[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Story Points: 4
> Use Spark SerializableConfiguration to avoid NPE in Kryo serde
> --
>
> Key: HUDI-7809
> URL: https://issues.apache.org/jira/browse/HUDI-7809
> Project: Apache Hudi
> Issue Type: Improvement
>Reporter: Ethan Guo
>Assignee: Ethan Guo
>Priority: Major
> Labels: hoodie-storage, pull-request-available
> Fix For: 0.15.0, 1.0.0
>
>
> With Hudi 0.14.1, without
> "spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi
> query in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the
> Kryo registratrar, the Hudi read throws NPE due to HadoopStorageConfiguration.
> {code:java}
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
> at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
> 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.Dataset.withAction(Dataset.scala:3704)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
> ... 47 elided
> Caused by: java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522)
> at
>
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Sprint: Sprint 2023-04-26 (was: Sprint 2023-04-26, Sprint 2023-04-27)
> Use Spark SerializableConfiguration to avoid NPE in Kryo serde
> --
>
> Key: HUDI-7809
> URL: https://issues.apache.org/jira/browse/HUDI-7809
> Project: Apache Hudi
> Issue Type: Improvement
>Reporter: Ethan Guo
>Assignee: Ethan Guo
>Priority: Major
> Labels: hoodie-storage, pull-request-available
> Fix For: 0.15.0, 1.0.0
>
>
> With Hudi 0.14.1, without
> "spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi
> query in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the
> Kryo registratrar, the Hudi read throws NPE due to HadoopStorageConfiguration.
> {code:java}
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
> at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$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.Dataset.withAction(Dataset.scala:3704)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
> ... 47 elided
> Caused by: java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522)
> at
>
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Sprint: Sprint 2023-04-26, Sprint 2023-04-27 (was: Sprint 2023-04-26)
> Use Spark SerializableConfiguration to avoid NPE in Kryo serde
> --
>
> Key: HUDI-7809
> URL: https://issues.apache.org/jira/browse/HUDI-7809
> Project: Apache Hudi
> Issue Type: Improvement
>Reporter: Ethan Guo
>Assignee: Ethan Guo
>Priority: Major
> Labels: hoodie-storage, pull-request-available
> Fix For: 0.15.0, 1.0.0
>
>
> With Hudi 0.14.1, without
> "spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi
> query in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the
> Kryo registratrar, the Hudi read throws NPE due to HadoopStorageConfiguration.
> {code:java}
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
> at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
> 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.Dataset.withAction(Dataset.scala:3704)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
> ... 47 elided
> Caused by: java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522)
> at
>
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Sprint: Sprint 2023-04-26
> Use Spark SerializableConfiguration to avoid NPE in Kryo serde
> --
>
> Key: HUDI-7809
> URL: https://issues.apache.org/jira/browse/HUDI-7809
> Project: Apache Hudi
> Issue Type: Improvement
>Reporter: Ethan Guo
>Assignee: Ethan Guo
>Priority: Major
> Labels: hoodie-storage, pull-request-available
> Fix For: 0.15.0, 1.0.0
>
>
> With Hudi 0.14.1, without
> "spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi
> query in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the
> Kryo registratrar, the Hudi read throws NPE due to HadoopStorageConfiguration.
> {code:java}
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
> at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$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.Dataset.withAction(Dataset.scala:3704)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
> ... 47 elided
> Caused by: java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522)
> at
>
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated HUDI-7809:
-
Labels: hoodie-storage pull-request-available (was: hoodie-storage)
> Use Spark SerializableConfiguration to avoid NPE in Kryo serde
> --
>
> Key: HUDI-7809
> URL: https://issues.apache.org/jira/browse/HUDI-7809
> Project: Apache Hudi
> Issue Type: Improvement
>Reporter: Ethan Guo
>Assignee: Ethan Guo
>Priority: Major
> Labels: hoodie-storage, pull-request-available
> Fix For: 0.15.0, 1.0.0
>
>
> With Hudi 0.14.1, without
> "spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi
> query in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the
> Kryo registratrar, the Hudi read throws NPE due to HadoopStorageConfiguration.
> {code:java}
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
> at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
> 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.Dataset.withAction(Dataset.scala:3704)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
> ... 47 elided
> Caused by: java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
> at
> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522)
> at
>
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Description:
With Hudi 0.14.1, without
"spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi query
in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the Kryo
registratrar, the Hudi read throws NPE due to HadoopStorageConfiguration.
{code:java}
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
at scala.Option.foreach(Option.scala:407)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$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.Dataset.withAction(Dataset.scala:3704)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
... 47 elided
Caused by: java.lang.NullPointerException
at
org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
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.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
org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
at
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Description:
With Hudi 0.14.1, without
"spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar", Hudi query
in Spark quick start guide succeeds. In Hudi 0.15.0-rc2, without the Kryo
registratrar, the
{code:java}
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
at scala.Option.foreach(Option.scala:407)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$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.Dataset.withAction(Dataset.scala:3704)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
... 47 elided
Caused by: java.lang.NullPointerException
at
org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
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.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[
https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ethan Guo updated HUDI-7809:
Description:
With 0.14
{code:java}
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
at scala.Option.foreach(Option.scala:407)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$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.Dataset.withAction(Dataset.scala:3704)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2728)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2935)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:326)
at org.apache.spark.sql.Dataset.show(Dataset.scala:806)
at org.apache.spark.sql.Dataset.show(Dataset.scala:765)
at org.apache.spark.sql.Dataset.show(Dataset.scala:774)
... 47 elided
Caused by: java.lang.NullPointerException
at
org.apache.spark.sql.execution.datasources.parquet.Spark32LegacyHoodieParquetFileFormat.$anonfun$buildReaderWithPartitionValues$2(Spark32LegacyHoodieParquetFileFormat.scala:152)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:187)
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.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[ https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Ethan Guo updated HUDI-7809: Fix Version/s: 0.15.0 1.0.0 > Use Spark SerializableConfiguration to avoid NPE in Kryo serde > -- > > Key: HUDI-7809 > URL: https://issues.apache.org/jira/browse/HUDI-7809 > Project: Apache Hudi > Issue Type: Improvement >Reporter: Ethan Guo >Assignee: Ethan Guo >Priority: Major > Fix For: 0.15.0, 1.0.0 > > -- This message was sent by Atlassian Jira (v8.20.10#820010)
[jira] [Updated] (HUDI-7809) Use Spark SerializableConfiguration to avoid NPE in Kryo serde
[ https://issues.apache.org/jira/browse/HUDI-7809?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Ethan Guo updated HUDI-7809: Labels: hoodie-storage (was: ) > Use Spark SerializableConfiguration to avoid NPE in Kryo serde > -- > > Key: HUDI-7809 > URL: https://issues.apache.org/jira/browse/HUDI-7809 > Project: Apache Hudi > Issue Type: Improvement >Reporter: Ethan Guo >Assignee: Ethan Guo >Priority: Major > Labels: hoodie-storage > Fix For: 0.15.0, 1.0.0 > > -- This message was sent by Atlassian Jira (v8.20.10#820010)
