| Commit message (Collapse) | Author | Age | Files | Lines |
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As of #1777 we log the name of the actor system when it binds to a port. The current name "spark" is super general and does not convey any meaning. For instance, the following line is taken from my driver log after setting `spark.driver.port` to 5001.
```
14/08/13 19:33:29 INFO Remoting: Remoting started; listening on addresses:
[akka.tcp://sparkandrews-mbp:5001]
14/08/13 19:33:29 INFO Remoting: Remoting now listens on addresses:
[akka.tcp://sparkandrews-mbp:5001]
14/08/06 13:40:05 INFO Utils: Successfully started service 'spark' on port 5001.
```
This commit renames this to "sparkDriver" and "sparkExecutor". The goal of this unambitious PR is simply to make the logged information more explicit without introducing any change in functionality.
Author: Andrew Or <andrewor14@gmail.com>
Closes #1810 from andrewor14/service-name and squashes the following commits:
8c459ed [Andrew Or] Use a common variable for driver/executor actor system names
3a92843 [Andrew Or] Change actor name to sparkDriver and sparkExecutor
921363e [Andrew Or] Merge branch 'master' of github.com:apache/spark into service-name
c8c6a62 [Andrew Or] Do not include hyphens in actor name
1c1b42e [Andrew Or] Avoid spaces in akka system name
f644b55 [Andrew Or] Use more specific service name
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or Jenkins will complain about no Apache header in checkpoint files. tdas rxin
Author: Xiangrui Meng <meng@databricks.com>
Closes #2046 from mengxr/tmp-checkpoint and squashes the following commits:
0d3ec73 [Xiangrui Meng] remove ssc.stop
9797843 [Xiangrui Meng] change checkpointDir to lazy val
89964ab [Xiangrui Meng] use temp folder for checkpoint
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Refactored tests for streaming linear regression to use existing streaming test utilities. Summary of changes:
- Made ``mllib`` depend on tests from ``streaming``
- Rewrote accuracy and convergence tests to use ``setupStreams`` and ``runStreams``
- Added new test for the accuracy of predictions generated by ``predictOnValue``
These tests should run faster, be easier to extend/maintain, and provide a reference for new tests.
mengxr tdas
Author: freeman <the.freeman.lab@gmail.com>
Closes #2037 from freeman-lab/streamingLR-predict-tests and squashes the following commits:
e851ca7 [freeman] Fixed long lines
50eb0bf [freeman] Refactored tests to use streaming test tools
32c43c2 [freeman] Added test for prediction
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Instead of keeping copies in all pages, just reference the values
kept in the base SparkUI instance (by making them available via
getters).
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes #1252 from vanzin/SPARK-2169 and squashes the following commits:
4412fc6 [Marcelo Vanzin] Simplify UIUtils.headerSparkPage signature.
4e5d35a [Marcelo Vanzin] [SPARK-2169] Don't copy appName / basePath everywhere.
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Not supported in Scala 2.11. Split them into separate methods instead.
Author: Anand Avati <avati@redhat.com>
Closes #1704 from avati/SPARK-1812-default-args and squashes the following commits:
3e3924a [Anand Avati] SPARK-1812: Add Mima excludes for the broken ABI
901dfc7 [Anand Avati] SPARK-1812: core - Fix overloaded methods with default arguments
07f00af [Anand Avati] SPARK-1812: streaming - Fix overloaded methods with default arguments
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- Added override.
- Marked some variables as private.
Author: Reynold Xin <rxin@apache.org>
Closes #1943 from rxin/metricsSource and squashes the following commits:
fbfa943 [Reynold Xin] Minor cleanup of metrics.Source. - Added override. - Marked some variables as private.
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When standalone Workers launch executors, they inherit the Spark home set by the driver. This means if the worker machines do not share the same directory structure as the driver node, the Workers will attempt to run scripts (e.g. bin/compute-classpath.sh) that do not exist locally and fail. This is a common scenario if the driver is launched from outside of the cluster.
The solution is to simply not pass the driver's Spark home to the Workers. This PR further makes an attempt to avoid overloading the usages of `spark.home`, which is now only used for setting executor Spark home on Mesos and in python.
This is based on top of #1392 and originally reported by YanTangZhai. Tested on standalone cluster.
Author: Andrew Or <andrewor14@gmail.com>
Closes #1734 from andrewor14/spark-home-reprise and squashes the following commits:
f71f391 [Andrew Or] Revert changes in python
1c2532c [Andrew Or] Merge branch 'master' of github.com:apache/spark into spark-home-reprise
188fc5d [Andrew Or] Avoid using spark.home where possible
09272b7 [Andrew Or] Always use Worker's working directory as spark home
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Author: joyyoj <sunshch@gmail.com>
Closes #1694 from joyyoj/SPARK-2379 and squashes the following commits:
d73790d [joyyoj] SPARK-2379 Fix the bug that streaming's receiver may fall into a dead loop
22e7821 [joyyoj] Merge remote-tracking branch 'apache/master'
3f4a602 [joyyoj] Merge remote-tracking branch 'remotes/apache/master'
f4660c5 [joyyoj] [SPARK-1998] SparkFlumeEvent with body bigger than 1020 bytes are not read properly
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**Problem.** When caching, we currently unroll the entire RDD partition before making sure we have enough free memory. This is a common cause for OOMs especially when (1) the BlockManager has little free space left in memory, and (2) the partition is large.
**Solution.** We maintain a global memory pool of `M` bytes shared across all threads, similar to the way we currently manage memory for shuffle aggregation. Then, while we unroll each partition, periodically check if there is enough space to continue. If not, drop enough RDD blocks to ensure we have at least `M` bytes to work with, then try again. If we still don't have enough space to unroll the partition, give up and drop the block to disk directly if applicable.
**New configurations.**
- `spark.storage.bufferFraction` - the value of `M` as a fraction of the storage memory. (default: 0.2)
- `spark.storage.safetyFraction` - a margin of safety in case size estimation is slightly off. This is the equivalent of the existing `spark.shuffle.safetyFraction`. (default 0.9)
For more detail, see the [design document](https://issues.apache.org/jira/secure/attachment/12651793/spark-1777-design-doc.pdf). Tests pending for performance and memory usage patterns.
Author: Andrew Or <andrewor14@gmail.com>
Closes #1165 from andrewor14/them-rdd-memories and squashes the following commits:
e77f451 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
c7c8832 [Andrew Or] Simplify logic + update a few comments
269d07b [Andrew Or] Very minor changes to tests
6645a8a [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
b7e165c [Andrew Or] Add new tests for unrolling blocks
f12916d [Andrew Or] Slightly clean up tests
71672a7 [Andrew Or] Update unrollSafely tests
369ad07 [Andrew Or] Correct ensureFreeSpace and requestMemory behavior
f4d035c [Andrew Or] Allow one thread to unroll multiple blocks
a66fbd2 [Andrew Or] Rename a few things + update comments
68730b3 [Andrew Or] Fix weird scalatest behavior
e40c60d [Andrew Or] Fix MIMA excludes
ff77aa1 [Andrew Or] Fix tests
1a43c06 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
b9a6eee [Andrew Or] Simplify locking behavior on unrollMemoryMap
ed6cda4 [Andrew Or] Formatting fix (super minor)
f9ff82e [Andrew Or] putValues -> putIterator + putArray
beb368f [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
8448c9b [Andrew Or] Fix tests
a49ba4d [Andrew Or] Do not expose unroll memory check period
69bc0a5 [Andrew Or] Always synchronize on putLock before unrollMemoryMap
3f5a083 [Andrew Or] Simplify signature of ensureFreeSpace
dce55c8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
8288228 [Andrew Or] Synchronize put and unroll properly
4f18a3d [Andrew Or] bufferFraction -> unrollFraction
28edfa3 [Andrew Or] Update a few comments / log messages
728323b [Andrew Or] Do not synchronize every 1000 elements
5ab2329 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
129c441 [Andrew Or] Fix bug: Use toArray rather than array
9a65245 [Andrew Or] Update a few comments + minor control flow changes
57f8d85 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
abeae4f [Andrew Or] Add comment clarifying the MEMORY_AND_DISK case
3dd96aa [Andrew Or] AppendOnlyBuffer -> Vector (+ a few small changes)
f920531 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
0871835 [Andrew Or] Add an effective storage level interface to BlockManager
64e7d4c [Andrew Or] Add/modify a few comments (minor)
8af2f35 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
4f4834e [Andrew Or] Use original storage level for blocks dropped to disk
ecc8c2d [Andrew Or] Fix binary incompatibility
24185ea [Andrew Or] Avoid dropping a block back to disk if reading from disk
2b7ee66 [Andrew Or] Fix bug in SizeTracking*
9b9a273 [Andrew Or] Fix tests
20eb3e5 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
649bdb3 [Andrew Or] Document spark.storage.bufferFraction
a10b0e7 [Andrew Or] Add initial memory request threshold + rename a few things
e9c3cb0 [Andrew Or] cacheMemoryMap -> unrollMemoryMap
198e374 [Andrew Or] Unfold -> unroll
0d50155 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
d9d02a8 [Andrew Or] Remove unused param in unfoldSafely
ec728d8 [Andrew Or] Add tests for safe unfolding of blocks
22b2209 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
078eb83 [Andrew Or] Add check for hasNext in PrimitiveVector.iterator
0871535 [Andrew Or] Fix tests in BlockManagerSuite
d68f31e [Andrew Or] Safely unfold blocks for all memory puts
5961f50 [Andrew Or] Fix tests
195abd7 [Andrew Or] Refactor: move unfold logic to MemoryStore
1e82d00 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
3ce413e [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
d5dd3b4 [Andrew Or] Free buffer memory in finally
ea02eec [Andrew Or] Fix tests
b8e1d9c [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
a8704c1 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
e1b8b25 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
87aa75c [Andrew Or] Fix mima excludes again (typo)
11eb921 [Andrew Or] Clarify comment (minor)
50cae44 [Andrew Or] Remove now duplicate mima exclude
7de5ef9 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
df47265 [Andrew Or] Fix binary incompatibility
6d05a81 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
f94f5af [Andrew Or] Update a few comments (minor)
776aec9 [Andrew Or] Prevent OOM if a single RDD partition is too large
bbd3eea [Andrew Or] Fix CacheManagerSuite to use Array
97ea499 [Andrew Or] Change BlockManager interface to use Arrays
c12f093 [Andrew Or] Add SizeTrackingAppendOnlyBuffer and tests
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Our program needs to receive a large amount of data and run for a long
time.
We set the log level to WARN but "Storing iterator" "received single"
as such message written to the log file. (over yarn)
Author: fireflyc <fireflyc@126.com>
Closes #1372 from fireflyc/fix-replace-stdout-log and squashes the following commits:
e684140 [fireflyc] 'info' modified into the 'debug'
fa22a38 [fireflyc] replace println to log4j
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cogroup
JIRA: https://issues.apache.org/jira/browse/SPARK-2657
Our current code uses ArrayBuffers for each group of values in groupBy, as well as for the key's elements in CoGroupedRDD. ArrayBuffers have a lot of overhead if there are few values in them, which is likely to happen in cases such as join. In particular, they have a pointer to an Object[] of size 16 by default, which is 24 bytes for the array header + 128 for the pointers in there, plus at least 32 for the ArrayBuffer data structure. This patch replaces the per-group buffers with a CompactBuffer class that can store up to 2 elements more efficiently (in fields of itself) and acts like an ArrayBuffer beyond that. For a key's elements in CoGroupedRDD, we use an Array of CompactBuffers instead of an ArrayBuffer of ArrayBuffers.
There are some changes throughout the code to deal with CoGroupedRDD returning Array instead. We can also decide not to do that but CoGroupedRDD is a `DeveloperAPI` so I think it's okay to change it here.
Author: Matei Zaharia <matei@databricks.com>
Closes #1555 from mateiz/compact-groupby and squashes the following commits:
845a356 [Matei Zaharia] Lower initial size of CompactBuffer's vector to 8
07621a7 [Matei Zaharia] Review comments
0c1cd12 [Matei Zaharia] Don't use varargs in CompactBuffer.apply
bdc8a39 [Matei Zaharia] Small tweak to +=, and typos
f61f040 [Matei Zaharia] Fix line lengths
59da88b0 [Matei Zaharia] Fix line lengths
197cde8 [Matei Zaharia] Make CompactBuffer extend Seq to make its toSeq more efficient
775110f [Matei Zaharia] Change CoGroupedRDD to give (K, Array[Iterable[_]]) to avoid wrappers
9b4c6e8 [Matei Zaharia] Use CompactBuffer in CoGroupedRDD
ed577ab [Matei Zaharia] Use CompactBuffer in groupByKey
10f0de1 [Matei Zaharia] A CompactBuffer that's more memory-efficient than ArrayBuffer for small buffers
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explicit return type for implicit function
Author: James Z.M. Gao <gaozhm@mediav.com>
Closes #153 from gzm55/work/streaming-compile and squashes the following commits:
11e9c8d [James Z.M. Gao] fix style error
fe88109 [James Z.M. Gao] fix compile error of streaming project
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Author: Reynold Xin <rxin@apache.org>
Closes #1433 from rxin/compile-warning and squashes the following commits:
8d0b890 [Reynold Xin] Remove some compiler warnings.
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consumption.
Author: Issac Buenrostro <buenrostro@ooyala.com>
Closes #945 from ibuenros/SPARK-1341-throttle and squashes the following commits:
5514916 [Issac Buenrostro] Formatting changes, added documentation for streaming throttling, stricter unit tests for throttling.
62f395f [Issac Buenrostro] Add comments and license to streaming RateLimiter.scala
7066438 [Issac Buenrostro] Moved throttle code to RateLimiter class, smoother pushing when throttling active
ccafe09 [Issac Buenrostro] Throttle BlockGenerator to limit rate of data consumption.
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Fix QueueInputDStream which was not removing dequeued items when used with the oneAtATime flag disabled.
Author: Manuel Laflamme <manuel.laflamme@gmail.com>
Closes #1285 from mlaflamm/spark-2343 and squashes the following commits:
61c9e38 [Manuel Laflamme] Unit tests for queue input stream
c51d029 [Manuel Laflamme] Fix QueueInputDStream with oneAtATime false
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The newFilesOnly logic should be inverted: the logic should be that if the flag newFilesOnly==true then only start reading files older than current time. As the code is now if newFilesOnly==true then it will start to read files that are older than 0L (that is: every file in the directory).
Author: Gabriele Nizzoli <mail@nizzoli.net>
Closes #1077 from gabrielenizzoli/master and squashes the following commits:
4f1d261 [Gabriele Nizzoli] Fix for newFilesOnly logic in file DStream
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These commits cause `ClosureCleaner.clean` to attempt to serialize the cleaned closure with the default closure serializer and throw a `SparkException` if doing so fails. This behavior is enabled by default but can be disabled at individual callsites of `SparkContext.clean`.
Commit 98e01ae8 fixes some no-op assertions in `GraphSuite` that this work exposed; I'm happy to put that in a separate PR if that would be more appropriate.
Author: William Benton <willb@redhat.com>
Closes #143 from willb/spark-897 and squashes the following commits:
bceab8a [William Benton] Commented DStream corner cases for serializability checking.
64d04d2 [William Benton] FailureSuite now checks both messages and causes.
3b3f74a [William Benton] Stylistic and doc cleanups.
b215dea [William Benton] Fixed spurious failures in ImplicitOrderingSuite
be1ecd6 [William Benton] Don't check serializability of DStream transforms.
abe816b [William Benton] Make proactive serializability checking optional.
5bfff24 [William Benton] Adds proactive closure-serializablilty checking
ed2ccf0 [William Benton] Test cases for SPARK-897.
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I got "java.util.NoSuchElementException: key not found: 1401756085000 ms" exception when using kafka stream and 1 sec batchPeriod.
Investigation showed that the reason is that ReceiverLauncher.startReceivers is asynchronous (started in a thread).
https://github.com/vchekan/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala#L206
In case of slow starting receiver, such as Kafka, it easily takes more than 2sec to start. In result, no single "compute" will be called on ReceiverInputDStream before first batch job is executed and receivedBlockInfo remains empty (obviously). Batch job will cause ReceiverInputDStream.getReceivedBlockInfo call and "key not found" exception.
The patch makes getReceivedBlockInfo more robust by tolerating missing values.
Author: Vadim Chekan <kot.begemot@gmail.com>
Closes #961 from vchekan/branch-1.0 and squashes the following commits:
e86f82b [Vadim Chekan] Fixed indentation
4609563 [Vadim Chekan] Key not found exception: if receiver is slow to start, it is possible that getReceivedBlockInfo will be called before compute has been called
(cherry picked from commit 26f6b989312a9a48a27a23ecc68702bd14032e55)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
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Author: Lars Albertsson <lalle@spotify.com>
Closes #1001 from lallea/contextwaiter_stopped and squashes the following commits:
93cd314 [Lars Albertsson] Mend StreamingContext stop() followed by awaitTermination().
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Author: witgo <witgo@qq.com>
Closes #1032 from witgo/ShouldMatchers and squashes the following commits:
7ebf34c [witgo] Resolve scalatest warnings during build
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Author: witgo <witgo@qq.com>
Closes #713 from witgo/scalatest and squashes the following commits:
b627a6a [witgo] merge master
51fb3d6 [witgo] merge master
3771474 [witgo] fix RDDSuite
996d6f9 [witgo] fix TimeStampedWeakValueHashMap test
9dfa4e7 [witgo] merge bug
1479b22 [witgo] merge master
29b9194 [witgo] fix code style
022a7a2 [witgo] fix test dependency
a52c0fa [witgo] fix test dependency
cd8f59d [witgo] Merge branch 'master' of https://github.com/apache/spark into scalatest
046540d [witgo] fix RDDSuite.scala
2c543b9 [witgo] fix ReplSuite.scala
c458928 [witgo] update scalatest to version 2.1.5
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stop resetting spark.driver.port in unit tests (scala, java and python).
Author: Syed Hashmi <shashmi@cloudera.com>
Author: CodingCat <zhunansjtu@gmail.com>
Closes #943 from syedhashmi/master and squashes the following commits:
885f210 [Syed Hashmi] Removing unnecessary file (created by mergetool)
b8bd4b5 [Syed Hashmi] Merge remote-tracking branch 'upstream/master'
b895e59 [Syed Hashmi] Revert "[SPARK-1784] Add a new partitioner"
57b6587 [Syed Hashmi] Revert "[SPARK-1784] Add a balanced partitioner"
1574769 [Syed Hashmi] [SPARK-1942] Stop clearing spark.driver.port in unit tests
4354836 [Syed Hashmi] Revert "SPARK-1686: keep schedule() calling in the main thread"
fd36542 [Syed Hashmi] [SPARK-1784] Add a balanced partitioner
6668015 [CodingCat] SPARK-1686: keep schedule() calling in the main thread
4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
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JIRA: https://issues.apache.org/jira/browse/SPARK-1878
Author: zsxwing <zsxwing@gmail.com>
Closes #822 from zsxwing/SPARK-1878 and squashes the following commits:
4a47e27 [zsxwing] SPARK-1878: Fix the incorrect initialization order
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This is a few changes based on the original patch by @scrapcodes.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes #785 from pwendell/package-docs and squashes the following commits:
c32b731 [Patrick Wendell] Changes based on Prashant's patch
c0463d3 [Prashant Sharma] added eof new line
ce8bf73 [Prashant Sharma] Added eof new line to all files.
4c35f2e [Prashant Sharma] SPARK-1563 Add package-info.java and package.scala files for all packages that appear in docs
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Three issues related to temp files that tests generate – these should be touched up for hygiene but are not urgent.
Modules have a log4j.properties which directs the unit-test.log output file to a directory like `[module]/target/unit-test.log`. But this ends up creating `[module]/[module]/target/unit-test.log` instead of former.
The `work/` directory is not deleted by "mvn clean", in the parent and in modules. Neither is the `checkpoint/` directory created under the various external modules.
Many tests create a temp directory, which is not usually deleted. This can be largely resolved by calling `deleteOnExit()` at creation and trying to call `Utils.deleteRecursively` consistently to clean up, sometimes in an `@After` method.
_If anyone seconds the motion, I can create a more significant change that introduces a new test trait along the lines of `LocalSparkContext`, which provides management of temp directories for subclasses to take advantage of._
Author: Sean Owen <sowen@cloudera.com>
Closes #732 from srowen/SPARK-1798 and squashes the following commits:
5af578e [Sean Owen] Try to consistently delete test temp dirs and files, and set deleteOnExit() for each
b21b356 [Sean Owen] Remove work/ and checkpoint/ dirs with mvn clean
bdd0f41 [Sean Owen] Remove duplicate module dir in log4j.properties output path for tests
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- [x] Move all of them into subpackages of org.apache.spark.examples (right now some are in org.apache.spark.streaming.examples, for instance, and others are in org.apache.spark.examples.mllib)
- [x] Move Python examples into examples/src/main/python
- [x] Update docs to reflect these changes
Author: Sandeep <sandeep@techaddict.me>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes #571 from techaddict/SPARK-1637 and squashes the following commits:
47ef86c [Sandeep] Changes based on Discussions on PR, removing use of RawTextHelper from examples
8ed2d3f [Sandeep] Docs Updated for changes, Change for java examples
5f96121 [Sandeep] Move Python examples into examples/src/main/python
0a8dd77 [Sandeep] Move all Scala Examples to org.apache.spark.examples (some are in org.apache.spark.streaming.examples, for instance, and others are in org.apache.spark.examples.mllib)
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- SPARK-1558: Updated custom receiver guide to match it with the new API
- SPARK-1504: Added deployment and monitoring subsection to streaming
- SPARK-1505: Added migration guide for migrating from 0.9.x and below to Spark 1.0
- Updated various Java streaming examples to use JavaReceiverInputDStream to highlight the API change.
- Removed the requirement for cleaner ttl from streaming guide
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #652 from tdas/doc-fix and squashes the following commits:
cb4f4b7 [Tathagata Das] Possible fix for flaky graceful shutdown test.
ab71f7f [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into doc-fix
8d6ff9b [Tathagata Das] Addded migration guide to Spark Streaming.
7d171df [Tathagata Das] Added reference to JavaReceiverInputStream in examples and streaming guide.
49edd7c [Tathagata Das] Change java doc links to use Java docs.
11528d7 [Tathagata Das] Updated links on index page.
ff80970 [Tathagata Das] More updates to streaming guide.
4dc42e9 [Tathagata Das] Added monitoring and other documentation in the streaming guide.
14c6564 [Tathagata Das] Updated custom receiver guide.
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JavaPairRDDStream.reduceByKeyAndWindow()
It appears that one of these methods doesn't use `org.apache.spark.api.java.function.Function2` like all the others, but uses Scala's `Function2`.
Author: Sean Owen <sowen@cloudera.com>
Closes #633 from srowen/SPARK-1663.2 and squashes the following commits:
1e0232d [Sean Owen] Fix signature of one version of reduceByKeyAndWindow to use Java API Function2, as apparently intended
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receiver in Java
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #558 from tdas/more-fixes and squashes the following commits:
c0c84e6 [Tathagata Das] Removing extra println()
d8a8cf4 [Tathagata Das] More tweaks to make unit test work in Jenkins.
b7caa98 [Tathagata Das] More tweaks.
d337367 [Tathagata Das] More tweaks
22d6f2d [Tathagata Das] Merge remote-tracking branch 'apache/master' into more-fixes
40a961b [Tathagata Das] Modified java test to reduce flakiness.
9410ca6 [Tathagata Das] Merge remote-tracking branch 'apache/master' into more-fixes
86d9147 [Tathagata Das] scala style fix
2f3d7b1 [Tathagata Das] Added Scala custom receiver example.
d677611 [Tathagata Das] Merge remote-tracking branch 'apache/master' into more-fixes
bec3fc2 [Tathagata Das] Added license.
51d6514 [Tathagata Das] Fixed docs on receiver.
81aafa0 [Tathagata Das] Added Java test for Receiver API, and added JavaCustomReceiver example.
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@zsxwing I cherry-picked your changes and merged the master. #365 had some conflicts once again!
Author: zsxwing <zsxwing@gmail.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #562 from tdas/SPARK-1382 and squashes the following commits:
e2962c1 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-1382
20968d9 [zsxwing] Replace Exception with SparkException in DStream
e476651 [zsxwing] Merge remote-tracking branch 'origin/master' into SPARK-1382
35ba56a [zsxwing] SPARK-1382: Fix NPE in DStream.slice
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socket receiver
1617: These changes expose the receiver state (active or inactive) and last error in the UI
1618: If the socket receiver cannot connect in the first attempt, it should try to restart after a delay. That was broken, as the thread that restarts (hence, stops) the receiver waited on Thread.join on itself!
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #540 from tdas/streaming-ui-fix and squashes the following commits:
e469434 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into streaming-ui-fix
dbddf75 [Tathagata Das] Style fix.
66df1a5 [Tathagata Das] Merge remote-tracking branch 'apache/master' into streaming-ui-fix
ad98bc9 [Tathagata Das] Refactored streaming listener to use ReceiverInfo.
d7f849c [Tathagata Das] Revert "Moved BatchInfo from streaming.scheduler to streaming.ui"
5c80919 [Tathagata Das] Moved BatchInfo from streaming.scheduler to streaming.ui
da244f6 [Tathagata Das] Fixed socket receiver as well as made receiver state and error visible in the streamign UI.
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This pulls in changes made by @jerryshao in https://github.com/apache/spark/pull/424 and merges with the master.
Author: jerryshao <saisai.shao@intel.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #545 from tdas/streaming-metrics and squashes the following commits:
034b443 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into streaming-metrics
fb3b0a5 [jerryshao] Modify according master update
21939f5 [jerryshao] Style changes according to style check error
976116b [jerryshao] Add StreamSource in StreamingContext for better monitoring through metrics system
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The raw input data is stored as blocks in BlockManagers. Earlier they were cleared by cleaner ttl. Now since streaming does not require cleaner TTL to be set, the block would not get cleared. This increases up the Spark's memory usage, which is not even accounted and shown in the Spark storage UI. It may cause the data blocks to spill over to disk, which eventually slows down the receiving of data (persisting to memory become bottlenecked by writing to disk).
The solution in this PR is to automatically remove those blocks. The mechanism to keep track of which BlockRDDs (which has presents the raw data blocks as a RDD) can be safely cleared already exists. Just use it to explicitly remove blocks from BlockRDDs.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #512 from tdas/block-rdd-unpersist and squashes the following commits:
d25e610 [Tathagata Das] Merge remote-tracking branch 'apache/master' into block-rdd-unpersist
5f46d69 [Tathagata Das] Merge remote-tracking branch 'apache/master' into block-rdd-unpersist
2c320cd [Tathagata Das] Updated configuration with spark.streaming.unpersist setting.
2d4b2fd [Tathagata Das] Automatically removed input blocks
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Any comments are welcome
Author: Sandeep <sandeep@techaddict.me>
Closes #531 from techaddict/stylefix-1 and squashes the following commits:
7492730 [Sandeep] Pass 4
98b2428 [Sandeep] fix rxin suggestions
b5e2e6f [Sandeep] Pass 3
05932d7 [Sandeep] fix if else styling 2
08690e5 [Sandeep] fix if else styling
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importing implicitConversion
A recent commit reintroduced some of the same warnings that SPARK-1488 resolved. These are just a few more of the same changes to remove these warnings.
Author: Sean Owen <sowen@cloudera.com>
Closes #528 from srowen/SPARK-1488.2 and squashes the following commits:
62d592c [Sean Owen] More feature warnings in tests
4e2e94b [Sean Owen] Squash more language feature warnings in new commits by importing implicitConversion
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In https://issues.apache.org/jira/browse/SPARK-1540 we'd like to look at Spark's API to see if we can take advantage of Comparable keys in more places, which will make external spilling more efficient. This PR is a first step towards that that shows how to pass an Ordering when available and still continue functioning otherwise. It does this using a new implicit parameter with a default value of null.
The API is currently only in Scala -- in Java we'd have to add new versions of mapToPair and such that take a Comparator, or a new method to add a "type hint" to an RDD. We can address those later though.
Unfortunately requiring all keys to be Comparable would not work without requiring RDDs in general to contain only Comparable types. The reason is that methods such as distinct() and intersection() do a shuffle, but should be usable on RDDs of any type. So ordering will have to remain an optimization for the types that can be ordered. I think this isn't a horrible outcome though because one of the nice things about Spark's API is that it works on objects of *any* type, without requiring you to specify a schema or implement Writable or stuff like that.
Author: Matei Zaharia <matei@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@apache.org>
Closes #487 from mateiz/ordered-keys and squashes the following commits:
bd565f6 [Matei Zaharia] Pass an Ordering to only one version of groupBy because the Scala language spec doesn't allow having an optional parameter on all of them (this was only compiling in Scala 2.10 due to a bug).
4629965 [Matei Zaharia] Add tests for other versions of groupBy
3beae85 [Matei Zaharia] Added a test for implicit orderings
80b7a3b [Matei Zaharia] Add an optional Ordering parameter to PairRDDFunctions.
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Since shuffles and RDDs that are out of context are automatically cleaned by Spark core (using ContextCleaner) there is no need for setting the cleaner TTL while creating a StreamingContext.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #491 from tdas/ttl-fix and squashes the following commits:
cf01dc7 [Tathagata Das] Removed requirement for TTL in StreamingContext.
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A simple change, mostly had to change a bunch of example code.
Author: Patrick Wendell <pwendell@gmail.com>
Closes #438 from pwendell/jar-of-class and squashes the following commits:
aa010ff [Patrick Wendell] SPARK-1496: Have jarOfClass return Option[String]
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[WIP]
The current Network Receiver API makes it slightly complicated to right a new receiver as one needs to create an instance of BlockGenerator as shown in SocketReceiver
https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala#L51
Exposing the BlockGenerator interface has made it harder to improve the receiving process. The API of NetworkReceiver (which was not a very stable API anyways) needs to be change if we are to ensure future stability.
Additionally, the functions like streamingContext.socketStream that create input streams, return DStream objects. That makes it hard to expose functionality (say, rate limits) unique to input dstreams. They should return InputDStream or NetworkInputDStream. This is still not yet implemented.
This PR is blocked on the graceful shutdown PR #247
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #300 from tdas/network-receiver-api and squashes the following commits:
ea27b38 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into network-receiver-api
3a4777c [Tathagata Das] Renamed NetworkInputDStream to ReceiverInputDStream, and ActorReceiver related stuff.
838dd39 [Tathagata Das] Added more events to the StreamingListener to report errors and stopped receivers.
a75c7a6 [Tathagata Das] Address some PR comments and fixed other issues.
91bfa72 [Tathagata Das] Fixed bugs.
8533094 [Tathagata Das] Scala style fixes.
028bde6 [Tathagata Das] Further refactored receiver to allow restarting of a receiver.
43f5290 [Tathagata Das] Made functions that create input streams return InputDStream and NetworkInputDStream, for both Scala and Java.
2c94579 [Tathagata Das] Fixed graceful shutdown by removing interrupts on receiving thread.
9e37a0b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into network-receiver-api
3223e95 [Tathagata Das] Refactored the code that runs the NetworkReceiver into further classes and traits to make them more testable.
a36cc48 [Tathagata Das] Refactored the NetworkReceiver API for future stability.
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This is currently causing many builds to hang.
https://issues.apache.org/jira/browse/SPARK-1530
Author: Patrick Wendell <pwendell@gmail.com>
Closes #440 from pwendell/uitest-fix and squashes the following commits:
9a143dc [Patrick Wendell] Ignore streaming UI test
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change _slideDuration to _windowDuration
Author: baishuo(白硕) <vc_java@hotmail.com>
Closes #425 from baishuo/master and squashes the following commits:
6f09ea1 [baishuo(白硕)] Update ReducedWindowedDStream.scala
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For your consideration: scalac currently notes a number of feature warnings during compilation:
```
[warn] there were 65 feature warning(s); re-run with -feature for details
```
Warnings are like:
```
[warn] /Users/srowen/Documents/spark/core/src/main/scala/org/apache/spark/SparkContext.scala:1261: implicit conversion method rddToPairRDDFunctions should be enabled
[warn] by making the implicit value scala.language.implicitConversions visible.
[warn] This can be achieved by adding the import clause 'import scala.language.implicitConversions'
[warn] or by setting the compiler option -language:implicitConversions.
[warn] See the Scala docs for value scala.language.implicitConversions for a discussion
[warn] why the feature should be explicitly enabled.
[warn] implicit def rddToPairRDDFunctions[K: ClassTag, V: ClassTag](rdd: RDD[(K, V)]) =
[warn] ^
```
scalac is suggesting that it's just best practice to explicitly enable certain language features by importing them where used.
This PR simply adds the imports it suggests (and squashes one other Java warning along the way). This leaves just deprecation warnings in the build.
Author: Sean Owen <sowen@cloudera.com>
Closes #404 from srowen/SPARK-1488 and squashes the following commits:
8598980 [Sean Owen] Quiet scalac warnings about language features by explicitly importing language features.
39bc831 [Sean Owen] Enable -feature in scalac to emit language feature warnings
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When debugging Spark Streaming applications it is necessary to monitor certain metrics that are not shown in the Spark application UI. For example, what is average processing time of batches? What is the scheduling delay? Is the system able to process as fast as it is receiving data? How many records I am receiving through my receivers?
While the StreamingListener interface introduced in the 0.9 provided some of this information, it could only be accessed programmatically. A UI that shows information specific to the streaming applications is necessary for easier debugging. This PR introduces such a UI. It shows various statistics related to the streaming application. Here is a screenshot of the UI running on my local machine.
http://i.imgur.com/1ooDGhm.png
This UI is integrated into the Spark UI running at 4040.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Andrew Or <andrewor14@gmail.com>
Closes #290 from tdas/streaming-web-ui and squashes the following commits:
fc73ca5 [Tathagata Das] Merge pull request #9 from andrewor14/ui-refactor
642dd88 [Andrew Or] Merge SparkUISuite.scala into UISuite.scala
eb30517 [Andrew Or] Merge github.com:apache/spark into ui-refactor
f4f4cbe [Tathagata Das] More minor fixes.
34bb364 [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
252c566 [Tathagata Das] Merge pull request #8 from andrewor14/ui-refactor
e038b4b [Tathagata Das] Addressed Patrick's comments.
125a054 [Andrew Or] Disable serving static resources with gzip
90feb8d [Andrew Or] Address Patrick's comments
89dae36 [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
72fe256 [Tathagata Das] Merge pull request #6 from andrewor14/ui-refactor
2fc09c8 [Tathagata Das] Added binary check exclusions
aa396d4 [Andrew Or] Rename tabs and pages (No more IndexPage.scala)
f8e1053 [Tathagata Das] Added Spark and Streaming UI unit tests.
caa5e05 [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
585cd65 [Tathagata Das] Merge pull request #5 from andrewor14/ui-refactor
914b8ff [Tathagata Das] Moved utils functions to UIUtils.
548c98c [Andrew Or] Wide refactoring of WebUI, UITab, and UIPage (see commit message)
6de06b0 [Tathagata Das] Merge remote-tracking branch 'apache/master' into streaming-web-ui
ee6543f [Tathagata Das] Minor changes based on Andrew's comments.
fa760fe [Tathagata Das] Fixed long line.
1c0bcef [Tathagata Das] Refactored streaming UI into two files.
1af239b [Tathagata Das] Changed streaming UI to attach itself as a tab with the Spark UI.
827e81a [Tathagata Das] Merge branch 'streaming-web-ui' of github.com:tdas/spark into streaming-web-ui
168fe86 [Tathagata Das] Merge pull request #2 from andrewor14/ui-refactor
3e986f8 [Tathagata Das] Merge remote-tracking branch 'apache/master' into streaming-web-ui
c78c92d [Andrew Or] Remove outdated comment
8f7323b [Andrew Or] End of file new lines, indentation, and imports (minor)
0d61ee8 [Andrew Or] Merge branch 'streaming-web-ui' of github.com:tdas/spark into ui-refactor
9a48fa1 [Andrew Or] Allow adding tabs to SparkUI dynamically + add example
61358e3 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into streaming-web-ui
53be2c5 [Tathagata Das] Minor style updates.
ed25dfc [Andrew Or] Generalize SparkUI header to display tabs dynamically
a37ad4f [Andrew Or] Comments, imports and formatting (minor)
cd000b0 [Andrew Or] Merge github.com:apache/spark into ui-refactor
7d57444 [Andrew Or] Refactoring the UI interface to add flexibility
aef4dd5 [Tathagata Das] Added Apache licenses.
db27bad [Tathagata Das] Added last batch processing time to StreamingUI.
4d86e98 [Tathagata Das] Added basic stats to the StreamingUI and refactored the UI to a Page to make it easier to transition to using SparkUI later.
93f1c69 [Tathagata Das] Added network receiver information to the Streaming UI.
56cc7fb [Tathagata Das] First cut implementation of Streaming UI.
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(This is for discussion at this point -- I'm not suggesting this should be committed.)
This is what removing fastutil looks like. Much of it is straightforward, like using `java.io` buffered stream classes, and Guava for murmurhash3.
Uses of the `FastByteArrayOutputStream` were a little trickier. In only one case though do I think the change to use `java.io` actually entails an extra array copy.
The rest is using `OpenHashMap` and `OpenHashSet`. These are now written in terms of more scala-like operations.
`OpenHashMap` is where I made three non-trivial changes to make it work, and they need review:
- It is no longer private
- The key must be a `ClassTag`
- Unless a lot of other code changes, the key type can't enforce being a supertype of `Null`
It all works and tests pass, and I think there is reason to believe it's OK from a speed perspective.
But what about those last changes?
Author: Sean Owen <sowen@cloudera.com>
Closes #266 from srowen/SPARK-1057-alternate and squashes the following commits:
2601129 [Sean Owen] Fix Map return type error not previously caught
ec65502 [Sean Owen] Updates from matei's review
00bc81e [Sean Owen] Remove use of fastutil and replace with use of java.io, spark.util and Guava classes
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update the content of Exception when windowDuration is not multiple of parent.slideDuration
Author: baishuo(白硕) <vc_java@hotmail.com>
Closes #390 from baishuo/windowdstream and squashes the following commits:
533c968 [baishuo(白硕)] Update WindowedDStream.scala
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stack these together in a commit else they show up chunk by chunk in different commits.
Author: Sandeep <sandeep@techaddict.me>
Closes #380 from techaddict/white_space and squashes the following commits:
b58f294 [Sandeep] Remove Unnecessary Whitespace's
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This reverts commit 8ca3b2bc90a63b23a03f339e390174cd7a672b40.
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[SPARK-729](https://spark-project.atlassian.net/browse/SPARK-729) concerns when free variables in closure arguments to transformations are captured. Currently, it is possible for closures to get the environment in which they are serialized (not the environment in which they are created). There are a few possible approaches to solving this problem and this PR will discuss some of them. The approach I took has the advantage of being simple, obviously correct, and minimally-invasive, but it preserves something that has been bothering me about Spark's closure handling, so I'd like to discuss an alternative and get some feedback on whether or not it is worth pursuing.
## What I did
The basic approach I took depends on the work I did for #143, and so this PR is based atop that. Specifically: #143 modifies `ClosureCleaner.clean` to preemptively determine whether or not closures are serializable immediately upon closure cleaning (rather than waiting for an job involving that closure to be scheduled). Thus non-serializable closure exceptions will be triggered by the line defining the closure rather than triggered where the closure is used.
Since the easiest way to determine whether or not a closure is serializable is to attempt to serialize it, the code in #143 is creating a serialized closure as part of `ClosureCleaner.clean`. `clean` currently modifies its argument, but the method in `SparkContext` that wraps it to return a value (a reference to the modified-in-place argument). This branch modifies `ClosureCleaner.clean` so that it returns a value: if it is cleaning a serializable closure, it returns the result of deserializing its serialized argument; therefore it is returning a closure with an environment captured at cleaning time. `SparkContext.clean` then returns the result of `ClosureCleaner.clean`, rather than a reference to its modified-in-place argument.
I've added tests for this behavior (777a1bc). The pull request as it stands, given the changes in #143, is nearly trivial. There is some overhead from deserializing the closure, but it is minimal and the benefit of obvious operational correctness (vs. a more sophisticated but harder-to-validate transformation in `ClosureCleaner`) seems pretty important. I think this is a fine way to solve this problem, but it's not perfect.
## What we might want to do
The thing that has been bothering me about Spark's handling of closures is that it seems like we should be able to statically ensure that cleaning and serialization happen exactly once for a given closure. If we serialize a closure in order to determine whether or not it is serializable, we should be able to hang on to the generated byte buffer and use it instead of re-serializing the closure later. By replacing closures with instances of a sum type that encodes whether or not a closure has been cleaned or serialized, we could handle clean, to-be-cleaned, and serialized closures separately with case matches. Here's a somewhat-concrete sketch (taken from my git stash) of what this might look like:
```scala
package org.apache.spark.util
import java.nio.ByteBuffer
import scala.reflect.ClassManifest
sealed abstract class ClosureBox[T] { def func: T }
final case class RawClosure[T](func: T) extends ClosureBox[T] {}
final case class CleanedClosure[T](func: T) extends ClosureBox[T] {}
final case class SerializedClosure[T](func: T, bytebuf: ByteBuffer) extends ClosureBox[T] {}
object ClosureBoxImplicits {
implicit def closureBoxFromFunc[T <: AnyRef](fun: T) = new RawClosure[T](fun)
}
```
With these types declared, we'd be able to change `ClosureCleaner.clean` to take a `ClosureBox[T=>U]` (possibly generated by implicit conversion) and return a `ClosureBox[T=>U]` (either a `CleanedClosure[T=>U]` or a `SerializedClosure[T=>U]`, depending on whether or not serializability-checking was enabled) instead of a `T=>U`. A case match could thus short-circuit cleaning or serializing closures that had already been cleaned or serialized (both in `ClosureCleaner` and in the closure serializer). Cleaned-and-serialized closures would be represented by a boxed tuple of the original closure and a serialized copy (complete with an environment quiesced at transformation time). Additional implicit conversions could convert from `ClosureBox` instances to the underlying function type where appropriate. Tracking this sort of state in the type system seems like the right thing to do to me.
### Why we might not want to do that
_It's pretty invasive._ Every function type used by every `RDD` subclass would have to change to reflect that they expected a `ClosureBox[T=>U]` instead of a `T=>U`. This obscures what's going on and is not a little ugly. Although I really like the idea of using the type system to enforce the clean-or-serialize once discipline, it might not be worth adding another layer of types (even if we could hide some of the extra boilerplate with judicious application of implicit conversions).
_It statically guarantees a property whose absence is unlikely to cause any serious problems as it stands._ It appears that all closures are currently dynamically cleaned once and it's not obvious that repeated closure-cleaning is likely to be a problem in the future. Furthermore, serializing closures is relatively cheap, so doing it once to check for serialization and once again to actually ship them across the wire doesn't seem like a big deal.
Taken together, these seem like a high price to pay for statically guaranteeing that closures are operated upon only once.
## Other possibilities
I felt like the serialize-and-deserialize approach was best due to its obvious simplicity. But it would be possible to do a more sophisticated transformation within `ClosureCleaner.clean`. It might also be possible for `clean` to modify its argument in a way so that whether or not a given closure had been cleaned would be apparent upon inspection; this would buy us some of the operational benefits of the `ClosureBox` approach but not the static cleanliness.
I'm interested in any feedback or discussion on whether or not the problems with the type-based approach indeed outweigh the advantage, as well as of approaches to this issue and to closure handling in general.
Author: William Benton <willb@redhat.com>
Closes #189 from willb/spark-729 and squashes the following commits:
f4cafa0 [William Benton] Stylistic changes and cleanups
b3d9c86 [William Benton] Fixed style issues in tests
9b56ce0 [William Benton] Added array-element capture test
97e9d91 [William Benton] Split closure-serializability failure tests
12ef6e3 [William Benton] Skip proactive closure capture for runJob
8ee3ee7 [William Benton] Predictable closure environment capture
12c63a7 [William Benton] Added tests for variable capture in closures
d6e8dd6 [William Benton] Don't check serializability of DStream transforms.
4ecf841 [William Benton] Make proactive serializability checking optional.
d8df3db [William Benton] Adds proactive closure-serializablilty checking
21b4b06 [William Benton] Test cases for SPARK-897.
d5947b3 [William Benton] Ensure assertions in Graph.apply are asserted.
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Author: Holden Karau <holden@pigscanfly.ca>
Closes #242 from holdenk/spark-1320-cogroupandgroupshouldpassiterator and squashes the following commits:
f289536 [Holden Karau] Fix bad merge, should have been Iterable rather than Iterator
77048f8 [Holden Karau] Fix merge up to master
d3fe909 [Holden Karau] use toSeq instead
7a092a3 [Holden Karau] switch resultitr to resultiterable
eb06216 [Holden Karau] maybe I should have had a coffee first. use correct import for guava iterables
c5075aa [Holden Karau] If guava 14 had iterables
2d06e10 [Holden Karau] Fix Java 8 cogroup tests for the new API
11e730c [Holden Karau] Fix streaming tests
66b583d [Holden Karau] Fix the core test suite to compile
4ed579b [Holden Karau] Refactor from iterator to iterable
d052c07 [Holden Karau] Python tests now pass with iterator pandas
3bcd81d [Holden Karau] Revert "Try and make pickling list iterators work"
cd1e81c [Holden Karau] Try and make pickling list iterators work
c60233a [Holden Karau] Start investigating moving to iterators for python API like the Java/Scala one. tl;dr: We will have to write our own iterator since the default one doesn't pickle well
88a5cef [Holden Karau] Fix cogroup test in JavaAPISuite for streaming
a5ee714 [Holden Karau] oops, was checking wrong iterator
e687f21 [Holden Karau] Fix groupbykey test in JavaAPISuite of streaming
ec8cc3e [Holden Karau] Fix test issues\!
4b0eeb9 [Holden Karau] Switch cast in PairDStreamFunctions
fa395c9 [Holden Karau] Revert "Add a join based on the problem in SVD"
ec99e32 [Holden Karau] Revert "Revert this but for now put things in list pandas"
b692868 [Holden Karau] Revert
7e533f7 [Holden Karau] Fix the bug
8a5153a [Holden Karau] Revert me, but we have some stuff to debug
b4e86a9 [Holden Karau] Add a join based on the problem in SVD
c4510e2 [Holden Karau] Revert this but for now put things in list pandas
b4e0b1d [Holden Karau] Fix style issues
71e8b9f [Holden Karau] I really need to stop calling size on iterators, it is the path of sadness.
b1ae51a [Holden Karau] Fix some of the types in the streaming JavaAPI suite. Probably still needs more work
37888ec [Holden Karau] core/tests now pass
249abde [Holden Karau] org.apache.spark.rdd.PairRDDFunctionsSuite passes
6698186 [Holden Karau] Revert "I think this might be a bad rabbit hole. Started work to make CoGroupedRDD use iterator and then went crazy"
fe992fe [Holden Karau] hmmm try and fix up basic operation suite
172705c [Holden Karau] Fix Java API suite
caafa63 [Holden Karau] I think this might be a bad rabbit hole. Started work to make CoGroupedRDD use iterator and then went crazy
88b3329 [Holden Karau] Fix groupbykey to actually give back an iterator
4991af6 [Holden Karau] Fix some tests
be50246 [Holden Karau] Calling size on an iterator is not so good if we want to use it after
687ffbc [Holden Karau] This is the it compiles point of replacing Seq with Iterator and JList with JIterator in the groupby and cogroup signatures
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Current version of StreamingContext.stop() directly kills all the data receivers (NetworkReceiver) without waiting for the data already received to be persisted and processed. This PR provides the fix. Now, when the StreamingContext.stop() is called, the following sequence of steps will happen.
1. The driver will send a stop signal to all the active receivers.
2. Each receiver, when it gets a stop signal from the driver, first stop receiving more data, then waits for the thread that persists data blocks to BlockManager to finish persisting all receive data, and finally quits.
3. After all the receivers have stopped, the driver will wait for the Job Generator and Job Scheduler to finish processing all the received data.
It also fixes the semantics of StreamingContext.start and stop. It will throw appropriate errors and warnings if stop() is called before start(), stop() is called twice, etc.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes #247 from tdas/graceful-shutdown and squashes the following commits:
61c0016 [Tathagata Das] Updated MIMA binary check excludes.
ae1d39b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into graceful-shutdown
6b59cfc [Tathagata Das] Minor changes based on Andrew's comment on PR.
d0b8d65 [Tathagata Das] Reduced time taken by graceful shutdown unit test.
f55bc67 [Tathagata Das] Fix scalastyle
c69b3a7 [Tathagata Das] Updates based on Patrick's comments.
c43b8ae [Tathagata Das] Added graceful shutdown to Spark Streaming.
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