tathagata Das] Fixed compilation errors.
b27f8e8 [Tathagata Das] Merge pull request #3 from andrewor14/cleanup
cd72d19 [Andrew Or] Make automatic cleanup configurable (not documented)
ada45f0 [Andrew Or] Merge branch 'state-cleanup' of github.com:tdas/spark into cleanup
a2cc8bc [Tathagata Das] Merge remote-tracking branch 'apache/master' into state-cleanup
c5b1d98 [Andrew Or] Address Patrick's comments
a6460d4 [Andrew Or] Merge github.com:apache/spark into cleanup
762a4d8 [Tathagata Das] Merge pull request #1 from andrewor14/cleanup
f0aabb1 [Andrew Or] Correct semantics for TimeStampedWeakValueHashMap + add tests
5016375 [Andrew Or] Address TD's comments
7ed72fb [Andrew Or] Fix style test fail + remove verbose test message regarding broadcast
634a097 [Andrew Or] Merge branch 'state-cleanup' of github.com:tdas/spark into cleanup
7edbc98 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into state-cleanup
8557c12 [Andrew Or] Merge github.com:apache/spark into cleanup
e442246 [Andrew Or] Merge github.com:apache/spark into cleanup
88904a3 [Andrew Or] Make TimeStampedWeakValueHashMap a wrapper of TimeStampedHashMap
fbfeec8 [Andrew Or] Add functionality to query executors for their local BlockStatuses
34f436f [Andrew Or] Generalize BroadcastBlockId to remove BroadcastHelperBlockId
0d17060 [Andrew Or] Import, comments, and style fixes (minor)
c92e4d9 [Andrew Or] Merge github.com:apache/spark into cleanup
f201a8d [Andrew Or] Test broadcast cleanup in ContextCleanerSuite + remove BoundedHashMap
e95479c [Andrew Or] Add tests for unpersisting broadcast
544ac86 [Andrew Or] Clean up broadcast blocks through BlockManager*
d0edef3 [Andrew Or] Add framework for broadcast cleanup
ba52e00 [Andrew Or] Refactor broadcast classes
c7ccef1 [Andrew Or] Merge branch 'bc-unpersist-merge' of github.com:ignatich/incubator-spark into cleanup
6c9dcf6 [Tathagata Das] Added missing Apache license
d2f8b97 [Tathagata Das] Removed duplicate unpersistRDD.
a007307 [Tathagata Das] Merge remote-tracking branch 'apache/master' into state-cleanup
620eca3 [Tathagata Das] Changes based on PR comments.
f2881fd [Tathagata Das] Changed ContextCleaner to use ReferenceQueue instead of finalizer
e1fba5f [Tathagata Das] Style fix
892b952 [Tathagata Das] Removed use of BoundedHashMap, and made BlockManagerSlaveActor cleanup shuffle metadata in MapOutputTrackerWorker.
a7260d3 [Tathagata Das] Added try-catch in context cleaner and null value cleaning in TimeStampedWeakValueHashMap.
e61daa0 [Tathagata Das] Modifications based on the comments on PR 126.
ae9da88 [Tathagata Das] Removed unncessary TimeStampedHashMap from DAGScheduler, added try-catches in finalize() methods, and replaced ArrayBlockingQueue to LinkedBlockingQueue to avoid blocking in Java's finalizing thread.
cb0a5a6 [Tathagata Das] Fixed docs and styles.
a24fefc [Tathagata Das] Merge remote-tracking branch 'apache/master' into state-cleanup
8512612 [Tathagata Das] Changed TimeStampedHashMap to use WrappedJavaHashMap.
e427a9e [Tathagata Das] Added ContextCleaner to automatically clean RDDs and shuffles when they fall out of scope. Also replaced TimeStampedHashMap to BoundedHashMaps and TimeStampedWeakValueHashMap for the necessary hashmap behavior.
80dd977 [Roman Pastukhov] Fix for Broadcast unpersist patch.
1e752f1 [Roman Pastukhov] Added unpersist method to Broadcast.
This is the default mode for running spark-shell and pyspark, intended to allow users running spark for the first time to see the performance benefits of using multiple cores, while not breaking backwards compatibility for users who use "local" mode and expect exactly 1 core.
Author: Aaron Davidson <aaron@databricks.com>
Closes#182 from aarondav/110 and squashes the following commits:
a88294c [Aaron Davidson] Rebased changes for new spark-shell
a9f393e [Aaron Davidson] SPARK-1099: Introduce local[*] mode to infer number of cores
While working on spark-1337 with @pwendell, we noticed that not all of the metadata maps in JobProgessListener were being properly cleaned. This could lead to a (hypothetical) memory leak issue should a job run long enough. This patch aims to address the issue.
Author: Davis Shepherd <davis@conviva.com>
Closes#338 from dgshep/master and squashes the following commits:
a77b65c [Davis Shepherd] In the contex of SPARK-1337: Make sure that all metadata fields are properly cleaned
This is a fix for [SPARK-1154](https://issues.apache.org/jira/browse/SPARK-1154). The issue is that worker nodes fill up with a huge number of app-* folders after some time. This change adds a periodic cleanup task which asynchronously deletes app directories older than a configurable TTL.
Two new configuration parameters have been introduced:
spark.worker.cleanup_interval
spark.worker.app_data_ttl
This change does not include moving the downloads of application jars to a location outside of the work directory. We will address that if we have time, but that potentially involves caching so it will come either as part of this PR or a separate PR.
Author: Evan Chan <ev@ooyala.com>
Author: Kelvin Chu <kelvinkwchu@yahoo.com>
Closes#288 from velvia/SPARK-1154-cleanup-app-folders and squashes the following commits:
0689995 [Evan Chan] CR from @aarondav - move config, clarify for standalone mode
9f10d96 [Evan Chan] CR from @pwendell - rename configs and add cleanup.enabled
f2f6027 [Evan Chan] CR from @andrewor14
553d8c2 [Kelvin Chu] change the variable name to currentTimeMillis since it actually tracks in seconds
8dc9cb5 [Kelvin Chu] Fixed a bug in Utils.findOldFiles() after merge.
cb52f2b [Kelvin Chu] Change the name of findOldestFiles() to findOldFiles()
72f7d2d [Kelvin Chu] Fix a bug of Utils.findOldestFiles(). file.lastModified is returned in milliseconds.
ad99955 [Kelvin Chu] Add unit test for Utils.findOldestFiles()
dc1a311 [Evan Chan] Don't recompute current time with every new file
e3c408e [Evan Chan] Document the two new settings
b92752b [Evan Chan] SPARK-1154: Add a periodic task to clean up app directories
Another handful of small build changes to organize and standardize a bit, and avoid warnings:
- Update Maven plugin versions for good measure
- Since plugins need maven 3.0.4 already, require it explicitly (<3.0.4 had some bugs anyway)
- Use variables to define versions across dependencies where they should move in lock step
- ... and make this consistent between Maven/SBT
OK, I also updated the JIRA URL while I was at it here.
Author: Sean Owen <sowen@cloudera.com>
Closes#291 from srowen/SPARK-1387 and squashes the following commits:
461eca1 [Sean Owen] Couldn't resist also updating JIRA location to new one
c2d5cc5 [Sean Owen] Update plugins and Maven version; use variables consistently across Maven/SBT to define dependency versions that should stay in step.
Author: Egor Pakhomov <pahomov.egor@gmail.com>
Closes#156 from epahomov/SPARK-1259 and squashes the following commits:
8ec8f24 [Egor Pakhomov] Make to local iterator shorter
34aa300 [Egor Pakhomov] Fix toLocalIterator docs
08363ef [Egor Pakhomov] SPARK-1259 from toLocallyIterable to toLocalIterator
6a994eb [Egor Pakhomov] SPARK-1259 Make RDD locally iterable
8be3dcf [Egor Pakhomov] SPARK-1259 Make RDD locally iterable
33ecb17 [Egor Pakhomov] SPARK-1259 Make RDD locally iterable
Change to Map and Set - not mutable HashMap and HashSet
Author: Mridul Muralidharan <mridulm80@apache.org>
Closes#302 from mridulm/master and squashes the following commits:
df747af [Mridul Muralidharan] Address review comments
17e2907 [Mridul Muralidharan] fix computePreferredLocations signature to not depend on underlying implementation
This method exposes the Stage objects, which are
private to Spark and should not be exposed to the
user.
This method was added in 01d77f329f; ccing @squito here in case there's a good reason to keep this!
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#308 from kayousterhout/remove_public_method and squashes the following commits:
2e2f009 [Kay Ousterhout] Remove the getStageInfo() method from SparkContext.
Move the PR#468 of apache-incubator-spark to the apache-spark
"Adding an option to persist Spark RDD blocks into Tachyon."
Author: Haoyuan Li <haoyuan@cs.berkeley.edu>
Author: RongGu <gurongwalker@gmail.com>
Closes#158 from RongGu/master and squashes the following commits:
72b7768 [Haoyuan Li] merge master
9f7fa1b [Haoyuan Li] fix code style
ae7834b [Haoyuan Li] minor cleanup
a8b3ec6 [Haoyuan Li] merge master branch
e0f4891 [Haoyuan Li] better check offheap.
55b5918 [RongGu] address matei's comment on the replication of offHeap storagelevel
7cd4600 [RongGu] remove some logic code for tachyonstore's replication
51149e7 [RongGu] address aaron's comment on returning value of the remove() function in tachyonstore
8adfcfa [RongGu] address arron's comment on inTachyonSize
120e48a [RongGu] changed the root-level dir name in Tachyon
5cc041c [Haoyuan Li] address aaron's comments
9b97935 [Haoyuan Li] address aaron's comments
d9a6438 [Haoyuan Li] fix for pspark
77d2703 [Haoyuan Li] change python api.git status
3dcace4 [Haoyuan Li] address matei's comments
91fa09d [Haoyuan Li] address patrick's comments
589eafe [Haoyuan Li] use TRY_CACHE instead of MUST_CACHE
64348b2 [Haoyuan Li] update conf docs.
ed73e19 [Haoyuan Li] Merge branch 'master' of github.com:RongGu/spark-1
619a9a8 [RongGu] set number of directories in TachyonStore back to 64; added a TODO tag for duplicated code from the DiskStore
be79d77 [RongGu] find a way to clean up some unnecessay metods and classed to make the code simpler
49cc724 [Haoyuan Li] update docs with off_headp option
4572f9f [RongGu] reserving the old apply function API of StorageLevel
04301d3 [RongGu] rename StorageLevel.TACHYON to Storage.OFF_HEAP
c9aeabf [RongGu] rename the StorgeLevel.TACHYON as StorageLevel.OFF_HEAP
76805aa [RongGu] unifies the config properties name prefix; add the configs into docs/configuration.md
e700d9c [RongGu] add the SparkTachyonHdfsLR example and some comments
fd84156 [RongGu] use randomUUID to generate sparkapp directory name on tachyon;minor code style fix
939e467 [Haoyuan Li] 0.4.1-thrift from maven central
86a2eab [Haoyuan Li] tachyon 0.4.1-thrift is in the staging repo. but jenkins failed to download it. temporarily revert it back to 0.4.1
16c5798 [RongGu] make the dependency on tachyon as tachyon-0.4.1-thrift
eacb2e8 [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1
bbeb4de [RongGu] fix the JsonProtocolSuite test failure problem
6adb58f [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1
d827250 [RongGu] fix JsonProtocolSuie test failure
716e93b [Haoyuan Li] revert the version
ca14469 [Haoyuan Li] bump tachyon version to 0.4.1-thrift
2825a13 [RongGu] up-merging to the current master branch of the apache spark
6a22c1a [Haoyuan Li] fix scalastyle
8968b67 [Haoyuan Li] exclude more libraries from tachyon dependency to be the same as referencing tachyon-client.
77be7e8 [RongGu] address mateiz's comment about the temp folder name problem. The implementation followed mateiz's advice.
1dcadf9 [Haoyuan Li] typo
bf278fa [Haoyuan Li] fix python tests
e82909c [Haoyuan Li] minor cleanup
776a56c [Haoyuan Li] address patrick's and ali's comments from the previous PR
8859371 [Haoyuan Li] various minor fixes and clean up
e3ddbba [Haoyuan Li] add doc to use Tachyon cache mode.
fcaeab2 [Haoyuan Li] address Aaron's comment
e554b1e [Haoyuan Li] add python code
47304b3 [Haoyuan Li] make tachyonStore in BlockMananger lazy val; add more comments StorageLevels.
dc8ef24 [Haoyuan Li] add old storelevel constructor
e01a271 [Haoyuan Li] update tachyon 0.4.1
8011a96 [RongGu] fix a brought-in mistake in StorageLevel
70ca182 [RongGu] a bit change in comment
556978b [RongGu] fix the scalastyle errors
791189b [RongGu] "Adding an option to persist Spark RDD blocks into Tachyon." move the PR#468 of apache-incubator-spark to the apache-spark
This was requested by a few different people and may be generally
useful, so I'd like to contribute this and not block on a different
PR for it to get in.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#326 from pwendell/class-loader-test-utils and squashes the following commits:
ff3e88e [Patrick Wendell] Add test utility for generating Jar files with compiled classes.
Also clarified comment on each file having to fit in memory
Author: Matei Zaharia <matei@databricks.com>
Closes#327 from mateiz/py-whole-files and squashes the following commits:
9ad64a5 [Matei Zaharia] SPARK-1414. Python API for SparkContext.wholeTextFiles
This works as is on Linux/Mac/etc but doesn't cover working on Windows. In here I use ln -sf for symlinks. Putting this up for comments on that. Do we want to create perhaps some classes for doing shell commands - Linux vs Windows. Is there some other way we want to do this? I assume we are still supporting jdk1.6?
Also should I update the Java API for pipes to allow this parameter?
Author: Thomas Graves <tgraves@apache.org>
Closes#128 from tgravescs/SPARK1198 and squashes the following commits:
abc1289 [Thomas Graves] remove extra tag in pom file
ba23fc0 [Thomas Graves] Add support for symlink on windows, remove commons-io usage
da4b221 [Thomas Graves] Merge branch 'master' of https://github.com/tgravescs/spark into SPARK1198
61be271 [Thomas Graves] Fix file name filter
6b783bd [Thomas Graves] style fixes
1ab49ca [Thomas Graves] Add support for running pipe tasks is separate directories
This reduces the time of the test from 11 seconds to 20 milliseconds.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#324 from pwendell/job-test and squashes the following commits:
868d9eb [Patrick Wendell] Don't create SparkContext in JobProgressListenerSuite.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#278 from sryza/sandy-spark-1375 and squashes the following commits:
5fbf1e9 [Sandy Ryza] SPARK-1375. Additional spark-submit cleanup
Here is a pointer to the former [PR164](https://github.com/apache/spark/pull/164).
I add the pull request for the JIRA issue [SPARK-1133](https://spark-project.atlassian.net/browse/SPARK-1133), which brings a new files reader API in MLlib.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#252 from yinxusen/whole-files-input and squashes the following commits:
7191be6 [Xusen Yin] refine comments
0af3faf [Xusen Yin] add JavaAPI test
01745ee [Xusen Yin] fix deletion error
cc97dca [Xusen Yin] move whole text file API to Spark core
d792cee [Xusen Yin] remove the typo character "+"
6bdf2c2 [Xusen Yin] test for small local file system block size
a1f1e7e [Xusen Yin] add two extra spaces
28cb0fe [Xusen Yin] add whole text files reader
Simple fix...
Author: Patrick Wendell <pwendell@gmail.com>
Closes#320 from pwendell/stage-clean-up and squashes the following commits:
29be62e [Patrick Wendell] SPARK-1337: Application web UI garbage collects newest stages instead old ones
Should be a painless upgrade, and does offer some significant advantages should we want to leverage FindBugs more during the 1.0 lifecycle. http://findbugs.sourceforge.net/findbugs2.html
Author: Mark Hamstra <markhamstra@gmail.com>
Closes#307 from markhamstra/findbugs and squashes the following commits:
99f2d09 [Mark Hamstra] Removed unnecessary findbugs jsr305 dependency
`BlockId.scala` offers a way to reconstruct a BlockId from a string through regex matching. `util/JsonProtocol.scala` duplicates this functionality by explicitly matching on the BlockId type.
With this PR, the de/serialization of BlockIds will go through the first (older) code path.
(Most of the line changes in this PR involve changing `==` to `===` in `JsonProtocolSuite.scala`)
Author: Andrew Or <andrewor14@gmail.com>
Closes#289 from andrewor14/blockid-json and squashes the following commits:
409d226 [Andrew Or] Simplify JSON de/serialization for BlockId
This data structure was misused and, as a result, later renamed to an incorrect name.
This data structure seems to have gotten into this tangled state as a result of @henrydavidge using the stageID instead of the job Id to index into it and later @andrewor14 renaming the data structure to reflect this misunderstanding.
This patch renames it and removes an incorrect indexing into it. The incorrect indexing into it meant that the code added by @henrydavidge to warn when a task size is too large (added here 57579934f0) was not always executed; this commit fixes that.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#301 from kayousterhout/fixCancellation and squashes the following commits:
bd3d3a4 [Kay Ousterhout] Renamed stageIdToActiveJob to jobIdToActiveJob.
Just a Scala version increment
Author: Mark Hamstra <markhamstra@gmail.com>
Closes#259 from markhamstra/scala-2.10.4 and squashes the following commits:
fbec547 [Mark Hamstra] [SPARK-1342] Bumped Scala version to 2.10.4
If a previously persisted RDD is re-used, its information disappears from the Storage page.
This is because the tasks associated with re-using the RDD do not report the RDD's blocks as updated (which is correct). On stage submit, however, we overwrite any existing information regarding that RDD with a fresh one, whether or not the information for the RDD already exists.
Author: Andrew Or <andrewor14@gmail.com>
Closes#281 from andrewor14/ui-storage-fix and squashes the following commits:
408585a [Andrew Or] Fix storage UI bug
Previous version was 7.6.8v20121106. The only difference between Jetty 7 and Jetty 8 is that the former uses Servlet API 2.5, while the latter uses Servlet API 3.0.
Author: Andrew Or <andrewor14@gmail.com>
Closes#280 from andrewor14/jetty-upgrade and squashes the following commits:
dd57104 [Andrew Or] Merge github.com:apache/spark into jetty-upgrade
e75fa85 [Andrew Or] Upgrade Jetty to 8.1.14v20131031
1. Better error messages when required arguments are missing.
2. Support for unit testing cases where presented arguments are invalid.
3. Bug fix: Only use environment varaibles when they are set (otherwise will cause NPE).
4. A verbose mode to aid debugging.
5. Visibility of several variables is set to private.
6. Deprecation warning for existing scripts.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#271 from pwendell/spark-submit and squashes the following commits:
9146def [Patrick Wendell] SPARK-1352: Improve robustness of spark-submit script
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#261 from ScrapCodes/comment-style-check2 and squashes the following commits:
6cde61e [Prashant Sharma] comment style space before ending */ check.
Author: Michael Armbrust <michael@databricks.com>
Closes#142 from marmbrus/kryoErrors and squashes the following commits:
9c72d1f [Michael Armbrust] Make the test more future proof.
78f5a42 [Michael Armbrust] Don't swallow all kryo errors, only those that indicate we are out of data.
This is a starting version of the spark-app script for running compiled binaries against Spark. It still needs tests and some polish. The only testing I've done so far has been using it to launch jobs in yarn-standalone mode against a pseudo-distributed cluster.
This leaves out the changes required for launching python scripts. I think it might be best to save those for another JIRA/PR (while keeping to the design so that they won't require backwards-incompatible changes).
Author: Sandy Ryza <sandy@cloudera.com>
Closes#86 from sryza/sandy-spark-1126 and squashes the following commits:
d428d85 [Sandy Ryza] Commenting, doc, and import fixes from Patrick's comments
e7315c6 [Sandy Ryza] Fix failing tests
34de899 [Sandy Ryza] Change --more-jars to --jars and fix docs
299ddca [Sandy Ryza] Fix scalastyle
a94c627 [Sandy Ryza] Add newline at end of SparkSubmit
04bc4e2 [Sandy Ryza] SPARK-1126. spark-submit script
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#124 from ScrapCodes/SPARK-1096/scalastyle-comment-check and squashes the following commits:
214135a [Prashant Sharma] Review feedback.
5eba88c [Prashant Sharma] Fixed style checks for ///+ comments.
e54b2f8 [Prashant Sharma] improved message, work around.
83e7144 [Prashant Sharma] removed dependency on scalastyle in plugin, since scalastyle sbt plugin already depends on the right version. Incase we update the plugin we will have to adjust our spark-style project to depend on right scalastyle version.
810a1d6 [Prashant Sharma] SPARK-1096, a space after comment style checker.
ba33193 [Prashant Sharma] scala style as a project
...r.
Constructor of `org.apache.spark.executor.Executor` should not set context class loader of current thread, which is backend Actor's thread.
Run the following code in local-mode REPL.
```
scala> case class Foo(i: Int)
scala> val ret = sc.parallelize((1 to 100).map(Foo), 10).collect
```
This causes errors as follows:
```
ERROR actor.OneForOneStrategy: [L$line5.$read$$iwC$$iwC$$iwC$$iwC$Foo;
java.lang.ArrayStoreException: [L$line5.$read$$iwC$$iwC$$iwC$$iwC$Foo;
at scala.runtime.ScalaRunTime$.array_update(ScalaRunTime.scala:88)
at org.apache.spark.SparkContext$$anonfun$runJob$3.apply(SparkContext.scala:870)
at org.apache.spark.SparkContext$$anonfun$runJob$3.apply(SparkContext.scala:870)
at org.apache.spark.scheduler.JobWaiter.taskSucceeded(JobWaiter.scala:56)
at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:859)
at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:616)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:207)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
```
This is because the class loaders to deserialize result `Foo` instances might be different from backend Actor's, and the Actor's class loader should be the same as Driver's.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#15 from ueshin/wip/wrongcontextclassloader and squashes the following commits:
d79e8c0 [Takuya UESHIN] Change a parent class loader of ExecutorURLClassLoader.
c6c09b6 [Takuya UESHIN] Add a test to collect objects of class defined in repl.
43e0feb [Takuya UESHIN] Prevent ContextClassLoader of Actor from becoming ClassLoader of Executor.
Symmetric difference (xor) in particular is useful for computing some distance metrics (e.g. Hamming). Unit tests added.
Author: Petko Nikolov <nikolov@soundcloud.com>
Closes#172 from petko-nikolov/bitset-imprv and squashes the following commits:
451f28b [Petko Nikolov] fixed style mistakes
5beba18 [Petko Nikolov] rm outer loop in andNot test
0e61035 [Petko Nikolov] conform to spark style; rm redundant asserts; more unit tests added; use arraycopy instead of loop
d53cdb9 [Petko Nikolov] rm incidentally added space
4e1df43 [Petko Nikolov] adding xor and and-not to BitSet; unit tests added
Excluded those that are self-evident and the cases that are discussed in the mailing list.
Author: NirmalReddy <nirmal_reddy2000@yahoo.com>
Author: NirmalReddy <nirmal.reddy@imaginea.com>
Closes#168 from NirmalReddy/Spark-1095 and squashes the following commits:
ac54b29 [NirmalReddy] import misplaced
8c5ff3e [NirmalReddy] Changed syntax of unit returning methods
02d0778 [NirmalReddy] fixed explicit types in all the other packages
1c17773 [NirmalReddy] fixed explicit types in core package
/cc @aarondav and @andrewor14
Author: Patrick Wendell <pwendell@gmail.com>
Closes#231 from pwendell/ui-binding and squashes the following commits:
e8025f8 [Patrick Wendell] SPARK-1324: SparkUI Should Not Bind to SPARK_PUBLIC_DNS
According to discussions in comments of PR #208, this PR unifies package definition format in Spark SQL.
Some broken links in ScalaDoc and typos detected along the way are also fixed.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#225 from liancheng/packageDefinition and squashes the following commits:
75c47b3 [Cheng Lian] Fixed file line length
4f87968 [Cheng Lian] Unified package definition format in Spark SQL
Also updated the documentation for top and takeOrdered.
On my simple test of sorting 100 million (Int, Int) tuples using Spark, Guava's top k implementation (in Ordering) is much faster than the BoundedPriorityQueue implementation for roughly sorted input (10 - 20X faster), and still faster for purely random input (2 - 5X).
Author: Reynold Xin <rxin@apache.org>
Closes#229 from rxin/takeOrdered and squashes the following commits:
0d11844 [Reynold Xin] Use Guava's top k implementation rather than our BoundedPriorityQueue based implementation. Also updated the documentation for top and takeOrdered.
This is an update on https://github.com/apache/spark/pull/180, which changes the solution from blacklisting "Option.scala" to avoiding the Option code path while generating the call path.
Also includes a unit test to prevent this issue in the future, and some minor refactoring.
Thanks @witgo for reporting this issue and working on the initial solution!
Author: witgo <witgo@qq.com>
Author: Aaron Davidson <aaron@databricks.com>
Closes#222 from aarondav/180 and squashes the following commits:
f74aad1 [Aaron Davidson] Avoid Option while generating call site & add unit tests
d2b4980 [witgo] Modify the position of the filter
1bc22d7 [witgo] Fix Stage.name return "apply at Option.scala:120"
Move CPUS_PER_TASK to TaskSchedulerImpl as the value is a constant and use it in both Mesos and CoarseGrained scheduler backends.
Thanks @kayousterhout for the design discussion
Author: Shivaram Venkataraman <shivaram@eecs.berkeley.edu>
Closes#219 from shivaram/multi-cpus and squashes the following commits:
5c7d685 [Shivaram Venkataraman] Don't pass availableCpus to TaskSetManager
260e4d5 [Shivaram Venkataraman] Add a check for non-zero CPUs in TaskSetManager
73fcf6f [Shivaram Venkataraman] Add documentation for spark.task.cpus
647bc45 [Shivaram Venkataraman] Fix scheduler to account for tasks using > 1 CPUs. Move CPUS_PER_TASK to TaskSchedulerImpl as the value is a constant and use it in both Mesos and CoarseGrained scheduler backends.
(This follows from a side point on SPARK-1133, in discussion of the PR: https://github.com/apache/spark/pull/164 )
Commons IO is barely used in the project, and can easily be replaced with equivalent calls to Guava or the existing Spark `Utils.scala` class.
Removing a dependency feels good, and this one in particular can get a little problematic since Hadoop uses it too.
Author: Sean Owen <sowen@cloudera.com>
Closes#226 from srowen/SPARK-1316 and squashes the following commits:
21efef3 [Sean Owen] Remove use of Commons IO
https://spark-project.atlassian.net/browse/SPARK-1128
The task properties are not set when constructing HadoopRDD in current implementation, this may limit the implementation based on
```
mapred.tip.id
mapred.task.id
mapred.task.is.map
mapred.task.partition
mapred.job.id
```
This patch also contains a small fix in createJobID (SparkHadoopWriter.scala), where the current implementation actually is not using time parameter
Author: CodingCat <zhunansjtu@gmail.com>
Author: Nan Zhu <CodingCat@users.noreply.github.com>
Closes#101 from CodingCat/SPARK-1128 and squashes the following commits:
ed0980f [CodingCat] make SparkHiveHadoopWriter belongs to spark package
5b1ad7d [CodingCat] move SparkHiveHadoopWriter to org.apache.spark package
258f92c [CodingCat] code cleanup
af88939 [CodingCat] update the comments and permission of SparkHadoopWriter
9bd1fe3 [CodingCat] move configuration for jobConf to HadoopRDD
b7bdfa5 [Nan Zhu] style fix
a3153a8 [Nan Zhu] style fix
c3258d2 [CodingCat] set hadoop task properties while using InputFormat
`SimpleDateFormat` is not thread-safe. Some places use the same SimpleDateFormat object without safeguard in the multiple threads. It will cause that the Web UI displays improper date.
This PR creates a new `SimpleDateFormat` every time when it's necessary. Another solution is using `ThreadLocal` to store a `SimpleDateFormat` in each thread. If this PR impacts the performance, I can change to the latter one.
Author: zsxwing <zsxwing@gmail.com>
Closes#179 from zsxwing/SPARK-1278 and squashes the following commits:
21fabd3 [zsxwing] SPARK-1278: Fix improper use of SimpleDateFormat
This is a bug fix for #42 (79d07d6604).
In Master, we do not bind() each SparkUI because we do not want to start a server for each finished application. However, when we remove the associated application, we call stop() on the SparkUI, which throws an assertion failure.
This fix ensures we don't call stop() on a SparkUI that was never bind()'ed.
Author: Andrew Or <andrewor14@gmail.com>
Closes#188 from andrewor14/ui-fix and squashes the following commits:
94a925f [Andrew Or] Do not stop SparkUI if bind() is not called
This is for JIRA:https://spark-project.atlassian.net/browse/SPARK-1099
And this is what I do in this patch (also commented in the JIRA) @aarondav
This is really a behavioral change, so I do this with great caution, and welcome any review advice:
1 I change the "MASTER=local" pattern of create LocalBackEnd . In the past, we passed 1 core to it . now it use a default cores
The reason here is that when someone use spark-shell to start local mode , Repl will use this "MASTER=local" pattern as default.
So if one also specify cores in the spark-shell command line, it will all go in here. So here pass 1 core is not suitalbe reponding to our change here.
2 In the LocalBackEnd , the "totalCores" variable are fetched following a different rule(in the past it just take in a userd passed cores, like 1 in "MASTER=local" pattern, 2 in "MASTER=local[2]" pattern"
rules:
a The second argument of LocalBackEnd 's constructor indicating cores have a default value which is Int.MaxValue. If user didn't pass it , its first default value is Int.MaxValue
b In getMaxCores, we first compare the former value to Int.MaxValue. if it's not equal, we think that user has passed their desired value, so just use it
c. If b is not satified, we then get cores from spark.cores.max, and we get real logical cores from Runtime. And if cores specified by spark.cores.max is bigger than logical cores, we use logical cores, otherwise we use spark.cores.max
3 In SparkContextSchedulerCreationSuite 's test("local") case, assertion is modified from 1 to logical cores, because "MASTER=local" pattern use default vaules.
Author: qqsun8819 <jin.oyj@alibaba-inc.com>
Closes#110 from qqsun8819/local-cores and squashes the following commits:
731aefa [qqsun8819] 1 LocalBackend not change 2 In SparkContext do some process to the cores and pass it to original LocalBackend constructor
78b9c60 [qqsun8819] 1 SparkContext MASTER=local pattern use default cores instead of 1 to construct LocalBackEnd , for use of spark-shell and cores specified in cmd line 2 some test case change from local to local[1]. 3 SparkContextSchedulerCreationSuite test spark.cores.max config in local pattern
6ae1ee8 [qqsun8819] Add a static function in LocalBackEnd to let it use spark.cores.max specified cores when no cores are passed to it
The fleeting nature of the Spark Web UI has long been a problem reported by many users: The existing Web UI disappears as soon as the associated application terminates. This is because SparkUI is tightly coupled with SparkContext, and cannot be instantiated independently from it. To solve this, some state must be saved to persistent storage while the application is still running.
The approach taken by this PR involves persisting the UI state through SparkListenerEvents. This requires a major refactor of the SparkListener interface because existing events (1) maintain deep references, making de/serialization is difficult, and (2) do not encode all the information displayed on the UI. In this design, each existing listener for the UI (e.g. ExecutorsListener) maintains state that can be fully constructed from SparkListenerEvents. This state is then supplied to the parent UI (e.g. ExecutorsUI), which renders the associated page(s) on demand.
This PR introduces two important classes: the **EventLoggingListener**, and the **ReplayListenerBus**. In a live application, SparkUI registers an EventLoggingListener with the SparkContext in addition to the existing listeners. Over the course of the application, this listener serializes and logs all events to persisted storage. Then, after the application has finished, the SparkUI can be revived by replaying all the logged events to the existing UI listeners through the ReplayListenerBus.
This feature is currently integrated with the Master Web UI, which optionally rebuilds a SparkUI from event logs as soon as the corresponding application finishes.
More details can be found in the commit messages, comments within the code, and the [design doc](https://spark-project.atlassian.net/secure/attachment/12900/PersistingSparkWebUI.pdf). Comments and feedback are most welcome.
Author: Andrew Or <andrewor14@gmail.com>
Author: andrewor14 <andrewor14@gmail.com>
Closes#42 from andrewor14/master and squashes the following commits:
e5f14fa [Andrew Or] Merge github.com:apache/spark
a1c5cd9 [Andrew Or] Merge github.com:apache/spark
b8ba817 [Andrew Or] Remove UI from map when removing application in Master
83af656 [Andrew Or] Scraps and pieces (no functionality change)
222adcd [Andrew Or] Merge github.com:apache/spark
124429f [Andrew Or] Clarify LiveListenerBus behavior + Add tests for new behavior
f80bd31 [Andrew Or] Simplify static handler and BlockManager status update logic
9e14f97 [Andrew Or] Moved around functionality + renamed classes per Patrick
6740e49 [Andrew Or] Fix comment nits
650eb12 [Andrew Or] Add unit tests + Fix bugs found through tests
45fd84c [Andrew Or] Remove now deprecated test
c5c2c8f [Andrew Or] Remove list of (TaskInfo, TaskMetrics) from StageInfo
3456090 [Andrew Or] Address Patrick's comments
bf80e3d [Andrew Or] Imports, comments, and code formatting, once again (minor)
ac69ec8 [Andrew Or] Fix test fail
d801d11 [Andrew Or] Merge github.com:apache/spark (major)
dc93915 [Andrew Or] Imports, comments, and code formatting (minor)
77ba283 [Andrew Or] Address Kay's and Patrick's comments
b6eaea7 [Andrew Or] Treating SparkUI as a handler of MasterUI
d59da5f [Andrew Or] Avoid logging all the blocks on each executor
d6e3b4a [Andrew Or] Merge github.com:apache/spark
ca258a4 [Andrew Or] Master UI - add support for reading compressed event logs
176e68e [Andrew Or] Fix deprecated message for JavaSparkContext (minor)
4f69c4a [Andrew Or] Master UI - Rebuild SparkUI on application finish
291b2be [Andrew Or] Correct directory in log message "INFO: Logging events to <dir>"
1ba3407 [Andrew Or] Add a few configurable options to event logging
e375431 [Andrew Or] Add new constructors for SparkUI
18b256d [Andrew Or] Refactor out event logging and replaying logic from UI
bb4c503 [Andrew Or] Use a more mnemonic path for logging
aef411c [Andrew Or] Fix bug: storage status was not reflected on UI in the local case
03eda0b [Andrew Or] Fix HDFS flush behavior
36b3e5d [Andrew Or] Add HDFS support for event logging
cceff2b [andrewor14] Fix 100 char format fail
2fee310 [Andrew Or] Address Patrick's comments
2981d61 [Andrew Or] Move SparkListenerBus out of DAGScheduler + Clean up
5d2cec1 [Andrew Or] JobLogger: ID -> Id
0503e4b [Andrew Or] Fix PySpark tests + remove sc.clearFiles/clearJars
4d2fb0c [Andrew Or] Fix format fail
faa113e [Andrew Or] General clean up
d47585f [Andrew Or] Clean up FileLogger
472fd8a [Andrew Or] Fix a couple of tests
996d7a2 [Andrew Or] Reflect RDD unpersist on UI
7b2f811 [Andrew Or] Guard against TaskMetrics NPE + Fix tests
d1f4285 [Andrew Or] Migrate from lift-json to json4s-jackson
28019ca [Andrew Or] Merge github.com:apache/spark
bbe3501 [Andrew Or] Embed storage status and RDD info in Task events
6631c02 [Andrew Or] More formatting changes, this time mainly for Json DSL
70e7e7a [Andrew Or] Formatting changes
e9e1c6d [Andrew Or] Move all JSON de/serialization logic to JsonProtocol
d646df6 [Andrew Or] Completely decouple SparkUI from SparkContext
6814da0 [Andrew Or] Explicitly register each UI listener rather than through some magic
64d2ce1 [Andrew Or] Fix BlockManagerUI bug by introducing new event
4273013 [Andrew Or] Add a gateway SparkListener to simplify event logging
904c729 [Andrew Or] Fix another major bug
5ac906d [Andrew Or] Mostly naming, formatting, and code style changes
3fd584e [Andrew Or] Fix two major bugs
f3fc13b [Andrew Or] General refactor
4dfcd22 [Andrew Or] Merge git://git.apache.org/incubator-spark into persist-ui
b3976b0 [Andrew Or] Add functionality of reconstructing a persisted UI from SparkContext
8add36b [Andrew Or] JobProgressUI: Add JSON functionality
d859efc [Andrew Or] BlockManagerUI: Add JSON functionality
c4cd480 [Andrew Or] Also deserialize new events
8a2ebe6 [Andrew Or] Fix bugs for EnvironmentUI and ExecutorsUI
de8a1cd [Andrew Or] Serialize events both to and from JSON (rather than just to)
bf0b2e9 [Andrew Or] ExecutorUI: Serialize events rather than arbitary executor information
bb222b9 [Andrew Or] ExecutorUI: render completely from JSON
dcbd312 [Andrew Or] Add JSON Serializability for all SparkListenerEvent's
10ed49d [Andrew Or] Merge github.com:apache/incubator-spark into persist-ui
8e09306 [Andrew Or] Use JSON for ExecutorsUI
e3ae35f [Andrew Or] Merge github.com:apache/incubator-spark
3ddeb7e [Andrew Or] Also privatize fields
090544a [Andrew Or] Privatize methods
13920c9 [Andrew Or] Update docs
bd5a1d7 [Andrew Or] Typo: phyiscal -> physical
287ef44 [Andrew Or] Avoid reading the entire batch into memory; also simplify streaming logic
3df7005 [Andrew Or] Merge branch 'master' of github.com:andrewor14/incubator-spark
a531d2e [Andrew Or] Relax assumptions on compressors and serializers when batching
164489d [Andrew Or] Relax assumptions on compressors and serializers when batching
Move the PR#517 of apache-incubator-spark to the apache-spark
Author: Mridul Muralidharan <mridul@gmail.com>
Closes#159 from mridulm/master and squashes the following commits:
5ff59c2 [Mridul Muralidharan] Change property in suite also
167fad8 [Mridul Muralidharan] Address review comments
9bda70e [Mridul Muralidharan] Address review comments, akwats add to failedExecutors
270d841 [Mridul Muralidharan] Address review comments
fa5d9f1 [Mridul Muralidharan] Bugfixes/improvements to scheduler : PR #517
Author: Thomas Graves <tgraves@apache.org>
Closes#173 from tgravescs/SPARK-1203 and squashes the following commits:
4fd5ded [Thomas Graves] adding import
964e3f7 [Thomas Graves] SPARK-1203 fix saving to hdfs from yarn
If a stage which has completed once loss parts of data, it will be resubmitted. At this time, it appears that stage.completionTime > stage.submissionTime.
Author: shiyun.wxm <shiyun.wxm@taobao.com>
Closes#170 from BlackNiuza/duration_problem and squashes the following commits:
a86d261 [shiyun.wxm] tow space indent
c0d7b24 [shiyun.wxm] change the style
3b072e1 [shiyun.wxm] fix scala style
f20701e [shiyun.wxm] bugfix: "Duration" in "Active Stages" in stages page
Author: witgo <witgo@qq.com>
Closes#150 from witgo/SPARK-1256 and squashes the following commits:
08044a2 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1256
c99b030 [witgo] Fix SPARK-1256
https://spark-project.atlassian.net/browse/SPARK-1102
Create a saveAsNewAPIHadoopDataset method
By @mateiz: "Right now RDDs can only be saved as files using the new Hadoop API, not as "datasets" with no filename and just a JobConf. See http://codeforhire.com/2014/02/18/using-spark-with-mongodb/ for an example of how you have to give a bogus filename. For the old Hadoop API, we have saveAsHadoopDataset."
Author: CodingCat <zhunansjtu@gmail.com>
Closes#12 from CodingCat/SPARK-1102 and squashes the following commits:
6ba0c83 [CodingCat] add test cases for saveAsHadoopDataSet (new&old API)
a8d11ba [CodingCat] style fix.........
95a6929 [CodingCat] code clean
7643c88 [CodingCat] change the parameter type back to Configuration
a8583ee [CodingCat] Create a saveAsNewAPIHadoopDataset method
This reverts commit ca4bf8c572.
Jetty 9 requires JDK7 which is probably not a dependency we want to bump right now. Before Spark 1.0 we should consider upgrading to Jetty 8. However, in the mean time to ease some pain let's revert this. Sorry for not catching this during the initial review. cc/ @rxin
Author: Patrick Wendell <pwendell@gmail.com>
Closes#167 from pwendell/jetty-revert and squashes the following commits:
811b1c5 [Patrick Wendell] Revert "SPARK-1236 - Upgrade Jetty to 9.1.3.v20140225."
Here's the addition of min and max to statscounter.py and min and max methods to rdd.py.
Author: Dan McClary <dan.mcclary@gmail.com>
Closes#144 from dwmclary/SPARK-1246-add-min-max-to-stat-counter and squashes the following commits:
fd3fd4b [Dan McClary] fixed error, updated test
82cde0e [Dan McClary] flipped incorrectly assigned inf values in StatCounter
5d96799 [Dan McClary] added max and min to StatCounter repr for pyspark
21dd366 [Dan McClary] added max and min to StatCounter output, updated doc
1a97558 [Dan McClary] added max and min to StatCounter output, updated doc
a5c13b0 [Dan McClary] Added min and max to Scala and Java RDD, added min and max to StatCounter
ed67136 [Dan McClary] broke min/max out into separate transaction, added to rdd.py
1e7056d [Dan McClary] added underscore to getBucket
37a7dea [Dan McClary] cleaned up boundaries for histogram -- uses real min/max when buckets are derived
29981f2 [Dan McClary] fixed indentation on doctest comment
eaf89d9 [Dan McClary] added correct doctest for histogram
4916016 [Dan McClary] added histogram method, added max and min to statscounter
This is a very small change on top of @andrewor14's patch in #147.
Author: Patrick Wendell <pwendell@gmail.com>
Author: Andrew Or <andrewor14@gmail.com>
Closes#152 from pwendell/akka-frame and squashes the following commits:
e5fb3ff [Patrick Wendell] Reversing test order
393af4c [Patrick Wendell] Small improvement suggested by Andrew Or
8045103 [Patrick Wendell] Breaking out into two tests
2b4e085 [Patrick Wendell] Consolidate Executor use of akka frame size
c9b6109 [Andrew Or] Simplify test + make access to akka frame size more modular
281d7c9 [Andrew Or] Throw exception on spark.akka.frameSize exceeded + Unit tests
https://spark-project.atlassian.net/browse/SPARK-1240
It seems that the current implementation does not handle the empty RDD case when run takeSample
In this patch, before calling sample() inside takeSample API, I add a checker for this case and returns an empty Array when it's a empty RDD; also in sample(), I add a checker for the invalid fraction value
In the test case, I also add several lines for this case
Author: CodingCat <zhunansjtu@gmail.com>
Closes#135 from CodingCat/SPARK-1240 and squashes the following commits:
fef57d4 [CodingCat] fix the same problem in PySpark
36db06b [CodingCat] create new test cases for takeSample from an empty red
810948d [CodingCat] further fix
a40e8fb [CodingCat] replace if with require
ad483fd [CodingCat] handle the case with empty RDD when take sample
This is more general than simply passing a string name and leaves more room for performance optimizations.
Note that this is technically an API breaking change in the following two ways:
1. The shuffle serializer specification in ShuffleDependency now require an object instead of a String (of the class name), but I suspect nobody else in this world has used this API other than me in GraphX and Shark.
2. Serializer's in Spark from now on are required to be serializable.
Author: Reynold Xin <rxin@apache.org>
Closes#149 from rxin/serializer and squashes the following commits:
5acaccd [Reynold Xin] Properly call serializer's constructors.
2a8d75a [Reynold Xin] Added more documentation for the serializer option in ShuffleDependency.
7420185 [Reynold Xin] Allow user to pass Serializer object instead of class name for shuffle.
Author: Michael Armbrust <michael@databricks.com>
Closes#141 from marmbrus/mutablePair and squashes the following commits:
f5c4783 [Michael Armbrust] Change function name to update
8bfd973 [Michael Armbrust] Fix serialization of MutablePair. Also provide an interface for easy updating.
Author: Reynold Xin <rxin@apache.org>
Closes#113 from rxin/jetty9 and squashes the following commits:
867a2ce [Reynold Xin] Updated Jetty version to 9.1.3.v20140225 in Maven build file.
d7c97ca [Reynold Xin] Return the correctly bound port.
d14706f [Reynold Xin] Upgrade Jetty to 9.1.3.v20140225.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#112 from pwendell/pyspark-take and squashes the following commits:
daae80e [Patrick Wendell] SPARK-1019: pyspark RDD take() throws an NPE
Author: CodingCat <zhunansjtu@gmail.com>
Closes#133 from CodingCat/SPARK-1160-2 and squashes the following commits:
6607155 [CodingCat] hot fix for PR105 - change to Java annotation
https://spark-project.atlassian.net/browse/SPARK-1160
reported by @mateiz: "It's redundant with collect() and the name doesn't make sense in Java, where we return a List (we can't return an array due to the way Java generics work). It's also missing in Python."
In this patch, I deprecated the method and changed the source files using it by replacing toArray with collect() directly
Author: CodingCat <zhunansjtu@gmail.com>
Closes#105 from CodingCat/SPARK-1060 and squashes the following commits:
286f163 [CodingCat] deprecate in JavaRDDLike
ee17b4e [CodingCat] add message and since
2ff7319 [CodingCat] deprecate toArray in RDD
Author: liguoqiang <liguoqiang@rd.tuan800.com>
Closes#44 from witgo/SPARK-1149 and squashes the following commits:
3dcdcaf [liguoqiang] Merge branch 'master' into SPARK-1149
8425395 [liguoqiang] Merge remote-tracking branch 'upstream/master' into SPARK-1149
3dad595 [liguoqiang] review comment
e3e56aa [liguoqiang] Merge branch 'master' into SPARK-1149
b0d5c07 [liguoqiang] review comment
d0a6005 [liguoqiang] review comment
3395ee7 [liguoqiang] Merge remote-tracking branch 'upstream/master' into SPARK-1149
ac006a3 [liguoqiang] code Formatting
3feb3a8 [liguoqiang] Merge branch 'master' into SPARK-1149
adc443e [liguoqiang] partitions check bugfix
928e1e3 [liguoqiang] Added a unit test for PairRDDFunctions.lookup with bad partitioner
db6ecc5 [liguoqiang] Merge branch 'master' into SPARK-1149
1e3331e [liguoqiang] Merge branch 'master' into SPARK-1149
3348619 [liguoqiang] Optimize performance for partitions check
61e5a87 [liguoqiang] Merge branch 'master' into SPARK-1149
e68210a [liguoqiang] add partition index check to submitJob
3a65903 [liguoqiang] make the code more readable
6bb725e [liguoqiang] fix #SPARK-1149 Bad partitioners can cause Spark to hang
Author: Thomas Graves <tgraves@apache.org>
Closes#127 from tgravescs/SPARK-1232 and squashes the following commits:
c05cfd4 [Thomas Graves] Fix the hadoop 0.23 yarn build
This patch removes Ganglia integration from the default build. It
allows users willing to link against LGPL code to use Ganglia
by adding build flags or linking against a new Spark artifact called
spark-ganglia-lgpl.
This brings Spark in line with the Apache policy on LGPL code
enumerated here:
https://www.apache.org/legal/3party.html#options-optional
Author: Patrick Wendell <pwendell@gmail.com>
Closes#108 from pwendell/ganglia and squashes the following commits:
326712a [Patrick Wendell] Responding to review feedback
5f28ee4 [Patrick Wendell] SPARK-1167: Remove metrics-ganglia from default build due to LGPL issues.
This patch removes the `generator` field and simplifies + documents
the tracking of callsites.
There are two places where we care about call sites, when a job is
run and when an RDD is created. This patch retains both of those
features but does a slight refactoring and renaming to make things
less confusing.
There was another feature of an rdd called the `generator` which was
by default the user class that in which the RDD was created. This is
used exclusively in the JobLogger. It been subsumed by the ability
to name a job group. The job logger can later be refectored to
read the job group directly (will require some work) but for now
this just preserves the default logged value of the user class.
I'm not sure any users ever used the ability to override this.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#106 from pwendell/callsite and squashes the following commits:
fc1d009 [Patrick Wendell] Compile fix
e17fb76 [Patrick Wendell] Review feedback: callSite -> creationSite
62e77ef [Patrick Wendell] Review feedback
576e60b [Patrick Wendell] SPARK-1205: Clean up callSite/origin/generator.
This makes two changes.
1) Spark uses the shaded version of asm that is (conveniently) published
with Kryo.
2) Existing exclude rules around asm are updated to reflect the new groupId
of `org.ow2.asm`. This made all of the old rules not work with newer Hadoop
versions that pull in new asm versions.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#100 from pwendell/asm and squashes the following commits:
9235f3f [Patrick Wendell] SPARK-782 Clean up for ASM dependency.
Currently, when fetch a file, the connection's connect timeout
and read timeout is based on the default jvm setting, in this change, I change it to
use spark.worker.timeout. This can be usefull, when the
connection status between worker is not perfect. And prevent
prematurely remove task set.
Author: Jiacheng Guo <guojc03@gmail.com>
Closes#98 from guojc/master and squashes the following commits:
abfe698 [Jiacheng Guo] add space according request
2a37c34 [Jiacheng Guo] Add timeout for fetch file Currently, when fetch a file, the connection's connect timeout and read timeout is based on the default jvm setting, in this change, I change it to use spark.worker.timeout. This can be usefull, when the connection status between worker is not perfect. And prevent prematurely remove task set.
(Continued from old repo, prior discussion at https://github.com/apache/incubator-spark/pull/615)
This patch cements our deprecation of the SPARK_MEM environment variable by replacing it with three more specialized variables:
SPARK_DAEMON_MEMORY, SPARK_EXECUTOR_MEMORY, and SPARK_DRIVER_MEMORY
The creation of the latter two variables means that we can safely set driver/job memory without accidentally setting the executor memory. Neither is public.
SPARK_EXECUTOR_MEMORY is only used by the Mesos scheduler (and set within SparkContext). The proper way of configuring executor memory is through the "spark.executor.memory" property.
SPARK_DRIVER_MEMORY is the new way of specifying the amount of memory run by jobs launched by spark-class, without possibly affecting executor memory.
Other memory considerations:
- The repl's memory can be set through the "--drivermem" command-line option, which really just sets SPARK_DRIVER_MEMORY.
- run-example doesn't use spark-class, so the only way to modify examples' memory is actually an unusual use of SPARK_JAVA_OPTS (which is normally overriden in all cases by spark-class).
This patch also fixes a lurking bug where spark-shell misused spark-class (the first argument is supposed to be the main class name, not java options), as well as a bug in the Windows spark-class2.cmd. I have not yet tested this patch on either Windows or Mesos, however.
Author: Aaron Davidson <aaron@databricks.com>
Closes#99 from aarondav/sparkmem and squashes the following commits:
9df4c68 [Aaron Davidson] SPARK-929: Fully deprecate usage of SPARK_MEM
Author: Patrick Wendell <pwendell@gmail.com>
Closes#107 from pwendell/logging and squashes the following commits:
be21c11 [Patrick Wendell] Logging fix
SPARK-1194: https://spark-project.atlassian.net/browse/SPARK-1194
In the current implementation, when selecting candidate blocks to be swapped out, once we find a block from the same RDD that the block to be stored belongs to, cache eviction fails and aborts.
In this PR, we keep selecting blocks *not* from the RDD that the block to be stored belongs to until either enough free space can be ensured (cache eviction succeeds) or all such blocks are checked (cache eviction fails).
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#96 from liancheng/fix-spark-1194 and squashes the following commits:
2524ab9 [Cheng Lian] Added regression test case for SPARK-1194
6e40c22 [Cheng Lian] Remove redundant comments
40cdcb2 [Cheng Lian] Bug fix, and addressed PR comments from @mridulm
62c92ac [Cheng Lian] Fixed SPARK-1194 https://spark-project.atlassian.net/browse/SPARK-1194
Author: Sandy Ryza <sandy@cloudera.com>
Closes#91 from sryza/sandy-spark-1193 and squashes the following commits:
a878124 [Sandy Ryza] SPARK-1193. Fix indentation in pom.xmls
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Prashant Sharma <scrapcodes@gmail.com>
Closes#80 from ScrapCodes/SPARK-1165/RDD.intersection and squashes the following commits:
9b015e9 [Prashant Sharma] Added a note, shuffle is required for intersection.
1fea813 [Prashant Sharma] correct the lines wrapping
d0c71f3 [Prashant Sharma] SPARK-1165 RDD.intersection in java
d6effee [Prashant Sharma] SPARK-1165 Implemented RDD.intersection in python.
Hadoop uses the config mapreduce.map.input.file to indicate the input filename to the map when the input split is of type FileSplit. Some of the hadoop input and output formats set or use this config. This config can also be used by user code.
PipedRDD runs an external process and the configs aren't available to that process. Hadoop Streaming does something very similar and the way they make configs available is exporting them into the environment replacing '.' with '_'. Spark should also export this variable when launching the pipe command so the user code has access to that config.
Note that the config mapreduce.map.input.file is the new one, the old one which is deprecated but not yet removed is map.input.file. So we should handle both.
Perhaps it would be better to abstract this out somehow so it goes into the HadoopParition code?
Author: Thomas Graves <tgraves@apache.org>
Closes#94 from tgravescs/map_input_file and squashes the following commits:
cc97a6a [Thomas Graves] Update test to check for existence of command, add a getPipeEnvVars function to HadoopRDD
e3401dc [Thomas Graves] Merge remote-tracking branch 'upstream/master' into map_input_file
2ba805e [Thomas Graves] set map_input_file environment variable in PipedRDD
This patch allows the FaultToleranceTest to work in newer versions of Docker.
See https://spark-project.atlassian.net/browse/SPARK-1136 for more details.
Besides changing the Docker and FaultToleranceTest internals, this patch also changes the behavior of Master to accept new Workers which share an address with a Worker that we are currently trying to recover. This can only happen when the Worker itself was restarted and got the same IP address/port at the same time as a Master recovery occurs.
Finally, this adds a good bit of ASCII art to the test to make failures, successes, and actions more apparent. This is very much needed.
Author: Aaron Davidson <aaron@databricks.com>
Closes#5 from aarondav/zookeeper and squashes the following commits:
5d7a72a [Aaron Davidson] SPARK-1136: Fix FaultToleranceTest for Docker 0.8.1
This patch changes "yarn-standalone" to "yarn-cluster" (but still supports the former). It also cleans up the Running on YARN docs and adds a section on how to view logs.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#95 from sryza/sandy-spark-1197 and squashes the following commits:
563ef3a [Sandy Ryza] Review feedback
6ad06d4 [Sandy Ryza] Change yarn-standalone to yarn-cluster and fix up running on YARN docs
resubmit pull request. was https://github.com/apache/incubator-spark/pull/332.
Author: Thomas Graves <tgraves@apache.org>
Closes#33 from tgravescs/security-branch-0.9-with-client-rebase and squashes the following commits:
dfe3918 [Thomas Graves] Fix merge conflict since startUserClass now using runAsUser
05eebed [Thomas Graves] Fix dependency lost in upmerge
d1040ec [Thomas Graves] Fix up various imports
05ff5e0 [Thomas Graves] Fix up imports after upmerging to master
ac046b3 [Thomas Graves] Merge remote-tracking branch 'upstream/master' into security-branch-0.9-with-client-rebase
13733e1 [Thomas Graves] Pass securityManager and SparkConf around where we can. Switch to use sparkConf for reading config whereever possible. Added ConnectionManagerSuite unit tests.
4a57acc [Thomas Graves] Change UI createHandler routines to createServlet since they now return servlets
2f77147 [Thomas Graves] Rework from comments
50dd9f2 [Thomas Graves] fix header in SecurityManager
ecbfb65 [Thomas Graves] Fix spacing and formatting
b514bec [Thomas Graves] Fix reference to config
ed3d1c1 [Thomas Graves] Add security.md
6f7ddf3 [Thomas Graves] Convert SaslClient and SaslServer to scala, change spark.authenticate.ui to spark.ui.acls.enable, and fix up various other things from review comments
2d9e23e [Thomas Graves] Merge remote-tracking branch 'upstream/master' into security-branch-0.9-with-client-rebase_rework
5721c5a [Thomas Graves] update AkkaUtilsSuite test for the actorSelection changes, fix typos based on comments, and remove extra lines I missed in rebase from AkkaUtils
f351763 [Thomas Graves] Add Security to Spark - Akka, Http, ConnectionManager, UI to use servlets
This is a port of a pull request original targeted at incubator-spark: https://github.com/apache/incubator-spark/pull/180
Essentially if a user returns a generative iterator (from a flatMap operation), when trying to persist the data, Spark would first unroll the iterator into an ArrayBuffer, and then try to figure out if it could store the data. In cases where the user provided an iterator that generated more data then available memory, this would case a crash. With this patch, if the user requests a persist with a 'StorageLevel.DISK_ONLY', the iterator will be unrolled as it is inputed into the serializer.
To do this, two changes where made:
1) The type of the 'values' argument in the putValues method of the BlockStore interface was changed from ArrayBuffer to Iterator (and all code interfacing with this method was modified to connect correctly.
2) The JavaSerializer now calls the ObjectOutputStream 'reset' method every 1000 objects. This was done because the ObjectOutputStream caches objects (thus preventing them from being GC'd) to write more compact serialization. If reset is never called, eventually the memory fills up, if it is called too often then the serialization streams become much larger because of redundant class descriptions.
Author: Kyle Ellrott <kellrott@gmail.com>
Closes#50 from kellrott/iterator-to-disk and squashes the following commits:
9ef7cb8 [Kyle Ellrott] Fixing formatting issues.
60e0c57 [Kyle Ellrott] Fixing issues (formatting, variable names, etc.) from review comments
8aa31cd [Kyle Ellrott] Merge ../incubator-spark into iterator-to-disk
33ac390 [Kyle Ellrott] Merge branch 'iterator-to-disk' of github.com:kellrott/incubator-spark into iterator-to-disk
2f684ea [Kyle Ellrott] Refactoring the BlockManager to replace the Either[Either[A,B]] usage. Now using trait 'Values'. Also modified BlockStore.putBytes call to return PutResult, so that it behaves like putValues.
f70d069 [Kyle Ellrott] Adding docs for spark.serializer.objectStreamReset configuration
7ccc74b [Kyle Ellrott] Moving the 'LargeIteratorSuite' to simply test persistance of iterators. It doesn't try to invoke a OOM error any more
16a4cea [Kyle Ellrott] Streamlined the LargeIteratorSuite unit test. It should now run in ~25 seconds. Confirmed that it still crashes an unpatched copy of Spark.
c2fb430 [Kyle Ellrott] Removing more un-needed array-buffer to iterator conversions
627a8b7 [Kyle Ellrott] Wrapping a few long lines
0f28ec7 [Kyle Ellrott] Adding second putValues to BlockStore interface that accepts an ArrayBuffer (rather then an Iterator). This will allow BlockStores to have slightly different behaviors dependent on whether they get an Iterator or ArrayBuffer. In the case of the MemoryStore, it needs to duplicate and cache an Iterator into an ArrayBuffer, but if handed a ArrayBuffer, it can skip the duplication.
656c33e [Kyle Ellrott] Fixing the JavaSerializer to read from the SparkConf rather then the System property.
8644ee8 [Kyle Ellrott] Merge branch 'master' into iterator-to-disk
00c98e0 [Kyle Ellrott] Making the Java ObjectStreamSerializer reset rate configurable by the system variable 'spark.serializer.objectStreamReset', default is not 10000.
40fe1d7 [Kyle Ellrott] Removing rouge space
31fe08e [Kyle Ellrott] Removing un-needed semi-colons
9df0276 [Kyle Ellrott] Added check to make sure that streamed-to-dist RDD actually returns good data in the LargeIteratorSuite
a6424ba [Kyle Ellrott] Wrapping long line
2eeda75 [Kyle Ellrott] Fixing dumb mistake ("||" instead of "&&")
0e6f808 [Kyle Ellrott] Deleting temp output directory when done
95c7f67 [Kyle Ellrott] Simplifying StorageLevel checks
56f71cd [Kyle Ellrott] Merge branch 'master' into iterator-to-disk
44ec35a [Kyle Ellrott] Adding some comments.
5eb2b7e [Kyle Ellrott] Changing the JavaSerializer reset to occur every 1000 objects.
f403826 [Kyle Ellrott] Merge branch 'master' into iterator-to-disk
81d670c [Kyle Ellrott] Adding unit test for straight to disk iterator methods.
d32992f [Kyle Ellrott] Merge remote-tracking branch 'origin/master' into iterator-to-disk
cac1fad [Kyle Ellrott] Fixing MemoryStore, so that it converts incoming iterators to ArrayBuffer objects. This was previously done higher up the stack.
efe1102 [Kyle Ellrott] Changing CacheManager and BlockManager to pass iterators directly to the serializer when a 'DISK_ONLY' persist is called. This is in response to SPARK-942.
https://spark-project.atlassian.net/browse/SPARK-1171
When the executor is removed, the current implementation will only minus the freeCores of that executor. Actually we should minus the totalCores...
Author: CodingCat <zhunansjtu@gmail.com>
Author: Nan Zhu <CodingCat@users.noreply.github.com>
Closes#63 from CodingCat/simplify_CoarseGrainedSchedulerBackend and squashes the following commits:
f6bf93f [Nan Zhu] code clean
19c2bb4 [CodingCat] use copy idiom to reconstruct the workerOffers
43c13e9 [CodingCat] keep WorkerOffer immutable
af470d3 [CodingCat] style fix
0c0e409 [CodingCat] simplify the implementation of CoarseGrainedSchedulerBackend
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#72 from ScrapCodes/SPARK-1164/deprecate-reducebykeytodriver and squashes the following commits:
ee521cd [Prashant Sharma] SPARK-1164 Deprecated reduceByKeyToDriver as it is an alias for reduceByKeyLocally
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#17 from ScrapCodes/java8-lambdas and squashes the following commits:
95850e6 [Patrick Wendell] Some doc improvements and build changes to the Java 8 patch.
85a954e [Prashant Sharma] Nit. import orderings.
673f7ac [Prashant Sharma] Added support for -java-home as well
80a13e8 [Prashant Sharma] Used fake class tag syntax
26eb3f6 [Prashant Sharma] Patrick's comments on PR.
35d8d79 [Prashant Sharma] Specified java 8 building in the docs
31d4cd6 [Prashant Sharma] Maven build to support -Pjava8-tests flag.
4ab87d3 [Prashant Sharma] Review feedback on the pr
c33dc2c [Prashant Sharma] SPARK-964, Java 8 API Support.
This method appears to be broken -- since it never removes
anything from messages, and it adds new messages to it,
the while loop is an infinite loop. The method also does not appear
to have ever been used since the code was added in 2012, so
this commit removes it.
cc @mateiz who originally added this method in case there's a reason it should be here! (63051dd2bc)
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#69 from kayousterhout/remove_get_fifo and squashes the following commits:
053bc59 [Kay Ousterhout] Remove broken/unused Connection.getChunkFIFO method.
Lookup didn't have a unit test. Added two tests, one for with a partitioner, and one for without.
Author: Bryn Keller <bryn.keller@intel.com>
Closes#36 from xoltar/lookup and squashes the following commits:
3bc0d44 [Bryn Keller] Added a unit test for PairRDDFunctions.lookup
This metric is confusing: it adds up all of the time to fetch
shuffle inputs, but fetches often happen in parallel, so
remoteFetchTime can be much longer than the task execution time.
@squito it looks like you added this metric -- do you have a use case for it?
cc @shivaram -- I know you've looked at the shuffle performance a lot so chime in here if this metric has turned out to be useful for you!
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#62 from kayousterhout/remove_fetch_variable and squashes the following commits:
43341eb [Kay Ousterhout] Remote the remoteFetchTime metric.
It looks like this comment was added a while ago by @mridulm as part of a merge and was accidentally checked in. We should remove it.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#61 from kayousterhout/remove_comment and squashes the following commits:
0b2b3f2 [Kay Ousterhout] Removed accidentally checked in comment
This lets us explicitly include Avro based on a profile for 0.23.X
builds. It makes me sad how convoluted it is to express this logic
in Maven. @tgraves and @sryza curious if this works for you.
I'm also considering just reverting to how it was before. The only
real problem was that Spark advertised a dependency on Avro
even though it only really depends transitively on Avro through
other deps.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#49 from pwendell/avro-build-fix and squashes the following commits:
8d6ee92 [Patrick Wendell] SPARK-1121: Add avro to yarn-alpha profile
(Ported from https://github.com/apache/incubator-spark/pull/650 )
This adds one more change though, to fix the scala version warning introduced by json4s recently.
Author: Sean Owen <sowen@cloudera.com>
Closes#32 from srowen/SPARK-1084.2 and squashes the following commits:
9240abd [Sean Owen] Avoid scala version conflict in scalap induced by json4s dependency
1561cec [Sean Owen] Remove "exclude *" dependencies that are causing Maven warnings, and that are apparently unneeded anyway
Previously, ZooKeeperPersistenceEngine would crash the whole Master process if
there was stored data from a prior Spark version. Now, we just delete these files.
Author: Aaron Davidson <aaron@databricks.com>
Closes#4 from aarondav/zookeeper2 and squashes the following commits:
fa8b40f [Aaron Davidson] SPARK-1137: Make ZK PersistenceEngine not crash for wrong serialVersionUID
This removes some loose ends not caught by the other (incubating -> tlp) patches. @markhamstra this updates the version as you mentioned earlier.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#51 from pwendell/tlp and squashes the following commits:
d553b1b [Patrick Wendell] Remove remaining references to incubation
Thanks for Diana Carroll to report this issue (https://spark-project.atlassian.net/browse/SPARK-1100)
the current saveAsTextFile/SequenceFile will overwrite the output directory silently if the directory already exists, this behaviour is not desirable because
overwriting the data silently is not user-friendly
if the partition number of two writing operation changed, then the output directory will contain the results generated by two runnings
My fix includes:
add some new APIs with a flag for users to define whether he/she wants to overwrite the directory:
if the flag is set to true, then the output directory is deleted first and then written into the new data to prevent the output directory contains results from multiple rounds of running;
if the flag is set to false, Spark will throw an exception if the output directory already exists
changed JavaAPI part
default behaviour is overwriting
Two questions
should we deprecate the old APIs without such a flag?
I noticed that Spark Streaming also called these APIs, I thought we don't need to change the related part in streaming? @tdas
Author: CodingCat <zhunansjtu@gmail.com>
Closes#11 from CodingCat/SPARK-1100 and squashes the following commits:
6a4e3a3 [CodingCat] code clean
ef2d43f [CodingCat] add new test cases and code clean
ac63136 [CodingCat] checkOutputSpecs not applicable to FSOutputFormat
ec490e8 [CodingCat] prevent Spark from overwriting directory silently and leaving dirty directory
https://spark-project.atlassian.net/browse/SPARK-1150
fix the repo location in create_release script
Author: Mark Grover <mark@apache.org>
Closes#48 from CodingCat/script_fixes and squashes the following commits:
01f4bf7 [Mark Grover] Fixing some nitpicks
d2244d4 [Mark Grover] SPARK-676: Abbreviation in SPARK_MEM but not in SPARK_WORKER_MEMORY
This commit randomizes the order of resource offers to avoid scheduling
all tasks on the same small set of machines.
This is a much simpler solution to SPARK-979 than #7.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#27 from kayousterhout/randomize and squashes the following commits:
435d817 [Kay Ousterhout] [SPARK-979] Randomize order of offers.
This reopens https://github.com/apache/incubator-spark/pull/538 against the new repo
Author: Sandy Ryza <sandy@cloudera.com>
Closes#29 from sryza/sandy-spark-1051 and squashes the following commits:
708ce49 [Sandy Ryza] SPARK-1051. doAs submitting user in YARN
This trait seems to have been created a while ago when there
were multiple implementations; now that there's just one, I think it
makes sense to merge it into the BlockFetcherIterator trait.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#39 from kayousterhout/remove_tracker and squashes the following commits:
8173939 [Kay Ousterhout] Remote BlockFetchTracker.
That patch removed the Maven avro declaration but didn't remove the
actual dependency in core. /cc @scrapcodes
Author: Patrick Wendell <pwendell@gmail.com>
Closes#37 from pwendell/master and squashes the following commits:
0ef3008 [Patrick Wendell] [HOTFIX] Patching maven build after #6 (SPARK-1121).
(Ported from https://github.com/apache/incubator-spark/pull/637 )
Author: Sean Owen <sowen@cloudera.com>
Closes#31 from srowen/SPARK-1084.1 and squashes the following commits:
6c4a32c [Sean Owen] Suppress warnings about legitimate unchecked array creations, or change code to avoid it
f35b833 [Sean Owen] Fix two misc javadoc problems
254e8ef [Sean Owen] Fix one new style error introduced in scaladoc warning commit
5b2fce2 [Sean Owen] Fix scaladoc invocation warning, and enable javac warnings properly, with plugin config updates
007762b [Sean Owen] Remove dead scaladoc links
b8ff8cb [Sean Owen] Replace deprecated Ant <tasks> with <target>
For standalone HA mode, A status is useful to identify the current master, already in json format too.
Author: Raymond Liu <raymond.liu@intel.com>
Closes#24 from colorant/status and squashes the following commits:
df630b3 [Raymond Liu] Show Master status on UI page
If the seed is zero, XORShift generates all zeros, which would create unexpected result.
JIRA: https://spark-project.atlassian.net/browse/SPARK-1129
Author: Xiangrui Meng <meng@databricks.com>
Closes#645 from mengxr/xor and squashes the following commits:
1b086ab [Xiangrui Meng] use MurmurHash3 to set seed in XORShiftRandom
45c6f16 [Xiangrui Meng] minor style change
51f4050 [Xiangrui Meng] use a predefined seed when seed is zero in XORShiftRandom
ClusterScheduler was renamed to TaskSchedulerImpl; this commit
updates comments and tests accordingly.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#9 from kayousterhout/cluster_scheduler_death and squashes the following commits:
d6fd119 [Kay Ousterhout] Remove references to ClusterScheduler.
PR [402](https://github.com/apache/incubator-spark/pull/402) from incubator repo.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#19 from ScrapCodes/java-api-completeness and squashes the following commits:
11d0c2b [Prashant Sharma] Integer -> java.lang.Integer
737819a [Prashant Sharma] SPARK-1095 add explicit return types to APIs.
3ddc8bb [Prashant Sharma] Deprected *With functions in scala and added a few missing Java APIs
The aim of the Json4s project is to provide a common API for
Scala JSON libraries. It is Apache-licensed, easier for
downstream distributions to package, and mostly API-compatible
with lift-json. Furthermore, the Jackson-backed implementation
parses faster than lift-json on all but the smallest inputs.
Author: William Benton <willb@redhat.com>
Closes#582 from willb/json4s and squashes the following commits:
7ca62c4 [William Benton] Replace lift-json with json4s-jackson.
[SPARK-1108] This allows us to use, e.g. HBase's TableOutputFormat with PairRDDFunctions.saveAsNewAPIHadoopFile, which otherwise would throw NullPointerException because the output table name hasn't been configured.
Note this bug also affects branch-0.9
Author: Bryn Keller <bryn.keller@intel.com>
Closes#638 from xoltar/SPARK-1108 and squashes the following commits:
7e94e7d [Bryn Keller] Import, comment, and format cleanup per code review
7cbcaa1 [Bryn Keller] For outputformats that are Configurable, call setConf before sending data to them. This allows us to use, e.g. HBase TableOutputFormat, which otherwise would throw NullPointerException because the output table name hasn't been configured
In the previous code, if you had a failing map stage and then tried to
run reduce stages on it repeatedly, the first reduce stage would fail
correctly, but the later ones would mistakenly believe that all map
outputs are available and start failing infinitely with fetch failures
from "null".
Prompted by a recent thread on the mailing list, I tried and failed to see if Spark can be made independent of log4j. There are a few cases where control of the underlying logging is pretty useful, and to do that, you have to bind to a specific logger.
Instead I propose some tidying that leaves Spark's use of log4j, but gets rid of warnings and should still enable downstream users to switch. The idea is to pipe everything (except log4j) through SLF4J, and have Spark use SLF4J directly when logging, and where Spark needs to output info (REPL and tests), bind from SLF4J to log4j.
This leaves the same behavior in Spark. It means that downstream users who want to use something except log4j should:
- Exclude dependencies on log4j, slf4j-log4j12 from Spark
- Include dependency on log4j-over-slf4j
- Include dependency on another logger X, and another slf4j-X
- Recreate any log config that Spark does, that is needed, in the other logger's config
That sounds about right.
Here are the key changes:
- Include the jcl-over-slf4j shim everywhere by depending on it in core.
- Exclude dependencies on commons-logging from third-party libraries.
- Include the jul-to-slf4j shim everywhere by depending on it in core.
- Exclude slf4j-* dependencies from third-party libraries to prevent collision or warnings
- Added missing slf4j-log4j12 binding to GraphX, Bagel module tests
And minor/incidental changes:
- Update to SLF4J 1.7.5, which happily matches Hadoop 2’s version and is a recommended update over 1.7.2
- (Remove a duplicate HBase dependency declaration in SparkBuild.scala)
- (Remove a duplicate mockito dependency declaration that was causing warnings and bugging me)
Author: Sean Owen <sowen@cloudera.com>
Closes#570 from srowen/SPARK-1071 and squashes the following commits:
52eac9f [Sean Owen] Add slf4j-over-log4j12 dependency to core (non-test) and remove it from things that depend on core.
77a7fa9 [Sean Owen] SPARK-1071: Tidy logging strategy and use of log4j
These classes can't be migrated:
StorageLevels: impossible to create static fields in Scala
JavaSparkContextVarargsWorkaround: incompatible varargs
JavaAPISuite: should test Java APIs in pure Java (for sanity)
Author: Punya Biswal <pbiswal@palantir.com>
Closes#605 from punya/move-java-sources and squashes the following commits:
25b00b2 [Punya Biswal] Remove redundant type param; reformat
853da46 [Punya Biswal] Use factory method rather than constructor
e5d53d9 [Punya Biswal] Migrate Java code to Scala or move it to src/main/java
The current doc hints spark doesn't support accumulators of type `Long`, which is wrong.
JIRA: https://spark-project.atlassian.net/browse/SPARK-1117
Author: Xiangrui Meng <meng@databricks.com>
Closes#631 from mengxr/acc and squashes the following commits:
45ecd25 [Xiangrui Meng] update accumulator docs
The original poster of this bug is @guojc, who opened a PR that preceded this one at https://github.com/apache/incubator-spark/pull/612.
ExternalAppendOnlyMap uses key hash code to order the buffer streams from which spilled files are read back into memory. When a buffer stream is empty, the default hash code for that stream is equal to Int.MaxValue. This is, however, a perfectly legitimate candidate for a key hash code. When reading from a spilled map containing such a key, a hash collision may occur, in which case we attempt to read from an empty stream and throw NoSuchElementException.
The fix is to maintain the invariant that empty buffer streams are never added back to the merge queue to be considered. This guarantees that we never read from an empty buffer stream, ever again.
This PR also includes two new tests for hash collisions.
Author: Andrew Or <andrewor14@gmail.com>
Closes#624 from andrewor14/spilling-bug and squashes the following commits:
9e7263d [Andrew Or] Slightly optimize next()
2037ae2 [Andrew Or] Move a few comments around...
cf95942 [Andrew Or] Remove default value of Int.MaxValue for minKeyHash
c11f03b [Andrew Or] Fix Int.MaxValue hash collision bug in ExternalAppendOnlyMap
21c1a39 [Andrew Or] Add hash collision tests to ExternalAppendOnlyMapSuite
Fixes an error where HDFS URL's cause an exception. Should be merged into master and 0.9.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#625 from pwendell/url-validation and squashes the following commits:
d14bfe3 [Patrick Wendell] SPARK-1111: URL Validation Throws Error for HDFS URL's
We changed the behavior in 0.9.0 from requiring that mergeCombiners be null when mapSideCombine was false to requiring that mergeCombiners *never* be null, for external sorting. This patch adds a require() to make this behavior change explicitly messaged rather than resulting in a NPE.
Author: Aaron Davidson <aaron@databricks.com>
Closes#623 from aarondav/master and squashes the following commits:
520b80c [Aaron Davidson] Super minor: Add require for mergeCombiners in combineByKey
Optimized imports and arranged according to scala style guide @
https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide#SparkCodeStyleGuide-Imports
Author: NirmalReddy <nirmal.reddy@imaginea.com>
Author: NirmalReddy <nirmal_reddy2000@yahoo.com>
Closes#613 from NirmalReddy/opt-imports and squashes the following commits:
578b4f5 [NirmalReddy] imported java.lang.Double as JDouble
a2cbcc5 [NirmalReddy] addressed the comments
776d664 [NirmalReddy] Optimized imports in core
Our usage of fake ClassTags in this manner is probably not healthy, but I'm not sure if there's a better solution available, so I just cleaned up and documented the current one.
Author: Aaron Davidson <aaron@databricks.com>
Closes#604 from aarondav/master and squashes the following commits:
b398e89 [Aaron Davidson] SPARK-1098: Minor cleanup of ClassTag usage in Java API
Author: Andrew Ash <andrew@andrewash.com>
Closes#608 from ash211/patch-7 and squashes the following commits:
bd85f2a [Andrew Ash] Worker registration logging fix
Author: Punya Biswal <pbiswal@palantir.com>
Closes#600 from punya/subtractByKey-java and squashes the following commits:
e961913 [Punya Biswal] Hide implicit ClassTags from Java API
c5d317b [Punya Biswal] Add subtractByKey to the JavaPairRDD wrapper
https://spark-project.atlassian.net/browse/SPARK-1092?jql=project%20%3D%20SPARK
print warning information if user set SPARK_MEM to regulate memory usage of executors
----
OUTDATED:
Currently, users will usually set SPARK_MEM to control the memory usage of driver programs, (in spark-class)
91 JAVA_OPTS="$OUR_JAVA_OPTS"
92 JAVA_OPTS="$JAVA_OPTS -Djava.library.path=$SPARK_LIBRARY_PATH"
93 JAVA_OPTS="$JAVA_OPTS -Xms$SPARK_MEM -Xmx$SPARK_MEM"
if they didn't set spark.executor.memory, the value in this environment variable will also affect the memory usage of executors, because the following lines in SparkContext
privatespark val executorMemory = conf.getOption("spark.executor.memory")
.orElse(Option(System.getenv("SPARK_MEM")))
.map(Utils.memoryStringToMb)
.getOrElse(512)
also
since SPARK_MEM has been (proposed to) deprecated in SPARK-929 (https://spark-project.atlassian.net/browse/SPARK-929) and the corresponding PR (https://github.com/apache/incubator-spark/pull/104)
we should remove this line
Author: CodingCat <zhunansjtu@gmail.com>
Closes#602 from CodingCat/clean_spark_mem and squashes the following commits:
302bb28 [CodingCat] print warning information if user use SPARK_MEM to regulate executor memory usage
SPARK-1076: [Fix#578] add @transient to some vals
I'll try to be more careful next time.
Author: Xiangrui Meng <meng@databricks.com>
Closes#591 and squashes the following commits:
2b4f044 [Xiangrui Meng] add @transient to prev in ZippedWithIndexRDD add @transient to seed in PartitionwiseSampledRDD
SPARK-1076: Convert Int to Long to avoid overflow
Patch for PR #578.
Author: Xiangrui Meng <meng@databricks.com>
Closes#589 and squashes the following commits:
98c435e [Xiangrui Meng] cast Int to Long to avoid Int overflow
SPARK-1076: zipWithIndex and zipWithUniqueId to RDD
Assign ranks to an ordered or unordered data set is a common operation. This could be done by first counting records in each partition and then assign ranks in parallel.
The purpose of assigning ranks to an unordered set is usually to get a unique id for each item, e.g., to map feature names to feature indices. In such cases, the assignment could be done without counting records, saving one spark job.
https://spark-project.atlassian.net/browse/SPARK-1076
== update ==
Because assigning ranks is very similar to Scala's zipWithIndex, I changed the method name to zipWithIndex and put the index in the value field.
Author: Xiangrui Meng <meng@databricks.com>
Closes#578 and squashes the following commits:
52a05e1 [Xiangrui Meng] changed assignRanks to zipWithIndex changed assignUniqueIds to zipWithUniqueId minor updates
756881c [Xiangrui Meng] simplified RankedRDD by implementing assignUniqueIds separately moved couting iterator size to Utils do not count items in the last partition and skip counting if there is only one partition
630868c [Xiangrui Meng] newline
21b434b [Xiangrui Meng] add assignRanks and assignUniqueIds to RDD
Minor fix for ZooKeeperPersistenceEngine to use configured working dir
Author: Raymond Liu <raymond.liu@intel.com>
Closes#583 and squashes the following commits:
91b0609 [Raymond Liu] Minor fix for ZooKeeperPersistenceEngine to use configured working dir
SPARK-1072 Use binary search when needed in RangePartioner
Author: Holden Karau <holden@pigscanfly.ca>
Closes#571 and squashes the following commits:
f31a2e1 [Holden Karau] Swith to using CollectionsUtils in Partitioner
4c7a0c3 [Holden Karau] Add CollectionsUtil as suggested by aarondav
7099962 [Holden Karau] Add the binary search to only init once
1bef01d [Holden Karau] CR feedback
a21e097 [Holden Karau] Use binary search if we have more than 1000 elements inside of RangePartitioner
SPARK-1058, Fix Style Errors and Add Scala Style to Spark Build. Pt 2
Continuation of PR #557
With this all scala style errors are fixed across the code base !!
The reason for creating a separate PR was to not interrupt an already reviewed and ready to merge PR. Hope this gets reviewed soon and merged too.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#567 and squashes the following commits:
3b1ec30 [Prashant Sharma] scala style fixes
[SPARK-1038] Add more fields in JsonProtocol and add tests that verify the JSON itself
This is a PR for SPARK-1038. Two major changes:
1 add some fields to JsonProtocol which is new and important to standalone-related data structures
2 Use Diff in liftweb.json to verity the stringified Json output for detecting someone mod type T to Option[T]
Author: qqsun8819 <jin.oyj@alibaba-inc.com>
Closes#551 and squashes the following commits:
fdf0b4e [qqsun8819] [SPARK-1038] 1. Change code style for more readable according to rxin review 2. change submitdate hard-coded string to a date object toString for more complexiblity
095a26f [qqsun8819] [SPARK-1038] mod according to review of pwendel, use hard-coded json string for json data validation. Each test use its own json string
0524e41 [qqsun8819] Merge remote-tracking branch 'upstream/master' into json-protocol
d203d5c [qqsun8819] [SPARK-1038] Add more fields in JsonProtocol and add tests that verify the JSON itself
[SPARK-1060] startJettyServer should explicitly use IP information
https://spark-project.atlassian.net/browse/SPARK-1060
In the current implementation, the webserver in Master/Worker is started with
val (srv, bPort) = JettyUtils.startJettyServer("0.0.0.0", port, handlers)
inside startJettyServer:
val server = new Server(currentPort) //here, the Server will take "0.0.0.0" as the hostname, i.e. will always bind to the IP address of the first NIC
this can cause wrong IP binding, e.g. if the host has two NICs, N1 and N2, the user specify the SPARK_LOCAL_IP as the N2's IP address, however, when starting the web server, for the reason stated above, it will always bind to the N1's address
Author: CodingCat <zhunansjtu@gmail.com>
== Merge branch commits ==
commit 6c6d9a8ccc9ec4590678a3b34cb03df19092029d
Author: CodingCat <zhunansjtu@gmail.com>
Date: Thu Feb 6 14:53:34 2014 -0500
startJettyServer should explicitly use IP information
[WIP] SPARK-1067: Default log4j initialization causes errors for those not using log4j
To fix this - we add a check when initializing log4j.
Author: Patrick Wendell <pwendell@gmail.com>
== Merge branch commits ==
commit ffdce513877f64b6eed6d36138c3e0003d392889
Author: Patrick Wendell <pwendell@gmail.com>
Date: Fri Feb 7 15:22:29 2014 -0800
Logging fix
Version number to 1.0.0-SNAPSHOT
Since 0.9.0-incubating is done and out the door, we shouldn't be building 0.9.0-incubating-SNAPSHOT anymore.
@pwendell
Author: Mark Hamstra <markhamstra@gmail.com>
== Merge branch commits ==
commit 1b00a8a7c1a7f251b4bb3774b84b9e64758eaa71
Author: Mark Hamstra <markhamstra@gmail.com>
Date: Wed Feb 5 09:30:32 2014 -0800
Version number to 1.0.0-SNAPSHOT
Kill drivers in postStop() for Worker.
JIRA SPARK-1068:https://spark-project.atlassian.net/browse/SPARK-1068
Author: Qiuzhuang Lian <Qiuzhuang.Lian@gmail.com>
== Merge branch commits ==
commit 9c19ce63637eee9369edd235979288d3d9fc9105
Author: Qiuzhuang Lian <Qiuzhuang.Lian@gmail.com>
Date: Sat Feb 8 16:07:39 2014 +0800
Kill drivers in postStop() for Worker.
JIRA SPARK-1068:https://spark-project.atlassian.net/browse/SPARK-1068
External spilling - generalize batching logic
The existing implementation consists of a hack for Kryo specifically and only works for LZF compression. Introducing an intermediate batch-level stream takes care of pre-fetching and other arbitrary behavior of higher level streams in a more general way.
Author: Andrew Or <andrewor14@gmail.com>
== Merge branch commits ==
commit 3ddeb7ef89a0af2b685fb5d071aa0f71c975cc82
Author: Andrew Or <andrewor14@gmail.com>
Date: Wed Feb 5 12:09:32 2014 -0800
Also privatize fields
commit 090544a87a0767effd0c835a53952f72fc8d24f0
Author: Andrew Or <andrewor14@gmail.com>
Date: Wed Feb 5 10:58:23 2014 -0800
Privatize methods
commit 13920c918efe22e66a1760b14beceb17a61fd8cc
Author: Andrew Or <andrewor14@gmail.com>
Date: Tue Feb 4 16:34:15 2014 -0800
Update docs
commit bd5a1d7350467ed3dc19c2de9b2c9f531f0e6aa3
Author: Andrew Or <andrewor14@gmail.com>
Date: Tue Feb 4 13:44:24 2014 -0800
Typo: phyiscal -> physical
commit 287ef44e593ad72f7434b759be3170d9ee2723d2
Author: Andrew Or <andrewor14@gmail.com>
Date: Tue Feb 4 13:38:32 2014 -0800
Avoid reading the entire batch into memory; also simplify streaming logic
Additionally, address formatting comments.
commit 3df700509955f7074821e9aab1e74cb53c58b5a5
Merge: a531d2e 164489d
Author: Andrew Or <andrewor14@gmail.com>
Date: Mon Feb 3 18:27:49 2014 -0800
Merge branch 'master' of github.com:andrewor14/incubator-spark
commit a531d2e347acdcecf2d0ab72cd4f965ab5e145d8
Author: Andrew Or <andrewor14@gmail.com>
Date: Mon Feb 3 18:18:04 2014 -0800
Relax assumptions on compressors and serializers when batching
This commit introduces an intermediate layer of an input stream on the batch level.
This guards against interference from higher level streams (i.e. compression and
deserialization streams), especially pre-fetching, without specifically targeting
particular libraries (Kryo) and forcing shuffle spill compression to use LZF.
commit 164489d6f176bdecfa9dabec2dfce5504d1ee8af
Author: Andrew Or <andrewor14@gmail.com>
Date: Mon Feb 3 18:18:04 2014 -0800
Relax assumptions on compressors and serializers when batching
This commit introduces an intermediate layer of an input stream on the batch level.
This guards against interference from higher level streams (i.e. compression and
deserialization streams), especially pre-fetching, without specifically targeting
particular libraries (Kryo) and forcing shuffle spill compression to use LZF.
Only run ResubmitFailedStages event after a fetch fails
Previously, the ResubmitFailedStages event was called every
200 milliseconds, leading to a lot of unnecessary event processing
and clogged DAGScheduler logs.
Author: Kay Ousterhout <kayousterhout@gmail.com>
== Merge branch commits ==
commit e603784b3a562980e6f1863845097effe2129d3b
Author: Kay Ousterhout <kayousterhout@gmail.com>
Date: Wed Feb 5 11:34:41 2014 -0800
Re-add check for empty set of failed stages
commit d258f0ef50caff4bbb19fb95a6b82186db1935bf
Author: Kay Ousterhout <kayousterhout@gmail.com>
Date: Wed Jan 15 23:35:41 2014 -0800
Only run ResubmitFailedStages event after a fetch fails
Previously, the ResubmitFailedStages event was called every
200 milliseconds, leading to a lot of unnecessary event processing
and clogged DAGScheduler logs.
Inform DAG scheduler about all started/finished tasks.
Previously, the DAG scheduler was not always informed
when tasks started and finished. The simplest example here
is for speculated tasks: the DAGScheduler was only told about
the first attempt of a task, meaning that SparkListeners were
also not told about multiple task attempts, so users can't see
what's going on with speculation in the UI. The DAGScheduler
also wasn't always told about finished tasks, so in the UI, some
tasks will never be shown as finished (this occurs, for example,
if a task set gets killed).
The other problem is that the fairness accounting was wrong
-- the number of running tasks in a pool was decreased when a
task set was considered done, even if all of its tasks hadn't
yet finished.
Author: Kay Ousterhout <kayousterhout@gmail.com>
== Merge branch commits ==
commit c8d547d0f7a17f5a193bef05f5872b9f475675c5
Author: Kay Ousterhout <kayousterhout@gmail.com>
Date: Wed Jan 15 16:47:33 2014 -0800
Addressed Reynold's review comments.
Always use a TaskEndReason (remove the option), and explicitly
signal when we don't know the reason. Also, always tell
DAGScheduler (and associated listeners) about started tasks, even
when they're speculated.
commit 3fee1e2e3c06b975ff7f95d595448f38cce97a04
Author: Kay Ousterhout <kayousterhout@gmail.com>
Date: Wed Jan 8 22:58:13 2014 -0800
Fixed broken test and improved logging
commit ff12fcaa2567c5d02b75a1d5db35687225bcd46f
Author: Kay Ousterhout <kayousterhout@gmail.com>
Date: Sun Dec 29 21:08:20 2013 -0800
Inform DAG scheduler about all finished tasks.
Previously, the DAG scheduler was not always informed
when tasks finished. For example, when a task set was
aborted, the DAG scheduler was never told when the tasks
in that task set finished. The DAG scheduler was also
never told about the completion of speculated tasks.
This led to confusion with SparkListeners because information
about the completion of those tasks was never passed on to
the listeners (so in the UI, for example, some tasks will never
be shown as finished).
The other problem is that the fairness accounting was wrong
-- the number of running tasks in a pool was decreased when a
task set was considered done, even if all of its tasks hadn't
yet finished.
SPARK-1056. Fix header comment in Executor to not imply that it's only u...
...sed for Mesos and Standalone.
Author: Sandy Ryza <sandy@cloudera.com>
== Merge branch commits ==
commit 1f2443d902a26365a5c23e4af9077e1539ed2eab
Author: Sandy Ryza <sandy@cloudera.com>
Date: Thu Feb 6 15:03:50 2014 -0800
SPARK-1056. Fix header comment in Executor to not imply that it's only used for Mesos and Standalone
remove actorToWorker in master.scala, which is actually not used
actorToWorker is actually not used in the code....just remove it
Author: CodingCat <zhunansjtu@gmail.com>
== Merge branch commits ==
commit 52656c2d4bbf9abcd8bef65d454badb9cb14a32c
Author: CodingCat <zhunansjtu@gmail.com>
Date: Thu Feb 6 00:28:26 2014 -0500
remove actorToWorker in master.scala, which is actually not used
Fixed warnings in test compilation.
This commit fixes two problems: a redundant import, and a
deprecated function.
Author: Kay Ousterhout <kayousterhout@gmail.com>
== Merge branch commits ==
commit da9d2e13ee4102bc58888df0559c65cb26232a82
Author: Kay Ousterhout <kayousterhout@gmail.com>
Date: Wed Feb 5 11:41:51 2014 -0800
Fixed warnings in test compilation.
This commit fixes two problems: a redundant import, and a
deprecated function.
Refactor RDD sampling and add randomSplit to RDD (update)
Replace SampledRDD by PartitionwiseSampledRDD, which accepts a RandomSampler instance as input. The current sample with/without replacement can be easily integrated via BernoulliSampler and PoissonSampler. The benefits are:
1) RDD.randomSplit is implemented in the same way, related to https://github.com/apache/incubator-spark/pull/513
2) Stratified sampling and importance sampling can be implemented in the same manner as well.
Unit tests are included for samplers and RDD.randomSplit.
This should performance better than my previous request where the BernoulliSampler creates many Iterator instances:
https://github.com/apache/incubator-spark/pull/513
Author: Xiangrui Meng <meng@databricks.com>
== Merge branch commits ==
commit e8ce957e5f0a600f2dec057924f4a2ca6adba373
Author: Xiangrui Meng <meng@databricks.com>
Date: Mon Feb 3 12:21:08 2014 -0800
more docs to PartitionwiseSampledRDD
commit fbb4586d0478ff638b24bce95f75ff06f713d43b
Author: Xiangrui Meng <meng@databricks.com>
Date: Mon Feb 3 00:44:23 2014 -0800
move XORShiftRandom to util.random and use it in BernoulliSampler
commit 987456b0ee8612fd4f73cb8c40967112dc3c4c2d
Author: Xiangrui Meng <meng@databricks.com>
Date: Sat Feb 1 11:06:59 2014 -0800
relax assertions in SortingSuite because the RangePartitioner has large variance in this case
commit 3690aae416b2dc9b2f9ba32efa465ba7948477f4
Author: Xiangrui Meng <meng@databricks.com>
Date: Sat Feb 1 09:56:28 2014 -0800
test split ratio of RDD.randomSplit
commit 8a410bc933a60c4d63852606f8bbc812e416d6ae
Author: Xiangrui Meng <meng@databricks.com>
Date: Sat Feb 1 09:25:22 2014 -0800
add a test to ensure seed distribution and minor style update
commit ce7e866f674c30ab48a9ceb09da846d5362ab4b6
Author: Xiangrui Meng <meng@databricks.com>
Date: Fri Jan 31 18:06:22 2014 -0800
minor style change
commit 750912b4d77596ed807d361347bd2b7e3b9b7a74
Author: Xiangrui Meng <meng@databricks.com>
Date: Fri Jan 31 18:04:54 2014 -0800
fix some long lines
commit c446a25c38d81db02821f7f194b0ce5ab4ed7ff5
Author: Xiangrui Meng <meng@databricks.com>
Date: Fri Jan 31 17:59:59 2014 -0800
add complement to BernoulliSampler and minor style changes
commit dbe2bc2bd888a7bdccb127ee6595840274499403
Author: Xiangrui Meng <meng@databricks.com>
Date: Fri Jan 31 17:45:08 2014 -0800
switch to partition-wise sampling for better performance
commit a1fca5232308feb369339eac67864c787455bb23
Merge: ac712e4 cf6128f
Author: Xiangrui Meng <meng@databricks.com>
Date: Fri Jan 31 16:33:09 2014 -0800
Merge branch 'sample' of github.com:mengxr/incubator-spark into sample
commit cf6128fb672e8c589615adbd3eaa3cbdb72bd461
Author: Xiangrui Meng <meng@databricks.com>
Date: Sun Jan 26 14:40:07 2014 -0800
set SampledRDD deprecated in 1.0
commit f430f847c3df91a3894687c513f23f823f77c255
Author: Xiangrui Meng <meng@databricks.com>
Date: Sun Jan 26 14:38:59 2014 -0800
update code style
commit a8b5e2021a9204e318c80a44d00c5c495f1befb6
Author: Xiangrui Meng <meng@databricks.com>
Date: Sun Jan 26 12:56:27 2014 -0800
move package random to util.random
commit ab0fa2c4965033737a9e3a9bf0a59cbb0df6a6f5
Author: Xiangrui Meng <meng@databricks.com>
Date: Sun Jan 26 12:50:35 2014 -0800
add Apache headers and update code style
commit 985609fe1a55655ad11966e05a93c18c138a403d
Author: Xiangrui Meng <meng@databricks.com>
Date: Sun Jan 26 11:49:25 2014 -0800
add new lines
commit b21bddf29850a2c006a868869b8f91960a029322
Author: Xiangrui Meng <meng@databricks.com>
Date: Sun Jan 26 11:46:35 2014 -0800
move samplers to random.IndependentRandomSampler and add tests
commit c02dacb4a941618e434cefc129c002915db08be6
Author: Xiangrui Meng <meng@databricks.com>
Date: Sat Jan 25 15:20:24 2014 -0800
add RandomSampler
commit 8ff7ba3c5cf1fc338c29ae8b5fa06c222640e89c
Author: Xiangrui Meng <meng@databricks.com>
Date: Fri Jan 24 13:23:22 2014 -0800
init impl of IndependentlySampledRDD
Remove explicit conversion to PairRDDFunctions in cogroup()
As SparkContext._ is already imported, using the implicit conversion appears to make the code much cleaner. Perhaps there was some sinister reason for doing the conversion explicitly, however.
Author: Aaron Davidson <aaron@databricks.com>
== Merge branch commits ==
commit aa4a63f1bfd5b5178fe67364dd7ce4d84c357996
Author: Aaron Davidson <aaron@databricks.com>
Date: Sun Feb 2 23:48:04 2014 -0800
Remove explicit conversion to PairRDDFunctions in cogroup()
As SparkContext._ is already imported, using the implicit conversion
appears to make the code much cleaner. Perhaps there was some sinister
reason for doing the converion explicitly, however.
Issue with failed worker registrations
I've been going through the spark source after having some odd issues with workers dying and not coming back. After some digging (I'm very new to scala and spark) I believe I've found a worker registration issue. It looks to me like a failed registration follows the same code path as a successful registration which end up with workers believing they are connected (since they received a `RegisteredWorker` event) even tho they are not registered on the Master.
This is a quick fix that I hope addresses this issue (assuming I didn't completely miss-read the code and I'm about to look like a silly person :P)
I'm opening this pr now to start a chat with you guys while I do some more testing on my side :)
Author: Erik Selin <erik.selin@jadedpixel.com>
== Merge branch commits ==
commit 973012f8a2dcf1ac1e68a69a2086a1b9a50f401b
Author: Erik Selin <erik.selin@jadedpixel.com>
Date: Tue Jan 28 23:36:12 2014 -0500
break logwarning into two lines to respect line character limit.
commit e3754dc5b94730f37e9806974340e6dd93400f85
Author: Erik Selin <erik.selin@jadedpixel.com>
Date: Tue Jan 28 21:16:21 2014 -0500
add log warning when worker registration fails due to attempt to re-register on same address.
commit 14baca241fa7823e1213cfc12a3ff2a9b865b1ed
Author: Erik Selin <erik.selin@jadedpixel.com>
Date: Wed Jan 22 21:23:26 2014 -0500
address code style comment
commit 71c0d7e6f59cd378d4e24994c21140ab893954ee
Author: Erik Selin <erik.selin@jadedpixel.com>
Date: Wed Jan 22 16:01:42 2014 -0500
Make a failed registration not persist, not send a `RegisteredWordker` event and not run `schedule` but rather send a `RegisterWorkerFailed` message to the worker attempting to register.
This fixes SPARK-1043, a bug introduced in 0.9.0
where PySpark couldn't serialize strings > 64kB.
This fix was written by @tyro89 and @bouk in #512.
This commit squashes and rebases their pull request
in order to fix some merge conflicts.
Allow files added through SparkContext.addFile() to be overwritten
This is useful for the cases when a file needs to be refreshed and downloaded by the executors periodically. For example, a possible use case is: the driver periodically renews a Hadoop delegation token and writes it to a token file. The token file needs to be downloaded by the executors whenever it gets renewed. However, the current implementation throws an exception when the target file exists and its contents do not match those of the new source. This PR adds an option to allow files to be overwritten to support use cases similar to the above.
Replace the check for None Option with isDefined and isEmpty in Scala code
Propose to replace the Scala check for Option "!= None" with Option.isDefined and "=== None" with Option.isEmpty.
I think this, using method call if possible then operator function plus argument, will make the Scala code easier to read and understand.
Pass compile and tests.
Fix PySpark hang when input files are deleted (SPARK-1025)
This pull request addresses [SPARK-1025](https://spark-project.atlassian.net/browse/SPARK-1025), an issue where PySpark could hang if its input files were deleted.
This fixes an issue where collectAsMap() could
fail when called on a JavaPairRDD that was derived
by transforming a non-JavaPairRDD.
The root problem was that we were creating the
JavaPairRDD's ClassTag by casting a
ClassTag[AnyRef] to a ClassTag[Tuple2[K2, V2]].
To fix this, I cast a ClassTag[Tuple2[_, _]]
instead, since this actually produces a ClassTag
of the appropriate type because ClassTags don't
capture type parameters:
scala> implicitly[ClassTag[Tuple2[_, _]]] == implicitly[ClassTag[Tuple2[Int, Int]]]
res8: Boolean = true
scala> implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[Tuple2[Int, Int]]] == implicitly[ClassTag[Tuple2[Int, Int]]]
res9: Boolean = false
Remove Hadoop object cloning and warn users making Hadoop RDD's.
The code introduced in #359 used Hadoop's WritableUtils.clone() to
duplicate objects when reading from Hadoop files. Some users have
reported exceptions when cloning data in various file formats,
including Avro and another custom format.
This patch removes that functionality to ensure stability for the
0.9 release. Instead, it puts a clear warning in the documentation
that copying may be necessary for Hadoop data sets.
Fix two bugs in PySpark cartesian(): SPARK-978 and SPARK-1034
This pull request fixes two bugs in PySpark's `cartesian()` method:
- [SPARK-978](https://spark-project.atlassian.net/browse/SPARK-978): PySpark's cartesian method throws ClassCastException exception
- [SPARK-1034](https://spark-project.atlassian.net/browse/SPARK-1034): Py4JException on PySpark Cartesian Result
The JIRAs have more details describing the fixes.
The code introduced in #359 used Hadoop's WritableUtils.clone() to
duplicate objects when reading from Hadoop files. Some users have
reported exceptions when cloning data in verious file formats,
including Avro and another custom format.
This patch removes that functionality to ensure stability for the
0.9 release. Instead, it puts a clear warning in the documentation
that copying may be necessary for Hadoop data sets.
Fix bug in worker clean-up in UI
Introduced in d5a96fec (/cc @aarondav).
This should be picked into 0.8 and 0.9 as well. The bug causes old (zombie) workers on a node to not disappear immediately from the UI when a new one registers.
fix for SPARK-1027
fix for SPARK-1027 (https://spark-project.atlassian.net/browse/SPARK-1027)
FIXES
1. change sparkhome from String to Option(String) in ApplicationDesc
2. remove sparkhome parameter in LaunchExecutor message
3. adjust involved files
This bug leads to a small performance hit because task
set managers will get offered each rejected resource
offer twice, but doesn't lead to any incorrect functionality.
Minor api usability changes
- Expose checkpoint directory - since it is autogenerated now
- null check for jars
- Expose SparkHadoopUtil : so that configuration creation is abstracted even from user code to avoid duplication of functionality already in spark.
Remove Typesafe Config usage and conf files to fix nested property names
With Typesafe Config we had the subtle problem of no longer allowing
nested property names, which are used for a few of our properties:
http://apache-spark-developers-list.1001551.n3.nabble.com/Config-properties-broken-in-master-td208.html
This PR is for branch 0.9 but should be added into master too.
(cherry picked from commit 34e911ce9a)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
This is useful for the cases when a file needs to be refreshed and downloaded
by the executors periodically.
Signed-off-by: Yinan Li <liyinan926@gmail.com>
Fail rather than hanging if a task crashes the JVM.
Prior to this commit, if a task crashes the JVM, the task (and
all other tasks running on that executor) is marked at KILLED rather
than FAILED. As a result, the TaskSetManager will retry the task
indefinitely rather than failing the job after maxFailures. Eventually,
this makes the job hang, because the Standalone Scheduler removes
the application after 10 works have failed, and then the app is left
in a state where it's disconnected from the master and waiting to reconnect.
This commit fixes that problem by marking tasks as FAILED rather than
killed when an executor is lost.
The downside of this commit is that if task A fails because another
task running on the same executor caused the VM to crash, the failure
will incorrectly be counted as a failure of task A. This should not
be an issue because we typically set maxFailures to 3, and it is
unlikely that a task will be co-located with a JVM-crashing task
multiple times.
Prior to this commit, if a task crashes the JVM, the task (and
all other tasks running on that executor) is marked at KILLED rather
than FAILED. As a result, the TaskSetManager will retry the task
indefiniteily rather than failing the job after maxFailures. This
commit fixes that problem by marking tasks as FAILED rather than
killed when an executor is lost.
The downside of this commit is that if task A fails because another
task running on the same executor caused the VM to crash, the failure
will incorrectly be counted as a failure of task A. This should not
be an issue because we typically set maxFailures to 3, and it is
unlikely that a task will be co-located with a JVM-crashing task
multiple times.
Workers should use working directory as spark home if it's not specified
If users don't set SPARK_HOME in their environment file when launching an application, the standalone cluster should default to the spark home of the worker.
Note that previously Broadcast class was accidentally marked as private[spark]. It needs to be public
for broadcast variables to work. Also exposing the broadcast varaible id.
GraphX: Unifying Graphs and Tables
GraphX extends Spark's distributed fault-tolerant collections API and interactive console with a new graph API which leverages recent advances in graph systems (e.g., [GraphLab](http://graphlab.org)) to enable users to easily and interactively build, transform, and reason about graph structured data at scale. See http://amplab.github.io/graphx/.
Thanks to @jegonzal, @rxin, @ankurdave, @dcrankshaw, @jianpingjwang, @amatsukawa, @kellrott, and @adamnovak.
Tasks left:
- [x] Graph-level uncache
- [x] Uncache previous iterations in Pregel
- [x] ~~Uncache previous iterations in GraphLab~~ (postponed to post-release)
- [x] - Describe GC issue with GraphLab
- [ ] Write `docs/graphx-programming-guide.md`
- [x] - Mention future Bagel support in docs
- [ ] - Section on caching/uncaching in docs: As with Spark, cache something that is used more than once. In an iterative algorithm, try to cache and force (i.e., materialize) something every iteration, then uncache the cached things that depended on the newly materialized RDD but that won't be referenced again.
- [x] Undo modifications to core collections and instead copy them to org.apache.spark.graphx
- [x] Make Graph serializable to work around capture in Spark shell
- [x] Rename graph -> graphx in package name and subproject
- [x] Remove standalone PageRank
- [x] ~~Fix amplab/graphx#52 by checking `iter.hasNext`~~
Improvements to external sorting
1. Adds the option of compressing outputs.
2. Adds batching to the serialization to prevent OOM on the read side.
3. Slight renaming of config options.
4. Use Spark's buffer size for reads in addition to writes.
Automatically unpersisting RDDs that have been cleaned up from DStreams
Earlier RDDs generated by DStreams were forgotten but not unpersisted. The system relied on the natural BlockManager LRU to drop the data. The cleaner.ttl was a hammer to clean up RDDs but it is something that needs to be set separately and need to be set very conservatively (at best, few minutes). This automatic unpersisting allows the system to handle this automatically, which reduces memory usage. As a side effect it will also improve GC performance as there are less number of objects stored in memory. In fact, for some workloads, it may allow RDDs to be cached as deserialized, which speeds up processing without too much GC overheads.
This is disabled by default. To enable it set configuration spark.streaming.unpersist to true. In future release, this will be set to true by default.
Also, reduced sleep time in TaskSchedulerImpl.stop() from 5 second to 1 second. From my conversation with Matei, there does not seem to be any good reason for the sleep for letting messages be sent out be so long.
1. Adds the option of compressing outputs.
2. Adds batching to the serialization to prevent OOM on the read side.
3. Slight renaming of config options.
4. Use Spark's buffer size for reads in addition to writes.
Remove now un-needed hostPort option
I noticed this was logging some scary error messages in various places. After I looked into it, this is no longer really used. I removed the option and re-wrote the one remaining use case (it was unnecessary there anyways).
Disable shuffle file consolidation by default
After running various performance tests for the 0.9 release, this still seems to have performance issues even on XFS. So let's keep this off-by-default for 0.9 and users can experiment with it depending on their disk configurations.
Remove simple redundant return statements for Scala methods/functions
Remove simple redundant return statements for Scala methods/functions:
-) Only change simple return statements at the end of method
-) Ignore the complex if-else check
-) Ignore the ones inside synchronized
-) Add small changes to making var to val if possible and remove () for simple get
This hopefully makes the review simpler =)
Pass compile and tests.
Setting load defaults to true in executor
This preserves the behavior in earlier releases. If properties are set for the executors via `spark-env.sh` on the slaves, then they should take precedence over spark defaults. This is useful for if system administrators are setting properties for a standalone cluster, such as shuffle locations.
/cc @andrewor14 who initially reported this issue.
Stop SparkListenerBus daemon thread when DAGScheduler is stopped.
Otherwise this leads to hundreds of SparkListenerBus daemon threads in our unit tests (and also problematic if user applications launches multiple SparkContext).
We clone hadoop key and values by default and reuse objects if asked to.
We try to clone for most common types of writables and we call WritableUtils.clone otherwise intention is to optimize, for example for NullWritable there is no need and for Long, int and String creating a new object with value set would be faster than doing copy on object hopefully.
There is another way to do this PR where we ask for both key and values whether to clone them or not, but could not think of a use case for it except either of them is actually a NullWritable for which I have already worked around. So thought that would be unnecessary.
API for automatic driver recovery for streaming programs and other bug fixes
1. Added Scala and Java API for automatically loading checkpoint if it exists in the provided checkpoint directory.
Scala API: `StreamingContext.getOrCreate(<checkpoint dir>, <function to create new StreamingContext>)` returns a StreamingContext
Java API: `JavaStreamingContext.getOrCreate(<checkpoint dir>, <factory obj of type JavaStreamingContextFactory>)`, return a JavaStreamingContext
See the RecoverableNetworkWordCount below as an example of how to use it.
2. Refactored streaming.Checkpoint*** code to fix bugs and make the DStream metadata checkpoint writing and reading more robust. Specifically, it fixes and improves the logic behind backing up and writing metadata checkpoint files. Also, it ensure that spark.driver.* and spark.hostPort is cleared from SparkConf before being written to checkpoint.
3. Fixed bug in cleaning up of checkpointed RDDs created by DStream. Specifically, this fix ensures that checkpointed RDD's files are not prematurely cleaned up, thus ensuring reliable recovery.
4. TimeStampedHashMap is upgraded to optionally update the timestamp on map.get(key). This allows clearing of data based on access time (i.e., clear records were last accessed before a threshold timestamp).
5. Added caching for file modification time in FileInputDStream using the updated TimeStampedHashMap. Without the caching, enumerating the mod times to find new files can take seconds if there are 1000s of files. This cache is automatically cleared.
This PR is not entirely final as I may make some minor additions - a Java examples, and adding StreamingContext.getOrCreate to unit test.
Edit: Java example to be added later, unit test added.
External Sorting for Aggregator and CoGroupedRDDs (Revisited)
(This pull request is re-opened from https://github.com/apache/incubator-spark/pull/303, which was closed because Jenkins / github was misbehaving)
The target issue for this patch is the out-of-memory exceptions triggered by aggregate operations such as reduce, groupBy, join, and cogroup. The existing AppendOnlyMap used by these operations resides purely in memory, and grows with the size of the input data until the amount of allocated memory is exceeded. Under large workloads, this problem is aggravated by the fact that OOM frequently occurs only after a very long (> 1 hour) map phase, in which case the entire job must be restarted.
The solution is to spill the contents of this map to disk once a certain memory threshold is exceeded. This functionality is provided by ExternalAppendOnlyMap, which additionally sorts this buffer before writing it out to disk, and later merges these buffers back in sorted order.
Under normal circumstances in which OOM is not triggered, ExternalAppendOnlyMap is simply a wrapper around AppendOnlyMap and incurs little overhead. Only when the memory usage is expected to exceed the given threshold does ExternalAppendOnlyMap spill to disk.
Aside from trivial formatting changes, use nulls instead of Options for
DiskMapIterator, and add documentation for spark.shuffle.externalSorting
and spark.shuffle.memoryFraction.
Also, set spark.shuffle.memoryFraction to 0.3, and spark.storage.memoryFraction = 0.6.
Yarn client addjar and misc fixes
Fix the addJar functionality in yarn-client mode, add support for the other options supported in yarn-standalone mode, set the application type on yarn in hadoop 2.X, add documentation, change heartbeat interval to be same code as the yarn-standalone so it doesn't take so long to get containers and exit.
Make DEBUG-level logs consummable.
Removes two things that caused issues with the debug logs:
(a) Internal polling in the DAGScheduler was polluting the logs.
(b) The Scala REPL logs were really noisy.
Removes two things that caused issues with the debug logs:
(a) Internal polling in the DAGScheduler was polluting the logs.
(b) The Scala REPL logs were really noisy.
Fix bug added when we changed AppDescription.maxCores to an Option
The Scala compiler warned about this -- we were comparing an Option against an integer now.
This is an alternative to the existing approach, which evenly distributes the
collective shuffle memory among all running tasks. In the new approach, each
thread requests a chunk of memory whenever its map is about to multiplicatively
grow. If there is sufficient memory in the global pool, the thread allocates it
and grows its map. Otherwise, it spills.
A danger with the previous approach is that a new task may quickly fill up its
map before old tasks finish spilling, potentially causing an OOM. This approach
prevents this scenario as it favors existing tasks over new tasks; any thread
that may step over the boundary of other threads defensively backs off and
starts spilling.
Testing through spark-perf reveals: (1) When no spills have occured, the
performance of external sorting using this memory management approach is
essentially the same as without external sorting. (2) When one or more spills
have occured, the performance of external sorting is a small multiple (3x) worse
Add some missing Java API methods
These are primarily for setting job groups, canceling jobs, and setting names on RDDs. Seemed like useful stuff to expose in Java.
Bug fixes for updating the RDD block's memory and disk usage information
Bug fixes for updating the RDD block's memory and disk usage information.
From the code context, we can find that the memSize and diskSize here are both always equal to the size of the block. Actually, they never be zero. Thus, the logic here is wrong for recording the block usage in BlockStatus, especially for the blocks which are dropped from memory to ensure space for the new input rdd blocks. I have tested it that this would cause the storage metrics shown in the Storage webpage wrong and misleading. With this patch, the metrics will be okay.
Finally, Merry Christmas, guys:)
SPARK-998: Support Launching Driver Inside of Standalone Mode
[NOTE: I need to bring the tests up to date with new changes, so for now they will fail]
This patch provides support for launching driver programs inside of a standalone cluster manager. It also supports monitoring and re-launching of driver programs which is useful for long running, recoverable applications such as Spark Streaming jobs. For those jobs, this patch allows a deployment mode which is resilient to the failure of any worker node, failure of a master node (provided a multi-master setup), and even failures of the applicaiton itself, provided they are recoverable on a restart. Driver information, such as the status and logs from a driver, is displayed in the UI
There are a few small TODO's here, but the code is generally feature-complete. They are:
- Bring tests up to date and add test coverage
- Restarting on failure should be optional and maybe off by default.
- See if we can re-use akka connections to facilitate clients behind a firewall
A sensible place to start for review would be to look at the `DriverClient` class which presents users the ability to launch their driver program. I've also added an example program (`DriverSubmissionTest`) that allows you to test this locally and play around with killing workers, etc. Most of the code is devoted to persisting driver state in the cluster manger, exposing it in the UI, and dealing correctly with various types of failures.
Instructions to test locally:
- `sbt/sbt assembly/assembly examples/assembly`
- start a local version of the standalone cluster manager
```
./spark-class org.apache.spark.deploy.client.DriverClient \
-j -Dspark.test.property=something \
-e SPARK_TEST_KEY=SOMEVALUE \
launch spark://10.99.1.14:7077 \
../path-to-examples-assembly-jar \
org.apache.spark.examples.DriverSubmissionTest 1000 some extra options --some-option-here -X 13
```
- Go in the UI and make sure it started correctly, look at the output etc
- Kill workers, the driver program, masters, etc.
Minor style cleanup. Mostly on indenting & line width changes.
Focused on the few important files since they are the files that new contributors usually read first.
