Read the port from RpcEnv to check the result so that it will success even if port conflicts
Author: zsxwing <zsxwing@gmail.com>
Closes#5822 from zsxwing/SPARK-7291 and squashes the following commits:
e521b84 [zsxwing] Fix a flaky test in AkkaRpcEnvSuite
andrewor14 pwendell I reenabled the test. Let's see if it's fixed. I did also notice that `--jars` started to fail after this was ignored though in the JIRA. like [here](https://amplab.cs.berkeley.edu/jenkins/job/Spark-Master-SBT/AMPLAB_JENKINS_BUILD_PROFILE=hadoop2.0,label=centos/2238/consoleFull), you see that --jars fails for the same exact reason.
Has any change been made to Spark Submit recently? Did the test setup on Jenkins change? If we look into flaky tests last month, you wouldn't find this test among them.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5826 from brkyvz/restart-test and squashes the following commits:
f509f68 [Burak Yavuz] enabled fixed test
Refer to the JIRA for the design doc and some perf results.
I wanted to call out some of the more possibly controversial changes up front:
* Map outputs are only stored in serialized form when Kryo is in use. I'm still unsure whether Java-serialized objects can be relocated. At the very least, Java serialization writes out a stream header which causes problems with the current approach, so I decided to leave investigating this to future work.
* The shuffle now explicitly operates on key-value pairs instead of any object. Data is written to shuffle files in alternating keys and values instead of key-value tuples. `BlockObjectWriter.write` now accepts a key argument and a value argument instead of any object.
* The map output buffer can hold a max of Integer.MAX_VALUE bytes. Though this wouldn't be terribly difficult to change.
* When spilling occurs, the objects that still in memory at merge time end up serialized and deserialized an extra time.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4450 from sryza/sandy-spark-4550 and squashes the following commits:
8c70dd9 [Sandy Ryza] Fix serialization
9c16fe6 [Sandy Ryza] Fix a couple tests and move getAutoReset to KryoSerializerInstance
6c54e06 [Sandy Ryza] Fix scalastyle
d8462d8 [Sandy Ryza] SPARK-4550
This is the classes for creating off-heap block storage API. It also includes the migration for Tachyon. The diff seems to be big, but it mainly just rename tachyon to offheap. New implementation for hdfs will be submit for review in spark-6112.
Author: Zhan Zhang <zhazhan@gmail.com>
Closes#5430 from zhzhan/SPARK-6479 and squashes the following commits:
60acd84 [Zhan Zhang] minor change to kickoff the test
12f54c9 [Zhan Zhang] solve merge conflicts
a54132c [Zhan Zhang] solve review comments
ffb8e00 [Zhan Zhang] rebase to sparkcontext change
6e121e0 [Zhan Zhang] resolve review comments and restructure blockmanasger code
a7aed6c [Zhan Zhang] add Tachyon migration code
186de31 [Zhan Zhang] initial commit for off-heap block storage api
Current Spark apps running on Secure YARN/HDFS would not be able to write data
to HDFS after 7 days, since delegation tokens cannot be renewed beyond that. This
means Spark Streaming apps will not be able to run on Secure YARN.
This commit adds basic functionality to fix this issue. In this patch:
- new parameters are added - principal and keytab, which can be used to login to a KDC
- the client logs in, and then get tokens to start the AM
- the keytab is copied to the staging directory
- the AM waits for 60% of the time till expiry of the tokens and then logs in using the keytab
- each time after 60% of the time, new tokens are created and sent to the executors
Currently, to avoid complicating the architecture, we set the keytab and principal in the
SparkHadoopUtil singleton, and schedule a login. Once the login is completed, a callback is scheduled.
This is being posted for feedback, so I can gather feedback on the general implementation.
There are currently a bunch of things to do:
- [x] logging
- [x] testing - I plan to manually test this soon. If you have ideas of how to add unit tests, comment.
- [x] add code to ensure that if these params are set in non-YARN cluster mode, we complain
- [x] documentation
- [x] Have the executors request for credentials from the AM, so that retries are possible.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#4688 from harishreedharan/kerberos-longrunning and squashes the following commits:
36eb8a9 [Hari Shreedharan] Change the renewal interval config param. Fix a bunch of comments.
611923a [Hari Shreedharan] Make sure the namenodes are listed correctly for creating tokens.
09fe224 [Hari Shreedharan] Use token.renew to get token's renewal interval rather than using hdfs-site.xml
6963bbc [Hari Shreedharan] Schedule renewal in AM before starting user class. Else, a restarted AM cannot access HDFS if the user class tries to.
072659e [Hari Shreedharan] Fix build failure caused by thread factory getting moved to ThreadUtils.
f041dd3 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
42eead4 [Hari Shreedharan] Remove RPC part. Refactor and move methods around, use renewal interval rather than max lifetime to create new tokens.
ebb36f5 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
bc083e3 [Hari Shreedharan] Overload RegisteredExecutor to send tokens. Minor doc updates.
7b19643 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
8a4f268 [Hari Shreedharan] Added docs in the security guide. Changed some code to ensure that the renewer objects are created only if required.
e800c8b [Hari Shreedharan] Restore original RegisteredExecutor message, and send new tokens via NewTokens message.
0e9507e [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
7f1bc58 [Hari Shreedharan] Minor fixes, cleanup.
bcd11f9 [Hari Shreedharan] Refactor AM and Executor token update code into separate classes, also send tokens via akka on executor startup.
f74303c [Hari Shreedharan] Move the new logic into specialized classes. Add cleanup for old credentials files.
2f9975c [Hari Shreedharan] Ensure new tokens are written out immediately on AM restart. Also, pikc up the latest suffix from HDFS if the AM is restarted.
61b2b27 [Hari Shreedharan] Account for AM restarts by making sure lastSuffix is read from the files on HDFS.
62c45ce [Hari Shreedharan] Relogin from keytab periodically.
fa233bd [Hari Shreedharan] Adding logging, fixing minor formatting and ordering issues.
42813b4 [Hari Shreedharan] Remove utils.sh, which was re-added due to merge with master.
0de27ee [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
55522e3 [Hari Shreedharan] Fix failure caused by Preconditions ambiguity.
9ef5f1b [Hari Shreedharan] Added explanation of how the credentials refresh works, some other minor fixes.
f4fd711 [Hari Shreedharan] Fix SparkConf usage.
2debcea [Hari Shreedharan] Change the file structure for credentials files. I will push a followup patch which adds a cleanup mechanism for old credentials files. The credentials files are small and few enough for it to cause issues on HDFS.
af6d5f0 [Hari Shreedharan] Cleaning up files where changes weren't required.
f0f54cb [Hari Shreedharan] Be more defensive when updating the credentials file.
f6954da [Hari Shreedharan] Got rid of Akka communication to renew, instead the executors check a known file's modification time to read the credentials.
5c11c3e [Hari Shreedharan] Move tests to YarnSparkHadoopUtil to fix compile issues.
b4cb917 [Hari Shreedharan] Send keytab to AM via DistributedCache rather than directly via HDFS
0985b4e [Hari Shreedharan] Write tokens to HDFS and read them back when required, rather than sending them over the wire.
d79b2b9 [Hari Shreedharan] Make sure correct credentials are passed to FileSystem#addDelegationTokens()
8c6928a [Hari Shreedharan] Fix issue caused by direct creation of Actor object.
fb27f46 [Hari Shreedharan] Make sure principal and keytab are set before CoarseGrainedSchedulerBackend is started. Also schedule re-logins in CoarseGrainedSchedulerBackend#start()
41efde0 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
d282d7a [Hari Shreedharan] Fix ClientSuite to set YARN mode, so that the correct class is used in tests.
bcfc374 [Hari Shreedharan] Fix Hadoop-1 build by adding no-op methods in SparkHadoopUtil, with impl in YarnSparkHadoopUtil.
f8fe694 [Hari Shreedharan] Handle None if keytab-login is not scheduled.
2b0d745 [Hari Shreedharan] [SPARK-5342][YARN] Allow long running Spark apps to run on secure YARN/HDFS.
ccba5bc [Hari Shreedharan] WIP: More changes wrt kerberos
77914dd [Hari Shreedharan] WIP: Add kerberos principal and keytab to YARN client.
This patch contains an `IvyTestUtils` file, which dynamically generates jars and pom files to test the `--packages` feature without having to rely on the internet, and Maven Central.
cc pwendell I know that there existed Util functions to create Jars and stuff already, but they didn't really serve my purposes as they appended random prefixes that was breaking things.
I also added the local repository tests. Notice that they work without passing the `repo` to `resolveMavenCoordinates`.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5790 from brkyvz/maven-utils and squashes the following commits:
3ec79b7 [Burak Yavuz] addressed comments v0.2
a39151b [Burak Yavuz] address comments v0.1
172dfef [Burak Yavuz] use Ivy format
7476d06 [Burak Yavuz] added mock repository generator
This is an initial commit for SPARK-6862. Once SPARK-6796 is merged, I will add the links to StreamingPage so that the user can jump to BatchPage.
Screenshots:
Author: zsxwing <zsxwing@gmail.com>
Closes#5473 from zsxwing/SPARK-6862 and squashes the following commits:
0727d35 [zsxwing] Change BatchUIData to a case class
b380cfb [zsxwing] Add createJobStart to eliminate duplicate codes
9a3083d [zsxwing] Rename XxxDatas -> XxxData
087ba98 [zsxwing] Refactor BatchInfo to store only necessary fields
cb62e4f [zsxwing] Use Seq[(OutputOpId, SparkJobId)] to store the id relations
72f8e7e [zsxwing] Add unit tests for BatchPage
1282b10 [zsxwing] Handle some corner cases and add tests for StreamingJobProgressListener
77a69ae [zsxwing] Refactor codes as per TD's comments
35ffd80 [zsxwing] Merge branch 'master' into SPARK-6862
15bdf9b [zsxwing] Add batch links and unit tests
4bf66b6 [zsxwing] Merge branch 'master' into SPARK-6862
7168807 [zsxwing] Limit the max width of the error message and fix nits in the UI
0b226f9 [zsxwing] Change 'Last Error' to 'Error'
fc98a43 [zsxwing] Put clearing local properties to finally and remove redundant private[streaming]
0c7b2eb [zsxwing] Add BatchPage to display details of a batch
See JIRA: https://issues.apache.org/jira/browse/SPARK-7155
SparkContext's newAPIHadoopFile() does not support comma-separated list of files. For example, the following:
```scala
sc.newAPIHadoopFile("/root/file1.txt,/root/file2.txt", classOf[TextInputFormat], classOf[LongWritable], classOf[Text])
```
will throw
```
org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/root/file1.txt,/root/file2.txt
```
However, the other API hadoopFile() is able to process comma-separated list of files correctly. In addition, since sc.textFile() uses hadoopFile(), it is also able to process comma-separated list of files correctly.
That means the behaviors of hadoopFile() and newAPIHadoopFile() are not aligned.
This pull request fix this issue and allows newAPIHadoopFile() to support comma-separated list of files as input.
A unit test has also been added in SparkContextSuite.scala. It creates two temporary text files as the input and tested against sc.textFile(), sc.hadoopFile(), and sc.newAPIHadoopFile().
Note: The contribution is my original work and that I license the work to the project under the project's open source license.
Author: yongtang <yongtang@users.noreply.github.com>
Closes#5708 from yongtang/SPARK-7155 and squashes the following commits:
654c80c [yongtang] [SPARK-7155] [CORE] Remove unneeded temp file deletion in unit test as parent dir is already temporary.
26faa6a [yongtang] [SPARK-7155] [CORE] Support comma-separated list of files as input for newAPIHadoopFile, wholeTextFiles, and binaryFiles. Use setInputPaths for consistency.
73e1f16 [yongtang] [SPARK-7155] [CORE] Allow newAPIHadoopFile to support comma-separated list of files as input.
see [SPARK-7181](https://issues.apache.org/jira/browse/SPARK-7181).
Author: Qiping Li <liqiping1991@gmail.com>
Closes#5737 from chouqin/externalsorter and squashes the following commits:
2924b93 [Qiping Li] fix inifite loop in Externalsorter's mergeWithAggregation
This is built on top of kaka1992 's PR #5711 using Logical plans.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5761 from brkyvz/random-sample and squashes the following commits:
a1fb0aa [Burak Yavuz] remove unrelated file
69669c3 [Burak Yavuz] fix broken test
1ddb3da [Burak Yavuz] copy base
6000328 [Burak Yavuz] added python api and fixed test
3c11d1b [Burak Yavuz] fixed broken test
f400ade [Burak Yavuz] fix build errors
2384266 [Burak Yavuz] addressed comments v0.1
e98ebac [Burak Yavuz] [SPARK-7156][SQL] support RandomSplit in DataFrames
When a job is submitted with a job group and that job group is inherited from a parent thread, there are multiple bugs that may prevent this job from being cancelable via `SparkContext.cancelJobGroup()`:
- When filtering jobs based on their job group properties, DAGScheduler calls `get()` instead of `getProperty()`, which does not respect inheritance, so it will skip over jobs whose job group properties were inherited.
- `Properties` objects are mutable, but we do not make defensive copies / snapshots, so modifications of the parent thread's job group will cause running jobs' groups to change; this also breaks cancelation.
Both of these issues are easy to fix: use `getProperty()` and perform defensive copying.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5288 from JoshRosen/localProperties-mutability-race and squashes the following commits:
9e29654 [Josh Rosen] Fix style issue
5d90750 [Josh Rosen] Merge remote-tracking branch 'origin/master' into localProperties-mutability-race
3f7b9e8 [Josh Rosen] Add JIRA reference; move clone into DAGScheduler
707e417 [Josh Rosen] Clone local properties to prevent mutations from breaking job cancellation.
b376114 [Josh Rosen] Fix bug that prevented jobs with inherited job group properties from being cancelled.
Original PR #5428 got reverted due to issues between MutableBoolean and Hadoop 1.0.4 (see JIRA). This replaces MutableBoolean with AtomicBoolean.
srowen pwendell
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#5773 from tdas/SPARK-6752 and squashes the following commits:
a0c0ead [Tathagata Das] Fix for hadoop 1.0.4
70ae85b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-6752
94db63c [Tathagata Das] Fix long line.
524f519 [Tathagata Das] Many changes based on PR comments.
eabd092 [Tathagata Das] Added Function0, Java API and unit tests for StreamingContext.getOrCreate
36a7823 [Tathagata Das] Minor changes.
204814e [Tathagata Das] Added StreamingContext.getOrCreate with existing SparkContext
The old naming scheme was very confusing between askWithReply and sendWithReply. I also divided RpcEnv.scala into multiple files.
Author: Reynold Xin <rxin@databricks.com>
Closes#5768 from rxin/rpc-rename and squashes the following commits:
a84058e [Reynold Xin] [SPARK-7223] Rename RPC askWithReply -> askWithReply, sendWithReply -> ask.
This patch adds managed-memory-based aggregation to Spark SQL / DataFrames. Instead of working with Java objects, this new aggregation path uses `sun.misc.Unsafe` to manipulate raw memory. This reduces the memory footprint for aggregations, resulting in fewer spills, OutOfMemoryErrors, and garbage collection pauses. As a result, this allows for higher memory utilization. It can also result in better cache locality since objects will be stored closer together in memory.
This feature can be eanbled by setting `spark.sql.unsafe.enabled=true`. For now, this feature is only supported when codegen is enabled and only supports aggregations for which the grouping columns are primitive numeric types or strings and aggregated values are numeric.
### Managing memory with sun.misc.Unsafe
This patch supports both on- and off-heap managed memory.
- In on-heap mode, memory addresses are identified by the combination of a base Object and an offset within that object.
- In off-heap mode, memory is addressed directly with 64-bit long addresses.
To support both modes, functions that manipulate memory accept both `baseObject` and `baseOffset` fields. In off-heap mode, we simply pass `null` as `baseObject`.
We allocate memory in large chunks, so memory fragmentation and allocation speed are not significant bottlenecks.
By default, we use on-heap mode. To enable off-heap mode, set `spark.unsafe.offHeap=true`.
To track allocated memory, this patch extends `SparkEnv` with an `ExecutorMemoryManager` and supplies each `TaskContext` with a `TaskMemoryManager`. These classes work together to track allocations and detect memory leaks.
### Compact tuple format
This patch introduces `UnsafeRow`, a compact row layout. In this format, each tuple has three parts: a null bit set, fixed length values, and variable-length values:
- Rows are always 8-byte word aligned (so their sizes will always be a multiple of 8 bytes)
- The bit set is used for null tracking:
- Position _i_ is set if and only if field _i_ is null
- The bit set is aligned to an 8-byte word boundary.
- Every field appears as an 8-byte word in the fixed-length values part:
- If a field is null, we zero out the values.
- If a field is variable-length, the word stores a relative offset (w.r.t. the base of the tuple) that points to the beginning of the field's data in the variable-length part.
- Each variable-length data type can have its own encoding:
- For strings, the first word stores the length of the string and is followed by UTF-8 encoded bytes. If necessary, the end of the string is padded with empty bytes in order to ensure word-alignment.
For example, a tuple that consists 3 fields of type (int, string, string), with value (null, “data”, “bricks”) would look like this:
This format allows us to compare tuples for equality by directly comparing their raw bytes. This also enables fast hashing of tuples.
### Hash map for performing aggregations
This patch introduces `UnsafeFixedWidthAggregationMap`, a hash map for performing aggregations where the aggregation result columns are fixed-with. This map's keys and values are `Row` objects. `UnsafeFixedWidthAggregationMap` is implemented on top of `BytesToBytesMap`, an append-only map which supports byte-array keys and values.
`BytesToBytesMap` stores pointers to key and value tuples. For each record with a new key, we copy the key and create the aggregation value buffer for that key and put them in a buffer. The hash table then simply stores pointers to the key and value. For each record with an existing key, we simply run the aggregation function to update the values in place.
This map is implemented using open hashing with triangular sequence probing. Each entry stores two words in a long array: the first word stores the address of the key and the second word stores the relative offset from the key tuple to the value tuple, as well as the key's 32-bit hashcode. By storing the full hashcode, we reduce the number of equality checks that need to be performed to handle position collisions ()since the chance of hashcode collision is much lower than position collision).
`UnsafeFixedWidthAggregationMap` allows regular Spark SQL `Row` objects to be used when probing the map. Internally, it encodes these rows into `UnsafeRow` format using `UnsafeRowConverter`. This conversion has a small overhead that can be eliminated in the future once we use UnsafeRows in other operators.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5725)
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Author: Josh Rosen <joshrosen@databricks.com>
Closes#5725 from JoshRosen/unsafe and squashes the following commits:
eeee512 [Josh Rosen] Add converters for Null, Boolean, Byte, and Short columns.
81f34f8 [Josh Rosen] Follow 'place children last' convention for GeneratedAggregate
1bc36cc [Josh Rosen] Refactor UnsafeRowConverter to avoid unnecessary boxing.
017b2dc [Josh Rosen] Remove BytesToBytesMap.finalize()
50e9671 [Josh Rosen] Throw memory leak warning even in case of error; add warning about code duplication
70a39e4 [Josh Rosen] Split MemoryManager into ExecutorMemoryManager and TaskMemoryManager:
6e4b192 [Josh Rosen] Remove an unused method from ByteArrayMethods.
de5e001 [Josh Rosen] Fix debug vs. trace in logging message.
a19e066 [Josh Rosen] Rename unsafe Java test suites to match Scala test naming convention.
78a5b84 [Josh Rosen] Add logging to MemoryManager
ce3c565 [Josh Rosen] More comments, formatting, and code cleanup.
529e571 [Josh Rosen] Measure timeSpentResizing in nanoseconds instead of milliseconds.
3ca84b2 [Josh Rosen] Only zero the used portion of groupingKeyConversionScratchSpace
162caf7 [Josh Rosen] Fix test compilation
b45f070 [Josh Rosen] Don't redundantly store the offset from key to value, since we can compute this from the key size.
a8e4a3f [Josh Rosen] Introduce MemoryManager interface; add to SparkEnv.
0925847 [Josh Rosen] Disable MiMa checks for new unsafe module
cde4132 [Josh Rosen] Add missing pom.xml
9c19fc0 [Josh Rosen] Add configuration options for heap vs. offheap
6ffdaa1 [Josh Rosen] Null handling improvements in UnsafeRow.
31eaabc [Josh Rosen] Lots of TODO and doc cleanup.
a95291e [Josh Rosen] Cleanups to string handling code
afe8dca [Josh Rosen] Some Javadoc cleanup
f3dcbfe [Josh Rosen] More mod replacement
854201a [Josh Rosen] Import and comment cleanup
06e929d [Josh Rosen] More warning cleanup
ef6b3d3 [Josh Rosen] Fix a bunch of FindBugs and IntelliJ inspections
29a7575 [Josh Rosen] Remove debug logging
49aed30 [Josh Rosen] More long -> int conversion.
b26f1d3 [Josh Rosen] Fix bug in murmur hash implementation.
765243d [Josh Rosen] Enable optional performance metrics for hash map.
23a440a [Josh Rosen] Bump up default hash map size
628f936 [Josh Rosen] Use ints intead of longs for indexing.
92d5a06 [Josh Rosen] Address a number of minor code review comments.
1f4b716 [Josh Rosen] Merge Unsafe code into the regular GeneratedAggregate, guarded by a configuration flag; integrate planner support and re-enable all tests.
d85eeff [Josh Rosen] Add basic sanity test for UnsafeFixedWidthAggregationMap
bade966 [Josh Rosen] Comment update (bumping to refresh GitHub cache...)
b3eaccd [Josh Rosen] Extract aggregation map into its own class.
d2bb986 [Josh Rosen] Update to implement new Row methods added upstream
58ac393 [Josh Rosen] Use UNSAFE allocator in GeneratedAggregate (TODO: make this configurable)
7df6008 [Josh Rosen] Optimizations related to zeroing out memory:
c1b3813 [Josh Rosen] Fix bug in UnsafeMemoryAllocator.free():
738fa33 [Josh Rosen] Add feature flag to guard UnsafeGeneratedAggregate
c55bf66 [Josh Rosen] Free buffer once iterator has been fully consumed.
62ab054 [Josh Rosen] Optimize for fact that get() is only called on String columns.
c7f0b56 [Josh Rosen] Reuse UnsafeRow pointer in UnsafeRowConverter
ae39694 [Josh Rosen] Add finalizer as "cleanup method of last resort"
c754ae1 [Josh Rosen] Now that the store*() contract has been stregthened, we can remove an extra lookup
f764d13 [Josh Rosen] Simplify address + length calculation in Location.
079f1bf [Josh Rosen] Some clarification of the BytesToBytesMap.lookup() / set() contract.
1a483c5 [Josh Rosen] First version that passes some aggregation tests:
fc4c3a8 [Josh Rosen] Sketch how the converters will be used in UnsafeGeneratedAggregate
53ba9b7 [Josh Rosen] Start prototyping Java Row -> UnsafeRow converters
1ff814d [Josh Rosen] Add reminder to free memory on iterator completion
8a8f9df [Josh Rosen] Add skeleton for GeneratedAggregate integration.
5d55cef [Josh Rosen] Add skeleton for Row implementation.
f03e9c1 [Josh Rosen] Play around with Unsafe implementations of more string methods.
ab68e08 [Josh Rosen] Begin merging the UTF8String implementations.
480a74a [Josh Rosen] Initial import of code from Databricks unsafe utils repo.
In addition, I made a small change that will allow users to import 2 different artifacts with the same name. That change is made in `[organization]_[artifact]-[revision].[ext]`. This used to be only `[artifact].[ext]` which might have caused collisions between artifacts with the same artifactId, but different groupId's.
cc pwendell
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5755 from brkyvz/local-caches and squashes the following commits:
c47c9c5 [Burak Yavuz] Small fixes to --packages
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#5751 from vanzin/cached-rdd-warning and squashes the following commits:
554cc07 [Marcelo Vanzin] Change message.
9efb9da [Marcelo Vanzin] [minor] [core] Warn users who try to cache RDDs with dynamic allocation on.
This patch adds the support for cluster mode to run on Mesos.
It introduces a new Mesos framework dedicated to launch new apps/drivers, and can be called with the spark-submit script and specifying --master flag to the cluster mode REST interface instead of Mesos master.
Example:
./bin/spark-submit --deploy-mode cluster --class org.apache.spark.examples.SparkPi --master mesos://10.0.0.206:8077 --executor-memory 1G --total-executor-cores 100 examples/target/spark-examples_2.10-1.3.0-SNAPSHOT.jar 30
Part of this patch is also to abstract the StandaloneRestServer so it can have different implementations of the REST endpoints.
Features of the cluster mode in this PR:
- Supports supervise mode where scheduler will keep trying to reschedule exited job.
- Adds a new UI for the cluster mode scheduler to see all the running jobs, finished jobs, and supervise jobs waiting to be retried
- Supports state persistence to ZK, so when the cluster scheduler fails over it can pick up all the queued and running jobs
Author: Timothy Chen <tnachen@gmail.com>
Author: Luc Bourlier <luc.bourlier@typesafe.com>
Closes#5144 from tnachen/mesos_cluster_mode and squashes the following commits:
069e946 [Timothy Chen] Fix rebase.
e24b512 [Timothy Chen] Persist submitted driver.
390c491 [Timothy Chen] Fix zk conf key for mesos zk engine.
e324ac1 [Timothy Chen] Fix merge.
fd5259d [Timothy Chen] Address review comments.
1553230 [Timothy Chen] Address review comments.
c6c6b73 [Timothy Chen] Pass spark properties to mesos cluster tasks.
f7d8046 [Timothy Chen] Change app name to spark cluster.
17f93a2 [Timothy Chen] Fix head of line blocking in scheduling drivers.
6ff8e5c [Timothy Chen] Address comments and add logging.
df355cd [Timothy Chen] Add metrics to mesos cluster scheduler.
20f7284 [Timothy Chen] Address review comments
7252612 [Timothy Chen] Fix tests.
a46ad66 [Timothy Chen] Allow zk cli param override.
920fc4b [Timothy Chen] Fix scala style issues.
862b5b5 [Timothy Chen] Support asking driver status when it's retrying.
7f214c2 [Timothy Chen] Fix RetryState visibility
e0f33f7 [Timothy Chen] Add supervise support and persist retries.
371ce65 [Timothy Chen] Handle cluster mode recovery and state persistence.
3d4dfa1 [Luc Bourlier] Adds support to kill submissions
febfaba [Timothy Chen] Bound the finished drivers in memory
543a98d [Timothy Chen] Schedule multiple jobs
6887e5e [Timothy Chen] Support looking at SPARK_EXECUTOR_URI env variable in schedulers
8ec76bc [Timothy Chen] Fix Mesos dispatcher UI.
d57d77d [Timothy Chen] Add documentation
825afa0 [Luc Bourlier] Supports more spark-submit parameters
b8e7181 [Luc Bourlier] Adds a shutdown latch to keep the deamon running
0fa7780 [Luc Bourlier] Launch task through the mesos scheduler
5b7a12b [Timothy Chen] WIP: Making a cluster mode a mesos framework.
4b2f5ef [Timothy Chen] Specify user jar in command to be replaced with local.
e775001 [Timothy Chen] Support fetching remote uris in driver runner.
7179495 [Timothy Chen] Change Driver page output and add logging
880bc27 [Timothy Chen] Add Mesos Cluster UI to display driver results
9986731 [Timothy Chen] Kill drivers when shutdown
67cbc18 [Timothy Chen] Rename StandaloneRestClient to RestClient and add sbin scripts
e3facdd [Timothy Chen] Add Mesos Cluster dispatcher
This is handled in the same way with [SPARK-6197](https://issues.apache.org/jira/browse/SPARK-6197). The result of this PR is that exception showed in history server log will be replaced by a warning, and the application that with un-complete history log file will be listed on history server webUI
Author: Zhang, Liye <liye.zhang@intel.com>
Closes#5736 from liyezhang556520/SPARK-6314 and squashes the following commits:
b8d2d88 [Zhang, Liye] handle JsonParseException for history server
I've added an interface to JavaUtils to do byte conversion and added hooks within Utils.scala to handle conversion within Spark code (like for time strings). I've added matching tests for size conversion, and then updated all deprecated configs and documentation as per SPARK-5933.
Author: Ilya Ganelin <ilya.ganelin@capitalone.com>
Closes#5574 from ilganeli/SPARK-5932 and squashes the following commits:
11f6999 [Ilya Ganelin] Nit fixes
49a8720 [Ilya Ganelin] Whitespace fix
2ab886b [Ilya Ganelin] Scala style
fc85733 [Ilya Ganelin] Got rid of floating point math
852a407 [Ilya Ganelin] [SPARK-5932] Added much improved overflow handling. Can now handle sizes up to Long.MAX_VALUE Petabytes instead of being capped at Long.MAX_VALUE Bytes
9ee779c [Ilya Ganelin] Simplified fraction matches
22413b1 [Ilya Ganelin] Made MAX private
3dfae96 [Ilya Ganelin] Fixed some nits. Added automatic conversion of old paramter for kryoserializer.mb to new values.
e428049 [Ilya Ganelin] resolving merge conflict
8b43748 [Ilya Ganelin] Fixed error in pattern matching for doubles
84a2581 [Ilya Ganelin] Added smoother handling of fractional values for size parameters. This now throws an exception and added a warning for old spark.kryoserializer.buffer
d3d09b6 [Ilya Ganelin] [SPARK-5932] Fixing error in KryoSerializer
fe286b4 [Ilya Ganelin] Resolved merge conflict
c7803cd [Ilya Ganelin] Empty lines
54b78b4 [Ilya Ganelin] Simplified byteUnit class
69e2f20 [Ilya Ganelin] Updates to code
f32bc01 [Ilya Ganelin] [SPARK-5932] Fixed error in API in SparkConf.scala where Kb conversion wasn't being done properly (was Mb). Added test cases for both timeUnit and ByteUnit conversion
f15f209 [Ilya Ganelin] Fixed conversion of kryo buffer size
0f4443e [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-5932
35a7fa7 [Ilya Ganelin] Minor formatting
928469e [Ilya Ganelin] [SPARK-5932] Converted some longs to ints
5d29f90 [Ilya Ganelin] [SPARK-5932] Finished documentation updates
7a6c847 [Ilya Ganelin] [SPARK-5932] Updated spark.shuffle.file.buffer
afc9a38 [Ilya Ganelin] [SPARK-5932] Updated spark.broadcast.blockSize and spark.storage.memoryMapThreshold
ae7e9f6 [Ilya Ganelin] [SPARK-5932] Updated spark.io.compression.snappy.block.size
2d15681 [Ilya Ganelin] [SPARK-5932] Updated spark.executor.logs.rolling.size.maxBytes
1fbd435 [Ilya Ganelin] [SPARK-5932] Updated spark.broadcast.blockSize
eba4de6 [Ilya Ganelin] [SPARK-5932] Updated spark.shuffle.file.buffer.kb
b809a78 [Ilya Ganelin] [SPARK-5932] Updated spark.kryoserializer.buffer.max
0cdff35 [Ilya Ganelin] [SPARK-5932] Updated to use bibibytes in method names. Updated spark.kryoserializer.buffer.mb and spark.reducer.maxMbInFlight
475370a [Ilya Ganelin] [SPARK-5932] Simplified ByteUnit code, switched to using longs. Updated docs to clarify that we use kibi, mebi etc instead of kilo, mega
851d691 [Ilya Ganelin] [SPARK-5932] Updated memoryStringToMb to use new interfaces
a9f4fcf [Ilya Ganelin] [SPARK-5932] Added unit tests for unit conversion
747393a [Ilya Ganelin] [SPARK-5932] Added unit tests for ByteString conversion
09ea450 [Ilya Ganelin] [SPARK-5932] Added byte string conversion to Jav utils
5390fd9 [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-5932
db9a963 [Ilya Ganelin] Closing second spark context
1dc0444 [Ilya Ganelin] Added ref equality check
8c884fa [Ilya Ganelin] Made getOrCreate synchronized
cb0c6b7 [Ilya Ganelin] Doc updates and code cleanup
270cfe3 [Ilya Ganelin] [SPARK-6703] Documentation fixes
15e8dea [Ilya Ganelin] Updated comments and added MiMa Exclude
0e1567c [Ilya Ganelin] Got rid of unecessary option for AtomicReference
dfec4da [Ilya Ganelin] Changed activeContext to AtomicReference
733ec9f [Ilya Ganelin] Fixed some bugs in test code
8be2f83 [Ilya Ganelin] Replaced match with if
e92caf7 [Ilya Ganelin] [SPARK-6703] Added test to ensure that getOrCreate both allows creation, retrieval, and a second context if desired
a99032f [Ilya Ganelin] Spacing fix
d7a06b8 [Ilya Ganelin] Updated SparkConf class to add getOrCreate method. Started test suite implementation
This allows Mesos deployments to use the shuffle service (and implicitly dynamic allocation). It does so by adding a new "main" class and two corresponding scripts in `sbin`:
- `sbin/start-shuffle-service.sh`
- `sbin/stop-shuffle-service.sh`
Specific options can be passed in `SPARK_SHUFFLE_OPTS`.
This is picking up work from #3861 /cc tnachen
Author: Iulian Dragos <jaguarul@gmail.com>
Closes#4990 from dragos/feature/external-shuffle-service and squashes the following commits:
6c2b148 [Iulian Dragos] Import order and wrong name fixup.
07804ad [Iulian Dragos] Moved ExternalShuffleService to the `deploy` package + other minor tweaks.
4dc1f91 [Iulian Dragos] Reviewer’s comments:
8145429 [Iulian Dragos] Add an external shuffle service that can be run as a daemon.
Author: Zhang, Liye <liye.zhang@intel.com>
Closes#5739 from liyezhang556520/trySafeFinally and squashes the following commits:
55683e5 [Zhang, Liye] replace try finally block with tryWithSafeFinally
Update Maven build plugin versions and centralize plugin version management
Author: Sean Owen <sowen@cloudera.com>
Closes#5720 from srowen/SPARK-7168 and squashes the following commits:
98a8947 [Sean Owen] Make install, deploy plugin versions explicit
4ecf3b2 [Sean Owen] Update Maven build plugin versions and centralize plugin version management
rxin
Author: Andrew Or <andrew@databricks.com>
Closes#5734 from andrewor14/ser-deb and squashes the following commits:
e8aad6c [Andrew Or] NonFatal
57d0ef4 [Andrew Or] try catch improveException
`HeartbeatReceiver` will call `TaskScheduler.executorHeartbeatReceived`, which is a blocking operation because `TaskScheduler.executorHeartbeatReceived` will call
```Scala
blockManagerMaster.driverEndpoint.askWithReply[Boolean](
BlockManagerHeartbeat(blockManagerId), 600 seconds)
```
finally. Even if it asks from a local Actor, it may block the current Akka thread. E.g., the reply may be dispatched to the same thread of the ask operation. So the reply cannot be processed. An extreme case is setting the thread number of Akka dispatch thread pool to 1.
jstack log:
```
"sparkDriver-akka.actor.default-dispatcher-14" daemon prio=10 tid=0x00007f2a8c02d000 nid=0x725 waiting on condition [0x00007f2b1d6d0000]
java.lang.Thread.State: TIMED_WAITING (parking)
at sun.misc.Unsafe.park(Native Method)
- parking to wait for <0x00000006197a0868> (a scala.concurrent.impl.Promise$CompletionLatch)
at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:226)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedNanos(AbstractQueuedSynchronizer.java:1033)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.tryAcquireSharedNanos(AbstractQueuedSynchronizer.java:1326)
at scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:208)
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:218)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107)
at akka.dispatch.MonitorableThreadFactory$AkkaForkJoinWorkerThread$$anon$3.block(ThreadPoolBuilder.scala:169)
at scala.concurrent.forkjoin.ForkJoinPool.managedBlock(ForkJoinPool.java:3640)
at akka.dispatch.MonitorableThreadFactory$AkkaForkJoinWorkerThread.blockOn(ThreadPoolBuilder.scala:167)
at scala.concurrent.Await$.result(package.scala:107)
at org.apache.spark.rpc.RpcEndpointRef.askWithReply(RpcEnv.scala:355)
at org.apache.spark.scheduler.DAGScheduler.executorHeartbeatReceived(DAGScheduler.scala:169)
at org.apache.spark.scheduler.TaskSchedulerImpl.executorHeartbeatReceived(TaskSchedulerImpl.scala:367)
at org.apache.spark.HeartbeatReceiver$$anonfun$receiveAndReply$1.applyOrElse(HeartbeatReceiver.scala:103)
at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$processMessage(AkkaRpcEnv.scala:182)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1$$anonfun$applyOrElse$4.apply$mcV$sp(AkkaRpcEnv.scala:128)
at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$safelyCall(AkkaRpcEnv.scala:203)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1.applyOrElse(AkkaRpcEnv.scala:127)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59)
at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
at org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1.aroundReceive(AkkaRpcEnv.scala:94)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
at akka.actor.ActorCell.invoke(ActorCell.scala:487)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
at akka.dispatch.Mailbox.run(Mailbox.scala:220)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
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 PR moved this blocking operation to a separated thread.
Author: zsxwing <zsxwing@gmail.com>
Closes#5723 from zsxwing/SPARK-7174 and squashes the following commits:
98bfe48 [zsxwing] Use a single thread for checking timeout and reporting executorHeartbeatReceived
5b3b545 [zsxwing] Move calling `TaskScheduler.executorHeartbeatReceived` to another thread to avoid blocking the Akka thread pool
Remove use of commons-lang in favor of commons-lang3 classes; remove commons-io use in favor of Guava
Author: Sean Owen <sowen@cloudera.com>
Closes#5703 from srowen/SPARK-7145 and squashes the following commits:
21fbe03 [Sean Owen] Remove use of commons-lang in favor of commons-lang3 classes; remove commons-io use in favor of Guava
Set up a shutdown hook to try to stop the Spark context in
case the user forgets to do it. The main effect is that any
open logs files are flushed and closed, which is particularly
interesting for event logs.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#5696 from vanzin/SPARK-3090 and squashes the following commits:
3b554b5 [Marcelo Vanzin] [SPARK-3090] [core] Stop SparkContext if user forgets to.
Added a check to the SparkContext.union method to check that a partitioner is defined on all RDDs when instantiating a PartitionerAwareUnionRDD.
Author: Steven She <steven@canopylabs.com>
Closes#5679 from stevencanopy/SPARK-7103 and squashes the following commits:
5a3d846 [Steven She] SPARK-7103: Fix crash with SparkContext.union when at least one RDD has no partitioner
Add a try/catch block around removeShutDownHook else IllegalStateException thrown in YARN cluster mode (see https://github.com/apache/spark/pull/4690)
cc andrewor14, srowen
Author: Nishkam Ravi <nravi@cloudera.com>
Author: nishkamravi2 <nishkamravi@gmail.com>
Author: nravi <nravi@c1704.halxg.cloudera.com>
Closes#5672 from nishkamravi2/master_nravi and squashes the following commits:
0f1abd0 [nishkamravi2] Update Utils.scala
474e3bf [nishkamravi2] Update DiskBlockManager.scala
97c383e [nishkamravi2] Update Utils.scala
8691e0c [Nishkam Ravi] Add a try/catch block around Utils.removeShutdownHook
2be1e76 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
1c13b79 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
bad4349 [nishkamravi2] Update Main.java
36a6f87 [Nishkam Ravi] Minor changes and bug fixes
b7f4ae7 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
4a45d6a [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
458af39 [Nishkam Ravi] Locate the jar using getLocation, obviates the need to pass assembly path as an argument
d9658d6 [Nishkam Ravi] Changes for SPARK-6406
ccdc334 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
3faa7a4 [Nishkam Ravi] Launcher library changes (SPARK-6406)
345206a [Nishkam Ravi] spark-class merge Merge branch 'master_nravi' of https://github.com/nishkamravi2/spark into master_nravi
ac58975 [Nishkam Ravi] spark-class changes
06bfeb0 [nishkamravi2] Update spark-class
35af990 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
32c3ab3 [nishkamravi2] Update AbstractCommandBuilder.java
4bd4489 [nishkamravi2] Update AbstractCommandBuilder.java
746f35b [Nishkam Ravi] "hadoop" string in the assembly name should not be mandatory (everywhere else in spark we mandate spark-assembly*hadoop*.jar)
bfe96e0 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
ee902fa [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
d453197 [nishkamravi2] Update NewHadoopRDD.scala
6f41a1d [nishkamravi2] Update NewHadoopRDD.scala
0ce2c32 [nishkamravi2] Update HadoopRDD.scala
f7e33c2 [Nishkam Ravi] Merge branch 'master_nravi' of https://github.com/nishkamravi2/spark into master_nravi
ba1eb8b [Nishkam Ravi] Try-catch block around the two occurrences of removeShutDownHook. Deletion of semi-redundant occurrences of expensive operation inShutDown.
71d0e17 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
494d8c0 [nishkamravi2] Update DiskBlockManager.scala
3c5ddba [nishkamravi2] Update DiskBlockManager.scala
f0d12de [Nishkam Ravi] Workaround for IllegalStateException caused by recent changes to BlockManager.stop
79ea8b4 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
b446edc [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
5c9a4cb [nishkamravi2] Update TaskSetManagerSuite.scala
535295a [nishkamravi2] Update TaskSetManager.scala
3e1b616 [Nishkam Ravi] Modify test for maxResultSize
9f6583e [Nishkam Ravi] Changes to maxResultSize code (improve error message and add condition to check if maxResultSize > 0)
5f8f9ed [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
636a9ff [nishkamravi2] Update YarnAllocator.scala
8f76c8b [Nishkam Ravi] Doc change for yarn memory overhead
35daa64 [Nishkam Ravi] Slight change in the doc for yarn memory overhead
5ac2ec1 [Nishkam Ravi] Remove out
dac1047 [Nishkam Ravi] Additional documentation for yarn memory overhead issue
42c2c3d [Nishkam Ravi] Additional changes for yarn memory overhead issue
362da5e [Nishkam Ravi] Additional changes for yarn memory overhead
c726bd9 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
f00fa31 [Nishkam Ravi] Improving logging for AM memoryOverhead
1cf2d1e [nishkamravi2] Update YarnAllocator.scala
ebcde10 [Nishkam Ravi] Modify default YARN memory_overhead-- from an additive constant to a multiplier (redone to resolve merge conflicts)
2e69f11 [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark into master_nravi
efd688a [Nishkam Ravi] Merge branch 'master' of https://github.com/apache/spark
2b630f9 [nravi] Accept memory input as "30g", "512M" instead of an int value, to be consistent with rest of Spark
3bf8fad [nravi] Merge branch 'master' of https://github.com/apache/spark
5423a03 [nravi] Merge branch 'master' of https://github.com/apache/spark
eb663ca [nravi] Merge branch 'master' of https://github.com/apache/spark
df2aeb1 [nravi] Improved fix for ConcurrentModificationIssue (Spark-1097, Hadoop-10456)
6b840f0 [nravi] Undo the fix for SPARK-1758 (the problem is fixed)
5108700 [nravi] Fix in Spark for the Concurrent thread modification issue (SPARK-1097, HADOOP-10456)
681b36f [nravi] Fix for SPARK-1758: failing test org.apache.spark.JavaAPISuite.wholeTextFiles
This is a reopening of #4867.
A short summary of the issues resolved from the previous PR:
1. HTTPClient version mismatch: Selenium (used for UI tests) requires version 4.3.x, and Tachyon included 4.2.5 through a transitive dependency of its shaded thrift jar. To address this, Tachyon 0.6.3 will promote the transitive dependencies of the shaded jar so they can be excluded in spark.
2. Jackson-Mapper-ASL version mismatch: In lower versions of hadoop-client (ie. 1.0.4), version 1.0.1 is included. The parquet library used in spark sql requires version 1.8+. Its unclear to me why upgrading tachyon-client would cause this dependency to break. The solution was to exclude jackson-mapper-asl from hadoop-client.
It seems that the dependency management in spark-parent will not work on transitive dependencies, one way to make sure jackson-mapper-asl is included with the correct version is to add it as a top level dependency. The best solution would be to exclude the dependency in the modules which require a higher version, but that did not fix the unit tests. Any suggestions on the best way to solve this would be appreciated!
Author: Calvin Jia <jia.calvin@gmail.com>
Closes#5354 from calvinjia/upgrade_tachyon_0.6.3 and squashes the following commits:
0eefe4d [Calvin Jia] Handle httpclient version in maven dependency management. Remove httpclient version setting from profiles.
7c00dfa [Calvin Jia] Set httpclient version to 4.3.2 for selenium. Specify version of httpclient for sql/hive (previously 4.2.5 transitive dependency of libthrift).
9263097 [Calvin Jia] Merge master to test latest changes
dbfc1bd [Calvin Jia] Use Tachyon 0.6.4 for cleaner dependencies.
e2ff80a [Calvin Jia] Exclude the jetty and curator promoted dependencies from tachyon-client.
a3a29da [Calvin Jia] Update tachyon-client exclusions.
0ae6c97 [Calvin Jia] Change tachyon version to 0.6.3
a204df9 [Calvin Jia] Update make distribution tachyon version.
a93c94f [Calvin Jia] Exclude jackson-mapper-asl from hadoop client since it has a lower version than spark's expected version.
a8a923c [Calvin Jia] Exclude httpcomponents from Tachyon
910fabd [Calvin Jia] Update to master
eed9230 [Calvin Jia] Update tachyon version to 0.6.1.
11907b3 [Calvin Jia] Use TachyonURI for tachyon paths instead of strings.
71bf441 [Calvin Jia] Upgrade Tachyon client version to 0.6.0.
When specifying non-spark properties (i.e. names don't start with spark.) in the command line and config file, spark-submit and spark-shell behave differently, causing confusion to users.
Here is the summary-
* spark-submit
* --conf k=v => silently ignored
* spark-defaults.conf => applied
* spark-shell
* --conf k=v => show a warning message and ignored
* spark-defaults.conf => show a warning message and ignored
I assume that ignoring non-spark properties is intentional. If so, it should always be ignored with a warning message in all cases.
Author: Cheolsoo Park <cheolsoop@netflix.com>
Closes#5617 from piaozhexiu/SPARK-7037 and squashes the following commits:
8957950 [Cheolsoo Park] Add IgnoreNonSparkProperties method
fedd01c [Cheolsoo Park] Ignore non-spark properties with a warning message in all cases
https://issues.apache.org/jira/browse/SPARK-6879
Use `applications` to replace `FileStatus`, and check if the app is completed before clean it up.
If an exception was throwed, add it to `applications` to wait for the next loop.
Author: WangTaoTheTonic <wangtao111@huawei.com>
Closes#5491 from WangTaoTheTonic/SPARK-6879 and squashes the following commits:
4a533eb [WangTaoTheTonic] treat ACE specially
cb45105 [WangTaoTheTonic] rebase
d4d5251 [WangTaoTheTonic] per Marcelo's comments
d7455d8 [WangTaoTheTonic] slightly change when delete file
b0abca5 [WangTaoTheTonic] use global var to store apps to clean
94adfe1 [WangTaoTheTonic] leave expired apps alone to be deleted
9872a9d [WangTaoTheTonic] use the right path
fdef4d6 [WangTaoTheTonic] check if app is completed before clean it up
The web UI's "task deserialization time" metric is slightly misleading because it does not capture the time taken to deserialize the broadcasted RDD.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5635 from JoshRosen/SPARK-7058 and squashes the following commits:
ed90f75 [Josh Rosen] Update UI tooltip
a3743b4 [Josh Rosen] Update comments.
4f52910 [Josh Rosen] Roll back whitespace change
e9cf9f4 [Josh Rosen] Remove unused variable
9f32e55 [Josh Rosen] Expose executorDeserializeTime on Task instead of pushing runtime calculation into Task.
21f5b47 [Josh Rosen] Don't double-count the broadcast deserialization time in task runtime
1752f0e [Josh Rosen] [SPARK-7058] Incorporate RDD deserialization time in task deserialization time metric
Currently if you want to create a StreamingContext from checkpoint information, the system will create a new SparkContext. This prevent StreamingContext to be recreated from checkpoints in managed environments where SparkContext is precreated.
The solution in this PR: Introduce the following methods on StreamingContext
1. `new StreamingContext(checkpointDirectory, sparkContext)`
Recreate StreamingContext from checkpoint using the provided SparkContext
2. `StreamingContext.getOrCreate(checkpointDirectory, sparkContext, createFunction: SparkContext => StreamingContext)`
If checkpoint file exists, then recreate StreamingContext using the provided SparkContext (that is, call 1.), else create StreamingContext using the provided createFunction
TODO: the corresponding Java and Python API has to be added as well.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#5428 from tdas/SPARK-6752 and squashes the following commits:
94db63c [Tathagata Das] Fix long line.
524f519 [Tathagata Das] Many changes based on PR comments.
eabd092 [Tathagata Das] Added Function0, Java API and unit tests for StreamingContext.getOrCreate
36a7823 [Tathagata Das] Minor changes.
204814e [Tathagata Das] Added StreamingContext.getOrCreate with existing SparkContext
This is a code cleanup.
The BlockResult class originally contained an InputMetrics object so that InputMetrics could
directly be used as the InputMetrics for the whole task. Now we copy the fields out of here, and
the presence of this object is confusing because it's only a partial input metrics (it doesn't
include the records read). Because this object is no longer useful (and is confusing), it should
be removed.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#5627 from kayousterhout/SPARK-7046 and squashes the following commits:
bf64bbe [Kay Ousterhout] Import fix
a08ca19 [Kay Ousterhout] [SPARK-7046] Remove InputMetrics from BlockResult
As per rxin 's suggestion in https://github.com/apache/spark/pull/5392/files#r28757176
What's more, there is a race condition in the global shared `daemonThreadFactoryBuilder`. `daemonThreadFactoryBuilder` may be modified by multiple threads. This PR removed the global `daemonThreadFactoryBuilder` and created a new `ThreadFactoryBuilder` every time.
Author: zsxwing <zsxwing@gmail.com>
Closes#5631 from zsxwing/thread-utils and squashes the following commits:
9fe5b0e [zsxwing] Add ThreadUtils and move thread methods from Utils to ThreadUtils
1. Clearly specifies the contract/interactions for users of this class.
2. Minor fix in one doc to avoid ambiguity.
Author: Patrick Wendell <patrick@databricks.com>
Closes#5620 from pwendell/cleanup and squashes the following commits:
8d8f44f [Patrick Wendell] [Minor] Comment improvements in ExternalSorter.
Added docs for rpc configurations and also fixed two places that should have been fixed in #5595.
Author: zsxwing <zsxwing@gmail.com>
Closes#5607 from zsxwing/SPARK-6490-docs and squashes the following commits:
25a6736 [zsxwing] Increase the default timeout to 120s
6e37c30 [zsxwing] Update docs
5577540 [zsxwing] Use spark.network.timeout as the default timeout if it presents
4f07174 [zsxwing] Fix unit tests
1c2cf26 [zsxwing] Add docs for rpc configurations
This change adds some new utility code to handle shutdown hooks in
Spark. The main goal is to take advantage of Hadoop 2.x's API for
shutdown hooks, which allows Spark to register a hook that will
run before the one that cleans up HDFS clients, and thus avoids
some races that would cause exceptions to show up and other issues
such as failure to properly close event logs.
Unfortunately, Hadoop 1.x does not have such APIs, so in that case
correctness is still left to chance.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#5560 from vanzin/SPARK-6014 and squashes the following commits:
edfafb1 [Marcelo Vanzin] Better scaladoc.
fcaeedd [Marcelo Vanzin] Merge branch 'master' into SPARK-6014
e7039dc [Marcelo Vanzin] [SPARK-6014] [core] Revamp Spark shutdown hooks, fix shutdown races.
Starting with version 0.21.0, Apache Mesos is very noisy if the filter parameter refuse_seconds is set to an invalid value like `-1`.
I have seen systems with millions of log lines like
```
W0420 18:00:48.773059 32352 hierarchical_allocator_process.hpp:589] Using the default value of 'refuse_seconds' to create the refused resources filter because the input value is negative
```
in the Mesos master INFO and WARNING log files.
Therefore the CoarseMesosSchedulerBackend should set the default value for refuse seconds (i.e. 5 seconds) directly.
This is no problem for the fine-grained MesosSchedulerBackend, as it uses the value 1 second for this parameter.
Author: mweindel <m.weindel@usu-software.de>
Closes#5597 from MartinWeindel/master and squashes the following commits:
2f99ffd [mweindel] Avoid warning message about invalid refuse_seconds value in Mesos >=0.21.
This patch modifies several shuffle-related code paths to share and re-use SerializerInstances instead of creating new ones. Some serializers, such as KryoSerializer or SqlSerializer, can be fairly expensive to create or may consume moderate amounts of memory, so it's probably best to avoid unnecessary serializer creation in hot code paths.
The key change in this patch is modifying `getDiskWriter()` / `DiskBlockObjectWriter` to accept `SerializerInstance`s instead of `Serializer`s (which are factories for instances). This allows the disk writer's creator to decide whether the serializer instance can be shared or re-used.
The rest of the patch modifies several write and read paths to use shared serializers. One big win is in `ShuffleBlockFetcherIterator`, where we used to create a new serializer per received block. Similarly, the shuffle write path used to create a new serializer per file even though in many cases only a single thread would be writing to a file at a time.
I made a small serializer reuse optimization in CoarseGrainedExecutorBackend as well, since it seemed like a small and obvious improvement.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5606 from JoshRosen/SPARK-3386 and squashes the following commits:
f661ce7 [Josh Rosen] Remove thread local; add comment instead
64f8398 [Josh Rosen] Use ThreadLocal for serializer instance in CoarseGrainedExecutorBackend
aeb680e [Josh Rosen] [SPARK-3386] Reuse SerializerInstance in shuffle code paths
CoGroupPartition, part of CoGroupedRDD, includes references to each RDD that the CoGroupedRDD narrowly depends on, and a reference to the ShuffleHandle. The partition is serialized separately from the RDD, so when the RDD and partition arrive on the worker, the references in the partition and in the RDD no longer point to the same object.
This is a relatively minor performance issue (the closure can be 2x larger than it needs to be because the rdds and partitions are serialized twice; see numbers below) but is more annoying as a developer issue (this is where I ran into): if any state is stored in the RDD or ShuffleHandle on the worker side, subtle bugs can appear due to the fact that the references to the RDD / ShuffleHandle in the RDD and in the partition point to separate objects. I'm not sure if this is enough of a potential future problem to fix this old and central part of the code, so hoping to get input from others here.
I did some simple experiments to see how much this effects closure size. For this example:
$ val a = sc.parallelize(1 to 10).map((_, 1))
$ val b = sc.parallelize(1 to 2).map(x => (x, 2*x))
$ a.cogroup(b).collect()
the closure was 1902 bytes with current Spark, and 1129 bytes after my change. The difference comes from eliminating duplicate serialization of the shuffle handle.
For this example:
$ val sortedA = a.sortByKey()
$ val sortedB = b.sortByKey()
$ sortedA.cogroup(sortedB).collect()
the closure was 3491 bytes with current Spark, and 1333 bytes after my change. Here, the difference comes from eliminating duplicate serialization of the two RDDs for the narrow dependencies.
The ShuffleHandle includes the ShuffleDependency, so this difference will get larger if a ShuffleDependency includes a serializer, a key ordering, or an aggregator (all set to None by default). It would also get bigger for a big RDD -- although I can't think of any examples where the RDD object gets large. The difference is not affected by the size of the function the user specifies, which (based on my understanding) is typically the source of large task closures.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#4145 from kayousterhout/SPARK-5360 and squashes the following commits:
85156c3 [Kay Ousterhout] Better comment the narrowDeps parameter
cff0209 [Kay Ousterhout] Fixed spelling issue
658e1af [Kay Ousterhout] [SPARK-5360] Eliminate duplicate objects in serialized CoGroupedRDD
Deprecated `spark.akka.num.retries`, `spark.akka.retry.wait`, `spark.akka.askTimeout`, `spark.akka.lookupTimeout`, and added `spark.rpc.num.retries`, `spark.rpc.retry.wait`, `spark.rpc.askTimeout`, `spark.rpc.lookupTimeout`.
Author: zsxwing <zsxwing@gmail.com>
Closes#5595 from zsxwing/SPARK-6490 and squashes the following commits:
e0d80a9 [zsxwing] Use getTimeAsMs and getTimeAsSeconds and other minor fixes
31dbe69 [zsxwing] Add spark.rpc.* and deprecate spark.akka.*
A subtask of [SPARK-5293](https://issues.apache.org/jira/browse/SPARK-5293)
Author: zsxwing <zsxwing@gmail.com>
Closes#5557 from zsxwing/SPARK-6983 and squashes the following commits:
e777e9f [zsxwing] Update ReceiverTrackerActor to use the new Rpc interface
cc andrewor14
Author: GuoQiang Li <witgo@qq.com>
Closes#5548 from witgo/SPARK-6963 and squashes the following commits:
964aea7 [GuoQiang Li] review commits
b08b3c9 [GuoQiang Li] Flaky test: o.a.s.ContextCleanerSuite automatically cleanup checkpoint
The default method will use Guava's Ordering instead of
java.util.Comparator.naturalOrder() because it's not available
in Java 7, only in Java 8.
Author: Olivier Girardot <o.girardot@lateral-thoughts.com>
Closes#5571 from ogirardot/master and squashes the following commits:
7fe2e9e [Olivier Girardot] SPARK-6993 : Add default min, max methods for JavaDoubleRDD
