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Posted to commits@hudi.apache.org by "PRASHANT BHOSALE (Jira)" <ji...@apache.org> on 2021/02/25 16:40:00 UTC
[jira] [Updated] (HUDI-1641) Issue for Integrating Hudi with Kafka
using Avro Schema
[ https://issues.apache.org/jira/browse/HUDI-1641?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
PRASHANT BHOSALE updated HUDI-1641:
-----------------------------------
Description:
I am trying to integrate Hudi with Kafka topic.
teps followed :
# Created Kafka topic in Confluent with schema defined in schema registry.
# Using kafka-avro-console-producer, I am trying to produce data.
# Running Hudi Delta Streamer in continuous mode to consume the data.
Infrastructure :
# AWS EMR
# Spark 2.4.4
# Hudi Utility ( Tried with 0.6.0 and 0.7.0 )
# Avro ( Tried avro-1.8.2, avro-1.9.2 and avro-1.10.0 )
{code:java}
21/02/24 13:02:08 ERROR TaskResultGetter: Exception while getting task result
org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.
at org.apache.spark.serializer.GenericAvroSerializer$$anonfun$4.apply(GenericAvroSerializer.scala:141)
at org.apache.spark.serializer.GenericAvroSerializer$$anonfun$4.apply(GenericAvroSerializer.scala:138)
at scala.collection.mutable.HashMap.getOrElseUpdate(HashMap.scala:79)
at org.apache.spark.serializer.GenericAvroSerializer.deserializeDatum(GenericAvroSerializer.scala:137)
at org.apache.spark.serializer.GenericAvroSerializer.read(GenericAvroSerializer.scala:162)
at org.apache.spark.serializer.GenericAvroSerializer.read(GenericAvroSerializer.scala:47)
at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:731)
at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:391)
at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:302)
at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:813)
at org.apache.spark.serializer.KryoSerializerInstance.deserialize(KryoSerializer.scala:371)
at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:88)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply$mcV$sp(TaskResultGetter.scala:72)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply(TaskResultGetter.scala:63)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply(TaskResultGetter.scala:63)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3.run(TaskResultGetter.scala:62)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
21/02/24 13:02:08 INFO YarnScheduler: Removed TaskSet 1.0, whose tasks have all completed, from pool
21/02/24 13:02:08 INFO YarnScheduler: Cancelling stage 1
21/02/24 13:02:08 INFO YarnScheduler: Killing all running tasks in stage 1: Stage cancelled
21/02/24 13:02:08 INFO DAGScheduler: ResultStage 1 (isEmpty at DeltaSync.java:380) failed in 1.415 s due to Job aborted due to stage failure: Exception while getting task result: org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.
21/02/24 13:02:08 INFO DAGScheduler: Job 5 failed: isEmpty at DeltaSync.java:380, took 1.422265 s
21/02/24 13:02:08 ERROR HoodieDeltaStreamer: Shutting down delta-sync due to exception
org.apache.spark.SparkException: Job aborted due to stage failure: Exception while getting task result: org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2041)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2029)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2028)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2028)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:966)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2262)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2211)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2200)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:777)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1364)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.take(RDD.scala:1337)
at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply$mcZ$sp(RDD.scala:1472)
at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1472)
at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1472)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.isEmpty(RDD.scala:1471)
at org.apache.spark.api.java.JavaRDDLike$class.isEmpty(JavaRDDLike.scala:544)
at org.apache.spark.api.java.AbstractJavaRDDLike.isEmpty(JavaRDDLike.scala:45)
at org.apache.hudi.utilities.deltastreamer.DeltaSync.readFromSource(DeltaSync.java:380)
at org.apache.hudi.utilities.deltastreamer.DeltaSync.syncOnce(DeltaSync.java:255)
at org.apache.hudi.utilities.deltastreamer.HoodieDeltaStreamer$DeltaSyncService.lambda$startService$0(HoodieDeltaStreamer.java:587)
at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1604)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
{code}
was:
I am trying to integrate Hudi with Kafka topic.
Steps followed :
# Created Kafka topic in confluent with schema defined.
# Using kafka-avro-console-producer, I am trying to produce data.
# I am running Hudi Delta Streamer in continuous mode.
I am getting the below error :
{code:java}
21/02/25 13:48:14 ERROR TaskResultGetter: Exception while getting task result21/02/25 13:48:14 ERROR TaskResultGetter: Exception while getting task resultorg.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context. at org.apache.spark.serializer.GenericAvroSerializer$$anonfun$4.apply(GenericAvroSerializer.scala:141) at org.apache.spark.serializer.GenericAvroSerializer$$anonfun$4.apply(GenericAvroSerializer.scala:138) at scala.collection.mutable.HashMap.getOrElseUpdate(HashMap.scala:79) at org.apache.spark.serializer.GenericAvroSerializer.deserializeDatum(GenericAvroSerializer.scala:137) at org.apache.spark.serializer.GenericAvroSerializer.read(GenericAvroSerializer.scala:162) at org.apache.spark.serializer.GenericAvroSerializer.read(GenericAvroSerializer.scala:47) at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:731) at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:391) at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:302) at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:813) at org.apache.spark.serializer.KryoSerializerInstance.deserialize(KryoSerializer.scala:371) at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:88) at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply$mcV$sp(TaskResultGetter.scala:72) at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply(TaskResultGetter.scala:63) at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply(TaskResultGetter.scala:63) at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945) at org.apache.spark.scheduler.TaskResultGetter$$anon$3.run(TaskResultGetter.scala:62) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)21/02/25 13:48:14 INFO YarnScheduler: Removed TaskSet 14.0, whose tasks have all completed, from pool 21/02/25 13:48:14 INFO YarnScheduler: Cancelling stage 1421/02/25 13:48:14 INFO YarnScheduler: Killing all running tasks in stage 14: Stage cancelled21/02/25 13:48:14 INFO DAGScheduler: ResultStage 14 (isEmpty at DeltaSync.java:380) failed in 0.696 s due to Job aborted due to stage failure: Exception while getting task result: org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.21/02/25 13:48:14 INFO DAGScheduler: Job 8 failed: isEmpty at DeltaSync.java:380, took 0.704193 s21/02/25 13:48:14 ERROR HoodieDeltaStreamer: Shutting down delta-sync due to exceptionorg.apache.spark.SparkException: Job aborted due to stage failure: Exception while getting task result: org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context. at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2041) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2029) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2028) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2028) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:966) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2262) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2211) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2200) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:777) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101) at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1364) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at org.apache.spark.rdd.RDD.take(RDD.scala:1337) at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply$mcZ$sp(RDD.scala:1472) at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1472) at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1472) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at org.apache.spark.rdd.RDD.isEmpty(RDD.scala:1471) at org.apache.spark.api.java.JavaRDDLike$class.isEmpty(JavaRDDLike.scala:544) at org.apache.spark.api.java.AbstractJavaRDDLike.isEmpty(JavaRDDLike.scala:45) at org.apache.hudi.utilities.deltastreamer.DeltaSync.readFromSource(DeltaSync.java:380) at org.apache.hudi.utilities.deltastreamer.DeltaSync.syncOnce(DeltaSync.java:255) at org.apache.hudi.utilities.deltastreamer.HoodieDeltaStreamer$DeltaSyncService.lambda$startService$0(HoodieDeltaStreamer.java:587) at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1604) 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)
{code}
Can someone please have a look at this and guide me if I need to see at any of my configurations in order to fix this.
> Issue for Integrating Hudi with Kafka using Avro Schema
> -------------------------------------------------------
>
> Key: HUDI-1641
> URL: https://issues.apache.org/jira/browse/HUDI-1641
> Project: Apache Hudi
> Issue Type: Bug
> Components: DeltaStreamer, Spark Integration, Utilities
> Reporter: PRASHANT BHOSALE
> Priority: Major
> Fix For: 0.7.0
>
>
> I am trying to integrate Hudi with Kafka topic.
> teps followed :
> # Created Kafka topic in Confluent with schema defined in schema registry.
> # Using kafka-avro-console-producer, I am trying to produce data.
> # Running Hudi Delta Streamer in continuous mode to consume the data.
> Infrastructure :
> # AWS EMR
> # Spark 2.4.4
> # Hudi Utility ( Tried with 0.6.0 and 0.7.0 )
> # Avro ( Tried avro-1.8.2, avro-1.9.2 and avro-1.10.0 )
> {code:java}
> 21/02/24 13:02:08 ERROR TaskResultGetter: Exception while getting task result
> org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.
> at org.apache.spark.serializer.GenericAvroSerializer$$anonfun$4.apply(GenericAvroSerializer.scala:141)
> at org.apache.spark.serializer.GenericAvroSerializer$$anonfun$4.apply(GenericAvroSerializer.scala:138)
> at scala.collection.mutable.HashMap.getOrElseUpdate(HashMap.scala:79)
> at org.apache.spark.serializer.GenericAvroSerializer.deserializeDatum(GenericAvroSerializer.scala:137)
> at org.apache.spark.serializer.GenericAvroSerializer.read(GenericAvroSerializer.scala:162)
> at org.apache.spark.serializer.GenericAvroSerializer.read(GenericAvroSerializer.scala:47)
> at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:731)
> at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:391)
> at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:302)
> at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:813)
> at org.apache.spark.serializer.KryoSerializerInstance.deserialize(KryoSerializer.scala:371)
> at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:88)
> at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply$mcV$sp(TaskResultGetter.scala:72)
> at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply(TaskResultGetter.scala:63)
> at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$1.apply(TaskResultGetter.scala:63)
> at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
> at org.apache.spark.scheduler.TaskResultGetter$$anon$3.run(TaskResultGetter.scala:62)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> 21/02/24 13:02:08 INFO YarnScheduler: Removed TaskSet 1.0, whose tasks have all completed, from pool
> 21/02/24 13:02:08 INFO YarnScheduler: Cancelling stage 1
> 21/02/24 13:02:08 INFO YarnScheduler: Killing all running tasks in stage 1: Stage cancelled
> 21/02/24 13:02:08 INFO DAGScheduler: ResultStage 1 (isEmpty at DeltaSync.java:380) failed in 1.415 s due to Job aborted due to stage failure: Exception while getting task result: org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.
> 21/02/24 13:02:08 INFO DAGScheduler: Job 5 failed: isEmpty at DeltaSync.java:380, took 1.422265 s
> 21/02/24 13:02:08 ERROR HoodieDeltaStreamer: Shutting down delta-sync due to exception
> org.apache.spark.SparkException: Job aborted due to stage failure: Exception while getting task result: org.apache.spark.SparkException: Error reading attempting to read avro data -- encountered an unknown fingerprint: 103427103938146401, not sure what schema to use. This could happen if you registered additional schemas after starting your spark context.
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2041)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2029)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2028)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2028)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966)
> at scala.Option.foreach(Option.scala:257)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:966)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2262)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2211)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2200)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:777)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1364)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
> at org.apache.spark.rdd.RDD.take(RDD.scala:1337)
> at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply$mcZ$sp(RDD.scala:1472)
> at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1472)
> at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1472)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
> at org.apache.spark.rdd.RDD.isEmpty(RDD.scala:1471)
> at org.apache.spark.api.java.JavaRDDLike$class.isEmpty(JavaRDDLike.scala:544)
> at org.apache.spark.api.java.AbstractJavaRDDLike.isEmpty(JavaRDDLike.scala:45)
> at org.apache.hudi.utilities.deltastreamer.DeltaSync.readFromSource(DeltaSync.java:380)
> at org.apache.hudi.utilities.deltastreamer.DeltaSync.syncOnce(DeltaSync.java:255)
> at org.apache.hudi.utilities.deltastreamer.HoodieDeltaStreamer$DeltaSyncService.lambda$startService$0(HoodieDeltaStreamer.java:587)
> at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1604)
> 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)
> {code}
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