Jerry Vinokurov created SPARK-29251:
---------------------------------------
Summary: intermittent serialization failures in spark
Key: SPARK-29251
URL: https://issues.apache.org/jira/browse/SPARK-29251
Project: Spark
Issue Type: Bug
Components: Spark Core
Affects Versions: 2.4.3
Environment: We are running Spark 2.4.3 on an AWS EMR cluster. Our
cluster consists of one driver instance, 3 core instances, and 3 to 12 task
instances; the task group autoscales as needed.
Reporter: Jerry Vinokurov
We are running an EMR cluster on AWS that processes somewhere around 100 batch
jobs a day. These jobs are running various SQL commands to transform data and
the data volume ranges between a dozen or a few hundred MB to a few GB on the
high end for some jobs, and even around ~1 TB for one particularly large one.
We use the Kryo serializer and preregister our classes like so:
{code:java}
object KryoRegistrar {
val classesToRegister: Array[Class[_]] = Array(
classOf[MyModel],
[etc]
)
}
// elsewhere
val sparkConf = new SparkConf()
.registerKryoClasses(KryoRegistrar.classesToRegister)
{code}
Intermittently throughout the cluster's operation we have observed jobs
terminating with the following stack trace:
{noformat}
org.apache.spark.SparkException: Failed to register classes with Kryo
at
org.apache.spark.serializer.KryoSerializer.newKryo(KryoSerializer.scala:140)
at
org.apache.spark.serializer.KryoSerializerInstance.borrowKryo(KryoSerializer.scala:324)
at
org.apache.spark.serializer.KryoSerializerInstance.<init>(KryoSerializer.scala:309)
at
org.apache.spark.serializer.KryoSerializer.newInstance(KryoSerializer.scala:218)
at
org.apache.spark.broadcast.TorrentBroadcast$.blockifyObject(TorrentBroadcast.scala:288)
at
org.apache.spark.broadcast.TorrentBroadcast.writeBlocks(TorrentBroadcast.scala:127)
at
org.apache.spark.broadcast.TorrentBroadcast.<init>(TorrentBroadcast.scala:88)
at
org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:34)
at
org.apache.spark.broadcast.BroadcastManager.newBroadcast(BroadcastManager.scala:62)
at org.apache.spark.SparkContext.broadcast(SparkContext.scala:1489)
at
org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.buildReader(CSVFileFormat.scala:103)
at
org.apache.spark.sql.execution.datasources.FileFormat$class.buildReaderWithPartitionValues(FileFormat.scala:129)
at
org.apache.spark.sql.execution.datasources.TextBasedFileFormat.buildReaderWithPartitionValues(FileFormat.scala:165)
at
org.apache.spark.sql.execution.FileSourceScanExec.inputRDD$lzycompute(DataSourceScanExec.scala:309)
at
org.apache.spark.sql.execution.FileSourceScanExec.inputRDD(DataSourceScanExec.scala:305)
at
org.apache.spark.sql.execution.FileSourceScanExec.inputRDDs(DataSourceScanExec.scala:327)
at
org.apache.spark.sql.execution.FilterExec.inputRDDs(basicPhysicalOperators.scala:121)
at
org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:41)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.prepareShuffleDependency(ShuffleExchangeExec.scala:92)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:128)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
at
org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.doExecute(ShuffleExchangeExec.scala:119)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:391)
at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:121)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.window.WindowExec.doExecute(WindowExec.scala:302)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:391)
at
org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:41)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.columnar.CachedRDDBuilder.buildBuffers(InMemoryRelation.scala:83)
at
org.apache.spark.sql.execution.columnar.CachedRDDBuilder.cachedColumnBuffers(InMemoryRelation.scala:59)
at
org.apache.spark.sql.execution.columnar.InMemoryTableScanExec.filteredCachedBatches(InMemoryTableScanExec.scala:276)
at
org.apache.spark.sql.execution.columnar.InMemoryTableScanExec.inputRDD$lzycompute(InMemoryTableScanExec.scala:105)
at
org.apache.spark.sql.execution.columnar.InMemoryTableScanExec.inputRDD(InMemoryTableScanExec.scala:104)
at
org.apache.spark.sql.execution.columnar.InMemoryTableScanExec.doExecute(InMemoryTableScanExec.scala:310)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:391)
at
org.apache.spark.sql.execution.FilterExec.inputRDDs(basicPhysicalOperators.scala:121)
at
org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:41)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:143)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:159)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:156)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at
org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at
org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at
org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at
org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
at
org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:285)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:229)
at org.apache.spark.sql.DataFrameWriter.csv(DataFrameWriter.scala:664)
[our code that writes data to CSV]
Caused by: java.lang.ClassNotFoundException: com.mycompany.models.MyModel
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at
org.apache.spark.serializer.KryoSerializer$$anonfun$newKryo$4.apply(KryoSerializer.scala:132)
at
org.apache.spark.serializer.KryoSerializer$$anonfun$newKryo$4.apply(KryoSerializer.scala:132)
at
scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at
org.apache.spark.serializer.KryoSerializer.newKryo(KryoSerializer.scala:132)
... 132 more{noformat}
The real name of the model has been changed as this is proprietary code, but
otherwise I have reproduced the stack trace in full. This error is not
reproducible and seems to strike mostly randomly. It does not seem to be
related to the size of the job, and if we rerun the job with identical
parameters, it usually just succeeds, although superficially it does seem to
coincide with times when cluster load is high. Most of our jobs are run with
the following params:
{noformat}
spark.driver.memory = 2G
spark.executor.memory = 4G
spark.driver.cores = 1
spark.executor.cores = 2
spark.executor.instances = 2{noformat}
We also use dynamic allocation to allow for up to 14 cores per job and fair
scheduling.
This error has been plaguing us for months, and I don't have a good handle on
what I can do about it. It seems like a bug in Spark internals and possibly
related to [SPARK-21928|https://issues.apache.org/jira/browse/SPARK-21928], but
we use Spark 2.4.3 and according to that ticket the problem has been fixed.
It's particularly frustrating because the error is not directly reproducible.
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