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* [MINOR] Add missing interpolation in NettyRPCEnvAndrew Or2015-12-161-1/+1
| | | | | | | | | | | | | | | ``` Exception in thread "main" org.apache.spark.rpc.RpcTimeoutException: Cannot receive any reply in ${timeout.duration}. This timeout is controlled by spark.rpc.askTimeout at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48) at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63) at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59) at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33) ``` Author: Andrew Or <andrew@databricks.com> Closes #10334 from andrewor14/rpc-typo.
* [SPARK-12345][MESOS] Filter SPARK_HOME when submitting Spark jobs with Mesos ↵Timothy Chen2015-12-162-2/+7
| | | | | | | | | | | | cluster mode. SPARK_HOME is now causing problem with Mesos cluster mode since spark-submit script has been changed recently to take precendence when running spark-class scripts to look in SPARK_HOME if it's defined. We should skip passing SPARK_HOME from the Spark client in cluster mode with Mesos, since Mesos shouldn't use this configuration but should use spark.executor.home instead. Author: Timothy Chen <tnachen@gmail.com> Closes #10332 from tnachen/scheduler_ui.
* [SPARK-12062][CORE] Change Master to asyc rebuild UI when application completesBryan Cutler2015-12-152-29/+52
| | | | | | | | This change builds the event history of completed apps asynchronously so the RPC thread will not be blocked and allow new workers to register/remove if the event log history is very large and takes a long time to rebuild. Author: Bryan Cutler <bjcutler@us.ibm.com> Closes #10284 from BryanCutler/async-MasterUI-SPARK-12062.
* [SPARK-9886][CORE] Fix to use ShutdownHookManager inNaveen2015-12-151-11/+5
| | | | | | | | ExternalBlockStore.scala Author: Naveen <naveenminchu@gmail.com> Closes #10313 from naveenminchu/branch-fix-SPARK-9886.
* [SPARK-10123][DEPLOY] Support specifying deploy mode from configurationjerryshao2015-12-152-1/+45
| | | | | | | | Please help to review, thanks a lot. Author: jerryshao <sshao@hortonworks.com> Closes #10195 from jerryshao/SPARK-10123.
* [SPARK-9026][SPARK-4514] Modifications to JobWaiter, FutureAction, and ↵Richard W. Eggert II2015-12-157-158/+251
| | | | | | | | | | | | | | | AsyncRDDActions to support non-blocking operation These changes rework the implementations of `SimpleFutureAction`, `ComplexFutureAction`, `JobWaiter`, and `AsyncRDDActions` such that asynchronous callbacks on the generated `Futures` NEVER block waiting for a job to complete. A small amount of mutex synchronization is necessary to protect the internal fields that manage cancellation, but these locks are only held very briefly and in practice should almost never cause any blocking to occur. The existing blocking APIs of these classes are retained, but they simply delegate to the underlying non-blocking API and `Await` the results with indefinite timeouts. Associated JIRA ticket: https://issues.apache.org/jira/browse/SPARK-9026 Also fixes: https://issues.apache.org/jira/browse/SPARK-4514 This pull request contains all my own original work, which I release to the Spark project under its open source license. Author: Richard W. Eggert II <richard.eggert@gmail.com> Closes #9264 from reggert/fix-futureaction.
* [SPARK-9516][UI] Improvement of Thread Dump PageCodingCat2015-12-154-43/+118
| | | | | | | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-9516 - [x] new look of Thread Dump Page - [x] click column title to sort - [x] grep - [x] search as you type squito JoshRosen It's ready for the review now Author: CodingCat <zhunansjtu@gmail.com> Closes #7910 from CodingCat/SPARK-9516.
* [SPARK-12130] Replace shuffleManagerClass with shortShuffleMgrNames in ↵Lianhui Wang2015-12-154-1/+9
| | | | | | | | | | ExternalShuffleBlockResolver Replace shuffleManagerClassName with shortShuffleMgrName is to reduce time of string's comparison. and put sort's comparison on the front. cc JoshRosen andrewor14 Author: Lianhui Wang <lianhuiwang09@gmail.com> Closes #10131 from lianhuiwang/spark-12130.
* [SPARK-12332][TRIVIAL][TEST] Fix minor typo in ResetSystemPropertiesHolden Karau2015-12-151-1/+1
| | | | | | | | Fix a minor typo (unbalanced bracket) in ResetSystemProperties. Author: Holden Karau <holden@us.ibm.com> Closes #10303 from holdenk/SPARK-12332-trivial-typo-in-ResetSystemProperties-comment.
* [SPARK-12281][CORE] Fix a race condition when reporting ExecutorState in the ↵Shixiong Zhu2015-12-133-3/+9
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | shutdown hook 1. Make sure workers and masters exit so that no worker or master will still be running when triggering the shutdown hook. 2. Set ExecutorState to FAILED if it's still RUNNING when executing the shutdown hook. This should fix the potential exceptions when exiting a local cluster ``` java.lang.AssertionError: assertion failed: executor 4 state transfer from RUNNING to RUNNING is illegal at scala.Predef$.assert(Predef.scala:179) at org.apache.spark.deploy.master.Master$$anonfun$receive$1.applyOrElse(Master.scala:260) at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:116) at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:204) at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:100) at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:215) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) java.lang.IllegalStateException: Shutdown hooks cannot be modified during shutdown. at org.apache.spark.util.SparkShutdownHookManager.add(ShutdownHookManager.scala:246) at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:191) at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:180) at org.apache.spark.deploy.worker.ExecutorRunner.start(ExecutorRunner.scala:73) at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:474) at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:116) at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:204) at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:100) at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:215) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) ``` Author: Shixiong Zhu <shixiong@databricks.com> Closes #10269 from zsxwing/executor-state.
* [SPARK-12267][CORE] Store the remote RpcEnv address to send the correct ↵Shixiong Zhu2015-12-124-1/+65
| | | | | | | | disconnetion message Author: Shixiong Zhu <shixiong@databricks.com> Closes #10261 from zsxwing/SPARK-12267.
* [SPARK-12155][SPARK-12253] Fix executor OOM in unified memory managementAndrew Or2015-12-104-31/+114
| | | | | | | | | | | | | | | | | | **Problem.** In unified memory management, acquiring execution memory may lead to eviction of storage memory. However, the space freed from evicting cached blocks is distributed among all active tasks. Thus, an incorrect upper bound on the execution memory per task can cause the acquisition to fail, leading to OOM's and premature spills. **Example.** Suppose total memory is 1000B, cached blocks occupy 900B, `spark.memory.storageFraction` is 0.4, and there are two active tasks. In this case, the cap on task execution memory is 100B / 2 = 50B. If task A tries to acquire 200B, it will evict 100B of storage but can only acquire 50B because of the incorrect cap. For another example, see this [regression test](https://github.com/andrewor14/spark/blob/fix-oom/core/src/test/scala/org/apache/spark/memory/UnifiedMemoryManagerSuite.scala#L233) that I stole from JoshRosen. **Solution.** Fix the cap on task execution memory. It should take into account the space that could have been freed by storage in addition to the current amount of memory available to execution. In the example above, the correct cap should have been 600B / 2 = 300B. This patch also guards against the race condition (SPARK-12253): (1) Existing tasks collectively occupy all execution memory (2) New task comes in and blocks while existing tasks spill (3) After tasks finish spilling, another task jumps in and puts in a large block, stealing the freed memory (4) New task still cannot acquire memory and goes back to sleep Author: Andrew Or <andrew@databricks.com> Closes #10240 from andrewor14/fix-oom.
* [SPARK-12251] Document and improve off-heap memory configurationsJosh Rosen2015-12-1011-19/+42
| | | | | | | | | | | | | This patch adds documentation for Spark configurations that affect off-heap memory and makes some naming and validation improvements for those configs. - Change `spark.memory.offHeapSize` to `spark.memory.offHeap.size`. This is fine because this configuration has not shipped in any Spark release yet (it's new in Spark 1.6). - Deprecated `spark.unsafe.offHeap` in favor of a new `spark.memory.offHeap.enabled` configuration. The motivation behind this change is to gather all memory-related configurations under the same prefix. - Add a check which prevents users from setting `spark.memory.offHeap.enabled=true` when `spark.memory.offHeap.size == 0`. After SPARK-11389 (#9344), which was committed in Spark 1.6, Spark enforces a hard limit on the amount of off-heap memory that it will allocate to tasks. As a result, enabling off-heap execution memory without setting `spark.memory.offHeap.size` will lead to immediate OOMs. The new configuration validation makes this scenario easier to diagnose, helping to avoid user confusion. - Document these configurations on the configuration page. Author: Josh Rosen <joshrosen@databricks.com> Closes #10237 from JoshRosen/SPARK-12251.
* [SPARK-11563][CORE][REPL] Use RpcEnv to transfer REPL-generated classes.Marcelo Vanzin2015-12-108-15/+98
| | | | | | | | | | | | | | | This avoids bringing up yet another HTTP server on the driver, and instead reuses the file server already managed by the driver's RpcEnv. As a bonus, the repl now inherits the security features of the network library. There's also a small change to create the directory for storing classes under the root temp dir for the application (instead of directly under java.io.tmpdir). Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #9923 from vanzin/SPARK-11563.
* [SPARK-12165][ADDENDUM] Fix outdated comments on unroll testAndrew Or2015-12-091-4/+9
| | | | | | | | JoshRosen Author: Andrew Or <andrew@databricks.com> Closes #10229 from andrewor14/unroll-test-comments.
* [SPARK-11824][WEBUI] WebUI does not render descriptions with 'bad' HTML, ↵Sean Owen2015-12-091-1/+0
| | | | | | | | | | | | | | throws console error Don't warn when description isn't valid HTML since it may properly be like "SELECT ... where foo <= 1" The tests for this code indicate that it's normal to handle strings like this that don't contain HTML as a string rather than markup. Hence logging every such instance as a warning is too noisy since it's not a problem. this is an issue for stages whose name contain SQL like the above CC tdas as author of this bit of code Author: Sean Owen <sowen@cloudera.com> Closes #10159 from srowen/SPARK-11824.
* [SPARK-12165][SPARK-12189] Fix bugs in eviction of storage memory by executionJosh Rosen2015-12-098-204/+230
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch fixes a bug in the eviction of storage memory by execution. ## The bug: In general, execution should be able to evict storage memory when the total storage memory usage is greater than `maxMemory * spark.memory.storageFraction`. Due to a bug, however, Spark might wind up evicting no storage memory in certain cases where the storage memory usage was between `maxMemory * spark.memory.storageFraction` and `maxMemory`. For example, here is a regression test which illustrates the bug: ```scala val maxMemory = 1000L val taskAttemptId = 0L val (mm, ms) = makeThings(maxMemory) // Since we used the default storage fraction (0.5), we should be able to allocate 500 bytes // of storage memory which are immune to eviction by execution memory pressure. // Acquire enough storage memory to exceed the storage region size assert(mm.acquireStorageMemory(dummyBlock, 750L, evictedBlocks)) assertEvictBlocksToFreeSpaceNotCalled(ms) assert(mm.executionMemoryUsed === 0L) assert(mm.storageMemoryUsed === 750L) // At this point, storage is using 250 more bytes of memory than it is guaranteed, so execution // should be able to reclaim up to 250 bytes of storage memory. // Therefore, execution should now be able to require up to 500 bytes of memory: assert(mm.acquireExecutionMemory(500L, taskAttemptId, MemoryMode.ON_HEAP) === 500L) // <--- fails by only returning 250L assert(mm.storageMemoryUsed === 500L) assert(mm.executionMemoryUsed === 500L) assertEvictBlocksToFreeSpaceCalled(ms, 250L) ``` The problem relates to the control flow / interaction between `StorageMemoryPool.shrinkPoolToReclaimSpace()` and `MemoryStore.ensureFreeSpace()`. While trying to allocate the 500 bytes of execution memory, the `UnifiedMemoryManager` discovers that it will need to reclaim 250 bytes of memory from storage, so it calls `StorageMemoryPool.shrinkPoolToReclaimSpace(250L)`. This method, in turn, calls `MemoryStore.ensureFreeSpace(250L)`. However, `ensureFreeSpace()` first checks whether the requested space is less than `maxStorageMemory - storageMemoryUsed`, which will be true if there is any free execution memory because it turns out that `MemoryStore.maxStorageMemory = (maxMemory - onHeapExecutionMemoryPool.memoryUsed)` when the `UnifiedMemoryManager` is used. The control flow here is somewhat confusing (it grew to be messy / confusing over time / as a result of the merging / refactoring of several components). In the pre-Spark 1.6 code, `ensureFreeSpace` was called directly by the `MemoryStore` itself, whereas in 1.6 it's involved in a confusing control flow where `MemoryStore` calls `MemoryManager.acquireStorageMemory`, which then calls back into `MemoryStore.ensureFreeSpace`, which, in turn, calls `MemoryManager.freeStorageMemory`. ## The solution: The solution implemented in this patch is to remove the confusing circular control flow between `MemoryManager` and `MemoryStore`, making the storage memory acquisition process much more linear / straightforward. The key changes: - Remove a layer of inheritance which made the memory manager code harder to understand (53841174760a24a0df3eb1562af1f33dbe340eb9). - Move some bounds checks earlier in the call chain (13ba7ada77f87ef1ec362aec35c89a924e6987cb). - Refactor `ensureFreeSpace()` so that the part which evicts blocks can be called independently from the part which checks whether there is enough free space to avoid eviction (7c68ca09cb1b12f157400866983f753ac863380e). - Realize that this lets us remove a layer of overloads from `ensureFreeSpace` (eec4f6c87423d5e482b710e098486b3bbc4daf06). - Realize that `ensureFreeSpace()` can simply be replaced with an `evictBlocksToFreeSpace()` method which is called [after we've already figured out](https://github.com/apache/spark/blob/2dc842aea82c8895125d46a00aa43dfb0d121de9/core/src/main/scala/org/apache/spark/memory/StorageMemoryPool.scala#L88) how much memory needs to be reclaimed via eviction; (2dc842aea82c8895125d46a00aa43dfb0d121de9). Along the way, I fixed some problems with the mocks in `MemoryManagerSuite`: the old mocks would [unconditionally](https://github.com/apache/spark/blob/80a824d36eec9d9a9f092ee1741453851218ec73/core/src/test/scala/org/apache/spark/memory/MemoryManagerSuite.scala#L84) report that a block had been evicted even if there was enough space in the storage pool such that eviction would be avoided. I also fixed a problem where `StorageMemoryPool._memoryUsed` might become negative due to freed memory being double-counted when excution evicts storage. The problem was that `StorageMemoryPoolshrinkPoolToFreeSpace` would [decrement `_memoryUsed`](https://github.com/apache/spark/commit/7c68ca09cb1b12f157400866983f753ac863380e#diff-935c68a9803be144ed7bafdd2f756a0fL133) even though `StorageMemoryPool.freeMemory` had already decremented it as each evicted block was freed. See SPARK-12189 for details. Author: Josh Rosen <joshrosen@databricks.com> Author: Andrew Or <andrew@databricks.com> Closes #10170 from JoshRosen/SPARK-12165.
* [SPARK-10582][YARN][CORE] Fix AM failure situation for dynamic allocationjerryshao2015-12-093-2/+119
| | | | | | | | | | | | Because of AM failure, the target executor number between driver and AM will be different, which will lead to unexpected behavior in dynamic allocation. So when AM is re-registered with driver, state in `ExecutorAllocationManager` and `CoarseGrainedSchedulerBacked` should be reset. This issue is originally addressed in #8737 , here re-opened again. Thanks a lot KaiXinXiaoLei for finding this issue. andrewor14 and vanzin would you please help to review this, thanks a lot. Author: jerryshao <sshao@hortonworks.com> Closes #9963 from jerryshao/SPARK-10582.
* [SPARK-12031][CORE][BUG] Integer overflow when do samplinguncleGen2015-12-092-7/+8
| | | | | | Author: uncleGen <hustyugm@gmail.com> Closes #10023 from uncleGen/1.6-bugfix.
* [SPARK-12222] [CORE] Deserialize RoaringBitmap using Kryo serializer throw ↵Fei Wang2015-12-082-2/+36
| | | | | | | | | | | | | | | | | | | | | | | | Buffer underflow exception Jira: https://issues.apache.org/jira/browse/SPARK-12222 Deserialize RoaringBitmap using Kryo serializer throw Buffer underflow exception: ``` com.esotericsoftware.kryo.KryoException: Buffer underflow. at com.esotericsoftware.kryo.io.Input.require(Input.java:156) at com.esotericsoftware.kryo.io.Input.skip(Input.java:131) at com.esotericsoftware.kryo.io.Input.skip(Input.java:264) ``` This is caused by a bug of kryo's `Input.skip(long count)`(https://github.com/EsotericSoftware/kryo/issues/119) and we call this method in `KryoInputDataInputBridge`. Instead of upgrade kryo's version, this pr bypass the kryo's `Input.skip(long count)` by directly call another `skip` method in kryo's Input.java(https://github.com/EsotericSoftware/kryo/blob/kryo-2.21/src/com/esotericsoftware/kryo/io/Input.java#L124), i.e. write the bug-fixed version of `Input.skip(long count)` in KryoInputDataInputBridge's `skipBytes` method. more detail link to https://github.com/apache/spark/pull/9748#issuecomment-162860246 Author: Fei Wang <wangfei1@huawei.com> Closes #10213 from scwf/patch-1.
* [SPARK-12187] *MemoryPool classes should not be fully publicAndrew Or2015-12-084-4/+4
| | | | | | | | This patch tightens them to `private[memory]`. Author: Andrew Or <andrew@databricks.com> Closes #10182 from andrewor14/memory-visibility.
* [SPARK-12074] Avoid memory copy involving ↵tedyu2015-12-083-7/+8
| | | | | | | | | | | | | ByteBuffer.wrap(ByteArrayOutputStream.toByteArray) SPARK-12060 fixed JavaSerializerInstance.serialize This PR applies the same technique on two other classes. zsxwing Author: tedyu <yuzhihong@gmail.com> Closes #10177 from tedyu/master.
* [SPARK-11155][WEB UI] Stage summary json should include stage durationXin Ren2015-12-0810-8/+121
| | | | | | | | | | The json endpoint for stages doesn't include information on the stage duration that is present in the UI. This looks like a simple oversight, they should be included. eg., the metrics should be included at api/v1/applications/<appId>/stages. Metrics I've added are: submissionTime, firstTaskLaunchedTime and completionTime Author: Xin Ren <iamshrek@126.com> Closes #10107 from keypointt/SPARK-11155.
* [SPARK-12060][CORE] Avoid memory copy in JavaSerializerInstance.serializeShixiong Zhu2015-12-072-4/+34
| | | | | | | | | | Merged #10051 again since #10083 is resolved. This reverts commit 328b757d5d4486ea3c2e246780792d7a57ee85e5. Author: Shixiong Zhu <shixiong@databricks.com> Closes #10167 from zsxwing/merge-SPARK-12060.
* [SPARK-12084][CORE] Fix codes that uses ByteBuffer.array incorrectlyShixiong Zhu2015-12-049-21/+35
| | | | | | | | | | `ByteBuffer` doesn't guarantee all contents in `ByteBuffer.array` are valid. E.g, a ByteBuffer returned by `ByteBuffer.slice`. We should not use the whole content of `ByteBuffer` unless we know that's correct. This patch fixed all places that use `ByteBuffer.array` incorrectly. Author: Shixiong Zhu <shixiong@databricks.com> Closes #10083 from zsxwing/bytebuffer-array.
* [SPARK-12080][CORE] Kryo - Support multiple user registratorsrotems2015-12-041-2/+4
| | | | | | Author: rotems <roter> Closes #10078 from Botnaim/KryoMultipleCustomRegistrators.
* [SPARK-12142][CORE]Reply false when container allocator is not ready and ↵meiyoula2015-12-041-0/+1
| | | | | | | | | | reset target Using Dynamic Allocation function, when a new AM is starting, and ExecutorAllocationManager send RequestExecutor message to AM. If the container allocator is not ready, the whole app will hang on Author: meiyoula <1039320815@qq.com> Closes #10138 from XuTingjun/patch-1.
* [SPARK-12112][BUILD] Upgrade to SBT 0.13.9Josh Rosen2015-12-053-10/+10
| | | | | | | | | | We should upgrade to SBT 0.13.9, since this is a requirement in order to use SBT's new Maven-style resolution features (which will be done in a separate patch, because it's blocked by some binary compatibility issues in the POM reader plugin). I also upgraded Scalastyle to version 0.8.0, which was necessary in order to fix a Scala 2.10.5 compatibility issue (see https://github.com/scalastyle/scalastyle/issues/156). The newer Scalastyle is slightly stricter about whitespace surrounding tokens, so I fixed the new style violations. Author: Josh Rosen <joshrosen@databricks.com> Closes #10112 from JoshRosen/upgrade-to-sbt-0.13.9.
* [SPARK-6990][BUILD] Add Java linting script; fix minor warningsDmitry Erastov2015-12-042-3/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This replaces https://github.com/apache/spark/pull/9696 Invoke Checkstyle and print any errors to the console, failing the step. Use Google's style rules modified according to https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide Some important checks are disabled (see TODOs in `checkstyle.xml`) due to multiple violations being present in the codebase. Suggest fixing those TODOs in a separate PR(s). More on Checkstyle can be found on the [official website](http://checkstyle.sourceforge.net/). Sample output (from [build 46345](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/46345/consoleFull)) (duplicated because I run the build twice with different profiles): > Checkstyle checks failed at following occurrences: [ERROR] src/main/java/org/apache/spark/sql/execution/datasources/parquet/UnsafeRowParquetRecordReader.java:[217,7] (coding) MissingSwitchDefault: switch without "default" clause. > [ERROR] src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java:[198,10] (modifier) ModifierOrder: 'protected' modifier out of order with the JLS suggestions. > [ERROR] src/main/java/org/apache/spark/sql/execution/datasources/parquet/UnsafeRowParquetRecordReader.java:[217,7] (coding) MissingSwitchDefault: switch without "default" clause. > [ERROR] src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java:[198,10] (modifier) ModifierOrder: 'protected' modifier out of order with the JLS suggestions. > [error] running /home/jenkins/workspace/SparkPullRequestBuilder2/dev/lint-java ; received return code 1 Also fix some of the minor violations that didn't require sweeping changes. Apologies for the previous botched PRs - I finally figured out the issue. cr: JoshRosen, pwendell > I state that the contribution is my original work, and I license the work to the project under the project's open source license. Author: Dmitry Erastov <derastov@gmail.com> Closes #9867 from dskrvk/master.
* [SPARK-12089] [SQL] Fix memory corrupt due to freeing a page being referencedNong2015-12-041-2/+5
| | | | | | | | | | When the spillable sort iterator was spilled, it was mistakenly keeping the last page in memory rather than the current page. This causes the current record to get corrupted. Author: Nong <nong@cloudera.com> Closes #10142 from nongli/spark-12089.
* [SPARK-11206] Support SQL UI on the history server (resubmit)Carson Wang2015-12-037-6/+57
| | | | | | | | | | | | | | | Resubmit #9297 and #9991 On the live web UI, there is a SQL tab which provides valuable information for the SQL query. But once the workload is finished, we won't see the SQL tab on the history server. It will be helpful if we support SQL UI on the history server so we can analyze it even after its execution. To support SQL UI on the history server: 1. I added an onOtherEvent method to the SparkListener trait and post all SQL related events to the same event bus. 2. Two SQL events SparkListenerSQLExecutionStart and SparkListenerSQLExecutionEnd are defined in the sql module. 3. The new SQL events are written to event log using Jackson. 4. A new trait SparkHistoryListenerFactory is added to allow the history server to feed events to the SQL history listener. The SQL implementation is loaded at runtime using java.util.ServiceLoader. Author: Carson Wang <carson.wang@intel.com> Closes #10061 from carsonwang/SqlHistoryUI.
* [SPARK-12056][CORE] Create a TaskAttemptContext only after calling setConf.Anderson de Andrade2015-12-031-2/+2
| | | | | | | | | | | | | | TaskAttemptContext's constructor will clone the configuration instead of referencing it. Calling setConf after creating TaskAttemptContext makes any changes to the configuration made inside setConf unperceived by RecordReader instances. As an example, Titan's InputFormat will change conf when calling setConf. They wrap their InputFormat around Cassandra's ColumnFamilyInputFormat, and append Cassandra's configuration. This change fixes the following error when using Titan's CassandraInputFormat with Spark: *java.lang.RuntimeException: org.apache.thrift.protocol.TProtocolException: Required field 'keyspace' was not present! Struct: set_key space_args(keyspace:null)* There's a discussion of this error here: https://groups.google.com/forum/#!topic/aureliusgraphs/4zpwyrYbGAE Author: Anderson de Andrade <adeandrade@verticalscope.com> Closes #10046 from adeandrade/newhadooprdd-fix.
* [SPARK-12108] Make event logs smallerAndrew Or2015-12-034-40/+20
| | | | | | | | | | | | **Problem.** Event logs in 1.6 were much bigger than 1.5. I ran page rank and the event log size in 1.6 was almost 5x that in 1.5. I did a bisect to find that the RDD callsite added in #9398 is largely responsible for this. **Solution.** This patch removes the long form of the callsite (which is not used!) from the event log. This reduces the size of the event log significantly. *Note on compatibility*: if this patch is to be merged into 1.6.0, then it won't break any compatibility. Otherwise, if it is merged into 1.6.1, then we might need to add more backward compatibility handling logic (currently does not exist yet). Author: Andrew Or <andrew@databricks.com> Closes #10115 from andrewor14/smaller-event-logs.
* [SPARK-12101][CORE] Fix thread pools that cannot cache tasks in Worker and ↵Shixiong Zhu2015-12-032-12/+8
| | | | | | | | | | AppClient `SynchronousQueue` cannot cache any task. This issue is similar to #9978. It's an easy fix. Just use the fixed `ThreadUtils.newDaemonCachedThreadPool`. Author: Shixiong Zhu <shixiong@databricks.com> Closes #10108 from zsxwing/fix-threadpool.
* [SPARK-12059][CORE] Avoid assertion error when unexpected state transition ↵jerryshao2015-12-031-2/+3
| | | | | | | | | | | | met in Master Downgrade to warning log for unexpected state transition. andrewor14 please review, thanks a lot. Author: jerryshao <sshao@hortonworks.com> Closes #10091 from jerryshao/SPARK-12059.
* [SPARK-11314][YARN] add service API and test service for Yarn Cluster schedulersSteve Loughran2015-12-031-226/+0
| | | | | | | | | | | | | | | | This is purely the yarn/src/main and yarn/src/test bits of the YARN ATS integration: the extension model to load and run implementations of `SchedulerExtensionService` in the yarn cluster scheduler process —and to stop them afterwards. There's duplication between the two schedulers, yarn-client and yarn-cluster, at least in terms of setting everything up, because the common superclass, `YarnSchedulerBackend` is in spark-core, and the extension services need the YARN app/attempt IDs. If you look at how the the extension services are loaded, the case class `SchedulerExtensionServiceBinding` is used to pass in config info -currently just the spark context and the yarn IDs, of which one, the attemptID, will be null when running client-side. I'm passing in a case class to ensure that it would be possible in future to add extra arguments to the binding class, yet, as the method signature will not have changed, still be able to load existing services. There's no functional extension service here, just one for testing. The real tests come in the bigger pull requests. At the same time, there's no restriction of this extension service purely to the ATS history publisher. Anything else that wants to listen to the spark context and publish events could use this, and I'd also consider writing one for the YARN-913 registry service, so that the URLs of the web UI would be locatable through that (low priority; would make more sense if integrated with a REST client). There's no minicluster test. Given the test execution overhead of setting up minicluster tests, it'd probably be better to add an extension service into one of the existing tests. Author: Steve Loughran <stevel@hortonworks.com> Closes #9182 from steveloughran/stevel/feature/SPARK-1537-service.
* [SPARK-12082][FLAKY-TEST] Increase timeouts in NettyBlockTransferSecuritySuiteJosh Rosen2015-12-031-1/+1
| | | | | | | | We should try increasing a timeout in NettyBlockTransferSecuritySuite in order to reduce that suite's flakiness in Jenkins. Author: Josh Rosen <joshrosen@databricks.com> Closes #10113 from JoshRosen/SPARK-12082.
* [SPARK-3580][CORE] Add Consistent Method To Get Number of RDD Partitions ↵Jeroen Schot2015-12-024-1/+26
| | | | | | | | | | | | Across Different Languages I have tried to address all the comments in pull request https://github.com/apache/spark/pull/2447. Note that the second commit (using the new method in all internal code of all components) is quite intrusive and could be omitted. Author: Jeroen Schot <jeroen.schot@surfsara.nl> Closes #9767 from schot/master.
* [SPARK-12081] Make unified memory manager work with small heapsAndrew Or2015-12-012-4/+38
| | | | | | | | | | The existing `spark.memory.fraction` (default 0.75) gives the system 25% of the space to work with. For small heaps, this is not enough: e.g. default 1GB leaves only 250MB system memory. This is especially a problem in local mode, where the driver and executor are crammed in the same JVM. Members of the community have reported driver OOM's in such cases. **New proposal.** We now reserve 300MB before taking the 75%. For 1GB JVMs, this leaves `(1024 - 300) * 0.75 = 543MB` for execution and storage. This is proposal (1) listed in the [JIRA](https://issues.apache.org/jira/browse/SPARK-12081). Author: Andrew Or <andrew@databricks.com> Closes #10081 from andrewor14/unified-memory-small-heaps.
* [SPARK-8414] Ensure context cleaner periodic cleanupsAndrew Or2015-12-011-1/+20
| | | | | | | | Garbage collection triggers cleanups. If the driver JVM is huge and there is little memory pressure, we may never clean up shuffle files on executors. This is a problem for long-running applications (e.g. streaming). Author: Andrew Or <andrew@databricks.com> Closes #10070 from andrewor14/periodic-gc.
* Revert "[SPARK-12060][CORE] Avoid memory copy in ↵Shixiong Zhu2015-12-012-34/+4
| | | | | | JavaSerializerInstance.serialize" This reverts commit 1401166576c7018c5f9c31e0a6703d5fb16ea339.
* [SPARK-12004] Preserve the RDD partitioner through RDD checkpointingTathagata Das2015-12-013-31/+173
| | | | | | | | The solution is the save the RDD partitioner in a separate file in the RDD checkpoint directory. That is, `<checkpoint dir>/_partitioner`. In most cases, whether the RDD partitioner was recovered or not, does not affect the correctness, only reduces performance. So this solution makes a best-effort attempt to save and recover the partitioner. If either fails, the checkpointing is not affected. This makes this patch safe and backward compatible. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #9983 from tdas/SPARK-12004.
* [SPARK-12065] Upgrade Tachyon from 0.8.1 to 0.8.2Josh Rosen2015-12-011-1/+1
| | | | | | | | This commit upgrades the Tachyon dependency from 0.8.1 to 0.8.2. Author: Josh Rosen <joshrosen@databricks.com> Closes #10054 from JoshRosen/upgrade-to-tachyon-0.8.2.
* [SPARK-11821] Propagate Kerberos keytab for all environmentswoj-i2015-12-011-0/+4
| | | | | | | | | andrewor14 the same PR as in branch 1.5 harishreedharan Author: woj-i <wojciechindyk@gmail.com> Closes #9859 from woj-i/master.
* [SPARK-12046][DOC] Fixes various ScalaDoc/JavaDoc issuesCheng Lian2015-12-0113-49/+53
| | | | | | | | This PR backports PR #10039 to master Author: Cheng Lian <lian@databricks.com> Closes #10063 from liancheng/spark-12046.doc-fix.master.
* [SPARK-12060][CORE] Avoid memory copy in JavaSerializerInstance.serializeShixiong Zhu2015-12-012-4/+34
| | | | | | | | | | `JavaSerializerInstance.serialize` uses `ByteArrayOutputStream.toByteArray` to get the serialized data. `ByteArrayOutputStream.toByteArray` needs to copy the content in the internal array to a new array. However, since the array will be converted to `ByteBuffer` at once, we can avoid the memory copy. This PR added `ByteBufferOutputStream` to access the protected `buf` and convert it to a `ByteBuffer` directly. Author: Shixiong Zhu <shixiong@databricks.com> Closes #10051 from zsxwing/SPARK-12060.
* [SPARK-12049][CORE] User JVM shutdown hook can cause deadlock at shutdownSean Owen2015-11-301-17/+16
| | | | | | | | Avoid potential deadlock with a user app's shutdown hook thread by more narrowly synchronizing access to 'hooks' Author: Sean Owen <sowen@cloudera.com> Closes #10042 from srowen/SPARK-12049.
* [SPARK-12007][NETWORK] Avoid copies in the network lib's RPC layer.Marcelo Vanzin2015-11-306-21/+24
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | This change seems large, but most of it is just replacing `byte[]` with `ByteBuffer` and `new byte[]` with `ByteBuffer.allocate()`, since it changes the network library's API. The following are parts of the code that actually have meaningful changes: - The Message implementations were changed to inherit from a new AbstractMessage that can optionally hold a reference to a body (in the form of a ManagedBuffer); this is similar to how ResponseWithBody worked before, except now it's not restricted to just responses. - The TransportFrameDecoder was pretty much rewritten to avoid copies as much as possible; it doesn't rely on CompositeByteBuf to accumulate incoming data anymore, since CompositeByteBuf has issues when slices are retained. The code now is able to create frames without having to resort to copying bytes except for a few bytes (containing the frame length) in very rare cases. - Some minor changes in the SASL layer to convert things back to `byte[]` since the JDK SASL API operates on those. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #9987 from vanzin/SPARK-12007.
* [SPARK-12037][CORE] initialize heartbeatReceiverRef before calling ↵CodingCat2015-11-301-3/+4
| | | | | | | | | | | | startDriverHeartbeat https://issues.apache.org/jira/browse/SPARK-12037 a simple fix by changing the order of the statements Author: CodingCat <zhunansjtu@gmail.com> Closes #10032 from CodingCat/SPARK-12037.
* [SPARK-12053][CORE] EventLoggingListener.getLogPath needs 4 parametersTeng Qiu2015-12-011-1/+1
| | | | | | | | | | | ```EventLoggingListener.getLogPath``` needs 4 input arguments: https://github.com/apache/spark/blob/v1.6.0-preview2/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala#L276-L280 the 3rd parameter should be appAttemptId, 4th parameter is codec... Author: Teng Qiu <teng.qiu@gmail.com> Closes #10044 from chutium/SPARK-12053.
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