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https://issues.apache.org/jira/browse/KAFKA-5649?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16721376#comment-16721376
]
Julian commented on KAFKA-5649:
-------------------------------
We have live Production streams for Structured Streaming and we are also
getting this error ({color:#333333}Failed to send SSL Close message{color})
every 1-2 hours for a given batch. We have cleared up most other errors now, so
this is seemingly the last enemy to solve. Actually, we are also losing data
but still need to investigate if that is directly related. For sure, it causes
the streaming process to stutter.
I also see this listed as a reopened Spark issue
(https://issues.apache.org/jira/browse/SPARK-21453) against Spark 2.2 which I
have commented on. My exact errors are there.
> Producer is being closed generating ssl exception
> -------------------------------------------------
>
> Key: KAFKA-5649
> URL: https://issues.apache.org/jira/browse/KAFKA-5649
> Project: Kafka
> Issue Type: Bug
> Components: producer
> Affects Versions: 0.10.2.1
> Environment: Spark 2.2.0 and kafka 0.10.2.0
> Reporter: Pablo Panero
> Priority: Major
>
> On a streaming job using built-in kafka source and sink (over SSL), with I am
> getting the following exception:
> 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}
> And in some cases it throws the exception making the spark job stuck in that
> step. Exception stack trace is the following:
> {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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