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* [SPARK-14055] writeLocksByTask need to be update when removeBlockErnest2016-03-231-0/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-14055 ## How was this patch tested? manual tests by running LiveJournalPageRank on a large dataset ( the dataset must larger enough to incure RDD partition eviction). Author: Ernest <earneyzxl@gmail.com> Closes #11875 from Earne/issue-14055.
* [SPARK-14075] Refactor MemoryStore to be testable independent of BlockManagerJosh Rosen2016-03-2318-386/+518
| | | | | | | | | | | | | This patch refactors the `MemoryStore` so that it can be tested without needing to construct / mock an entire `BlockManager`. - The block manager's serialization- and compression-related methods have been moved from `BlockManager` to `SerializerManager`. - `BlockInfoManager `is now passed directly to classes that need it, rather than being passed via the `BlockManager`. - The `MemoryStore` now calls `dropFromMemory` via a new `BlockEvictionHandler` interface rather than directly calling the `BlockManager`. This change helps to enforce a narrow interface between the `MemoryStore` and `BlockManager` functionality and makes this interface easier to mock in tests. - Several of the block unrolling tests have been moved from `BlockManagerSuite` into a new `MemoryStoreSuite`. Author: Josh Rosen <joshrosen@databricks.com> Closes #11899 from JoshRosen/reduce-memorystore-blockmanager-coupling.
* [SPARK-14072][CORE] Show JVM/OS version information when we run a benchmark ↵Kazuaki Ishizaki2016-03-221-1/+17
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | program ## What changes were proposed in this pull request? This PR allows us to identify what JVM is used when someone ran a benchmark program. In some cases, a JVM version may affect performance result. Thus, it would be good to show processor information and JVM version information. ``` model name : Intel(R) Xeon(R) CPU E5-2697 v2 2.70GHz JVM information : OpenJDK 64-Bit Server VM, 1.7.0_65-mockbuild_2014_07_14_06_19-b00 Int and String Scan: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------- SQL Parquet Vectorized 981 / 994 10.7 93.5 1.0X SQL Parquet MR 2518 / 2542 4.2 240.1 0.4X ``` ``` model name : Intel(R) Xeon(R) CPU E5-2697 v2 2.70GHz JVM information : IBM J9 VM, pxa6480sr2-20151023_01 (SR2) String Dictionary: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------- SQL Parquet Vectorized 693 / 740 15.1 66.1 1.0X SQL Parquet MR 2501 / 2562 4.2 238.5 0.3X ``` ## How was this patch tested? Tested by using existing benchmark programs (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com> Closes #11893 from kiszk/SPARK-14072.
* [SPARK-13990] Automatically pick serializer when caching RDDsJosh Rosen2016-03-2113-151/+216
| | | | | | | | | | | | Building on the `SerializerManager` introduced in SPARK-13926/ #11755, this patch Spark modifies Spark's BlockManager to use RDD's ClassTags in order to select the best serializer to use when caching RDD blocks. When storing a local block, the BlockManager `put()` methods use implicits to record ClassTags and stores those tags in the blocks' BlockInfo records. When reading a local block, the stored ClassTag is used to pick the appropriate serializer. When a block is stored with replication, the class tag is written into the block transfer metadata and will also be stored in the remote BlockManager. There are two or three places where we don't properly pass ClassTags, including TorrentBroadcast and BlockRDD. I think this happens to work because the missing ClassTag always happens to be `ClassTag.Any`, but it might be worth looking more carefully at those places to see whether we should be more explicit. Author: Josh Rosen <joshrosen@databricks.com> Closes #11801 from JoshRosen/pick-best-serializer-for-caching.
* [SPARK-14007] [SQL] Manage the memory used by hash map in shuffled hash joinDavies Liu2016-03-211-1/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR try acquire the memory for hash map in shuffled hash join, fail the task if there is no enough memory (otherwise it could OOM the executor). It also removed unused HashedRelation. ## How was this patch tested? Existing unit tests. Manual tests with TPCDS Q78. Author: Davies Liu <davies@databricks.com> Closes #11826 from davies/cleanup_hash2.
* [SPARK-13986][CORE][MLLIB] Remove `DeveloperApi`-annotations for non-publicsDongjoon Hyun2016-03-212-5/+0
| | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Spark uses `DeveloperApi` annotation, but sometimes it seems to conflict with visibility. This PR tries to fix those conflict by removing annotations for non-publics. The following is the example. **JobResult.scala** ```scala DeveloperApi sealed trait JobResult DeveloperApi case object JobSucceeded extends JobResult -DeveloperApi private[spark] case class JobFailed(exception: Exception) extends JobResult ``` ## How was this patch tested? Pass the existing Jenkins test. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11797 from dongjoon-hyun/SPARK-13986.
* [MINOR][DOCS] Add proper periods and spaces for CLI help messages and ↵Dongjoon Hyun2016-03-211-3/+3
| | | | | | | | | | | | | | | | `config` doc. ## What changes were proposed in this pull request? This PR adds some proper periods and spaces to Spark CLI help messages and SQL/YARN conf docs for consistency. ## How was this patch tested? Manual. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11848 from dongjoon-hyun/add_proper_period_and_space.
* [SPARK-14011][CORE][SQL] Enable `LineLength` Java checkstyle ruleDongjoon Hyun2016-03-2120-261/+270
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? [Spark Coding Style Guide](https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide) has 100-character limit on lines, but it's disabled for Java since 11/09/15. This PR enables **LineLength** checkstyle again. To help that, this also introduces **RedundantImport** and **RedundantModifier**, too. The following is the diff on `checkstyle.xml`. ```xml - <!-- TODO: 11/09/15 disabled - the lengths are currently > 100 in many places --> - <!-- <module name="LineLength"> <property name="max" value="100"/> <property name="ignorePattern" value="^package.*|^import.*|a href|href|http://|https://|ftp://"/> </module> - --> <module name="NoLineWrap"/> <module name="EmptyBlock"> <property name="option" value="TEXT"/> -167,5 +164,7 </module> <module name="CommentsIndentation"/> <module name="UnusedImports"/> + <module name="RedundantImport"/> + <module name="RedundantModifier"/> ``` ## How was this patch tested? Currently, `lint-java` is disabled in Jenkins. It needs a manual test. After passing the Jenkins tests, `dev/lint-java` should passes locally. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11831 from dongjoon-hyun/SPARK-14011.
* [SPARK-13958] Executor OOM due to unbounded growth of pointer array in…Sital Kedia2016-03-182-2/+24
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This change fixes the executor OOM which was recently introduced in PR apache/spark#11095 (Please fill in changes proposed in this fix) ## How was this patch tested? Tested by running a spark job on the cluster. (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) … Sorter Author: Sital Kedia <skedia@fb.com> Closes #11794 from sitalkedia/SPARK-13958.
* [SPARK-13885][YARN] Fix attempt id regression for Spark running on Yarnjerryshao2016-03-182-19/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This regression is introduced in #9182, previously attempt id is simply as counter "1" or "2". With the change of #9182, it is changed to full name as "appattemtp-xxx-00001", this will affect all the parts which uses this attempt id, like event log file name, history server app url link. So here change it back to the counter to keep consistent with previous code. Also revert back this patch #11518, this patch fix the url link of history log according to the new way of attempt id, since here we change back to the previous way, so this patch is not necessary, here to revert it. Also clean "spark.yarn.app.id" and "spark.yarn.app.attemptId", since it is useless now. ## How was this patch tested? Test it with unit test and manually test different scenario: 1. application running in yarn-client mode. 2. application running in yarn-cluster mode. 3. application running in yarn-cluster mode with multiple attempts. Checked both the event log file name and url link. CC vanzin tgravescs , please help to review, thanks a lot. Author: jerryshao <sshao@hortonworks.com> Closes #11721 from jerryshao/SPARK-13885.
* [SPARK-13921] Store serialized blocks as multiple chunks in MemoryStoreJosh Rosen2016-03-1713-128/+447
| | | | | | | | | | | | This patch modifies the BlockManager, MemoryStore, and several other storage components so that serialized cached blocks are stored as multiple small chunks rather than as a single contiguous ByteBuffer. This change will help to improve the efficiency of memory allocation and the accuracy of memory accounting when serializing blocks. Our current serialization code uses a ByteBufferOutputStream, which doubles and re-allocates its backing byte array; this increases the peak memory requirements during serialization (since we need to hold extra memory while expanding the array). In addition, we currently don't account for the extra wasted space at the end of the ByteBuffer's backing array, so a 129 megabyte serialized block may actually consume 256 megabytes of memory. After switching to storing blocks in multiple chunks, we'll be able to efficiently trim the backing buffers so that no space is wasted. This change is also a prerequisite to being able to cache blocks which are larger than 2GB (although full support for that depends on several other changes which have not bee implemented yet). Author: Josh Rosen <joshrosen@databricks.com> Closes #11748 from JoshRosen/chunked-block-serialization.
* [SPARK-13776][WEBUI] Limit the max number of acceptors and selectors for JettyShixiong Zhu2016-03-171-1/+16
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? As each acceptor/selector in Jetty will use one thread, the number of threads should at least be the number of acceptors and selectors plus 1. Otherwise, the thread pool of Jetty server may be exhausted by acceptors/selectors and not be able to response any request. To avoid wasting threads, the PR limits the max number of acceptors and selectors and also updates the max thread number if necessary. ## How was this patch tested? Just make sure we don't break any existing tests Author: Shixiong Zhu <shixiong@databricks.com> Closes #11615 from zsxwing/SPARK-13776.
* [SPARK-13928] Move org.apache.spark.Logging into ↵Wenchen Fan2016-03-17165-120/+248
| | | | | | | | | | | | | | | | org.apache.spark.internal.Logging ## What changes were proposed in this pull request? Logging was made private in Spark 2.0. If we move it, then users would be able to create a Logging trait themselves to avoid changing their own code. ## How was this patch tested? existing tests. Author: Wenchen Fan <wenchen@databricks.com> Closes #11764 from cloud-fan/logger.
* [SPARK-13901][CORE] correct the logDebug information when jump to the next ↵trueyao2016-03-171-2/+2
| | | | | | | | | | | locality level JIRA Issue:https://issues.apache.org/jira/browse/SPARK-13901 In getAllowedLocalityLevel method of TaskSetManager,we get wrong logDebug information when jump to the next locality level.So we should fix it. Author: trueyao <501663994@qq.com> Closes #11719 from trueyao/logDebug-localityWait.
* [SPARK-13926] Automatically use Kryo serializer when shuffling RDDs with ↵Josh Rosen2016-03-1618-70/+127
| | | | | | | | | | | | | | simple types Because ClassTags are available when constructing ShuffledRDD we can use them to automatically use Kryo for shuffle serialization when the RDD's types are known to be compatible with Kryo. This patch introduces `SerializerManager`, a component which picks the "best" serializer for a shuffle given the elements' ClassTags. It will automatically pick a Kryo serializer for ShuffledRDDs whose key, value, and/or combiner types are primitives, arrays of primitives, or strings. In the future we can use this class as a narrow extension point to integrate specialized serializers for other types, such as ByteBuffers. In a planned followup patch, I will extend the BlockManager APIs so that we're able to use similar automatic serializer selection when caching RDDs (this is a little trickier because the ClassTags need to be threaded through many more places). Author: Josh Rosen <joshrosen@databricks.com> Closes #11755 from JoshRosen/automatically-pick-best-serializer.
* [SPARK-13281][CORE] Switch broadcast of RDD to exception from warningWesley Tang2016-03-162-6/+9
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In SparkContext, throw Illegalargumentexception when trying to broadcast rdd directly, instead of logging the warning. ## How was this patch tested? mvn clean install Add UT in BroadcastSuite Author: Wesley Tang <tangmingjun@mininglamp.com> Closes #11735 from breakdawn/master.
* [SPARK-13793][CORE] PipedRDD doesn't propagate exceptions while reading ↵Tejas Patil2016-03-162-32/+86
| | | | | | | | | | | | | | | | | | parent RDD ## What changes were proposed in this pull request? PipedRDD creates a child thread to read output of the parent stage and feed it to the pipe process. Used a variable to save the exception thrown in the child thread and then propagating the exception in the main thread if the variable was set. ## How was this patch tested? - Added a unit test - Ran all the existing tests in PipedRDDSuite and they all pass with the change - Tested the patch with a real pipe() job, bounced the executor node which ran the parent stage to simulate a fetch failure and observed that the parent stage was re-ran. Author: Tejas Patil <tejasp@fb.com> Closes #11628 from tejasapatil/pipe_rdd.
* [SPARK-13396] Stop using our internal deprecated .metrics on Exceptio…GayathriMurali2016-03-161-8/+14
| | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-13396 Stop using our internal deprecated .metrics on ExceptionFailure instead use accumUpdates Author: GayathriMurali <gayathri.m.softie@gmail.com> Closes #11544 from GayathriMurali/SPARK-13396.
* [SPARK-13823][SPARK-13397][SPARK-13395][CORE] More warnings, StandardCharset ↵Sean Owen2016-03-1616-32/+37
| | | | | | | | | | | | | | | | | | | | follow up ## What changes were proposed in this pull request? Follow up to https://github.com/apache/spark/pull/11657 - Also update `String.getBytes("UTF-8")` to use `StandardCharsets.UTF_8` - And fix one last new Coverity warning that turned up (use of unguarded `wait()` replaced by simpler/more robust `java.util.concurrent` classes in tests) - And while we're here cleaning up Coverity warnings, just fix about 15 more build warnings ## How was this patch tested? Jenkins tests Author: Sean Owen <sowen@cloudera.com> Closes #11725 from srowen/SPARK-13823.2.
* [SPARK-13906] Ensure that there are at least 2 dispatcher threads.Yonathan Randolph2016-03-161-1/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Force at least two dispatcher-event-loop threads. Since SparkDeploySchedulerBackend (in AppClient) calls askWithRetry to CoarseGrainedScheduler in the same process, there the driver needs at least two dispatcher threads to prevent the dispatcher thread from hanging. ## How was this patch tested? Manual. Author: Yonathan Randolph <yonathangmail.com> Author: Yonathan Randolph <yonathan@liftigniter.com> Closes #11728 from yonran/SPARK-13906.
* [SPARK-13626][CORE] Revert change to SparkConf's constructor.Marcelo Vanzin2016-03-151-1/+1
| | | | | | | | It shouldn't be private. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #11734 from vanzin/SPARK-13626-api.
* [MINOR] a minor fix for the comments of a method in RPC DispatcherCodingCat2016-03-151-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? a minor fix for the comments of a method in RPC Dispatcher ## How was this patch tested? existing unit tests Author: CodingCat <zhunansjtu@gmail.com> Closes #11738 from CodingCat/minor_rpc.
* [SPARK-13803] restore the changes in SPARK-3411CodingCat2016-03-151-4/+17
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch contains the functionality to balance the load of the cluster-mode drivers among workers This patch restores the changes in https://github.com/apache/spark/pull/1106 which was erased due to the merging of https://github.com/apache/spark/pull/731 ## How was this patch tested? test with existing test cases Author: CodingCat <zhunansjtu@gmail.com> Closes #11702 from CodingCat/SPARK-13803.
* [SPARK-13626][CORE] Avoid duplicate config deprecation warnings.Marcelo Vanzin2016-03-144-20/+26
| | | | | | | | | | | | | | | | | | | | | | | | Three different things were needed to get rid of spurious warnings: - silence deprecation warnings when cloning configuration - change the way SparkHadoopUtil instantiates SparkConf to silence warnings - avoid creating new SparkConf instances where it's not needed. On top of that, I changed the way that Logging.scala detects the repl; now it uses a method that is overridden in the repl's Main class, and the hack in Utils.scala is not needed anymore. This makes the 2.11 repl behave like the 2.10 one and set the default log level to WARN, which is a lot better. Previously, this wasn't working because the 2.11 repl triggers log initialization earlier than the 2.10 one. I also removed and simplified some other code in the 2.11 repl's Main to avoid replicating logic that already exists elsewhere in Spark. Tested the 2.11 repl in local and yarn modes. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #11510 from vanzin/SPARK-13626.
* [SPARK-10907][SPARK-6157] Remove pendingUnrollMemory from MemoryStoreJosh Rosen2016-03-143-238/+224
| | | | | | | | | | | | | | | | | This patch refactors the MemoryStore to remove the concept of `pendingUnrollMemory`. It also fixes fixes SPARK-6157: "Unrolling with MEMORY_AND_DISK should always release memory". Key changes: - Inline `MemoryStore.tryToPut` at its three call sites in the `MemoryStore`. - Inline `Memory.unrollSafely` at its only call site (in `MemoryStore.putIterator`). - Inline `MemoryManager.acquireStorageMemory` at its call sites. - Simplify the code as a result of this inlining (some parameters have fixed values after inlining, so lots of branches can be removed). - Remove the `pendingUnrollMemory` map by returning the amount of unrollMemory allocated when returning an iterator after a failed `putIterator` call. - Change `putIterator` to return an instance of `PartiallyUnrolledIterator`, a special iterator subclass which will automatically free the unroll memory of its partially-unrolled elements when the iterator is consumed. To handle cases where the iterator is not consumed (e.g. when a MEMORY_ONLY put fails), `PartiallyUnrolledIterator` exposes a `close()` method which may be called to discard the unrolled values and free their memory. Author: Josh Rosen <joshrosen@databricks.com> Closes #11613 from JoshRosen/cleanup-unroll-memory.
* [SPARK-13054] Always post TaskEnd event for tasksThomas Graves2016-03-142-9/+65
| | | | | | | | | | | | I am using dynamic container allocation and speculation and am seeing issues with the active task accounting. The Executor UI still shows active tasks on the an executor but the job/stage is all completed. I think its also affecting the dynamic allocation being able to release containers because it thinks there are still tasks. There are multiple issues with this: - If the task end for tasks (in this case probably because of speculation) comes in after the stage is finished, then the DAGScheduler.handleTaskCompletion will skip the task completion event Author: Thomas Graves <tgraves@prevailsail.corp.gq1.yahoo.com> Author: Thomas Graves <tgraves@staydecay.corp.gq1.yahoo.com> Author: Tom Graves <tgraves@yahoo-inc.com> Closes #10951 from tgravescs/SPARK-11701.
* [SPARK-12583][MESOS] Mesos shuffle service: Don't delete shuffle files ↵Bertrand Bossy2016-03-143-35/+65
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | before application has stopped ## Problem description: Mesos shuffle service is completely unusable since Spark 1.6.0 . The problem seems to occur since the move from akka to netty in the networking layer. Until now, a connection from the driver to each shuffle service was used as a signal for the shuffle service to determine, whether the driver is still running. Since 1.6.0, this connection is closed after spark.shuffle.io.connectionTimeout (or spark.network.timeout if the former is not set) due to it being idle. The shuffle service interprets this as a signal that the driver has stopped, despite the driver still being alive. Thus, shuffle files are deleted before the application has stopped. ### Context and analysis: spark shuffle fails with mesos after 2mins: https://issues.apache.org/jira/browse/SPARK-12583 External shuffle service broken w/ Mesos: https://issues.apache.org/jira/browse/SPARK-13159 This is a follow up on #11207 . ## What changes were proposed in this pull request? This PR adds a heartbeat signal from the Driver (in MesosExternalShuffleClient) to all registered external mesos shuffle service instances. In MesosExternalShuffleBlockHandler, a thread periodically checks whether a driver has timed out and cleans an application's shuffle files if this is the case. ## How was the this patch tested? This patch has been tested on a small mesos test cluster using the spark-shell. Log output from mesos shuffle service: ``` 16/02/19 15:13:45 INFO mesos.MesosExternalShuffleBlockHandler: Received registration request from app 294def07-3249-4e0f-8d71-bf8c83c58a50-0018 (remote address /xxx.xxx.xxx.xxx:52391, heartbeat timeout 120000 ms). 16/02/19 15:13:47 INFO shuffle.ExternalShuffleBlockResolver: Registered executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=3} with ExecutorShuffleInfo{localDirs=[/foo/blockmgr-c84c0697-a3f9-4f61-9c64-4d3ee227c047], subDirsPerLocalDir=64, shuffleManager=sort} 16/02/19 15:13:47 INFO shuffle.ExternalShuffleBlockResolver: Registered executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=7} with ExecutorShuffleInfo{localDirs=[/foo/blockmgr-bf46497a-de80-47b9-88f9-563123b59e03], subDirsPerLocalDir=64, shuffleManager=sort} 16/02/19 15:16:02 INFO mesos.MesosExternalShuffleBlockHandler: Application 294def07-3249-4e0f-8d71-bf8c83c58a50-0018 timed out. Removing shuffle files. 16/02/19 15:16:02 INFO shuffle.ExternalShuffleBlockResolver: Application 294def07-3249-4e0f-8d71-bf8c83c58a50-0018 removed, cleanupLocalDirs = true 16/02/19 15:16:02 INFO shuffle.ExternalShuffleBlockResolver: Cleaning up executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=3}'s 1 local dirs 16/02/19 15:16:02 INFO shuffle.ExternalShuffleBlockResolver: Cleaning up executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=7}'s 1 local dirs ``` Note: there are 2 executors running on this slave. Author: Bertrand Bossy <bertrand.bossy@teralytics.net> Closes #11272 from bbossy/SPARK-12583-mesos-shuffle-service-heartbeat.
* [SPARK-13848][SPARK-5185] Update to Py4J 0.9.2 in order to fix classloading ↵Josh Rosen2016-03-142-2/+2
| | | | | | | | | | | | | | | | issue This patch upgrades Py4J from 0.9.1 to 0.9.2 in order to include a patch which modifies Py4J to use the current thread's ContextClassLoader when performing reflection / class loading. This is necessary in order to fix [SPARK-5185](https://issues.apache.org/jira/browse/SPARK-5185), a longstanding issue affecting the use of `--jars` and `--packages` in PySpark. In order to demonstrate that the fix works, I removed the workarounds which were added as part of [SPARK-6027](https://issues.apache.org/jira/browse/SPARK-6027) / #4779 and other patches. Py4J diff: https://github.com/bartdag/py4j/compare/0.9.1...0.9.2 /cc zsxwing tdas davies brkyvz Author: Josh Rosen <joshrosen@databricks.com> Closes #11687 from JoshRosen/py4j-0.9.2.
* [SPARK-13833] Guard against race condition when re-caching disk blocks in memoryJosh Rosen2016-03-141-53/+84
| | | | | | | | | | | | When reading data from the DiskStore and attempting to cache it back into the memory store, we should guard against race conditions where multiple readers are attempting to re-cache the same block in memory. This patch accomplishes this by synchronizing on the block's `BlockInfo` object while trying to re-cache a block. (Will file JIRA as soon as ASF JIRA stops being down / laggy). Author: Josh Rosen <joshrosen@databricks.com> Closes #11660 from JoshRosen/concurrent-recaching-fixes.
* [SPARK-13746][TESTS] stop using deprecated SynchronizedSetWilson Wu2016-03-141-16/+25
| | | | | | | | trait SynchronizedSet in package mutable is deprecated Author: Wilson Wu <wilson888888888@gmail.com> Closes #11580 from wilson888888888/spark-synchronizedset.
* [MINOR][DOCS] Fix more typos in comments/strings.Dongjoon Hyun2016-03-1426-36/+36
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes 135 typos over 107 files: * 121 typos in comments * 11 typos in testcase name * 3 typos in log messages ## How was this patch tested? Manual. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11689 from dongjoon-hyun/fix_more_typos.
* [SPARK-13823][CORE][STREAMING][SQL] Always specify Charset in String <-> ↵Sean Owen2016-03-1325-68/+81
| | | | | | | | | | | | | | | | | | | | byte[] conversions (and remaining Coverity items) ## What changes were proposed in this pull request? - Fixes calls to `new String(byte[])` or `String.getBytes()` that rely on platform default encoding, to use UTF-8 - Same for `InputStreamReader` and `OutputStreamWriter` constructors - Standardizes on UTF-8 everywhere - Standardizes specifying the encoding with `StandardCharsets.UTF-8`, not the Guava constant or "UTF-8" (which means handling `UnuspportedEncodingException`) - (also addresses the other remaining Coverity scan issues, which are pretty trivial; these are separated into commit https://github.com/srowen/spark/commit/1deecd8d9ca986d8adb1a42d315890ce5349d29c ) ## How was this patch tested? Jenkins tests Author: Sean Owen <sowen@cloudera.com> Closes #11657 from srowen/SPARK-13823.
* [SPARK-13810][CORE] Add Port Configuration Suggestions on Bind ExceptionsBjorn Jonsson2016-03-131-2/+4
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently, when a java.net.BindException is thrown, it displays the following message: java.net.BindException: Address already in use: Service '$serviceName' failed after 16 retries! This change adds port configuration suggestions to the BindException, for example, for the UI, it now displays java.net.BindException: Address already in use: Service 'SparkUI' failed after 16 retries! Consider explicitly setting the appropriate port for 'SparkUI' (for example spark.ui.port for SparkUI) to an available port or increasing spark.port.maxRetries. ## How was this patch tested? Manual tests Author: Bjorn Jonsson <bjornjon@gmail.com> Closes #11644 from bjornjon/master.
* [SPARK-13830] prefer block manager than direct result for large resultDavies Liu2016-03-111-3/+6
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The current RPC can't handle large blocks very well, it's very slow to fetch 100M block (about 1 minute). Once switch to block manager to fetch that, it took about 10 seconds (still could be improved). ## How was this patch tested? existing unit tests. Author: Davies Liu <davies@databricks.com> Closes #11659 from davies/direct_result.
* [SPARK-13328][CORE] Poor read performance for broadcast variables with ↵Nezih Yigitbasi2016-03-112-15/+116
| | | | | | | | | | dynamic resource allocation When dynamic resource allocation is enabled fetching broadcast variables from removed executors were causing job failures and SPARK-9591 fixed this problem by trying all locations of a block before giving up. However, the locations of a block is retrieved only once from the driver in this process and the locations in this list can be stale due to dynamic resource allocation. This situation gets worse when running on a large cluster as the size of this location list can be in the order of several hundreds out of which there may be tens of stale entries. What we have observed is with the default settings of 3 max retries and 5s between retries (that's 15s per location) the time it takes to read a broadcast variable can be as high as ~17m (70 failed attempts * 15s/attempt) Author: Nezih Yigitbasi <nyigitbasi@netflix.com> Closes #11241 from nezihyigitbasi/SPARK-13328.
* [SPARK-13577][YARN] Allow Spark jar to be multiple jars, archive.Marcelo Vanzin2016-03-112-2/+3
| | | | | | | | | | | | | | | | | | | | | | | | In preparation for the demise of assemblies, this change allows the YARN backend to use multiple jars and globs as the "Spark jar". The config option has been renamed to "spark.yarn.jars" to reflect that. A second option "spark.yarn.archive" was also added; if set, this takes precedence and uploads an archive expected to contain the jar files with the Spark code and its dependencies. Existing deployments should keep working, mostly. This change drops support for the "SPARK_JAR" environment variable, and also does not fall back to using "jarOfClass" if no configuration is set, falling back to finding files under SPARK_HOME instead. This should be fine since "jarOfClass" probably wouldn't work unless you were using spark-submit anyway. Tested with the unit tests, and trying the different config options on a YARN cluster. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #11500 from vanzin/SPARK-13577.
* [MINOR][CORE] Fix a duplicate "and" in a log message.Marcelo Vanzin2016-03-101-1/+1
| | | | | | Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #11642 from vanzin/spark-conf-typo.
* [SPARK-13604][CORE] Sync worker's state after registering with masterShixiong Zhu2016-03-104-5/+90
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Here lists all cases that Master cannot talk with Worker for a while and then network is back. 1. Master doesn't know the network issue (not yet timeout) a. Worker doesn't know the network issue (onDisconnected is not called) - Worker keeps sending Heartbeat. Both Worker and Master don't know the network issue. Nothing to do. (Finally, Master will notice the heartbeat timeout if network is not recovered) b. Worker knows the network issue (onDisconnected is called) - Worker stops sending Heartbeat and sends `RegisterWorker` to master. Master will reply `RegisterWorkerFailed("Duplicate worker ID")`. Worker calls "System.exit(1)" (Finally, Master will notice the heartbeat timeout if network is not recovered) (May leak driver processes. See [SPARK-13602](https://issues.apache.org/jira/browse/SPARK-13602)) 2. Worker timeout (Master knows the network issue). In such case, master removes Worker and its executors and drivers. a. Worker doesn't know the network issue (onDisconnected is not called) - Worker keeps sending Heartbeat. - If the network is back, say Master receives Heartbeat, Master sends `ReconnectWorker` to Worker - Worker send `RegisterWorker` to master. - Master accepts `RegisterWorker` but doesn't know executors and drivers in Worker. (may leak executors) b. Worker knows the network issue (onDisconnected is called) - Worker stop sending `Heartbeat`. Worker will send "RegisterWorker" to master. - Master accepts `RegisterWorker` but doesn't know executors and drivers in Worker. (may leak executors) This PR fixes executors and drivers leak in 2.a and 2.b when Worker reregisters with Master. The approach is making Worker send `WorkerLatestState` to sync the state after registering with master successfully. Then Master will ask Worker to kill unknown executors and drivers. Note: Worker cannot just kill executors after registering with master because in the worker, `LaunchExecutor` and `RegisteredWorker` are processed in two threads. If `LaunchExecutor` happens before `RegisteredWorker`, Worker's executor list will contain new executors after Master accepts `RegisterWorker`. We should not kill these executors. So sending the list to Master and let Master tell Worker which executors should be killed. ## How was this patch tested? test("SPARK-13604: Master should ask Worker kill unknown executors and drivers") Author: Shixiong Zhu <shixiong@databricks.com> Closes #11455 from zsxwing/orphan-executors.
* [SPARK-3854][BUILD] Scala style: require spaces before `{`.Dongjoon Hyun2016-03-109-9/+9
| | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Since the opening curly brace, '{', has many usages as discussed in [SPARK-3854](https://issues.apache.org/jira/browse/SPARK-3854), this PR adds a ScalaStyle rule to prevent '){' pattern for the following majority pattern and fixes the code accordingly. If we enforce this in ScalaStyle from now, it will improve the Scala code quality and reduce review time. ``` // Correct: if (true) { println("Wow!") } // Incorrect: if (true){ println("Wow!") } ``` IntelliJ also shows new warnings based on this. ## How was this patch tested? Pass the Jenkins ScalaStyle test. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11637 from dongjoon-hyun/SPARK-3854.
* [SPARK-13696] Remove BlockStore class & simplify interfaces of mem. & disk ↵Josh Rosen2016-03-1016-611/+528
| | | | | | | | | | | | | | stores Today, both the MemoryStore and DiskStore implement a common `BlockStore` API, but I feel that this API is inappropriate because it abstracts away important distinctions between the behavior of these two stores. For instance, the disk store doesn't have a notion of storing deserialized objects, so it's confusing for it to expose object-based APIs like putIterator() and getValues() instead of only exposing binary APIs and pushing the responsibilities of serialization and deserialization to the client. Similarly, the DiskStore put() methods accepted a `StorageLevel` parameter even though the disk store can only store blocks in one form. As part of a larger BlockManager interface cleanup, this patch remove the BlockStore interface and refines the MemoryStore and DiskStore interfaces to reflect more narrow sets of responsibilities for those components. Some of the benefits of this interface cleanup are reflected in simplifications to several unit tests to eliminate now-unnecessary mocking, significant simplification of the BlockManager's `getLocal()` and `doPut()` methods, and a narrower API between the MemoryStore and DiskStore. Author: Josh Rosen <joshrosen@databricks.com> Closes #11534 from JoshRosen/remove-blockstore-interface.
* [SPARK-13727][CORE] SparkConf.contains does not consider deprecated keysbomeng2016-03-102-1/+18
| | | | | | | | | | | | | | | | | | | | | | The contains() method does not return consistently with get() if the key is deprecated. For example, import org.apache.spark.SparkConf val conf = new SparkConf() conf.set("spark.io.compression.lz4.block.size", "12345") # display some deprecated warning message conf.get("spark.io.compression.lz4.block.size") # return 12345 conf.get("spark.io.compression.lz4.blockSize") # return 12345 conf.contains("spark.io.compression.lz4.block.size") # return true conf.contains("spark.io.compression.lz4.blockSize") # return false The fix will make the contains() and get() more consistent. I've added a test case for this. (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) Unit tests should be sufficient. Author: bomeng <bmeng@us.ibm.com> Closes #11568 from bomeng/SPARK-13727.
* [SPARK-13758][STREAMING][CORE] enhance exception message to avoid misleadingmwws2016-03-101-4/+8
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | We have a recoverable Spark streaming job with checkpoint enabled, it could be executed correctly at first time, but throw following exception when restarted and recovered from checkpoint. ``` org.apache.spark.SparkException: RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(x => rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063. at org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$sc(RDD.scala:87) at org.apache.spark.rdd.RDD.withScope(RDD.scala:352) at org.apache.spark.rdd.RDD.union(RDD.scala:565) at org.apache.spark.streaming.Repo$$anonfun$createContext$1.apply(Repo.scala:23) at org.apache.spark.streaming.Repo$$anonfun$createContext$1.apply(Repo.scala:19) at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627) ``` According to exception, it shows I invoked transformations and actions in other transformations, but I did not. The real reason is that I used external RDD in DStream operation. External RDD data is not stored in checkpoint, so that during recovering, the initial value of _sc in this RDD is assigned to null and hit above exception. But you can find the error message is misleading, it indicates nothing about the real issue Here is the code to reproduce it. ```scala object Repo { def createContext(ip: String, port: Int, checkpointDirectory: String):StreamingContext = { println("Creating new context") val sparkConf = new SparkConf().setAppName("Repo").setMaster("local[2]") val ssc = new StreamingContext(sparkConf, Seconds(2)) ssc.checkpoint(checkpointDirectory) var cached = ssc.sparkContext.parallelize(Seq("apple, banana")) val words = ssc.socketTextStream(ip, port).flatMap(_.split(" ")) words.foreachRDD((rdd: RDD[String]) => { val res = rdd.map(word => (word, word.length)).collect() println("words: " + res.mkString(", ")) cached = cached.union(rdd) cached.checkpoint() println("cached words: " + cached.collect.mkString(", ")) }) ssc } def main(args: Array[String]) { val ip = "localhost" val port = 9999 val dir = "/home/maowei/tmp" val ssc = StreamingContext.getOrCreate(dir, () => { createContext(ip, port, dir) }) ssc.start() ssc.awaitTermination() } } ``` Author: mwws <wei.mao@intel.com> Closes #11595 from mwws/SPARK-MissleadingLog.
* [SPARK-13492][MESOS] Configurable Mesos framework webui URL.Sergiusz Urbaniak2016-03-098-10/+77
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Previously the Mesos framework webui URL was being derived only from the Spark UI address leaving no possibility to configure it. This commit makes it configurable. If unset it falls back to the previous behavior. Motivation: This change is necessary in order to be able to install Spark on DCOS and to be able to give it a custom service link. The configured `webui_url` is configured to point to a reverse proxy in the DCOS environment. ## How was this patch tested? Locally, using unit tests and on DCOS testing and stable revision. Author: Sergiusz Urbaniak <sur@mesosphere.io> Closes #11369 from s-urbaniak/sur-webui-url.
* [SPARK-13775] History page sorted by completed time desc by default.zhuol2016-03-091-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Originally the page is sorted by AppID by default. After tests with users' feedback, we think it might be best to sort by completed time (desc). ## How was this patch tested? Manually test, with screenshot as follows. ![sorted-by-complete-time-desc](https://cloud.githubusercontent.com/assets/11683054/13647686/d6dea924-e5fa-11e5-8fc5-68e039b74b6f.png) Author: zhuol <zhuol@yahoo-inc.com> Closes #11608 from zhuoliu/13775.
* [SPARK-13778][CORE] Set the executor state for a worker when removing itShixiong Zhu2016-03-091-0/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When a worker is lost, the executors on this worker are also lost. But Master's ApplicationPage still displays their states as running. This patch just sets the executor state to `LOST` when a worker is lost. ## How was this patch tested? manual tests Author: Shixiong Zhu <shixiong@databricks.com> Closes #11609 from zsxwing/SPARK-13778.
* [SPARK-13747][SQL] Fix concurrent query with fork-join poolAndrew Or2016-03-091-1/+6
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fix this use case, which was already fixed in SPARK-10548 in 1.6 but was broken in master due to #9264: ``` (1 to 100).par.foreach { _ => sc.parallelize(1 to 5).map { i => (i, i) }.toDF("a", "b").count() } ``` This threw `IllegalArgumentException` consistently before this patch. For more detail, see the JIRA. ## How was this patch tested? New test in `SQLExecutionSuite`. Author: Andrew Or <andrew@databricks.com> Closes #11586 from andrewor14/fix-concurrent-sql.
* [SPARK-13769][CORE] Update Java Doc in Spark SubmitAhmed Kamal2016-03-091-1/+1
| | | | | | | | | | | JIRA : https://issues.apache.org/jira/browse/SPARK-13769 The java doc here (https://github.com/apache/spark/blob/e97fc7f176f8bf501c9b3afd8410014e3b0e1602/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L51) needs to be updated from "The latter two operations are currently supported only for standalone cluster mode." to "The latter two operations are currently supported only for standalone and mesos cluster modes." Author: Ahmed Kamal <ahmed.kamal@badrit.com> Closes #11600 from AhmedKamal/SPARK-13769.
* [SPARK-13702][CORE][SQL][MLLIB] Use diamond operator for generic instance ↵Dongjoon Hyun2016-03-097-20/+17
| | | | | | | | | | | | | | | | | | | | | | | | | creation in Java code. ## What changes were proposed in this pull request? In order to make `docs/examples` (and other related code) more simple/readable/user-friendly, this PR replaces existing codes like the followings by using `diamond` operator. ``` - final ArrayList<Product2<Object, Object>> dataToWrite = - new ArrayList<Product2<Object, Object>>(); + final ArrayList<Product2<Object, Object>> dataToWrite = new ArrayList<>(); ``` Java 7 or higher supports **diamond** operator which replaces the type arguments required to invoke the constructor of a generic class with an empty set of type parameters (<>). Currently, Spark Java code use mixed usage of this. ## How was this patch tested? Manual. Pass the existing tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11541 from dongjoon-hyun/SPARK-13702.
* [SPARK-13631][CORE] Thread-safe getLocationsWithLargestOutputsAndy Sloane2016-03-091-23/+29
| | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? If a job is being scheduled in one thread which has a dependency on an RDD currently executing a shuffle in another thread, Spark would throw a NullPointerException. This patch synchronizes access to `mapStatuses` and skips null status entries (which are in-progress shuffle tasks). ## How was this patch tested? Our client code unit test suite, which was reliably reproducing the race condition with 10 threads, shows that this fixes it. I have not found a minimal test case to add to Spark, but I will attempt to do so if desired. The same test case was tripping up on SPARK-4454, which was fixed by making other DAGScheduler code thread-safe. shivaram srowen Author: Andy Sloane <asloane@tetrationanalytics.com> Closes #11505 from a1k0n/SPARK-13631.
* [SPARK-13692][CORE][SQL] Fix trivial Coverity/Checkstyle defectsDongjoon Hyun2016-03-092-3/+3
| | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This issue fixes the following potential bugs and Java coding style detected by Coverity and Checkstyle. - Implement both null and type checking in equals functions. - Fix wrong type casting logic in SimpleJavaBean2.equals. - Add `implement Cloneable` to `UTF8String` and `SortedIterator`. - Remove dereferencing before null check in `AbstractBytesToBytesMapSuite`. - Fix coding style: Add '{}' to single `for` statement in mllib examples. - Remove unused imports in `ColumnarBatch` and `JavaKinesisStreamSuite`. - Remove unused fields in `ChunkFetchIntegrationSuite`. - Add `stop()` to prevent resource leak. Please note that the last two checkstyle errors exist on newly added commits after [SPARK-13583](https://issues.apache.org/jira/browse/SPARK-13583). ## How was this patch tested? manual via `./dev/lint-java` and Coverity site. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11530 from dongjoon-hyun/SPARK-13692.
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