Hi Team,
Version: 3.2.2
Java Version: 1.8.0_211
Scala Version: 2.12.15
Cluster: Standalone
I am using Spark Streaming to read from Kafka and write to S3. The job
fails with below error if there are no records published to Kafka for a few
days and then there are some records published. Could someone help me in
identifying the root cause of this job failure.
24/01/17 10:49:22 ERROR MicroBatchExecution: Query [id =
72ee1070-7e05-4999-8b55-2a99e216ec51, runId =
0919e548-9706-4757-be94-359848100070] terminated with error
org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find
any valid local directory for s3ablock-0001-
at
org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
at
org.apache.hadoop.fs.s3a.S3AFileSystem.createTmpFileForWrite(S3AFileSystem.java:1019)
at
org.apache.hadoop.fs.s3a.S3ADataBlocks$DiskBlockFactory.create(S3ADataBlocks.java:816)
at
org.apache.hadoop.fs.s3a.S3ABlockOutputStream.createBlockIfNeeded(S3ABlockOutputStream.java:204)
at
org.apache.hadoop.fs.s3a.S3ABlockOutputStream.<init>(S3ABlockOutputStream.java:182)
at
org.apache.hadoop.fs.s3a.S3AFileSystem.create(S3AFileSystem.java:1369)
at org.apache.hadoop.fs.FileSystem.primitiveCreate(FileSystem.java:1305)
at
org.apache.hadoop.fs.DelegateToFileSystem.createInternal(DelegateToFileSystem.java:102)
at
org.apache.hadoop.fs.AbstractFileSystem.create(AbstractFileSystem.java:626)
at org.apache.hadoop.fs.FileContext$3.next(FileContext.java:701)
at org.apache.hadoop.fs.FileContext$3.next(FileContext.java:697)
at org.apache.hadoop.fs.FSLinkResolver.resolve(FSLinkResolver.java:90)
at org.apache.hadoop.fs.FileContext.create(FileContext.java:703)
at
org.apache.spark.sql.execution.streaming.FileContextBasedCheckpointFileManager.createTempFile(CheckpointFileManager.scala:327)
at
org.apache.spark.sql.execution.streaming.CheckpointFileManager$RenameBasedFSDataOutputStream.<init>(CheckpointFileManager.scala:140)
at
org.apache.spark.sql.execution.streaming.CheckpointFileManager$RenameBasedFSDataOutputStream.<init>(CheckpointFileManager.scala:143)
at
org.apache.spark.sql.execution.streaming.FileContextBasedCheckpointFileManager.createAtomic(CheckpointFileManager.scala:333)
at
org.apache.spark.sql.execution.streaming.HDFSMetadataLog.$anonfun$addNewBatchByStream$2(HDFSMetadataLog.scala:173)
at
scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23)
at scala.Option.getOrElse(Option.scala:189)
at
org.apache.spark.sql.execution.streaming.HDFSMetadataLog.addNewBatchByStream(HDFSMetadataLog.scala:171)
at
org.apache.spark.sql.execution.streaming.HDFSMetadataLog.add(HDFSMetadataLog.scala:116)
at
org.apache.spark.sql.execution.streaming.OffsetSeqLog.add(OffsetSeqLog.scala:53)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$constructNextBatch$14(MicroBatchExecution.scala:442)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$constructNextBatch$1(MicroBatchExecution.scala:440)
at
scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.withProgressLocked(MicroBatchExecution.scala:627)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.constructNextBatch(MicroBatchExecution.scala:380)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:210)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:193)
at
org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:57)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:187)
at
org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:303)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:286)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:209)
Dataset<Row> df =
spark
.readStream()
.format("org.apache.spark.sql.kafka010.KafkaSourceProvider")
.options(appConfig.getKafka().getConf())
.load()
.selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)");
df.writeStream()
.foreachBatch(new KafkaS3PipelineImplementation(applicationId, appConfig))
.option("checkpointLocation", appConfig.getChk().getPath())
.start()
.awaitTermination();
Regards,
Abhishek Singla
