Hi, When playing around with spark.dynamicAllocation.enabled I face the following error after the first round of executors have been killed.
Py4JJavaError: An error occurred while calling o337.showString. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 18.0 failed 4 times, most recent failure: Lost task 1.3 in stage 18.0 (TID 220) (10.128.6.170 executor 13): java.lang.NoClassDefFoundError: Could not initialize class org.apache.spark.sql.catalyst.util.RebaseDateTime$ at org.apache.spark.sql.catalyst.util.RebaseDateTime.lastSwitchJulianTs(RebaseDateTime.scala) at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdaterFactory.rebaseTimestamp(ParquetVectorUpdaterFactory.java:1067) at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdaterFactory.rebaseInt96(ParquetVectorUpdaterFactory.java:1088) at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdaterFactory.access$1500(ParquetVectorUpdaterFactory.java:43) at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdaterFactory$BinaryToSQLTimestampRebaseUpdater.decodeSingleDictionaryId(ParquetVectorUpdaterFactory.java:860) at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdater.decodeDictionaryIds(ParquetVectorUpdater.java:75) at org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.readBatch(VectorizedColumnReader.java:216) at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:298) at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:196) at org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) at org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_1$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) We tested on Spark 3.2.1 k8s with these dynamicAllocation settings: spark.dynamicAllocation.enabled=true spark.dynamicAllocation.maxExecutors=4 spark.dynamicAllocation.minExecutors=1 spark.dynamicAllocation.executorIdleTimeout=30s spark.dynamicAllocation.shuffleTracking.enabled=true spark.dynamicAllocation.shuffleTracking.timeout=30s spark.decommission.enabled=true Might be related to SPARK-34772 / https://www.mail-archive.com/commits@spark.apache.org/msg50240.html but as this was fixed for 3.2.0 it might be worth another issue ? Best regards Andreas
