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* [SPARK-17816][CORE] Fix ConcurrentModificationException issue in ↵Ergin Seyfe2016-10-103-42/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | BlockStatusesAccumulator ## What changes were proposed in this pull request? Change the BlockStatusesAccumulator to return immutable object when value method is called. ## How was this patch tested? Existing tests plus I verified this change by running a pipeline which consistently repro this issue. This is the stack trace for this exception: ` java.util.ConcurrentModificationException at java.util.ArrayList$Itr.checkForComodification(ArrayList.java:901) at java.util.ArrayList$Itr.next(ArrayList.java:851) at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:43) at scala.collection.Iterator$class.foreach(Iterator.scala:893) at scala.collection.AbstractIterator.foreach(Iterator.scala:1336) at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) at scala.collection.AbstractIterable.foreach(Iterable.scala:54) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ListBuffer.$plus$plus$eq(ListBuffer.scala:183) at scala.collection.mutable.ListBuffer.$plus$plus$eq(ListBuffer.scala:45) at scala.collection.TraversableLike$class.to(TraversableLike.scala:590) at scala.collection.AbstractTraversable.to(Traversable.scala:104) at scala.collection.TraversableOnce$class.toList(TraversableOnce.scala:294) at scala.collection.AbstractTraversable.toList(Traversable.scala:104) at org.apache.spark.util.JsonProtocol$.accumValueToJson(JsonProtocol.scala:314) at org.apache.spark.util.JsonProtocol$$anonfun$accumulableInfoToJson$5.apply(JsonProtocol.scala:291) at org.apache.spark.util.JsonProtocol$$anonfun$accumulableInfoToJson$5.apply(JsonProtocol.scala:291) at scala.Option.map(Option.scala:146) at org.apache.spark.util.JsonProtocol$.accumulableInfoToJson(JsonProtocol.scala:291) at org.apache.spark.util.JsonProtocol$$anonfun$taskInfoToJson$12.apply(JsonProtocol.scala:283) at org.apache.spark.util.JsonProtocol$$anonfun$taskInfoToJson$12.apply(JsonProtocol.scala:283) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.immutable.List.foreach(List.scala:381) at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35) at scala.collection.mutable.ListBuffer.foreach(ListBuffer.scala:45) at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) at scala.collection.AbstractTraversable.map(Traversable.scala:104) at org.apache.spark.util.JsonProtocol$.taskInfoToJson(JsonProtocol.scala:283) at org.apache.spark.util.JsonProtocol$.taskEndToJson(JsonProtocol.scala:145) at org.apache.spark.util.JsonProtocol$.sparkEventToJson(JsonProtocol.scala:76) ` Author: Ergin Seyfe <eseyfe@fb.com> Closes #15371 from seyfe/race_cond_jsonprotocal.
* [SPARK-17417][CORE] Fix # of partitions for Reliable RDD checkpointingDhruve Ashar2016-10-101-2/+2
| | | | | | | | | | | | ## What changes were proposed in this pull request? Currently the no. of partition files are limited to 10000 files (%05d format). If there are more than 10000 part files, the logic goes for a toss while recreating the RDD as it sorts them by string. More details can be found in the JIRA desc [here](https://issues.apache.org/jira/browse/SPARK-17417). ## How was this patch tested? I tested this patch by checkpointing a RDD and then manually renaming part files to the old format and tried to access the RDD. It was successfully created from the old format. Also verified loading a sample parquet file and saving it as multiple formats - CSV, JSON, Text, Parquet, ORC and read them successfully back from the saved files. I couldn't launch the unit test from my local box, so will wait for the Jenkins output. Author: Dhruve Ashar <dhruveashar@gmail.com> Closes #15370 from dhruve/bug/SPARK-17417.
* [SPARK-17338][SQL] add global temp viewWenchen Fan2016-10-101-0/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Global temporary view is a cross-session temporary view, which means it's shared among all sessions. Its lifetime is the lifetime of the Spark application, i.e. it will be automatically dropped when the application terminates. It's tied to a system preserved database `global_temp`(configurable via SparkConf), and we must use the qualified name to refer a global temp view, e.g. SELECT * FROM global_temp.view1. changes for `SessionCatalog`: 1. add a new field `gloabalTempViews: GlobalTempViewManager`, to access the shared global temp views, and the global temp db name. 2. `createDatabase` will fail if users wanna create `global_temp`, which is system preserved. 3. `setCurrentDatabase` will fail if users wanna set `global_temp`, which is system preserved. 4. add `createGlobalTempView`, which is used in `CreateViewCommand` to create global temp views. 5. add `dropGlobalTempView`, which is used in `CatalogImpl` to drop global temp view. 6. add `alterTempViewDefinition`, which is used in `AlterViewAsCommand` to update the view definition for local/global temp views. 7. `renameTable`/`dropTable`/`isTemporaryTable`/`lookupRelation`/`getTempViewOrPermanentTableMetadata`/`refreshTable` will handle global temp views. changes for SQL commands: 1. `CreateViewCommand`/`AlterViewAsCommand` is updated to support global temp views 2. `ShowTablesCommand` outputs a new column `database`, which is used to distinguish global and local temp views. 3. other commands can also handle global temp views if they call `SessionCatalog` APIs which accepts global temp views, e.g. `DropTableCommand`, `AlterTableRenameCommand`, `ShowColumnsCommand`, etc. changes for other public API 1. add a new method `dropGlobalTempView` in `Catalog` 2. `Catalog.findTable` can find global temp view 3. add a new method `createGlobalTempView` in `Dataset` ## How was this patch tested? new tests in `SQLViewSuite` Author: Wenchen Fan <wenchen@databricks.com> Closes #14897 from cloud-fan/global-temp-view.
* [MINOR][SQL] Use resource path for test_script.shWeiqing Yang2016-10-083-4/+16
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR modified the test case `test("script")` to use resource path for `test_script.sh`. Make the test case portable (even in IntelliJ). ## How was this patch tested? Passed the test case. Before: Run `test("script")` in IntelliJ: ``` Caused by: org.apache.spark.SparkException: Subprocess exited with status 127. Error: bash: src/test/resources/test_script.sh: No such file or directory ``` After: Test passed. Author: Weiqing Yang <yangweiqing001@gmail.com> Closes #15246 from weiqingy/hivetest.
* [SPARK-17768][CORE] Small (Sum,Count,Mean)Evaluator problems and suboptimalitiesSean Owen2016-10-0810-332/+203
| | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fix: - GroupedMeanEvaluator and GroupedSumEvaluator are unused, as is the StudentTCacher support class - CountEvaluator can return a lower bound < 0, when counts can't be negative - MeanEvaluator will actually fail on exactly 1 datum (yields t-test with 0 DOF) - CountEvaluator uses a normal distribution, which may be an inappropriate approximation (leading to above) - Test for SumEvaluator asserts incorrect expected sums – e.g. after observing 10% of data has sum of 2, expectation should be 20, not 38 - CountEvaluator, MeanEvaluator have no unit tests to catch these - Duplication of distribution code across CountEvaluator, GroupedCountEvaluator - The stats in each could use a bit of documentation as I had to guess at them - (Code could use a few cleanups and optimizations too) ## How was this patch tested? Existing and new tests Author: Sean Owen <sowen@cloudera.com> Closes #15341 from srowen/SPARK-17768.
* [SPARK-17793][WEB UI] Sorting on the description on the Job or Stage page ↵Alex Bozarth2016-10-084-188/+49
| | | | | | | | | | | | | | | | | | | | | | | doesn’t always work ## What changes were proposed in this pull request? Added secondary sorting on stage name for the description column. This provide a clearer behavior in the common case where the Description column only comprises of Stage names instead of the option description value. ## How was this patch tested? manual testing and dev/run-tests Screenshots of sorting on both description and stage name as well as an example of both: ![screen shot 2016-10-04 at 1 09 39 pm](https://cloud.githubusercontent.com/assets/13952758/19135523/067b042e-8b1a-11e6-912e-e6371d006d21.png) ![screen shot 2016-10-04 at 1 09 51 pm](https://cloud.githubusercontent.com/assets/13952758/19135526/06960936-8b1a-11e6-85e9-8aaf694c5f7b.png) ![screen shot 2016-10-05 at 1 14 45 pm](https://cloud.githubusercontent.com/assets/13952758/19135525/069547da-8b1a-11e6-8692-6524c75c4c07.png) ![screen shot 2016-10-05 at 1 14 51 pm](https://cloud.githubusercontent.com/assets/13952758/19135524/0694b4d2-8b1a-11e6-92dc-c8aa514e4f62.png) ![screen shot 2016-10-05 at 4 42 52 pm](https://cloud.githubusercontent.com/assets/13952758/19135618/e232eafe-8b1a-11e6-88b3-ff0bbb26b7f8.png) Author: Alex Bozarth <ajbozart@us.ibm.com> Closes #15366 from ajbozarth/spark17793.
* [SPARK-17707][WEBUI] Web UI prevents spark-submit application to be finishedSean Owen2016-10-072-6/+22
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This expands calls to Jetty's simple `ServerConnector` constructor to explicitly specify a `ScheduledExecutorScheduler` that makes daemon threads. It should otherwise result in exactly the same configuration, because the other args are copied from the constructor that is currently called. (I'm not sure we should change the Hive Thriftserver impl, but I did anyway.) This also adds `sc.stop()` to the quick start guide example. ## How was this patch tested? Existing tests; _pending_ at least manual verification of the fix. Author: Sean Owen <sowen@cloudera.com> Closes #15381 from srowen/SPARK-17707.
* [SPARK-16827] Stop reporting spill metrics as shuffle metricsBrian Cho2016-10-071-1/+3
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fix a bug where spill metrics were being reported as shuffle metrics. Eventually these spill metrics should be reported (SPARK-3577), but separate from shuffle metrics. The fix itself basically reverts the line to what it was in 1.6. ## How was this patch tested? Tested on a job that was reporting shuffle writes even for the final stage, when no shuffle writes should take place. After the change the job no longer shows these writes. Before: ![screen shot 2016-10-03 at 6 39 59 pm](https://cloud.githubusercontent.com/assets/1514239/19085897/dbf59a92-8a20-11e6-9f68-a978860c0d74.png) After: <img width="1052" alt="screen shot 2016-10-03 at 11 44 44 pm" src="https://cloud.githubusercontent.com/assets/1514239/19085903/e173a860-8a20-11e6-85e3-d47f9835f494.png"> Author: Brian Cho <bcho@fb.com> Closes #15347 from dafrista/shuffle-metrics.
* [SPARK-17795][WEB UI] Sorting on stage or job tables doesn’t reload page ↵Alex Bozarth2016-10-075-23/+42
| | | | | | | | | | | | | | | | | | on that table ## What changes were proposed in this pull request? Added anchor on table header id to sorting links on job and stage tables. This make the page reload after a sort load the page at the sorted table. This only changes page load behavior so no UI changes ## How was this patch tested? manually tested and dev/run-tests Author: Alex Bozarth <ajbozart@us.ibm.com> Closes #15369 from ajbozarth/spark17795.
* [SPARK-17346][SQL] Add Kafka source for Structured StreamingShixiong Zhu2016-10-051-7/+0
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR adds a new project ` external/kafka-0-10-sql` for Structured Streaming Kafka source. It's based on the design doc: https://docs.google.com/document/d/19t2rWe51x7tq2e5AOfrsM9qb8_m7BRuv9fel9i0PqR8/edit?usp=sharing tdas did most of work and part of them was inspired by koeninger's work. ### Introduction The Kafka source is a structured streaming data source to poll data from Kafka. The schema of reading data is as follows: Column | Type ---- | ---- key | binary value | binary topic | string partition | int offset | long timestamp | long timestampType | int The source can deal with deleting topics. However, the user should make sure there is no Spark job processing the data when deleting a topic. ### Configuration The user can use `DataStreamReader.option` to set the following configurations. Kafka Source's options | value | default | meaning ------ | ------- | ------ | ----- startingOffset | ["earliest", "latest"] | "latest" | The start point when a query is started, either "earliest" which is from the earliest offset, or "latest" which is just from the latest offset. Note: This only applies when a new Streaming query is started, and that resuming will always pick up from where the query left off. failOnDataLost | [true, false] | true | Whether to fail the query when it's possible that data is lost (e.g., topics are deleted, or offsets are out of range). This may be a false alarm. You can disable it when it doesn't work as you expected. subscribe | A comma-separated list of topics | (none) | The topic list to subscribe. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source. subscribePattern | Java regex string | (none) | The pattern used to subscribe the topic. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source. kafka.consumer.poll.timeoutMs | long | 512 | The timeout in milliseconds to poll data from Kafka in executors fetchOffset.numRetries | int | 3 | Number of times to retry before giving up fatch Kafka latest offsets. fetchOffset.retryIntervalMs | long | 10 | milliseconds to wait before retrying to fetch Kafka offsets Kafka's own configurations can be set via `DataStreamReader.option` with `kafka.` prefix, e.g, `stream.option("kafka.bootstrap.servers", "host:port")` ### Usage * Subscribe to 1 topic ```Scala spark .readStream .format("kafka") .option("kafka.bootstrap.servers", "host:port") .option("subscribe", "topic1") .load() ``` * Subscribe to multiple topics ```Scala spark .readStream .format("kafka") .option("kafka.bootstrap.servers", "host:port") .option("subscribe", "topic1,topic2") .load() ``` * Subscribe to a pattern ```Scala spark .readStream .format("kafka") .option("kafka.bootstrap.servers", "host:port") .option("subscribePattern", "topic.*") .load() ``` ## How was this patch tested? The new unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Author: Tathagata Das <tathagata.das1565@gmail.com> Author: Shixiong Zhu <zsxwing@gmail.com> Author: cody koeninger <cody@koeninger.org> Closes #15102 from zsxwing/kafka-source.
* [SPARK-17778][TESTS] Mock SparkContext to reduce memory usage of ↵Shixiong Zhu2016-10-051-1/+4
| | | | | | | | | | | | | | | | BlockManagerSuite ## What changes were proposed in this pull request? Mock SparkContext to reduce memory usage of BlockManagerSuite ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #15350 from zsxwing/SPARK-17778.
* [SPARK-16962][CORE][SQL] Fix misaligned record accesses for SPARC architecturessumansomasundar2016-10-043-38/+52
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Made changes to record length offsets to make them uniform throughout various areas of Spark core and unsafe ## How was this patch tested? This change affects only SPARC architectures and was tested on X86 architectures as well for regression. Author: sumansomasundar <suman.somasundar@oracle.com> Closes #14762 from sumansomasundar/master.
* [SPARK-17671][WEBUI] Spark 2.0 history server summary page is slow even set ↵Sean Owen2016-10-046-35/+20
| | | | | | | | | | | | | | | | | | spark.history.ui.maxApplications ## What changes were proposed in this pull request? Return Iterator of applications internally in history server, for consistency and performance. See https://github.com/apache/spark/pull/15248 for some back-story. The code called by and calling HistoryServer.getApplicationList wants an Iterator, but this method materializes an Iterable, which potentially causes a performance problem. It's simpler too to make this internal method also pass through an Iterator. ## How was this patch tested? Existing tests. Author: Sean Owen <sowen@cloudera.com> Closes #15321 from srowen/SPARK-17671.
* [SPARK-14914][CORE][SQL] Skip/fix some test cases on Windows due to ↵Tao LI2016-10-024-11/+14
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | limitation of Windows ## What changes were proposed in this pull request? This PR proposes to fix/skip some tests failed on Windows. This PR takes over https://github.com/apache/spark/pull/12696. **Before** - **SparkSubmitSuite** ``` [info] - launch simple application with spark-submit *** FAILED *** (202 milliseconds) [info] java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specifie [info] - includes jars passed in through --jars *** FAILED *** (1 second, 625 milliseconds) [info] java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified ``` - **DiskStoreSuite** ``` [info] - reads of memory-mapped and non memory-mapped files are equivalent *** FAILED *** (1 second, 78 milliseconds) [info] diskStoreMapped.remove(blockId) was false (DiskStoreSuite.scala:41) ``` **After** - **SparkSubmitSuite** ``` [info] - launch simple application with spark-submit (578 milliseconds) [info] - includes jars passed in through --jars (1 second, 875 milliseconds) ``` - **DiskStoreSuite** ``` [info] DiskStoreSuite: [info] - reads of memory-mapped and non memory-mapped files are equivalent !!! CANCELED !!! (766 milliseconds ``` For `CreateTableAsSelectSuite` and `FsHistoryProviderSuite`, I could not reproduce as the Java version seems higher than the one that has the bugs about `setReadable(..)` and `setWritable(...)` but as they are bugs reported clearly, it'd be sensible to skip those. We should revert the changes for both back as soon as we drop the support of Java 7. ## How was this patch tested? Manually tested via AppVeyor. Closes #12696 Author: Tao LI <tl@microsoft.com> Author: U-FAREAST\tl <tl@microsoft.com> Author: hyukjinkwon <gurwls223@gmail.com> Closes #15320 from HyukjinKwon/SPARK-14914.
* [SPARK-17740] Spark tests should mock / interpose HDFS to ensure that ↵Eric Liang2016-09-302-3/+128
| | | | | | | | | | | | | | | | | | | streams are closed ## What changes were proposed in this pull request? As a followup to SPARK-17666, ensure filesystem connections are not leaked at least in unit tests. This is done here by intercepting filesystem calls as suggested by JoshRosen . At the end of each test, we assert no filesystem streams are left open. This applies to all tests using SharedSQLContext or SharedSparkContext. ## How was this patch tested? I verified that tests in sql and core are indeed using the filesystem backend, and fixed the detected leaks. I also checked that reverting https://github.com/apache/spark/pull/15245 causes many actual test failures due to connection leaks. Author: Eric Liang <ekl@databricks.com> Author: Eric Liang <ekhliang@gmail.com> Closes #15306 from ericl/sc-4672.
* [SPARK-15353][CORE] Making peer selection for block replication pluggableShubham Chopra2016-09-309-99/+492
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR makes block replication strategies pluggable. It provides two trait that can be implemented, one that maps a host to its topology and is used in the master, and the second that helps prioritize a list of peers for block replication and would run in the executors. This patch contains default implementations of these traits that make sure current Spark behavior is unchanged. ## How was this patch tested? This patch should not change Spark behavior in any way, and was tested with unit tests for storage. Author: Shubham Chopra <schopra31@bloomberg.net> Closes #13152 from shubhamchopra/RackAwareBlockReplication.
* [SPARK-17676][CORE] FsHistoryProvider should ignore hidden filesImran Rashid2016-09-292-3/+40
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? FsHistoryProvider was writing a hidden file (to check the fs's clock). Even though it deleted the file immediately, sometimes another thread would try to scan the files on the fs in-between, and then there would be an error msg logged which was very misleading for the end-user. (The logged error was harmless, though.) ## How was this patch tested? I added one unit test, but to be clear, that test was passing before. The actual change in behavior in that test is just logging (after the change, there is no more logged error), which I just manually verified. Author: Imran Rashid <irashid@cloudera.com> Closes #15250 from squito/SPARK-17676.
* [SPARK-17715][SCHEDULER] Make task launch logs DEBUGBrian Cho2016-09-291-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Ramp down the task launch logs from INFO to DEBUG. Task launches can happen orders of magnitude more than executor registration so it makes the logs easier to handle if they are different log levels. For larger jobs, there can be 100,000s of task launches which makes the driver log huge. ## How was this patch tested? No tests, as this is a trivial change. Author: Brian Cho <bcho@fb.com> Closes #15290 from dafrista/ramp-down-task-logging.
* [SPARK-17672] Spark 2.0 history server web Ui takes too long for a single ↵Gang Wu2016-09-296-1/+19
| | | | | | | | | | | | | | application Added a new API getApplicationInfo(appId: String) in class ApplicationHistoryProvider and class SparkUI to get app info. In this change, FsHistoryProvider can directly fetch one app info in O(1) time complexity compared to O(n) before the change which used an Iterator.find() interface. Both ApplicationCache and OneApplicationResource classes adopt this new api. manual tests Author: Gang Wu <wgtmac@uber.com> Closes #15247 from wgtmac/SPARK-17671.
* [SPARK-17648][CORE] TaskScheduler really needs offers to be an IndexedSeqImran Rashid2016-09-295-25/+24
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The Seq[WorkerOffer] is accessed by index, so it really should be an IndexedSeq, otherwise an O(n) operation becomes O(n^2). In practice this hasn't been an issue b/c where these offers are generated, the call to `.toSeq` just happens to create an IndexedSeq anyway.I got bitten by this in performance tests I was doing, and its better for the types to be more precise so eg. a change in Scala doesn't destroy performance. ## How was this patch tested? Unit tests via jenkins. Author: Imran Rashid <irashid@cloudera.com> Closes #15221 from squito/SPARK-17648.
* [SPARK-17710][HOTFIX] Fix ClassCircularityError in ReplSuite tests in Maven ↵Weiqing Yang2016-09-281-2/+4
| | | | | | | | | | | | | | | | | | | | | | | | | build: use 'Class.forName' instead of 'Utils.classForName' ## What changes were proposed in this pull request? Fix ClassCircularityError in ReplSuite tests when Spark is built by Maven build. ## How was this patch tested? (1) ``` build/mvn -DskipTests -Phadoop-2.3 -Pyarn -Phive -Phive-thriftserver -Pkinesis-asl -Pmesos clean package ``` Then test: ``` build/mvn -Dtest=none -DwildcardSuites=org.apache.spark.repl.ReplSuite test ``` ReplSuite tests passed (2) Manual Tests against some Spark applications in Yarn client mode and Yarn cluster mode. Need to check if spark caller contexts are written into HDFS hdfs-audit.log and Yarn RM audit log successfully. Author: Weiqing Yang <yangweiqing001@gmail.com> Closes #15286 from Sherry302/SPARK-16757.
* [SPARK-17644][CORE] Do not add failedStages when abortStage for fetch failurew002289702016-09-282-12/+70
| | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? | Time |Thread 1 , Job1 | Thread 2 , Job2 | |:-------------:|:-------------:|:-----:| | 1 | abort stage due to FetchFailed | | | 2 | failedStages += failedStage | | | 3 | | task failed due to FetchFailed | | 4 | | can not post ResubmitFailedStages because failedStages is not empty | Then job2 of thread2 never resubmit the failed stage and hang. We should not add the failedStages when abortStage for fetch failure ## How was this patch tested? added unit test Author: w00228970 <wangfei1@huawei.com> Author: wangfei <wangfei_hello@126.com> Closes #15213 from scwf/dag-resubmit.
* [SPARK-17056][CORE] Fix a wrong assert regarding unroll memory in MemoryStoreLiang-Chi Hsieh2016-09-271-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? There is an assert in MemoryStore's putIteratorAsValues method which is used to check if unroll memory is not released too much. This assert looks wrong. ## How was this patch tested? Jenkins tests. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Closes #14642 from viirya/fix-unroll-memory.
* [SPARK-16757] Set up Spark caller context to HDFS and YARNWeiqing Yang2016-09-276-9/+116
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? 1. Pass `jobId` to Task. 2. Invoke Hadoop APIs. * A new function `setCallerContext` is added in `Utils`. `setCallerContext` function invokes APIs of `org.apache.hadoop.ipc.CallerContext` to set up spark caller contexts, which will be written into `hdfs-audit.log` and Yarn RM audit log. * For HDFS: Spark sets up its caller context by invoking`org.apache.hadoop.ipc.CallerContext` in `Task` and Yarn `Client` and `ApplicationMaster`. * For Yarn: Spark sets up its caller context by invoking `org.apache.hadoop.ipc.CallerContext` in Yarn `Client`. ## How was this patch tested? Manual Tests against some Spark applications in Yarn client mode and Yarn cluster mode. Need to check if spark caller contexts are written into HDFS hdfs-audit.log and Yarn RM audit log successfully. For example, run SparkKmeans in Yarn client mode: ``` ./bin/spark-submit --verbose --executor-cores 3 --num-executors 1 --master yarn --deploy-mode client --class org.apache.spark.examples.SparkKMeans examples/target/original-spark-examples_2.11-2.1.0-SNAPSHOT.jar hdfs://localhost:9000/lr_big.txt 2 5 ``` **Before**: There will be no Spark caller context in records of `hdfs-audit.log` and Yarn RM audit log. **After**: Spark caller contexts will be written in records of `hdfs-audit.log` and Yarn RM audit log. These are records in `hdfs-audit.log`: ``` 2016-09-20 11:54:24,116 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_CLIENT_AppId_application_1474394339641_0005 2016-09-20 11:54:28,164 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0005_JobId_0_StageId_0_AttemptId_0_TaskId_2_AttemptNum_0 2016-09-20 11:54:28,164 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0005_JobId_0_StageId_0_AttemptId_0_TaskId_1_AttemptNum_0 2016-09-20 11:54:28,164 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0005_JobId_0_StageId_0_AttemptId_0_TaskId_0_AttemptNum_0 ``` ``` 2016-09-20 11:59:33,868 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=mkdirs src=/private/tmp/hadoop-wyang/nm-local-dir/usercache/wyang/appcache/application_1474394339641_0006/container_1474394339641_0006_01_000001/spark-warehouse dst=null perm=wyang:supergroup:rwxr-xr-x proto=rpc callerContext=SPARK_APPLICATION_MASTER_AppId_application_1474394339641_0006_AttemptId_1 2016-09-20 11:59:37,214 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0006_AttemptId_1_JobId_0_StageId_0_AttemptId_0_TaskId_1_AttemptNum_0 2016-09-20 11:59:37,215 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0006_AttemptId_1_JobId_0_StageId_0_AttemptId_0_TaskId_2_AttemptNum_0 2016-09-20 11:59:37,215 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0006_AttemptId_1_JobId_0_StageId_0_AttemptId_0_TaskId_0_AttemptNum_0 2016-09-20 11:59:42,391 INFO FSNamesystem.audit: allowed=true ugi=wyang (auth:SIMPLE) ip=/127.0.0.1 cmd=open src=/lr_big.txt dst=null perm=null proto=rpc callerContext=SPARK_TASK_AppId_application_1474394339641_0006_AttemptId_1_JobId_0_StageId_0_AttemptId_0_TaskId_3_AttemptNum_0 ``` This is a record in Yarn RM log: ``` 2016-09-20 11:59:24,050 INFO org.apache.hadoop.yarn.server.resourcemanager.RMAuditLogger: USER=wyang IP=127.0.0.1 OPERATION=Submit Application Request TARGET=ClientRMService RESULT=SUCCESS APPID=application_1474394339641_0006 CALLERCONTEXT=SPARK_CLIENT_AppId_application_1474394339641_0006 ``` Author: Weiqing Yang <yangweiqing001@gmail.com> Closes #14659 from Sherry302/callercontextSubmit.
* Fix two comments since Actor is not used anymore.Ding Fei2016-09-262-2/+3
| | | | | | | | | | ## What changes were proposed in this pull request? Fix two comments since Actor is not used anymore. Author: Ding Fei <danis@danix> Closes #15251 from danix800/comment-fixing.
* [SPARK-17649][CORE] Log how many Spark events got dropped in LiveListenerBusShixiong Zhu2016-09-261-1/+25
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Log how many Spark events got dropped in LiveListenerBus so that the user can get insights on how to set a correct event queue size. ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #15220 from zsxwing/SPARK-17649.
* [SPARK-17650] malformed url's throw exceptions before bricking ExecutorsBurak Yavuz2016-09-253-7/+51
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When a malformed URL was sent to Executors through `sc.addJar` and `sc.addFile`, the executors become unusable, because they constantly throw `MalformedURLException`s and can never acknowledge that the file or jar is just bad input. This PR tries to fix that problem by making sure MalformedURLs can never be submitted through `sc.addJar` and `sc.addFile`. Another solution would be to blacklist bad files and jars on Executors. Maybe fail the first time, and then ignore the second time (but print a warning message). ## How was this patch tested? Unit tests in SparkContextSuite Author: Burak Yavuz <brkyvz@gmail.com> Closes #15224 from brkyvz/SPARK-17650.
* [SPARK-12221] add cpu time to metricsjisookim2016-09-2329-21/+488
| | | | | | | | Currently task metrics don't support executor CPU time, so there's no way to calculate how much CPU time a stage/task took from History Server metrics. This PR enables reporting CPU time. Author: jisookim <jisookim0513@gmail.com> Closes #10212 from jisookim0513/add-cpu-time-metric.
* [SPARK-16861][PYSPARK][CORE] Refactor PySpark accumulator API on top of ↵Holden Karau2016-09-231-19/+23
| | | | | | | | | | | | | | | | Accumulator V2 ## What changes were proposed in this pull request? Move the internals of the PySpark accumulator API from the old deprecated API on top of the new accumulator API. ## How was this patch tested? The existing PySpark accumulator tests (both unit tests and doc tests at the start of accumulator.py). Author: Holden Karau <holden@us.ibm.com> Closes #14467 from holdenk/SPARK-16861-refactor-pyspark-accumulator-api.
* [SPARK-17365][CORE] Remove/Kill multiple executors together to reduce RPC ↵Dhruve Ashar2016-09-227-51/+224
| | | | | | | | | | | | | | | call time. ## What changes were proposed in this pull request? We are killing multiple executors together instead of iterating over expensive RPC calls to kill single executor. ## How was this patch tested? Executed sample spark job to observe executors being killed/removed with dynamic allocation enabled. Author: Dhruve Ashar <dashar@yahoo-inc.com> Author: Dhruve Ashar <dhruveashar@gmail.com> Closes #15152 from dhruve/impr/SPARK-17365.
* [SPARK-17577][SPARKR][CORE] SparkR support add files to Spark job and get by ↵Yanbo Liang2016-09-211-3/+3
| | | | | | | | | | | | | | | executors ## What changes were proposed in this pull request? Scala/Python users can add files to Spark job by submit options ```--files``` or ```SparkContext.addFile()```. Meanwhile, users can get the added file by ```SparkFiles.get(filename)```. We should also support this function for SparkR users, since they also have the requirements for some shared dependency files. For example, SparkR users can download third party R packages to driver firstly, add these files to the Spark job as dependency by this API and then each executor can install these packages by ```install.packages```. ## How was this patch tested? Add unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15131 from yanboliang/spark-17577.
* [SPARK-17512][CORE] Avoid formatting to python path for yarn and mesos ↵jerryshao2016-09-212-3/+29
| | | | | | | | | | | | | | | | cluster mode ## What changes were proposed in this pull request? Yarn and mesos cluster mode support remote python path (HDFS/S3 scheme) by their own mechanism, it is not necessary to check and format the python when running on these modes. This is a potential regression compared to 1.6, so here propose to fix it. ## How was this patch tested? Unit test to verify SparkSubmit arguments, also with local cluster verification. Because of lack of `MiniDFSCluster` support in Spark unit test, there's no integration test added. Author: jerryshao <sshao@hortonworks.com> Closes #15137 from jerryshao/SPARK-17512.
* [SPARK-17623][CORE] Clarify type of TaskEndReason with a failed task.Imran Rashid2016-09-217-19/+13
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In TaskResultGetter, enqueueFailedTask currently deserializes the result as a TaskEndReason. But the type is actually more specific, its a TaskFailedReason. This just leads to more blind casting later on – it would be more clear if the msg was cast to the right type immediately, so method parameter types could be tightened. ## How was this patch tested? Existing unit tests via jenkins. Note that the code was already performing a blind-cast to a TaskFailedReason before in any case, just in a different spot, so there shouldn't be any behavior change. Author: Imran Rashid <irashid@cloudera.com> Closes #15181 from squito/SPARK-17623.
* [SPARK-4563][CORE] Allow driver to advertise a different network address.Marcelo Vanzin2016-09-2115-33/+100
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The goal of this feature is to allow the Spark driver to run in an isolated environment, such as a docker container, and be able to use the host's port forwarding mechanism to be able to accept connections from the outside world. The change is restricted to the driver: there is no support for achieving the same thing on executors (or the YARN AM for that matter). Those still need full access to the outside world so that, for example, connections can be made to an executor's block manager. The core of the change is simple: add a new configuration that tells what's the address the driver should bind to, which can be different than the address it advertises to executors (spark.driver.host). Everything else is plumbing the new configuration where it's needed. To use the feature, the host starting the container needs to set up the driver's port range to fall into a range that is being forwarded; this required the block manager port to need a special configuration just for the driver, which falls back to the existing spark.blockManager.port when not set. This way, users can modify the driver settings without affecting the executors; it would theoretically be nice to also have different retry counts for driver and executors, but given that docker (at least) allows forwarding port ranges, we can probably live without that for now. Because of the nature of the feature it's kinda hard to add unit tests; I just added a simple one to make sure the configuration works. This was tested with a docker image running spark-shell with the following command: docker blah blah blah \ -p 38000-38100:38000-38100 \ [image] \ spark-shell \ --num-executors 3 \ --conf spark.shuffle.service.enabled=false \ --conf spark.dynamicAllocation.enabled=false \ --conf spark.driver.host=[host's address] \ --conf spark.driver.port=38000 \ --conf spark.driver.blockManager.port=38020 \ --conf spark.ui.port=38040 Running on YARN; verified the driver works, executors start up and listen on ephemeral ports (instead of using the driver's config), and that caching and shuffling (without the shuffle service) works. Clicked through the UI to make sure all pages (including executor thread dumps) worked. Also tested apps without docker, and ran unit tests. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #15120 from vanzin/SPARK-4563.
* [CORE][MINOR] Add minor code change to TaskState and Taskerenavsarogullari2016-09-212-2/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? - TaskState and ExecutorState expose isFailed and isFinished functions. It can be useful to add test coverage for different states. Currently, Other enums do not expose any functions so this PR aims just these two enums. - `private` access modifier is added for Finished Task States Set - A minor doc change is added. ## How was this patch tested? New Unit tests are added and run locally. Author: erenavsarogullari <erenavsarogullari@gmail.com> Closes #15143 from erenavsarogullari/SPARK-17584.
* [SPARK-17585][PYSPARK][CORE] PySpark SparkContext.addFile supports adding ↵Yanbo Liang2016-09-211-0/+13
| | | | | | | | | | | | | | files recursively ## What changes were proposed in this pull request? Users would like to add a directory as dependency in some cases, they can use ```SparkContext.addFile``` with argument ```recursive=true``` to recursively add all files under the directory by using Scala. But Python users can only add file not directory, we should also make it supported. ## How was this patch tested? Unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15140 from yanboliang/spark-17585.
* [CORE][DOC] Fix errors in commentswm624@hotmail.com2016-09-211-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? While reading source code of CORE and SQL core, I found some minor errors in comments such as extra space, missing blank line and grammar error. I fixed these minor errors and might find more during my source code study. ## How was this patch tested? Manually build Author: wm624@hotmail.com <wm624@hotmail.com> Closes #15151 from wangmiao1981/mem.
* [MINOR][BUILD] Fix CheckStyle ErrorWeiqing Yang2016-09-203-7/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR is to fix the code style errors before 2.0.1 release. ## How was this patch tested? Manual. Before: ``` ./dev/lint-java Using `mvn` from path: /usr/local/bin/mvn Checkstyle checks failed at following occurrences: [ERROR] src/main/java/org/apache/spark/network/client/TransportClient.java:[153] (sizes) LineLength: Line is longer than 100 characters (found 107). [ERROR] src/main/java/org/apache/spark/network/client/TransportClient.java:[196] (sizes) LineLength: Line is longer than 100 characters (found 108). [ERROR] src/main/java/org/apache/spark/network/client/TransportClient.java:[239] (sizes) LineLength: Line is longer than 100 characters (found 115). [ERROR] src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:[119] (sizes) LineLength: Line is longer than 100 characters (found 107). [ERROR] src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:[129] (sizes) LineLength: Line is longer than 100 characters (found 104). [ERROR] src/main/java/org/apache/spark/network/util/LevelDBProvider.java:[124,11] (modifier) ModifierOrder: 'static' modifier out of order with the JLS suggestions. [ERROR] src/main/java/org/apache/spark/network/util/TransportConf.java:[26] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[33] (sizes) LineLength: Line is longer than 100 characters (found 110). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[38] (sizes) LineLength: Line is longer than 100 characters (found 110). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[43] (sizes) LineLength: Line is longer than 100 characters (found 106). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[48] (sizes) LineLength: Line is longer than 100 characters (found 110). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeInMemorySorter.java:[0] (misc) NewlineAtEndOfFile: File does not end with a newline. [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeSorterSpillReader.java:[67] (sizes) LineLength: Line is longer than 100 characters (found 106). [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[200] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[309] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[332] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[348] (regexp) RegexpSingleline: No trailing whitespace allowed. ``` After: ``` ./dev/lint-java Using `mvn` from path: /usr/local/bin/mvn Checkstyle checks passed. ``` Author: Weiqing Yang <yangweiqing001@gmail.com> Closes #15170 from Sherry302/fixjavastyle.
* [SPARK-17438][WEBUI] Show Application.executorLimit in the application pageShixiong Zhu2016-09-192-1/+17
| | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR adds `Application.executorLimit` to the applicatino page ## How was this patch tested? Checked the UI manually. Screenshots: 1. Dynamic allocation is disabled <img width="484" alt="screen shot 2016-09-07 at 4 21 49 pm" src="https://cloud.githubusercontent.com/assets/1000778/18332029/210056ea-7518-11e6-9f52-76d96046c1c0.png"> 2. Dynamic allocation is enabled. <img width="466" alt="screen shot 2016-09-07 at 4 25 30 pm" src="https://cloud.githubusercontent.com/assets/1000778/18332034/2c07700a-7518-11e6-8fce-aebe25014902.png"> Author: Shixiong Zhu <shixiong@databricks.com> Closes #15001 from zsxwing/fix-core-info.
* [SPARK-17586][BUILD] Do not call static member via instance referencehyukjinkwon2016-09-181-1/+1
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes a warning message as below: ``` [WARNING] .../UnsafeInMemorySorter.java:284: warning: [static] static method should be qualified by type name, TaskMemoryManager, instead of by an expression [WARNING] currentPageNumber = memoryManager.decodePageNumber(recordPointer) ``` by referencing the static member via class not instance reference. ## How was this patch tested? Existing tests should cover this - Jenkins tests. Author: hyukjinkwon <gurwls223@gmail.com> Closes #15141 from HyukjinKwon/SPARK-17586.
* [SPARK-17491] Close serialization stream to fix wrong answer bug in ↵Josh Rosen2016-09-178-44/+344
| | | | | | | | | | | | | | | | | | | | | | putIteratorAsBytes() ## What changes were proposed in this pull request? `MemoryStore.putIteratorAsBytes()` may silently lose values when used with `KryoSerializer` because it does not properly close the serialization stream before attempting to deserialize the already-serialized values, which may cause values buffered in Kryo's internal buffers to not be read. This is the root cause behind a user-reported "wrong answer" bug in PySpark caching reported by bennoleslie on the Spark user mailing list in a thread titled "pyspark persist MEMORY_ONLY vs MEMORY_AND_DISK". Due to Spark 2.0's automatic use of KryoSerializer for "safe" types (such as byte arrays, primitives, etc.) this misuse of serializers manifested itself as silent data corruption rather than a StreamCorrupted error (which you might get from JavaSerializer). The minimal fix, implemented here, is to close the serialization stream before attempting to deserialize written values. In addition, this patch adds several additional assertions / precondition checks to prevent misuse of `PartiallySerializedBlock` and `ChunkedByteBufferOutputStream`. ## How was this patch tested? The original bug was masked by an invalid assert in the memory store test cases: the old assert compared two results record-by-record with `zip` but didn't first check that the lengths of the two collections were equal, causing missing records to go unnoticed. The updated test case reproduced this bug. In addition, I added a new `PartiallySerializedBlockSuite` to unit test that component. Author: Josh Rosen <joshrosen@databricks.com> Closes #15043 from JoshRosen/partially-serialized-block-values-iterator-bugfix.
* [SPARK-17529][CORE] Implement BitSet.clearUntil and use it during merge joinsDavid Navas2016-09-172-10/+50
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add a clearUntil() method on BitSet (adapted from the pre-existing setUntil() method). Use this method to clear the subset of the BitSet which needs to be used during merge joins. ## How was this patch tested? dev/run-tests, as well as performance tests on skewed data as described in jira. I expect there to be a small local performance hit using BitSet.clearUntil rather than BitSet.clear for normally shaped (unskewed) joins (additional read on the last long). This is expected to be de-minimis and was not specifically tested. Author: David Navas <davidn@clearstorydata.com> Closes #15084 from davidnavas/bitSet.
* [SPARK-17567][DOCS] Use valid url to Spark RDD paperXin Ren2016-09-171-1/+1
| | | | | | | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-17567 ## What changes were proposed in this pull request? Documentation (http://spark.apache.org/docs/latest/api/scala/#org.apache.spark.rdd.RDD) contains broken link to Spark paper (http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf). I found it elsewhere (https://www.usenix.org/system/files/conference/nsdi12/nsdi12-final138.pdf) and I hope it is the same one. It should be uploaded to and linked from some Apache controlled storage, so it won't break again. ## How was this patch tested? Tested manually on local laptop. Author: Xin Ren <iamshrek@126.com> Closes #15121 from keypointt/SPARK-17567.
* [SPARK-17484] Prevent invalid block locations from being reported after ↵Josh Rosen2016-09-152-8/+63
| | | | | | | | | | | | | | | | | | | | | | | | | | put() exceptions ## What changes were proposed in this pull request? If a BlockManager `put()` call failed after the BlockManagerMaster was notified of a block's availability then incomplete cleanup logic in a `finally` block would never send a second block status method to inform the master of the block's unavailability. This, in turn, leads to fetch failures and used to be capable of causing complete job failures before #15037 was fixed. This patch addresses this issue via multiple small changes: - The `finally` block now calls `removeBlockInternal` when cleaning up from a failed `put()`; in addition to removing the `BlockInfo` entry (which was _all_ that the old cleanup logic did), this code (redundantly) tries to remove the block from the memory and disk stores (as an added layer of defense against bugs lower down in the stack) and optionally notifies the master of block removal (which now happens during exception-triggered cleanup). - When a BlockManager receives a request for a block that it does not have it will now notify the master to update its block locations. This ensures that bad metadata pointing to non-existent blocks will eventually be fixed. Note that I could have implemented this logic in the block manager client (rather than in the remote server), but that would introduce the problem of distinguishing between transient and permanent failures; on the server, however, we know definitively that the block isn't present. - Catch `NonFatal` instead of `Exception` to avoid swallowing `InterruptedException`s thrown from synchronous block replication calls. This patch depends upon the refactorings in #15036, so that other patch will also have to be backported when backporting this fix. For more background on this issue, including example logs from a real production failure, see [SPARK-17484](https://issues.apache.org/jira/browse/SPARK-17484). ## How was this patch tested? Two new regression tests in BlockManagerSuite. Author: Josh Rosen <joshrosen@databricks.com> Closes #15085 from JoshRosen/SPARK-17484.
* [SPARK-17547] Ensure temp shuffle data file is cleaned up after errorJosh Rosen2016-09-154-49/+73
| | | | | | | | | | SPARK-8029 (#9610) modified shuffle writers to first stage their data to a temporary file in the same directory as the final destination file and then to atomically rename this temporary file at the end of the write job. However, this change introduced the potential for the temporary output file to be leaked if an exception occurs during the write because the shuffle writers' existing error cleanup code doesn't handle deletion of the temp file. This patch avoids this potential cause of disk-space leaks by adding `finally` blocks to ensure that temp files are always deleted if they haven't been renamed. Author: Josh Rosen <joshrosen@databricks.com> Closes #15104 from JoshRosen/cleanup-tmp-data-file-in-shuffle-writer.
* [SPARK-17451][CORE] CoarseGrainedExecutorBackend should inform driver before ↵Tejas Patil2016-09-152-6/+23
| | | | | | | | | | | | | | | | | | | | | | | | self-kill ## What changes were proposed in this pull request? Jira : https://issues.apache.org/jira/browse/SPARK-17451 `CoarseGrainedExecutorBackend` in some failure cases exits the JVM. While this does not have any issue, from the driver UI there is no specific reason captured for this. In this PR, I am adding functionality to `exitExecutor` to notify driver that the executor is exiting. ## How was this patch tested? Ran the change over a test env and took down shuffle service before the executor could register to it. In the driver logs, where the job failure reason is mentioned (ie. `Job aborted due to stage ...` it gives the correct reason: Before: `ExecutorLostFailure (executor ZZZZZZZZZ exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.` After: `ExecutorLostFailure (executor ZZZZZZZZZ exited caused by one of the running tasks) Reason: Unable to create executor due to java.util.concurrent.TimeoutException: Timeout waiting for task.` Author: Tejas Patil <tejasp@fb.com> Closes #15013 from tejasapatil/SPARK-17451_inform_driver.
* [SPARK-17406][WEB UI] limit timeline executor eventscenyuhai2016-09-157-148/+150
| | | | | | | | | ## What changes were proposed in this pull request? The job page will be too slow to open when there are thousands of executor events(added or removed). I found that in ExecutorsTab file, executorIdToData will not remove elements, it will increase all the time.Before this pr, it looks like [timeline1.png](https://issues.apache.org/jira/secure/attachment/12827112/timeline1.png). After this pr, it looks like [timeline2.png](https://issues.apache.org/jira/secure/attachment/12827113/timeline2.png)(we can set how many executor events will be displayed) Author: cenyuhai <cenyuhai@didichuxing.com> Closes #14969 from cenyuhai/SPARK-17406.
* [SPARK-17521] Error when I use sparkContext.makeRDD(Seq())codlife2016-09-151-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? when i use sc.makeRDD below ``` val data3 = sc.makeRDD(Seq()) println(data3.partitions.length) ``` I got an error: Exception in thread "main" java.lang.IllegalArgumentException: Positive number of slices required We can fix this bug just modify the last line ,do a check of seq.size ``` def makeRDD[T: ClassTag](seq: Seq[(T, Seq[String])]): RDD[T] = withScope { assertNotStopped() val indexToPrefs = seq.zipWithIndex.map(t => (t._2, t._1._2)).toMap new ParallelCollectionRDD[T](this, seq.map(_._1), math.max(seq.size, defaultParallelism), indexToPrefs) } ``` ## How was this patch tested? manual tests (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: codlife <1004910847@qq.com> Author: codlife <wangjianfei15@otcaix.iscas.ac.cn> Closes #15077 from codlife/master.
* [SPARK-17465][SPARK CORE] Inappropriate memory management in ↵Xing SHI2016-09-141-3/+3
| | | | | | | | | | | | | | `org.apache.spark.storage.MemoryStore` may lead to memory leak The expression like `if (memoryMap(taskAttemptId) == 0) memoryMap.remove(taskAttemptId)` in method `releaseUnrollMemoryForThisTask` and `releasePendingUnrollMemoryForThisTask` should be called after release memory operation, whatever `memoryToRelease` is > 0 or not. If the memory of a task has been set to 0 when calling a `releaseUnrollMemoryForThisTask` or a `releasePendingUnrollMemoryForThisTask` method, the key in the memory map corresponding to that task will never be removed from the hash map. See the details in [SPARK-17465](https://issues.apache.org/jira/browse/SPARK-17465). Author: Xing SHI <shi-kou@indetail.co.jp> Closes #15022 from saturday-shi/SPARK-17465.
* [SPARK-17463][CORE] Make CollectionAccumulator and SetAccumulator's value ↵Shixiong Zhu2016-09-144-23/+39
| | | | | | | | | | | | | | | | can be read thread-safely ## What changes were proposed in this pull request? Make CollectionAccumulator and SetAccumulator's value can be read thread-safely to fix the ConcurrentModificationException reported in [JIRA](https://issues.apache.org/jira/browse/SPARK-17463). ## How was this patch tested? Existing tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #15063 from zsxwing/SPARK-17463.
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