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From "Mridul Muralidharan (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-21549) Spark fails to complete job correctly in case of OutputFormat which do not write into hdfs
Date Sat, 07 Oct 2017 03:47:01 GMT

     [ https://issues.apache.org/jira/browse/SPARK-21549?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Mridul Muralidharan resolved SPARK-21549.
-----------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.3.0
                   2.2.1

Issue resolved by pull request 19294
[https://github.com/apache/spark/pull/19294]

> 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
>             Fix For: 2.2.1, 2.3.0
>
>
> 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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