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Posted to issues@spark.apache.org by "Ankur Dave (Jira)" <ji...@apache.org> on 2020/09/13 20:52:00 UTC
[jira] [Created] (SPARK-32872) BytesToBytesMap exceeds growth
threshold when close to MAX_CAPACITY
Ankur Dave created SPARK-32872:
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Summary: BytesToBytesMap exceeds growth threshold when close to MAX_CAPACITY
Key: SPARK-32872
URL: https://issues.apache.org/jira/browse/SPARK-32872
Project: Spark
Issue Type: Bug
Components: Spark Core
Affects Versions: 3.0.1, 2.4.7
Reporter: Ankur Dave
Assignee: Ankur Dave
When BytesToBytesMap is close to MAX_CAPACITY and needs to grow, numKeys >= growthThreshold is true but longArray.size() / 2 < MAX_CAPACITY is false. This correctly prevents the map from growing, but canGrowArray incorrectly remains true. Therefore the map keeps accepting new keys and exceeds its growth threshold. If we attempt to spill the map in this state, the UnsafeKVExternalSorter will not be able to reuse the long array for sorting, causing grouping aggregations to fail with the following error:
2020-09-13 18:33:48,765 ERROR Executor - Exception in task 0.0 in stage 7.0 (TID 69)2020-09-13 18:33:48,765 ERROR Executor - Exception in task 0.0 in stage 7.0 (TID 69)org.apache.spark.memory.SparkOutOfMemoryError: Unable to acquire 12982025696 bytes of memory, got 0 at org.apache.spark.memory.MemoryConsumer.throwOom(MemoryConsumer.java:160) at org.apache.spark.memory.MemoryConsumer.allocateArray(MemoryConsumer.java:100) at org.apache.spark.sql.execution.UnsafeKVExternalSorter.<init>(UnsafeKVExternalSorter.java:118) at org.apache.spark.sql.execution.UnsafeFixedWidthAggregationMap.destructAndCreateExternalSorter(UnsafeFixedWidthAggregationMap.java:253) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.agg_doConsume_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.agg_doAggregateWithKeys_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.agg_doAggregateWithoutKey_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:733) at org.apache.spark.sql.execution.collect.UnsafeRowBatchUtils$.encodeUnsafeRows(UnsafeRowBatchUtils.scala:80) at org.apache.spark.sql.execution.collect.Collector.$anonfun$processFunc$1(Collector.scala:187) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.doRunTask(Task.scala:144) at org.apache.spark.scheduler.Task.run(Task.scala:117) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$9(Executor.scala:660) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1581) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:663) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)
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