Because of the way we shade jetty, we lose its dependency orbit
in the assembly jar, which includes the javax servlet API's. This
adds back orbit explicitly, using the version that matches
our jetty version.
Author: Patrick Wendell <patrick@databricks.com>
Closes#4411 from pwendell/servlet-api and squashes the following commits:
445f868 [Patrick Wendell] SPARK-5557: Explicitly include servlet API in dependencies.
This PR adds three major improvements to Parquet data source:
1. Partition discovery
While reading Parquet files resides in Hive style partition directories, `ParquetRelation2` automatically discovers partitioning information and infers partition column types.
This is also a partial work for [SPARK-5182] [1], which aims to provide first class partitioning support for the data source API. Related code in this PR can be easily extracted to the data source API level in future versions.
1. Schema merging
When enabled, Parquet data source collects schema information from all Parquet part-files and tries to merge them. Exceptions are thrown when incompatible schemas are detected. This feature is controlled by data source option `parquet.mergeSchema`, and is enabled by default.
1. Metastore Parquet table conversion moved to analysis phase
This greatly simplifies the conversion logic. `ParquetConversion` strategy can be removed once the old Parquet implementation is removed in the future.
This version of Parquet data source aims to entirely replace the old Parquet implementation. However, the old version hasn't been removed yet. Users can fall back to the old version by turning off SQL configuration `spark.sql.parquet.useDataSourceApi`.
Other JIRA tickets fixed as side effects in this PR:
- [SPARK-5509] [3]: `EqualTo` now uses a proper `Ordering` to compare binary types.
- [SPARK-3575] [4]: Metastore schema is now preserved and passed to `ParquetRelation2` via data source option `parquet.metastoreSchema`.
TODO:
- [ ] More test cases for partition discovery
- [x] Fix write path after data source write support (#4294) is merged
It turned out to be non-trivial to fall back to old Parquet implementation on the write path when Parquet data source is enabled. Since we're planning to include data source write support in 1.3.0, I simply ignored two test cases involving Parquet insertion for now.
- [ ] Fix outdated comments and documentations
PS: This PR looks big, but more than a half of the changed lines in this PR are trivial changes to test cases. To test Parquet with and without the new data source, almost all Parquet test cases are moved into wrapper driver functions. This introduces hundreds of lines of changes.
[1]: https://issues.apache.org/jira/browse/SPARK-5182
[2]: https://issues.apache.org/jira/browse/SPARK-5528
[3]: https://issues.apache.org/jira/browse/SPARK-5509
[4]: https://issues.apache.org/jira/browse/SPARK-3575
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Author: Cheng Lian <lian@databricks.com>
Closes#4308 from liancheng/parquet-partition-discovery and squashes the following commits:
b6946e6 [Cheng Lian] Fixes MiMA issues, addresses comments
8232e17 [Cheng Lian] Write support for Parquet data source
a49bd28 [Cheng Lian] Fixes spelling typo in trait name "CreateableRelationProvider"
808380f [Cheng Lian] Fixes issues introduced while rebasing
50dd8d1 [Cheng Lian] Addresses @rxin's comment, fixes UDT schema merging
adf2aae [Cheng Lian] Fixes compilation error introduced while rebasing
4e0175f [Cheng Lian] Fixes Python Parquet API, we need Py4J array to call varargs method
0d8ec1d [Cheng Lian] Adds more test cases
b35c8c6 [Cheng Lian] Fixes some typos and outdated comments
dd704fd [Cheng Lian] Fixes Python Parquet API
596c312 [Cheng Lian] Uses switch to control whether use Parquet data source or not
7d0f7a2 [Cheng Lian] Fixes Metastore Parquet table conversion
a1896c7 [Cheng Lian] Fixes all existing Parquet test suites except for ParquetMetastoreSuite
5654c9d [Cheng Lian] Draft version of Parquet partition discovery and schema merging
`Await.result` and `selection.resolveOne` runs the same timeout simultaneously. When `Await.result` timeout is reached first, then `TimeoutException` is thrown. On the other hand, when `selection.resolveOne` timeout is reached first, `ActorNotFoundException` is thrown. This is an obvious race condition and the easiest way to fix it is to increase the timeout of one method to make sure the code fails on the other method first.
Author: Jacek Lewandowski <lewandowski.jacek@gmail.com>
Closes#4343 from jacek-lewandowski/SPARK-5548-1.3 and squashes the following commits:
b9ba47e [Jacek Lewandowski] SPARK-5548: Fixed a race condition in AkkaUtilsSuite
This adds a recursive option to the addFile API to satisfy Hive's needs. It only allows specifying HDFS dirs that will be copied down on every executor.
There are a couple outstanding questions.
* Should we allow specifying local dirs as well? The best way to do this would probably be to archive them. The drawback is that it would require a fair bit of code that I don't know of any current use cases for.
* The addFiles implementation has a caching component that I don't entirely understand. What events are we caching between? AFAICT it's users calling addFile on the same file in the same app at different times? Do we want/need to add something similar for addDirectory.
* The addFiles implementation will check to see if an added file already exists and has the same contents. I imagine we want the same behavior, so planning to add this unless people think otherwise.
I plan to add some tests if people are OK with the approach.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#3670 from sryza/sandy-spark-4687 and squashes the following commits:
f9fc77f [Sandy Ryza] Josh's comments
70cd24d [Sandy Ryza] Add another test
13da824 [Sandy Ryza] Revert executor changes
38bf94d [Sandy Ryza] Marcelo's comments
ca83849 [Sandy Ryza] Add addFile test
1941be3 [Sandy Ryza] Fix test and avoid HTTP server in local mode
31f15a9 [Sandy Ryza] Use cache recursively and fix some compile errors
0239c3d [Sandy Ryza] Change addDirectory to addFile with recursive
46fe70a [Sandy Ryza] SPARK-4687. Add a addDirectory API
This patch introduces a new configuration option, `spark.extraListeners`, that allows SparkListeners to be specified in SparkConf and registered before the SparkContext is initialized. From the configuration documentation:
> A comma-separated list of classes that implement SparkListener; when initializing SparkContext, instances of these classes will be created and registered with Spark's listener bus. If a class has a single-argument constructor that accepts a SparkConf, that constructor will be called; otherwise, a zero-argument constructor will be called. If no valid constructor can be found, the SparkContext creation will fail with an exception.
This motivation for this patch is to allow monitoring code to be easily injected into existing Spark programs without having to modify those programs' code.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#4111 from JoshRosen/SPARK-5190-register-sparklistener-in-sc-constructor and squashes the following commits:
8370839 [Josh Rosen] Two minor fixes after merging with master
6e0122c [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-5190-register-sparklistener-in-sc-constructor
1a5b9a0 [Josh Rosen] Remove SPARK_EXTRA_LISTENERS environment variable.
2daff9b [Josh Rosen] Add a couple of explanatory comments for SPARK_EXTRA_LISTENERS.
b9973da [Josh Rosen] Add test to ensure that conf and env var settings are merged, not overriden.
d6f3113 [Josh Rosen] Use getConstructors() instead of try-catch to find right constructor.
d0d276d [Josh Rosen] Move code into setupAndStartListenerBus() method
b22b379 [Josh Rosen] Instantiate SparkListeners from classes listed in configurations.
9c0d8f1 [Josh Rosen] Revert "[SPARK-5190] Allow SparkListeners to be registered before SparkContext starts."
217ecc0 [Josh Rosen] Revert "Add addSparkListener to JavaSparkContext"
25988f3 [Josh Rosen] Add addSparkListener to JavaSparkContext
163ba19 [Josh Rosen] [SPARK-5190] Allow SparkListeners to be registered before SparkContext starts.
Currently, if there are different locality in a task set, the tasks with NODE_LOCAL only get scheduled after all the PROCESS_LOCAL tasks are scheduled and timeout with spark.locality.wait.process (3 seconds by default). In local mode, the LocalScheduler will never call resourceOffer() again once it failed to get a task with same locality, then all the NODE_LOCAL tasks will be never scheduled.
This bug could be reproduced by run example python/streaming/stateful_network_wordcount.py, it will hang after finished a batch with some data.
This patch will check whether there is task for current locality level, if not, it will change to next locality level without waiting for `spark.locality.wait.process` seconds. It works for all locality levels.
Because the list of pending tasks are updated lazily, the check can be false-positive, it means it will not move to next locality level even there is no valid pending tasks, it will wait for timeout.
Author: Davies Liu <davies@databricks.com>
Closes#3779 from davies/local_streaming and squashes the following commits:
2d25fb3 [Davies Liu] Update TaskSetManager.scala
1550668 [Davies Liu] add comment
1c37aac [Davies Liu] address comments
6b13824 [Davies Liu] address comments
906f456 [Davies Liu] Merge branch 'master' of github.com:apache/spark into local_streaming
414e79e [Davies Liu] fix bug, add logging
ff8eabb [Davies Liu] Merge branch 'master' into local_streaming
28d1b3c [Davies Liu] check tasks
9d0ceab [Davies Liu] Merge branch 'master' of github.com:apache/spark into local_streaming
37a2804 [Davies Liu] fix tests
49bda82 [Davies Liu] address comment
d8fb95a [Davies Liu] move to next locality level if no more tasks
2d6ae73 [Davies Liu] add comments
32d363f [Davies Liu] add regression test
7d8c5a5 [Davies Liu] jump to next locality if no pending tasks for executors
https://issues.apache.org/jira/browse/SPARK-5574
very minor, doesn't effect external behavior at all.
Note that after this change, some of these dirs no longer will have "spark" in the name at all. I could change those locations that do pass in a name prefix to also include "spark", eg. "blockmgr" -> "spark-blockmgr"
Author: Imran Rashid <irashid@cloudera.com>
Closes#4344 from squito/SPARK-5574 and squashes the following commits:
33a84fe [Imran Rashid] use given name prefix in dir
This PR adds support for using maven coordinates as dependencies to spark-shell.
Coordinates can be provided as a comma-delimited string after the flag `--packages`.
Additional remote repositories (like SonaType) can be supplied as a comma-delimited string after the flag
`--repositories`.
Uses the Ivy library to resolve dependencies. Unfortunately the library has no decent documentation, therefore solving more complex dependency issues can be a problem.
pwendell, mateiz, mengxr
**Note: This is still a WIP. The following need to be handled:**
- [x] add docs for the methods
- [x] take local ivy cache path as an argument
- [x] add tests
- [x] add Windows compatibility
- [x] exclude unused Ivy dependencies
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#4215 from brkyvz/SPARK-5341ivy and squashes the following commits:
9215851 [Burak Yavuz] ready to merge
db2a5cc [Burak Yavuz] changed logging to printStream
9dae87f [Burak Yavuz] file separators changed
71c374d [Burak Yavuz] merge conflicts fixed
c08dc9f [Burak Yavuz] fixed merge conflicts
3ada19a [Burak Yavuz] fixed Jenkins error (hopefully) and added comment on oro
43c2290 [Burak Yavuz] fixed that ONE line
231f72f [Burak Yavuz] addressed code review
2cd6562 [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into SPARK-5341ivy
85ec5a3 [Burak Yavuz] added oro as a dependency explicitly
ea44ca4 [Burak Yavuz] add oro back to dependencies
cef0e24 [Burak Yavuz] IntelliJ is just messing things up
97c4a92 [Burak Yavuz] fix more weird IntelliJ formatting
9cf077d [Burak Yavuz] fix weird IntelliJ formatting
dcf5e13 [Burak Yavuz] fix windows command line flags
3a23f21 [Burak Yavuz] excluded ivy dependencies
53423e0 [Burak Yavuz] tests added
3705907 [Burak Yavuz] remove ivy-repo as a command line argument. Use global ivy cache as default
c04d885 [Burak Yavuz] take path to ivy cache as a conf
2edc9b5 [Burak Yavuz] managed to exclude Spark and it's dependencies
a0870af [Burak Yavuz] add docs. remove unnecesary new lines
6645af4 [Burak Yavuz] [SPARK-5341] added base implementation
882c4c8 [Burak Yavuz] added maven dependency download
The locality timeout assume that the SchedulerBackend can revive offers periodically, but currently LocalBackend did do that, then some job with mixed locality levels in local mode will hang forever.
This PR let LocalBackend revive offers periodically, just like in cluster mode.
Author: Davies Liu <davies@databricks.com>
Closes#4147 from davies/revive and squashes the following commits:
2acdf9d [Davies Liu] Update LocalBackend.scala
3c8ca7c [Davies Liu] Update LocalBackend.scala
d1b60d2 [Davies Liu] address comments from Kay
33ac9bb [Davies Liu] fix build
d0da0d5 [Davies Liu] Merge branch 'master' of github.com:apache/spark into revive
6cf5972 [Davies Liu] fix thread-safety
ed62a31 [Davies Liu] fix scala style
df9008b [Davies Liu] fix typo
bfc1396 [Davies Liu] revive offers periodically in LocalBackend
In Spark 1.2 we added a `binaryRecords` input method for loading flat binary data. This format is useful for numerical array data, e.g. in scientific computing applications. This PR adds support for the same format in Streaming applications, where it is similarly useful, especially for streaming time series or sensor data.
Summary of additions
- adding `binaryRecordsStream` to Spark Streaming
- exposing `binaryRecordsStream` in the new PySpark Streaming
- new unit tests in Scala and Python
This required adding an optional Hadoop configuration param to `fileStream` and `FileInputStream`, but was otherwise straightforward.
tdas davies
Author: freeman <the.freeman.lab@gmail.com>
Closes#3803 from freeman-lab/streaming-binary-records and squashes the following commits:
b676534 [freeman] Clarify note
5ff1b75 [freeman] Add note to java streaming context
eba925c [freeman] Simplify notes
c4237b8 [freeman] Add experimental tag
30eba67 [freeman] Add filter and newFilesOnly alongside conf
c2cfa6d [freeman] Expose new version of fileStream with conf in java
34d20ef [freeman] Add experimental tag
14bca9a [freeman] Add experimental tag
b85bffc [freeman] Formatting
47560f4 [freeman] Space formatting
9a3715a [freeman] Refactor to reflect changes to FileInputSuite
7373f73 [freeman] Add note and defensive assertion for byte length
3ceb684 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-binary-records
317b6d1 [freeman] Make test inline
fcb915c [freeman] Formatting
becb344 [freeman] Formatting
d3e75b2 [freeman] Add tests in python
a4324a3 [freeman] Line length
029d49c [freeman] Formatting
1c739aa [freeman] Simpler default arg handling
94d90d0 [freeman] Spelling
2843e9d [freeman] Add params to docstring
8b70fbc [freeman] Reorganization
28bff9b [freeman] Fix missing arg
9398bcb [freeman] Expose optional hadoop configuration
23dd69f [freeman] Tests for binaryRecordsStream
36cb0fd [freeman] Add binaryRecordsStream to scala
fe4e803 [freeman] Add binaryRecordStream to Java API
ecef0eb [freeman] Add binaryRecordsStream to python
8550c26 [freeman] Expose additional argument combination
Try to redesign the "primitive type => Writable" implicit APIs to make them be activated automatically and without breaking binary compatibility.
However, this PR will breaking the source compatibility if people use `xxxToXxxWritable` occasionally. See the unit test in `graphx`.
Author: zsxwing <zsxwing@gmail.com>
Closes#3642 from zsxwing/SPARK-4795 and squashes the following commits:
914b2d6 [zsxwing] Add implicit back to the Writables methods
0b9017f [zsxwing] Add some docs
a0e8509 [zsxwing] Merge branch 'master' into SPARK-4795
39343de [zsxwing] Fix the unit test
64853af [zsxwing] Reorganize the rest 'implicit' methods in SparkContext
Made a mistake in https://github.com/apache/spark/pull/4324
Author: Reynold Xin <rxin@databricks.com>
Closes#4333 from rxin/taskcontext-deprecate and squashes the following commits:
61c44ee [Reynold Xin] Minor: Fix TaskContext deprecated annotations.
So the interface documentation shows up in ScalaDoc.
Author: Reynold Xin <rxin@databricks.com>
Closes#4324 from rxin/TaskContext-scala and squashes the following commits:
2480a17 [Reynold Xin] comment
573756f [Reynold Xin] style fixes and javadoc fixes.
87dd537 [Reynold Xin] [SPARK-5549] Define TaskContext interface in Scala.
There isn't a good way to write a SparkListener that receives all SparkListener events and which will be future-compatible (e.g. it will receive events introduced in newer versions of Spark without having to override new methods to process those events).
To address this, this patch adds `SparkFirehoseListener`, a SparkListener implementation that receives all events and dispatches them to a single `onEvent` method (which can be overridden by users).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#4210 from JoshRosen/firehose-listener and squashes the following commits:
223f579 [Josh Rosen] Expand comment to explain rationale for this being a Java class.
ecdfaed [Josh Rosen] Add SparkFirehoseListener class for consuming all SparkListener events.
.this was https://github.com/apache/spark/pull/2676https://issues.apache.org/jira/browse/SPARK-3778
This affects if someone is trying to access secure hdfs something like:
val lines = {
val hconf = new Configuration()
hconf.set("mapred.input.dir", "mydir")
hconf.set("textinputformat.record.delimiter","\003432\n")
sc.newAPIHadoopRDD(hconf, classOf[TextInputFormat], classOf[LongWritable], classOf[Text])
}
Author: Thomas Graves <tgraves@apache.org>
Closes#4292 from tgravescs/SPARK-3788 and squashes the following commits:
cf3b453 [Thomas Graves] newAPIHadoopRDD doesn't properly pass credentials for secure hdfs on yarn
Author: zsxwing <zsxwing@gmail.com>
Closes#4019 from zsxwing/SPARK-5219 and squashes the following commits:
36a8b4e [zsxwing] Add locks to avoid race conditions
These are needed transitively from the other Jetty libraries
we include. It was not picked up by unit tests because we
disable the UI.
Author: Patrick Wendell <patrick@databricks.com>
Closes#4323 from pwendell/jetty and squashes the following commits:
d8669da [Patrick Wendell] SPARK-3996: Add jetty servlet and continuations.
Simple PR to Remove unused import JsonUtil from from org.apache.spark.util.JsonProtocol.scala which fails builds with older versions of hadoop-core
This import is unused. It was introduced in PR #4029https://github.com/apache/spark/pull/4029 as a part of JIRA SPARK-5231
Author: nemccarthy <nathan@nemccarthy.me>
Closes#4320 from nemccarthy/master and squashes the following commits:
8e34a11 [nemccarthy] [SPARK-5543][WebUI] Remove unused import JsonUtil from from org.apache.spark.util.JsonProtocol.scala which fails builds with older versions of hadoop-core
This PR brings the Python API for Spark Streaming Kafka data source.
```
class KafkaUtils(__builtin__.object)
| Static methods defined here:
|
| createStream(ssc, zkQuorum, groupId, topics, storageLevel=StorageLevel(True, True, False, False,
2), keyDecoder=<function utf8_decoder>, valueDecoder=<function utf8_decoder>)
| Create an input stream that pulls messages from a Kafka Broker.
|
| :param ssc: StreamingContext object
| :param zkQuorum: Zookeeper quorum (hostname:port,hostname:port,..).
| :param groupId: The group id for this consumer.
| :param topics: Dict of (topic_name -> numPartitions) to consume.
| Each partition is consumed in its own thread.
| :param storageLevel: RDD storage level.
| :param keyDecoder: A function used to decode key
| :param valueDecoder: A function used to decode value
| :return: A DStream object
```
run the example:
```
bin/spark-submit --driver-class-path external/kafka-assembly/target/scala-*/spark-streaming-kafka-assembly-*.jar examples/src/main/python/streaming/kafka_wordcount.py localhost:2181 test
```
Author: Davies Liu <davies@databricks.com>
Author: Tathagata Das <tdas@databricks.com>
Closes#3715 from davies/kafka and squashes the following commits:
d93bfe0 [Davies Liu] Update make-distribution.sh
4280d04 [Davies Liu] address comments
e6d0427 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka
f257071 [Davies Liu] add tests for null in RDD
23b039a [Davies Liu] address comments
9af51c4 [Davies Liu] Merge branch 'kafka' of github.com:davies/spark into kafka
a74da87 [Davies Liu] address comments
dc1eed0 [Davies Liu] Update kafka_wordcount.py
31e2317 [Davies Liu] Update kafka_wordcount.py
370ba61 [Davies Liu] Update kafka.py
97386b3 [Davies Liu] address comment
2c567a5 [Davies Liu] update logging and comment
33730d1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka
adeeb38 [Davies Liu] Merge pull request #3 from tdas/kafka-python-api
aea8953 [Tathagata Das] Kafka-assembly for Python API
eea16a7 [Davies Liu] refactor
f6ce899 [Davies Liu] add example and fix bugs
98c8d17 [Davies Liu] fix python style
5697a01 [Davies Liu] bypass decoder in scala
048dbe6 [Davies Liu] fix python style
75d485e [Davies Liu] add mqtt
07923c4 [Davies Liu] support kafka in Python
SPARK-3883: SSL support for Akka connections and Jetty based file servers.
This story introduced the following changes:
- Introduced SSLOptions object which holds the SSL configuration and can build the appropriate configuration for Akka or Jetty. SSLOptions can be created by parsing SparkConf entries at a specified namespace.
- SSLOptions is created and kept by SecurityManager
- All Akka actor address creation snippets based on interpolated strings were replaced by a dedicated methods from AkkaUtils. Those methods select the proper Akka protocol - whether akka.tcp or akka.ssl.tcp
- Added tests cases for AkkaUtils, FileServer, SSLOptions and SecurityManager
- Added a way to use node local SSL configuration by executors and driver in standalone mode. It can be done by specifying spark.ssl.useNodeLocalConf in SparkConf.
- Made CoarseGrainedExecutorBackend not overwrite the settings which are executor startup configuration - they are passed anyway from Worker
Refer to https://github.com/apache/spark/pull/3571 for discussion and details
Author: Jacek Lewandowski <lewandowski.jacek@gmail.com>
Author: Jacek Lewandowski <jacek.lewandowski@datastax.com>
Closes#3571 from jacek-lewandowski/SPARK-3883-master and squashes the following commits:
9ef4ed1 [Jacek Lewandowski] Merge pull request #2 from jacek-lewandowski/SPARK-3883-docs2
fb31b49 [Jacek Lewandowski] SPARK-3883: Added SSL setup documentation
2532668 [Jacek Lewandowski] SPARK-3883: Refactored AkkaUtils.protocol method to not use Try
90a8762 [Jacek Lewandowski] SPARK-3883: Refactored methods to resolve Akka address and made it possible to easily configure multiple communication layers for SSL
72b2541 [Jacek Lewandowski] SPARK-3883: A reference to the fallback SSLOptions can be provided when constructing SSLOptions
93050f4 [Jacek Lewandowski] SPARK-3883: SSL support for HttpServer and Akka
...ll cause problems
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4293 from sryza/sandy-spark-5500 and squashes the following commits:
e9ce742 [Sandy Ryza] Change to warning
cc46e52 [Sandy Ryza] Add instructions and extend to NewHadoopRDD
6e1932a [Sandy Ryza] Throw exception on cache
0f6c4eb [Sandy Ryza] SPARK-5500. Document that feeding hadoopFile into a shuffle operation will cause problems
SPARK-5425: Fixed usages of system properties
This patch fixes few problems caused by the fact that the Scala wrapper over system properties is not thread-safe and is basically invalid because it doesn't take into account the default values which could have been set in the properties object. The problem is fixed by modifying `Utils.getSystemProperties` method so that it uses `stringPropertyNames` method of the `Properties` class, which is thread-safe (internally it creates a defensive copy in a synchronized method) and returns keys of the properties which were set explicitly and which are defined as defaults.
The other related problem, which is fixed here. was in `ResetSystemProperties` mix-in. It created a copy of the system properties in the wrong way.
This patch also introduces a test case for thread-safeness of SparkConf creation.
Refer to the discussion in https://github.com/apache/spark/pull/4220 for more details.
Author: Jacek Lewandowski <lewandowski.jacek@gmail.com>
Closes#4222 from jacek-lewandowski/SPARK-5425-1.3 and squashes the following commits:
03da61b [Jacek Lewandowski] SPARK-5425: Modified Utils.getSystemProperties to return a map of all system properties - explicit + defaults
8faf2ea [Jacek Lewandowski] SPARK-5425: Use SerializationUtils to save properties in ResetSystemProperties trait
71aa572 [Jacek Lewandowski] SPARK-5425: Use synchronised methods in system properties to create SparkConf
This patch makes Spark 1.2.1rc2 work again on Windows.
Without it you get following log output on creating a Spark context:
INFO org.apache.spark.SparkEnv:59 - Registering BlockManagerMaster
ERROR org.apache.spark.util.Utils:75 - Failed to create local root dir in .... Ignoring this directory.
ERROR org.apache.spark.storage.DiskBlockManager:75 - Failed to create any local dir.
Author: Martin Weindel <martin.weindel@gmail.com>
Author: mweindel <m.weindel@usu-software.de>
Closes#4299 from MartinWeindel/branch-1.2 and squashes the following commits:
535cb7f [Martin Weindel] fixed last commit
f17072e [Martin Weindel] moved condition to caller to avoid confusion on chmod700() return value
4de5e91 [Martin Weindel] reverted to unix line ends
fe2740b [mweindel] moved comment
ac4749c [mweindel] fixed chmod700 for Windows
Whenever a directory is created by the utility method, immediately restrict
its permissions so that only the owner has access to its contents.
Signed-off-by: Josh Rosen <joshrosen@databricks.com>
now when we run python application on yarn cluster mode through spark-submit, spark-submit does not support python application on yarn cluster mode. so i modify code of submit and yarn's AM in order to support it.
through specifying .py file or primaryResource file via spark-submit, we can make pyspark run in yarn-cluster mode.
example:spark-submit --master yarn-master --num-executors 1 --driver-memory 1g --executor-memory 1g xx.py --primaryResource yy.conf
this config is same as pyspark on yarn-client mode.
firstly,we put local path of .py or primaryResource to yarn's dist.files.that can be distributed on slave nodes.and then in spark-submit we transfer --py-files and --primaryResource to yarn.Client and use "org.apache.spark.deploy.PythonRunner" to user class that can run .py files on ApplicationMaster.
in yarn.Client we transfer --py-files and --primaryResource to ApplicationMaster.
in ApplicationMaster, user's class is org.apache.spark.deploy.PythonRunner, and user's args is primaryResource and -py-files. so that can make pyspark run on ApplicationMaster.
JoshRosen tgravescs sryza
Author: lianhuiwang <lianhuiwang09@gmail.com>
Author: Wang Lianhui <lianhuiwang09@gmail.com>
Closes#3976 from lianhuiwang/SPARK-5173 and squashes the following commits:
28a8a58 [lianhuiwang] fix variable name
67f8cee [lianhuiwang] update with andrewor's comments
0319ae3 [lianhuiwang] address with sryza's comments
2385ef6 [lianhuiwang] address with sryza's comments
03640ab [lianhuiwang] add sparkHome to env
47d2fc3 [lianhuiwang] fix test
2adc8f5 [lianhuiwang] add spark.test.home
d60bc60 [lianhuiwang] fix test
5b30064 [lianhuiwang] add test
097a5ec [lianhuiwang] fix line length exceeds 100
905a106 [lianhuiwang] update with sryza and andrewor 's comments
f1f55b6 [lianhuiwang] when yarn-cluster, all python files can be non-local
172eec1 [Wang Lianhui] fix a min submit's bug
9c941bc [lianhuiwang] support python application running on yarn cluster mode
... initial number
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4051 from sryza/sandy-spark-4585 and squashes the following commits:
d1dd039 [Sandy Ryza] Add spark.dynamicAllocation.initialNumExecutors and make min and max not required
b7c59dc [Sandy Ryza] SPARK-4585. Spark dynamic executor allocation should use minExecutors as initial number
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4305 from sryza/sandy-spark-5492 and squashes the following commits:
b7d4497 [Sandy Ryza] SPARK-5492. Thread statistics can break with older Hadoop versions
(v2 of this patch with a fix that was only relevant for the maven build).
This patch piggy-back's on vanzin's work to simplify the Guava shading,
and adds Jetty as a shaded library in Spark. Other than adding Jetty,
it consilidates the <artifactSet>'s into the root pom. I found it was
a bit easier to follow that way, since you don't need to look into
child pom's to find out specific artifact sets included in shading.
Author: Patrick Wendell <patrick@databricks.com>
Closes#4285 from pwendell/jetty and squashes the following commits:
d3e7f4e [Patrick Wendell] Fix for shaded deps causing compile errors
19f0710 [Patrick Wendell] More code review feedback
961452d [Patrick Wendell] Responding to feedback from Marcello
6df25ca [Patrick Wendell] [WIP] [SPARK-3996]: Shade Jetty in Spark deliverables
Output an error message if the thrift server is started in cluster mode.
Author: Tom Panning <tom.panning@nextcentury.com>
Closes#4137 from tpanningnextcen/spark-5176-thrift-cluster-mode-error and squashes the following commits:
f5c0509 [Tom Panning] [SPARK-5176] The thrift server does not support cluster mode
This PR refactors LiveListenerBus and StreamingListenerBus and extracts the common codes to a parent class `ListenerBus`.
It also includes bug fixes in #3710:
1. Fix the race condition of queueFullErrorMessageLogged in LiveListenerBus and StreamingListenerBus to avoid outputing `queue-full-error` logs multiple times.
2. Make sure the SHUTDOWN message will be delivered to listenerThread, so that we can make sure listenerThread will always be able to exit.
3. Log the error from listener rather than crashing listenerThread in StreamingListenerBus.
During fixing the above bugs, we find it's better to make LiveListenerBus and StreamingListenerBus have the same bahaviors. Then there will be many duplicated codes in LiveListenerBus and StreamingListenerBus.
Therefore, I extracted their common codes to `ListenerBus` as a parent class: LiveListenerBus and StreamingListenerBus only need to extend `ListenerBus` and implement `onPostEvent` (how to process an event) and `onDropEvent` (do something when droppping an event).
Author: zsxwing <zsxwing@gmail.com>
Closes#4006 from zsxwing/SPARK-4859-refactor and squashes the following commits:
c8dade2 [zsxwing] Fix the code style after renaming
5715061 [zsxwing] Rename ListenerHelper to ListenerBus and the original ListenerBus to AsynchronousListenerBus
f0ef647 [zsxwing] Fix the code style
4e85ffc [zsxwing] Merge branch 'master' into SPARK-4859-refactor
d2ef990 [zsxwing] Add private[spark]
4539f91 [zsxwing] Remove final to pass MiMa tests
a9dccd3 [zsxwing] Remove SparkListenerShutdown
7cc04c3 [zsxwing] Refactor LiveListenerBus and StreamingListenerBus and make them share same code base
Depends on [SPARK-5413](https://issues.apache.org/jira/browse/SPARK-5413) / #4209, included here, will rebase once the latter's merged.
Author: Ryan Williams <ryan.blake.williams@gmail.com>
Closes#4218 from ryan-williams/udp and squashes the following commits:
ebae393 [Ryan Williams] Add support for sending Graphite metrics via UDP
cb58262 [Ryan Williams] bump metrics dependency to v3.1.0
These are more `javadoc` 8-related changes I spotted while investigating. These should be helpful in any event, but this does not nearly resolve SPARK-3359, which may never be feasible while using `unidoc` and `javadoc` 8.
Author: Sean Owen <sowen@cloudera.com>
Closes#4193 from srowen/SPARK-3359 and squashes the following commits:
5b33f66 [Sean Owen] Additional scaladoc fixes for javadoc 8; still not going to be javadoc 8 compatible
Just in case there is a bug in the SerializationDebugger that makes error reporting worse than it was.
Author: Reynold Xin <rxin@databricks.com>
Closes#4297 from rxin/ser-config and squashes the following commits:
f1d4629 [Reynold Xin] [SPARK-5307] Add a config option for SerializationDebugger.
This patch adds a SerializationDebugger that is used to add serialization path to a NotSerializableException. When a NotSerializableException is encountered, the debugger visits the object graph to find the path towards the object that cannot be serialized, and constructs information to help user to find the object.
The patch uses the internals of JVM serialization (in particular, heavy usage of ObjectStreamClass). Compared with an earlier attempt, this one provides extra information including field names, array offsets, writeExternal calls, etc.
An example serialization stack:
```
Serialization stack:
- object not serializable (class: org.apache.spark.serializer.NotSerializable, value: org.apache.spark.serializer.NotSerializable2c43caa4)
- element of array (index: 0)
- array (class [Ljava.lang.Object;, size 1)
- field (class: org.apache.spark.serializer.SerializableArray, name: arrayField, type: class [Ljava.lang.Object;)
- object (class org.apache.spark.serializer.SerializableArray, org.apache.spark.serializer.SerializableArray193c5908)
- writeExternal data
- externalizable object (class org.apache.spark.serializer.ExternalizableClass, org.apache.spark.serializer.ExternalizableClass320bdadc)
```
Author: Reynold Xin <rxin@databricks.com>
Closes#4098 from rxin/SerializationDebugger and squashes the following commits:
553b3ff [Reynold Xin] Update SerializationDebuggerSuite.scala
572d0cb [Reynold Xin] Disable automatically when reflection fails.
b349b77 [Reynold Xin] [SPARK-5307] SerializationDebugger to help debug NotSerializableException - take 2
Previously I had tried to solve this with by adding a line in Spark's log4j-defaults.properties.
The issue with the message in log4j-defaults.properties was that the log4j.properties packaged inside Hadoop was getting picked up instead. While it would be ideal to fix that as well, we still want to quiet this in situations where a user supplies their own custom log4j properties.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4192 from sryza/sandy-spark-5393 and squashes the following commits:
4d5dedc [Sandy Ryza] Only set log level if unset
46e07c5 [Sandy Ryza] SPARK-5393. Flood of util.RackResolver log messages after SPARK-1714
Currently, the Python process is released into pool only after the task had finished, it cause many process forked if coalesce() is called.
This PR will change it to release the process as soon as read all the data from it (finish the partition), then a process could be reused to process multiple partitions in a single task.
Author: Davies Liu <davies@databricks.com>
Closes#4238 from davies/py_leak and squashes the following commits:
ec80a43 [Davies Liu] add @volatile
6da437a [Davies Liu] address comments
24ed322 [Davies Liu] fix python process leak while coalesce()
This patch piggy-back's on vanzin's work to simplify the Guava shading,
and adds Jetty as a shaded library in Spark. Other than adding Jetty,
it consilidates the \<artifactSet\>'s into the root pom. I found it was
a bit easier to follow that way, since you don't need to look into
child pom's to find out specific artifact sets included in shading.
Author: Patrick Wendell <patrick@databricks.com>
Closes#4252 from pwendell/jetty and squashes the following commits:
19f0710 [Patrick Wendell] More code review feedback
961452d [Patrick Wendell] Responding to feedback from Marcello
6df25ca [Patrick Wendell] [WIP] [SPARK-3996]: Shade Jetty in Spark deliverables
One side-effect of shading guava is that it disappears as a transitive
dependency. For Hadoop 2.x, this was masked by the fact that Hadoop
itself depends on guava. But certain versions of Hadoop 1.x also
shade guava, leaving either no guava or some random version pulled
by another dependency on the classpath.
So be explicit about the dependency in modules that use guava directly,
which is the right thing to do anyway.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#4272 from vanzin/SPARK-5466 and squashes the following commits:
e3f30e5 [Marcelo Vanzin] Dependency for catalyst is not needed.
d3b2c84 [Marcelo Vanzin] [SPARK-5466] Add explicit guava dependencies where needed.
We have seen many use cases of `treeAggregate`/`treeReduce` outside the ML domain. Maybe it is time to move them to Core. pwendell
Author: Xiangrui Meng <meng@databricks.com>
Closes#4228 from mengxr/SPARK-5430 and squashes the following commits:
20ad40d [Xiangrui Meng] exclude tree* from mima
e89a43e [Xiangrui Meng] fix compile and update java doc
3ae1a4b [Xiangrui Meng] add treeReduce/treeAggregate to Python
6f948c5 [Xiangrui Meng] add treeReduce/treeAggregate to JavaRDDLike
d600b6c [Xiangrui Meng] move treeReduce and treeAggregate to core
SerDeUtil.pairRDDToPython and SerDeUtil.pythonToPairRDD now both support empty RDDs by checking the result of take(1) instead of calling first which throws an exception.
Author: Michael Nazario <mnazario@palantir.com>
Closes#4236 from mnazario/feature/empty-first and squashes the following commits:
a531c0c [Michael Nazario] Added regression tests for SPARK-5441
e3b2fb6 [Michael Nazario] Added acceptance of the empty case
This happens inside SparkEnv initialization as of #4194
Author: Ryan Williams <ryan.blake.williams@gmail.com>
Closes#4213 from ryan-williams/exec-id-set and squashes the following commits:
b3e4f7b [Ryan Williams] Remove redundant executor-id set() call
In DriverSuite, we currently set a timeout of 60 seconds. If after this time the process has not terminated, we leak the process because we never destroy it.
In SparkSubmitSuite, we currently do not have a timeout so the test can hang indefinitely.
Author: Andrew Or <andrew@databricks.com>
Closes#4230 from andrewor14/fix-driver-suite and squashes the following commits:
f5c80fd [Andrew Or] Fix timeout behaviors in both suites
8092c36 [Andrew Or] Stop SparkContext after every individual test
This change reshuffles the order of initialization in `ConnectionManager` so that the last thing that happens is running `selectorThread`, which invokes a method that relies on object state in `ConnectionManager`
zsxwing also reported a similar problem in `BlockManager` in the JIRA, but I can't find a similar pattern there. Maybe it was subsequently fixed?
Author: Sean Owen <sowen@cloudera.com>
Closes#4225 from srowen/SPARK-1934 and squashes the following commits:
c4dec3b [Sean Owen] Init all object state in ConnectionManager constructor before starting thread in constructor that accesses object's state
This is found through reading RDD from `sc.newAPIHadoopRDD` and writing it back using `rdd.saveAsNewAPIHadoopFile` in pyspark.
It turns out that whenever there are multiple RDD conversions from JavaRDD to PythonRDD then back to JavaRDD, the exception below happens:
```
15/01/16 10:28:31 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 7)
java.lang.ClassCastException: [Ljava.lang.Object; cannot be cast to java.util.ArrayList
at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:157)
at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:153)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
```
The test case code below reproduces it:
```
from pyspark.rdd import RDD
dl = [
(u'2', {u'director': u'David Lean'}),
(u'7', {u'director': u'Andrew Dominik'})
]
dl_rdd = sc.parallelize(dl)
tmp = dl_rdd._to_java_object_rdd()
tmp2 = sc._jvm.SerDe.javaToPython(tmp)
t = RDD(tmp2, sc)
t.count()
tmp = t._to_java_object_rdd()
tmp2 = sc._jvm.SerDe.javaToPython(tmp)
t = RDD(tmp2, sc)
t.count() # it blows up here during the 2nd time of conversion
```
Author: Winston Chen <wchen@quid.com>
Closes#4146 from wingchen/master and squashes the following commits:
903df7d [Winston Chen] SPARK-5361, update to toSeq based on the PR
5d90a83 [Winston Chen] SPARK-5361, make python pretty, so to pass PEP 8 checks
126be6b [Winston Chen] SPARK-5361, add in test case
4cf1187 [Winston Chen] SPARK-5361, add in test case
9f1a097 [Winston Chen] add in tuple handling while converting form python RDD back to JavaRDD
Recently `SparkListenerExecutorAdded` and `SparkListenerExecutorRemoved` are added.
I think it's useful if they have timestamp and the reason why an executor is removed.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#4082 from sarutak/SPARK-5291 and squashes the following commits:
a026ff2 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5291
979dfe1 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5291
cf9f9080 [Kousuke Saruta] Fixed test case
1f2a89b [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5291
243f2a60 [Kousuke Saruta] Modified MesosSchedulerBackendSuite
a527c35 [Kousuke Saruta] Added timestamp to SparkListenerExecutorAdded
The current way of shading Guava is a little problematic. Code that
depends on "spark-core" does not see the transitive dependency, yet
classes in "spark-core" actually depend on Guava. So it's a little
tricky to run unit tests that use spark-core classes, since you need
a compatible version of Guava in your dependencies when running the
tests. This can become a little tricky, and is kind of a bad user
experience.
This change modifies the way Guava is shaded so that it's applied
uniformly across the Spark build. This means Guava is shaded inside
spark-core itself, so that the dependency issues above are solved.
Aside from that, all Spark sub-modules have their Guava references
relocated, so that they refer to the relocated classes now packaged
inside spark-core. Before, this was only done by the time the assembly
was built, so projects that did not end up inside the assembly (such
as streaming backends) could still reference the original location
of Guava classes.
The Guava classes are added to the "first" artifact Spark generates
(network-common), so that all downstream modules have the needed
classes available. Since "network-common" is a dependency of spark-core,
all Spark apps should get the relocated classes automatically.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#3658 from vanzin/SPARK-4809 and squashes the following commits:
3c93e42 [Marcelo Vanzin] Shade Guava in the network-common artifact.
5d69ec9 [Marcelo Vanzin] Merge branch 'master' into SPARK-4809
b3104fc [Marcelo Vanzin] Add comment.
941848f [Marcelo Vanzin] Merge branch 'master' into SPARK-4809
f78c48a [Marcelo Vanzin] Merge branch 'master' into SPARK-4809
8053dd4 [Marcelo Vanzin] Merge branch 'master' into SPARK-4809
107d7da [Marcelo Vanzin] Add fix for SPARK-5052 (PR #3874).
40b8723 [Marcelo Vanzin] Merge branch 'master' into SPARK-4809
4a4ed42 [Marcelo Vanzin] [SPARK-4809] Rework Guava library shading.
...mbineFileSplits
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4050 from sryza/sandy-spark-5199 and squashes the following commits:
864514b [Sandy Ryza] Add tests and fix bug
0d504f1 [Sandy Ryza] Prettify
915c7e6 [Sandy Ryza] Get metrics from all filesystems
cdbc3e8 [Sandy Ryza] SPARK-5199. Input metrics should show up for InputFormats that return CombineFileSplits
