Archit jain created SPARK-36517: ----------------------------------- Summary: spark-sql-kafka source in spark 2.4.2 causes reading stream failure frequently Key: SPARK-36517 URL: https://issues.apache.org/jira/browse/SPARK-36517 Project: Spark Issue Type: Bug Components: Structured Streaming Affects Versions: 2.4.2 Reporter: Archit jain
Hi Team, I am getting the below error intermittently **due to which I am facing a data loss issue in the application. The packets consumed are not equal to the packets produced. *[ERROR] o.a.s.e.Executor:91 [Executor task launch worker for task 6503931] - Exception in task 17.0 in stage 89080.0 (TID 6503931) java.util.concurrent.TimeoutException: Cannot fetch record for offset 43751946 in 7168 milliseconds* *Stack Trace:* {code:java} [ERROR] o.a.s.e.Executor:91 [Executor task launch worker for task 6503931] - Exception in task 17.0 in stage 89080.0 (TID 6503931) java.util.concurrent.TimeoutException: Cannot fetch record for offset 43751946 in 7168 milliseconds at org.apache.spark.sql.kafka010.InternalKafkaConsumer.fetchData(KafkaDataConsumer.scala:489) at org.apache.spark.sql.kafka010.InternalKafkaConsumer.fetchRecord(KafkaDataConsumer.scala:361) at org.apache.spark.sql.kafka010.InternalKafkaConsumer.$anonfun$get$1(KafkaDataConsumer.scala:251) at org.apache.spark.util.UninterruptibleThread.runUninterruptibly(UninterruptibleThread.scala:77) at org.apache.spark.sql.kafka010.InternalKafkaConsumer.runUninterruptiblyIfPossible(KafkaDataConsumer.scala:209) at org.apache.spark.sql.kafka010.InternalKafkaConsumer.get(KafkaDataConsumer.scala:234) at org.apache.spark.sql.kafka010.KafkaDataConsumer.get(KafkaDataConsumer.scala:64) at org.apache.spark.sql.kafka010.KafkaDataConsumer.get$(KafkaDataConsumer.scala:59) at org.apache.spark.sql.kafka010.KafkaDataConsumer$NonCachedKafkaDataConsumer.get(KafkaDataConsumer.scala:506) at org.apache.spark.sql.kafka010.KafkaMicroBatchInputPartitionReader.next(KafkaMicroBatchReader.scala:357) at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:49) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$2.hasNext(WholeStageCodegenExec.scala:636) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$2(WriteToDataSourceV2Exec.scala:117) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:116) at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.$anonfun$doExecute$2(WriteToDataSourceV2Exec.scala:67) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) {code} I am using the below spark and kafka versions: {code:java} <spark.version>2.4.2</spark.version> <kafka.version>2.2.1</kafka.version> <scala.tools.version>2.12</scala.tools.version>{code} My pom looks like this: {code:java} <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-sql-kafka-0-10_${scala.tools.version}</artifactId> <version>${spark.version}</version> </dependency> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-sql_${scala.tools.version}</artifactId> <version>${spark.version}</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-clients</artifactId> <version>${kafka.version}</version> </dependency> {code} Can you please help here. Thanks Archit Jain -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org