numberlabs-developers / hudi

Upserts, Deletes And Incremental Processing on Big Data.
https://hudi.apache.org/
Apache License 2.0
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[SUPPORT] Hi After Creating the table using hudi with 0 #188

Open torvalds-dev-testbot[bot] opened 10 months ago

torvalds-dev-testbot[bot] commented 10 months ago

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Describe the problem you faced Hi After Creating the table using hudi with 0.14.0 in spark 3.3, while reading I am not able to read the table throwing below error. But i am able to query using sql table or in athena but not directly from a path. at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.isNullAt(OnHeapColumnVector.java:130) at org.apache.spark.sql.vectorized.ColumnarBatchRow.isNullAt(ColumnarBatchRow.java:96) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.writeFields_0_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source) at org.apache.spark.sql.execution.RowDataSourceScanExec.$anonfun$doExecute$2(DataSourceScanExec.scala:131) at scala.collection.Iterator$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:384) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365) at org.apache.spark.rdd.RDD.iterator(RDD.scala:329) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:138) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1516) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:750)

Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2863) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2799) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2798) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2798) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1239) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1239) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1239) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3051) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2993) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2982) at org.apache.spark.util.EventLoop$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:1009) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2229) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2250) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2269) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:533) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:486) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3932) at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2904) at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:3922) at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:552) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3920) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:224) at org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:114) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$7(SQLExecution.scala:139) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:224) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:139) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:245) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:138) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3920) at org.apache.spark.sql.Dataset.head(Dataset.scala:2904) at org.apache.spark.sql.Dataset.take(Dataset.scala:3125) at org.apache.spark.sql.Dataset.takeAsList(Dataset.scala:3148) at org.apache.zeppelin.spark.Spark3Shims.showDataFrame(Spark3Shims.java:74) at org.apache.zeppelin.spark.SparkZeppelinContext.showData(SparkZeppelinContext.scala:70) at org.apache.zeppelin.interpreter.ZeppelinContext.showData(ZeppelinContext.java:67) at org.apache.zeppelin.interpreter.ZeppelinContext.show(ZeppelinContext.java:428) at org.apache.zeppelin.interpreter.ZeppelinContext.show(ZeppelinContext.java:414) A clear and concise description of the problem.

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