[
https://issues.apache.org/jira/browse/SPARK-52819?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Herman van Hövell resolved SPARK-52819.
---------------------------------------
Fix Version/s: 4.2.0
4.1.1
4.0.2
Resolution: Fixed
Issue resolved by pull request 51615
[https://github.com/apache/spark/pull/51615]
> Structured Streaming: FlatMapGroupsWithState:
> java.io.NotSerializableException:
> org.apache.spark.sql.catalyst.encoders.KryoSerializationCodec$
> ----------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-52819
> URL: https://issues.apache.org/jira/browse/SPARK-52819
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 4.0.0
> Reporter: Quirin Kögl
> Assignee: Kristin Cowalcijk
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.2.0, 4.1.1, 4.0.2
>
> Attachments: Main.java
>
>
> When trying to use a kryo serializer for the State using the
> Dataset.flatMapGroupsWithState function.
> The following exception occurs:
> org.apache.spark.SparkException: Task not serializable
> at
> org.apache.spark.util.SparkClosureCleaner$.clean(SparkClosureCleaner.scala:45)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:2839)
> at
> org.apache.spark.sql.execution.streaming.state.package$StateStoreOps.mapPartitionsWithStateStore(package.scala:67)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase.doExecute(FlatMapGroupsWithStateExec.scala:263)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase.doExecute$(FlatMapGroupsWithStateExec.scala:207)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExec.doExecute(FlatMapGroupsWithStateExec.scala:403)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeRDD$1(SparkPlan.scala:188)
> at scala.util.Try$.apply(Try.scala:217)
> at
> org.apache.spark.util.Utils$.doTryWithCallerStacktrace(Utils.scala:1378)
> at org.apache.spark.util.LazyTry.tryT$lzycompute(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.tryT(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.get(LazyTry.scala:58)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:201)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:260)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:257)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:197)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:533)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:461)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:460)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:504)
> at
> org.apache.spark.sql.execution.SerializeFromObjectExec.inputRDDs(objects.scala:117)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:761)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeRDD$1(SparkPlan.scala:188)
> at scala.util.Try$.apply(Try.scala:217)
> at
> org.apache.spark.util.Utils$.getTryWithCallerStacktrace(Utils.scala:1439)
> at org.apache.spark.util.LazyTry.get(LazyTry.scala:58)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:201)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:260)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:257)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:197)
> at
> org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2(WriteToDataSourceV2Exec.scala:399)
> at
> org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2$(WriteToDataSourceV2Exec.scala:397)
> at
> org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.writeWithV2(WriteToDataSourceV2Exec.scala:329)
> at
> org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.run(WriteToDataSourceV2Exec.scala:340)
> at
> org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result$lzycompute(V2CommandExec.scala:43)
> at
> org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result(V2CommandExec.scala:43)
> at
> org.apache.spark.sql.execution.datasources.v2.V2CommandExec.executeCollect(V2CommandExec.scala:49)
> at
> org.apache.spark.sql.classic.Dataset.collectFromPlan(Dataset.scala:2244)
> at
> org.apache.spark.sql.classic.Dataset.$anonfun$collect$1(Dataset.scala:1482)
> at
> org.apache.spark.sql.classic.Dataset.$anonfun$withAction$2(Dataset.scala:2234)
> at
> org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:654)
> at
> org.apache.spark.sql.classic.Dataset.$anonfun$withAction$1(Dataset.scala:2232)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$8(SQLExecution.scala:162)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSessionTagsApplied(SQLExecution.scala:268)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$7(SQLExecution.scala:124)
> at
> org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
> at
> org.apache.spark.sql.artifact.ArtifactManager.$anonfun$withResources$1(ArtifactManager.scala:112)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:106)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:111)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$6(SQLExecution.scala:124)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:291)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$1(SQLExecution.scala:123)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId0(SQLExecution.scala:77)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:233)
> at org.apache.spark.sql.classic.Dataset.withAction(Dataset.scala:2232)
> at org.apache.spark.sql.classic.Dataset.collect(Dataset.scala:1482)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$17(MicroBatchExecution.scala:888)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$8(SQLExecution.scala:162)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSessionTagsApplied(SQLExecution.scala:268)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$7(SQLExecution.scala:124)
> at
> org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
> at
> org.apache.spark.sql.artifact.ArtifactManager.$anonfun$withResources$1(ArtifactManager.scala:112)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:106)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:111)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$6(SQLExecution.scala:124)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:291)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$1(SQLExecution.scala:123)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId0(SQLExecution.scala:77)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:233)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:876)
> at
> org.apache.spark.sql.execution.streaming.ProgressContext.reportTimeTaken(ProgressReporter.scala:186)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:876)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$executeOneBatch$2(MicroBatchExecution.scala:394)
> at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
> at
> org.apache.spark.sql.execution.streaming.ProgressContext.reportTimeTaken(ProgressReporter.scala:186)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.executeOneBatch(MicroBatchExecution.scala:364)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:344)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1$adapted(MicroBatchExecution.scala:344)
> at
> org.apache.spark.sql.execution.streaming.TriggerExecutor.runOneBatch(TriggerExecutor.scala:39)
> at
> org.apache.spark.sql.execution.streaming.TriggerExecutor.runOneBatch$(TriggerExecutor.scala:37)
> at
> org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.runOneBatch(TriggerExecutor.scala:70)
> at
> org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:82)
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:344)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:337)
> at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:311)
> at
> org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:226)
> Suppressed: org.apache.spark.util.Utils$OriginalTryStackTraceException:
> Full stacktrace of original doTryWithCallerStacktrace caller
> at
> org.apache.spark.util.SparkClosureCleaner$.clean(SparkClosureCleaner.scala:45)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:2839)
> at
> org.apache.spark.sql.execution.streaming.state.package$StateStoreOps.mapPartitionsWithStateStore(package.scala:67)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase.doExecute(FlatMapGroupsWithStateExec.scala:263)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase.doExecute$(FlatMapGroupsWithStateExec.scala:207)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExec.doExecute(FlatMapGroupsWithStateExec.scala:403)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeRDD$1(SparkPlan.scala:188)
> at scala.util.Try$.apply(Try.scala:217)
> at
> org.apache.spark.util.Utils$.doTryWithCallerStacktrace(Utils.scala:1378)
> at org.apache.spark.util.LazyTry.tryT$lzycompute(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.tryT(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.get(LazyTry.scala:58)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:201)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:260)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:257)
> at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:197)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:533)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:461)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:460)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:504)
> at
> org.apache.spark.sql.execution.SerializeFromObjectExec.inputRDDs(objects.scala:117)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:761)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeRDD$1(SparkPlan.scala:188)
> at scala.util.Try$.apply(Try.scala:217)
> at
> org.apache.spark.util.Utils$.doTryWithCallerStacktrace(Utils.scala:1378)
> at org.apache.spark.util.LazyTry.tryT$lzycompute(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.tryT(LazyTry.scala:46)
> ... 66 more
> Caused by: java.io.NotSerializableException:
> org.apache.spark.sql.catalyst.encoders.KryoSerializationCodec$
> Serialization stack:
> - object not serializable (class:
> org.apache.spark.sql.catalyst.encoders.KryoSerializationCodec$, value:
> <function0>)
> - field (class:
> org.apache.spark.sql.catalyst.encoders.AgnosticEncoders$TransformingEncoder,
> name: codecProvider, type: interface scala.Function0)
> - object (class
> org.apache.spark.sql.catalyst.encoders.AgnosticEncoders$TransformingEncoder,
> TransformingEncoder(qukoegl.Main$State,BinaryEncoder,<function0>,false))
> - field (class: org.apache.spark.sql.catalyst.encoders.ExpressionEncoder,
> name: encoder, type: interface
> org.apache.spark.sql.catalyst.encoders.AgnosticEncoder)
> - object (class org.apache.spark.sql.catalyst.encoders.ExpressionEncoder,
> class[value[0]: binary])
> - field (class:
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExec, name:
> stateEncoder, type: class
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder)
> - object (class
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExec,
> FlatMapGroupsWithState
> org.apache.spark.sql.internal.ToScalaUDF$$$Lambda$1541/0x00000116e397f3e8@6578637,
> decodeusingserializer(value#16, qukoegl.Main$Key, true),
> decodeusingserializer(value#10, qukoegl.Main$Input, true),
> decodeusingserializer(value#16, qukoegl.Main$Key, true), [value#16|#16],
> [value#16|#16], [value#10|#10], [value#10|#10], obj#21: qukoegl.Main$Result,
> state info [ checkpoint =
> [file:/C:/Users/koeglq/AppData/Local/Temp/temporary-3e5bc956-591a-4e55-8c49-f24a41eb99ca/state|file:///C:/Users/koeglq/AppData/Local/Temp/temporary-3e5bc956-591a-4e55-8c49-f24a41eb99ca/state],
> runId = c125342a-6ab9-42c8-962d-c1ccdbba9ce4, opId = 0, ver = 0,
> numPartitions = 2] stateStoreCkptIds = None, class[value[0]: binary], 2,
> Append, NoTimeout, 1752568574400, 0, 0, false, false
> :- *(2) Sort [value#16 ASC NULLS FIRST|#16 ASC NULLS FIRST], false, 0
> : +- Exchange hashpartitioning(value#16, 2), REQUIRED_BY_STATEFUL_OPERATOR,
> [plan_id=52]
> : +- AppendColumnsWithObject
> org.apache.spark.sql.internal.ToScalaUDF$$$Lambda$1539/0x00000116e397b708@59abcdc,
> [encodeusingserializer(input[0, qukoegl.Main$Input, false], true) AS
> value#10|#10], [encodeusingserializer(input[0, qukoegl.Main$Key, false],
> true) AS value#16|#16]
> : +- MapElements
> qukoegl.Main$$Lambda$1414/0x00000116e391ec40@5d777d92, obj#8:
> qukoegl.Main$Input
> : +- DeserializeToObject
> createexternalrow(static_invoke(DateTimeUtils.toJavaTimestamp(timestamp#0)),
> static_invoke(java.lang.Long.valueOf(value#1L)),
> StructField(timestamp,TimestampType,true), StructField(value,LongType,true)),
> obj#6: org.apache.spark.sql.Row
> : +- *(1) Project [timestamp#0, value#1L|#0, value#1L]
> : +- MicroBatchScan[timestamp#0, value#1L|#0, value#1L] class
> org.apache.spark.sql.execution.streaming.sources.RateStreamTable$$anon$1
> +- PlanLater LocalRelation <empty>, [value#23|#23]
> )
> - element of array (index: 0)
> - array (class [Ljava.lang.Object;, size 1)
> - field (class: java.lang.invoke.SerializedLambda, name: capturedArgs,
> type: class [Ljava.lang.Object;)
> - object (class java.lang.invoke.SerializedLambda,
> SerializedLambda[capturingClass=interface
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase,
> functionalInterfaceMethod=scala/Function2.apply:(Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;,
> implementation=invokeStatic
> org/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExecBase.$anonfun$doExecute$3:(Lorg/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExecBase;Lorg/apache/spark/sql/execution/streaming/state/StateStore;Lscala/collection/Iterator;)Lscala/collection/Iterator;,
>
> instantiatedMethodType=(Lorg/apache/spark/sql/execution/streaming/state/StateStore;Lscala/collection/Iterator;)Lscala/collection/Iterator;,
> numCaptured=1])
> - writeReplace data (class: java.lang.invoke.SerializedLambda)
> - object (class
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase$$Lambda$2446/0x00000116e3cb4c30,
>
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase$$Lambda$2446/0x00000116e3cb4c30@72c241e1)
> at
> org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:43)
> at
> org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:50)
> at
> org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:122)
> at
> org.apache.spark.util.SparkClosureCleaner$.clean(SparkClosureCleaner.scala:42)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:2839)
> at
> org.apache.spark.sql.execution.streaming.state.package$StateStoreOps.mapPartitionsWithStateStore(package.scala:67)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase.doExecute(FlatMapGroupsWithStateExec.scala:263)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExecBase.doExecute$(FlatMapGroupsWithStateExec.scala:207)
> at
> org.apache.spark.sql.execution.streaming.FlatMapGroupsWithStateExec.doExecute(FlatMapGroupsWithStateExec.scala:403)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeRDD$1(SparkPlan.scala:188)
> at scala.util.Try$.apply(Try.scala:217)
> at
> org.apache.spark.util.Utils$.doTryWithCallerStacktrace(Utils.scala:1378)
> at org.apache.spark.util.LazyTry.tryT$lzycompute(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.tryT(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.get(LazyTry.scala:58)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:201)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:260)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:257)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:197)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:533)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:461)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:460)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:504)
> at
> org.apache.spark.sql.execution.SerializeFromObjectExec.inputRDDs(objects.scala:117)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:761)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeRDD$1(SparkPlan.scala:188)
> at scala.util.Try$.apply(Try.scala:217)
> at
> org.apache.spark.util.Utils$.doTryWithCallerStacktrace(Utils.scala:1378)
> at org.apache.spark.util.LazyTry.tryT$lzycompute(LazyTry.scala:46)
> at org.apache.spark.util.LazyTry.tryT(LazyTry.scala:46)
> ... 66 more
> Seemingly he want to serialize the Kryo Serializer but this is not possible
> since KryoSerializationCodec$ & scala.Function0 are not serializeable.
> To reproduce this issue:
> Use the following dependencies:
> {code:java}
> <dependency>
> <groupId>org.apache.spark</groupId>
> <artifactId>spark-sql_2.13</artifactId>
> <version>4.0.0</version>
> </dependency>
> <dependency>
> <groupId>org.projectlombok</groupId>
> <artifactId>lombok</artifactId>
> <version>1.18.38</version>
> </dependency> {code}
> And the following code snippet:
> {color:#cc7832}-> See Main.java{color}
> {color:#cc7832}
> {color:#172b4d}If you simply change {color}
> Encoders.kryo(State.class{color})
> to{color:#cc7832}
> Encoders.bean(State.class{color})
> This example starts working
> I could not find a feasible work around so i created this as major issue, i
> hope that fits.
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