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Date: Wed, 9 Aug 2017 18:14:00 +0000 (UTC)
From: "Shixiong Zhu (JIRA)" <jira@apache.org>
To: issues@spark.apache.org
Message-ID: <JIRA.13087872.1500366840000.130550.1502302440201@Atlassian.JIRA>
In-Reply-To: <JIRA.13087872.1500366840000@Atlassian.JIRA>
References: <JIRA.13087872.1500366840000@Atlassian.JIRA> <JIRA.13087872.1500366840974@jira-lw-us.apache.org>
Subject: [jira] [Commented] (SPARK-21453) Cached Kafka consumer may be
 closed too early
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archived-at: Wed, 09 Aug 2017 18:14:07 -0000


    [ https://issues.apache.org/jira/browse/SPARK-21453?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16120393#comment-16120393 ] 

Shixiong Zhu commented on SPARK-21453:
--------------------------------------

The error message looks like the Kafka broker storing the record for offset 7591351 is offline/standby. If it can recover fast, you can just restart your query and it will start from the failed point.

> Cached Kafka consumer may be closed too early
> ---------------------------------------------
>
>                 Key: SPARK-21453
>                 URL: https://issues.apache.org/jira/browse/SPARK-21453
>             Project: Spark
>          Issue Type: Bug
>          Components: Structured Streaming
>    Affects Versions: 2.2.0
>         Environment: Spark 2.2.0 and kafka 0.10.2.0
>            Reporter: Pablo Panero
>            Priority: Minor
>
> On a streaming job using built-in kafka source and sink (over SSL), with  I am getting the following exception:
> Config of the source:
> {code:java}
> val df = spark.readStream
>       .format("kafka")
>       .option("kafka.bootstrap.servers", config.bootstrapServers)
>       .option("failOnDataLoss", value = false)
>       .option("kafka.connections.max.idle.ms", 3600000)
>       //SSL: this only applies to communication between Spark and Kafka brokers; you are still responsible for separately securing Spark inter-node communication.
>       .option("kafka.security.protocol", "SASL_SSL")
>       .option("kafka.sasl.mechanism", "GSSAPI")
>       .option("kafka.sasl.kerberos.service.name", "kafka")
>       .option("kafka.ssl.truststore.location", "/etc/pki/java/cacerts")
>       .option("kafka.ssl.truststore.password", "changeit")
>       .option("subscribe", config.topicConfigList.keys.mkString(","))
>       .load()
> {code}
> Config of the sink:
> {code:java}
> .writeStream
>         .option("checkpointLocation", s"${config.checkpointDir}/${topicConfig._1}/")
>         .format("kafka")
>         .option("kafka.bootstrap.servers", config.bootstrapServers)
>         .option("kafka.connections.max.idle.ms", 3600000)
>         //SSL: this only applies to communication between Spark and Kafka brokers; you are still responsible for separately securing Spark inter-node communication.
>         .option("kafka.security.protocol", "SASL_SSL")
>         .option("kafka.sasl.mechanism", "GSSAPI")
>         .option("kafka.sasl.kerberos.service.name", "kafka")
>         .option("kafka.ssl.truststore.location", "/etc/pki/java/cacerts")
>         .option("kafka.ssl.truststore.password", "changeit")
>         .start()
> {code}
> {code:java}
> 17/07/18 10:11:58 WARN SslTransportLayer: Failed to send SSL Close message 
> java.io.IOException: Broken pipe
> 	at sun.nio.ch.FileDispatcherImpl.write0(Native Method)
> 	at sun.nio.ch.SocketDispatcher.write(SocketDispatcher.java:47)
> 	at sun.nio.ch.IOUtil.writeFromNativeBuffer(IOUtil.java:93)
> 	at sun.nio.ch.IOUtil.write(IOUtil.java:65)
> 	at sun.nio.ch.SocketChannelImpl.write(SocketChannelImpl.java:471)
> 	at org.apache.kafka.common.network.SslTransportLayer.flush(SslTransportLayer.java:195)
> 	at org.apache.kafka.common.network.SslTransportLayer.close(SslTransportLayer.java:163)
> 	at org.apache.kafka.common.utils.Utils.closeAll(Utils.java:731)
> 	at org.apache.kafka.common.network.KafkaChannel.close(KafkaChannel.java:54)
> 	at org.apache.kafka.common.network.Selector.doClose(Selector.java:540)
> 	at org.apache.kafka.common.network.Selector.close(Selector.java:531)
> 	at org.apache.kafka.common.network.Selector.pollSelectionKeys(Selector.java:378)
> 	at org.apache.kafka.common.network.Selector.poll(Selector.java:303)
> 	at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:349)
> 	at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:226)
> 	at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:1047)
> 	at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:995)
> 	at org.apache.spark.sql.kafka010.CachedKafkaConsumer.poll(CachedKafkaConsumer.scala:298)
> 	at org.apache.spark.sql.kafka010.CachedKafkaConsumer.org$apache$spark$sql$kafka010$CachedKafkaConsumer$$fetchData(CachedKafkaConsumer.scala:206)
> 	at org.apache.spark.sql.kafka010.CachedKafkaConsumer$$anonfun$get$1.apply(CachedKafkaConsumer.scala:117)
> 	at org.apache.spark.sql.kafka010.CachedKafkaConsumer$$anonfun$get$1.apply(CachedKafkaConsumer.scala:106)
> 	at org.apache.spark.util.UninterruptibleThread.runUninterruptibly(UninterruptibleThread.scala:85)
> 	at org.apache.spark.sql.kafka010.CachedKafkaConsumer.runUninterruptiblyIfPossible(CachedKafkaConsumer.scala:68)
> 	at org.apache.spark.sql.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:106)
> 	at org.apache.spark.sql.kafka010.KafkaSourceRDD$$anon$1.getNext(KafkaSourceRDD.scala:157)
> 	at org.apache.spark.sql.kafka010.KafkaSourceRDD$$anon$1.getNext(KafkaSourceRDD.scala:148)
> 	at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
> 	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> 	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> 	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> 	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> 	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
> 	at org.apache.spark.sql.kafka010.KafkaWriteTask.execute(KafkaWriteTask.scala:47)
> 	at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$1.apply$mcV$sp(KafkaWriter.scala:91)
> 	at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$1.apply(KafkaWriter.scala:91)
> 	at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$1.apply(KafkaWriter.scala:91)
> 	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1337)
> 	at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(KafkaWriter.scala:91)
> 	at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(KafkaWriter.scala:89)
> 	at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
> 	at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:926)
> 	at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
> 	at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
> 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:108)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:748)
> {code}


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