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https://issues.apache.org/jira/browse/SPARK-21549?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16171393#comment-16171393
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Steve Loughran commented on SPARK-21549:
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Linking to SPARK-20045, which highlights the commit logic, especially the abort
code, needs to be resilient to failures, including that of the invoked
{{OutputCommitter.abort()}} calls from raising exceptions. While people
implementing committers should be expected to write resilient abort routines,
you can't rely on it. Same for calling fs.delete()...it could also fall, so
wrapping everything in an exception handler would at least make abort resilient.
> Spark fails to complete job correctly in case of OutputFormat which do not
> write into hdfs
> ------------------------------------------------------------------------------------------
>
> Key: SPARK-21549
> URL: https://issues.apache.org/jira/browse/SPARK-21549
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.2.0
> Environment: spark 2.2.0
> scala 2.11
> Reporter: Sergey Zhemzhitsky
>
> Spark fails to complete job correctly in case of custom OutputFormat
> implementations.
> There are OutputFormat implementations which do not need to use
> *mapreduce.output.fileoutputformat.outputdir* standard hadoop property.
> [But spark reads this property from the
> configuration|https://github.com/apache/spark/blob/v2.2.0/core/src/main/scala/org/apache/spark/internal/io/SparkHadoopMapReduceWriter.scala#L79]
> while setting up an OutputCommitter
> {code:javascript}
> val committer = FileCommitProtocol.instantiate(
> className = classOf[HadoopMapReduceCommitProtocol].getName,
> jobId = stageId.toString,
> outputPath = conf.value.get("mapreduce.output.fileoutputformat.outputdir"),
> isAppend = false).asInstanceOf[HadoopMapReduceCommitProtocol]
> committer.setupJob(jobContext)
> {code}
> ... and then uses this property later on while [commiting the
> job|https://github.com/apache/spark/blob/v2.2.0/core/src/main/scala/org/apache/spark/internal/io/HadoopMapReduceCommitProtocol.scala#L132],
> [aborting the
> job|https://github.com/apache/spark/blob/v2.2.0/core/src/main/scala/org/apache/spark/internal/io/HadoopMapReduceCommitProtocol.scala#L141],
> [creating task's temp
> path|https://github.com/apache/spark/blob/v2.2.0/core/src/main/scala/org/apache/spark/internal/io/HadoopMapReduceCommitProtocol.scala#L95]
> In that cases when the job completes then following exception is thrown
> {code}
> Can not create a Path from a null string
> java.lang.IllegalArgumentException: Can not create a Path from a null string
> at org.apache.hadoop.fs.Path.checkPathArg(Path.java:123)
> at org.apache.hadoop.fs.Path.<init>(Path.java:135)
> at org.apache.hadoop.fs.Path.<init>(Path.java:89)
> at
> org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.absPathStagingDir(HadoopMapReduceCommitProtocol.scala:58)
> at
> org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.abortJob(HadoopMapReduceCommitProtocol.scala:141)
> at
> org.apache.spark.internal.io.SparkHadoopMapReduceWriter$.write(SparkHadoopMapReduceWriter.scala:106)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1085)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:1085)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:1085)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
> at
> org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:1084)
> ...
> {code}
> So it seems that all the jobs which use OutputFormats which don't write data
> into HDFS-compatible file systems are broken.
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