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https://issues.apache.org/jira/browse/SPARK-39132?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17534134#comment-17534134
]
XiDuo You commented on SPARK-39132:
-----------------------------------
same bug with SPARK-39104
> spark3.2.1 cache throw NPE
> --------------------------
>
> Key: SPARK-39132
> URL: https://issues.apache.org/jira/browse/SPARK-39132
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
> Affects Versions: 3.2.1
> Environment: i set it a driver and 2 executors executor allocate 2g
> memory and old generation usage rate about 50%, i think it is health
> Reporter: cxb
> Priority: Major
> Original Estimate: 72h
> Remaining Estimate: 72h
>
> a job running some time about 1 day will throw the exception when i upgrade
> spark version to 3.2.1
> gc log:
> {code:java}
> Heap
> par new generation total 307840K, used 239453K [0x0000000080000000,
> 0x0000000094e00000, 0x00000000aaaa0000)
> eden space 273664K, 81% used [0x0000000080000000, 0x000000008da4bdd0,
> 0x0000000090b40000)
> from space 34176K, 46% used [0x0000000092ca0000, 0x0000000093c2b6b8,
> 0x0000000094e00000)
> to space 34176K, 0% used [0x0000000090b40000, 0x0000000090b40000,
> 0x0000000092ca0000)
> concurrent mark-sweep generation total 811300K, used 451940K
> [0x00000000aaaa0000, 0x00000000dc2e9000, 0x0000000100000000)
> Metaspace used 102593K, capacity 110232K, committed 121000K, reserved
> 1155072K
> class space used 12473K, capacity 13482K, committed 15584K, reserved
> 1048576K {code}
> code:
> {{}}{{}}
>
> {code:java}
> sparkSession
> .readStream
> .format('kafka')
> .load
> .repartition(4)
> ...project
> .watermark
> .groupby(k1, k2)
> .agg(size(collect_set('xxx')))
> .writeStream
> .foreachBatch(function test)
> .start
> def test:(Dataset[Row], Long) => Unit = (ds: Dataset[Row], _: Long) => {
> ds.persist(StorageLevel.MEMORY_AND_DISK_SER)
> ds.write
> .option("collection", s"col_1")
> .option("maxBatchSize", "2048")
> .mode("append")
> .mongo()
> ds..write
> .option("collection", s"col_2")
> .option("maxBatchSize", "2048")
> .mode("append")
> .mongo()
> ds.unpersist()
> }{code}
>
>
> exception log
>
> {code:java}
> {code}
> 22/05/09 21:11:28 ERROR streaming.MicroBatchExecution: Query rydts_regist_gp
> [id = 669c2031-71b2-422b-859d-336722d289e9, runId =
> 049de32c-e6ff-48f1-8742-bb95122a36ea] terminated with error
> java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.columnar.CachedRDDBuilder.$anonfun$isCachedRDDLoaded$1(InMemoryRelation.scala:248)
> at
> org.apache.spark.sql.execution.columnar.CachedRDDBuilder.$anonfun$isCachedRDDLoaded$1$adapted(InMemoryRelation.scala:247)
> at
> scala.collection.IndexedSeqOptimized.prefixLengthImpl(IndexedSeqOptimized.scala:41)
> at
> scala.collection.IndexedSeqOptimized.forall(IndexedSeqOptimized.scala:46)
> at
> scala.collection.IndexedSeqOptimized.forall$(IndexedSeqOptimized.scala:46)
> at scala.collection.mutable.ArrayOps$ofRef.forall(ArrayOps.scala:198)
> at
> org.apache.spark.sql.execution.columnar.CachedRDDBuilder.isCachedRDDLoaded(InMemoryRelation.scala:247)
> at
> org.apache.spark.sql.execution.columnar.CachedRDDBuilder.isCachedColumnBuffersLoaded(InMemoryRelation.scala:241)
> at
> org.apache.spark.sql.execution.CacheManager.$anonfun$uncacheQuery$8(CacheManager.scala:189)
> at
> org.apache.spark.sql.execution.CacheManager.$anonfun$uncacheQuery$8$adapted(CacheManager.scala:176)
> at
> scala.collection.TraversableLike.$anonfun$filterImpl$1(TraversableLike.scala:304)
> at scala.collection.Iterator.foreach(Iterator.scala:943)
> at scala.collection.Iterator.foreach$(Iterator.scala:943)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
> at scala.collection.IterableLike.foreach(IterableLike.scala:74)
> at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
> at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
> at scala.collection.TraversableLike.filterImpl(TraversableLike.scala:303)
> at scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:297)
> at scala.collection.AbstractTraversable.filterImpl(Traversable.scala:108)
> at scala.collection.TraversableLike.filter(TraversableLike.scala:395)
> at scala.collection.TraversableLike.filter$(TraversableLike.scala:395)
> at scala.collection.AbstractTraversable.filter(Traversable.scala:108)
> at
> org.apache.spark.sql.execution.CacheManager.recacheByCondition(CacheManager.scala:219)
> at
> org.apache.spark.sql.execution.CacheManager.uncacheQuery(CacheManager.scala:176)
> at org.apache.spark.sql.Dataset.unpersist(Dataset.scala:3220)
> at org.apache.spark.sql.Dataset.unpersist(Dataset.scala:3231)
> at common.job.xxx$.$anonfun$main$3(xxx.scala:117)
> at common.job.xxx$.$anonfun$main$3$adapted(xxx.scala:103)
> at
> org.apache.spark.sql.execution.streaming.sources.ForeachBatchSink.addBatch(ForeachBatchSink.scala:35)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$17(MicroBatchExecution.scala:600)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:598)
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:598)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:228)
> at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:193)
> at
> org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:57)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:187)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:303)
> at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:286)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:209)
>
>
>
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