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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/01/18 06:53:00 UTC
[jira] [Commented] (SPARK-10030) Managed memory leak detected when
cache table
[ https://issues.apache.org/jira/browse/SPARK-10030?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16330143#comment-16330143 ]
Apache Spark commented on SPARK-10030:
--------------------------------------
User 'cloud-fan' has created a pull request for this issue:
https://github.com/apache/spark/pull/20310
> Managed memory leak detected when cache table
> ---------------------------------------------
>
> Key: SPARK-10030
> URL: https://issues.apache.org/jira/browse/SPARK-10030
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: wangwei
> Assignee: Yin Huai
> Priority: Blocker
> Fix For: 1.5.1
>
>
> I test the lastest spark-1.5.0 in local, standalone, yarn mode and follow the steps bellow, then errors occured.
> 1. create table cache_test(id int, name string) stored as textfile ;
> 2. load data local inpath 'SparkSource/sql/hive/src/test/resources/data/files/kv1.txt' into table cache_test;
> 3. cache table test as select * from cache_test distribute by id;
> configuration:
> spark.driver.memory 5g
> spark.executor.memory 28g
> spark.cores.max 21
> {code}
> 15/08/16 17:14:47 ERROR Executor: Managed memory leak detected; size = 67108864 bytes, TID = 434
> 15/08/16 17:14:47 ERROR Executor: Exception in task 23.0 in stage 9.0 (TID 434)
> java.util.NoSuchElementException: key not found: val_54
> at scala.collection.MapLike$class.default(MapLike.scala:228)
> at scala.collection.AbstractMap.default(Map.scala:58)
> at scala.collection.mutable.HashMap.apply(HashMap.scala:64)
> at org.apache.spark.sql.columnar.compression.DictionaryEncoding$Encoder.compress(compressionSchemes.scala:258)
> at org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder$class.build(CompressibleColumnBuilder.scala:110)
> at org.apache.spark.sql.columnar.NativeColumnBuilder.build(ColumnBuilder.scala:87)
> at org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1$$anonfun$next$2.apply(InMemoryColumnarTableScan.scala:153)
> at org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1$$anonfun$next$2.apply(InMemoryColumnarTableScan.scala:153)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
> at org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:153)
> at org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:120)
> at org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:278)
> at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:262)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:46)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
> at java.lang.Thread.run(Thread.java:722)
> {code}
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