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Posted to issues@spark.apache.org by "Bertrand Bossy (JIRA)" <ji...@apache.org> on 2014/08/14 15:44:11 UTC
[jira] [Updated] (SPARK-3039) Spark assembly for new hadoop API
(hadoop 2) contains avro-mapred for hadoop 1 API
[ https://issues.apache.org/jira/browse/SPARK-3039?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Bertrand Bossy updated SPARK-3039:
----------------------------------
Affects Version/s: 1.1.0
> Spark assembly for new hadoop API (hadoop 2) contains avro-mapred for hadoop 1 API
> ----------------------------------------------------------------------------------
>
> Key: SPARK-3039
> URL: https://issues.apache.org/jira/browse/SPARK-3039
> Project: Spark
> Issue Type: Bug
> Components: Build, Input/Output, Spark Core
> Affects Versions: 0.9.1, 1.0.0, 1.1.0
> Environment: hadoop2, hadoop-2.4.0, HDP-2.1
> Reporter: Bertrand Bossy
>
> The spark assembly contains the artifact "org.apache.avro:avro-mapred" as a dependency of "org.spark-project.hive:hive-serde".
> The avro-mapred package provides a hadoop FileInputFormat to read and write avro files. There are two versions of this package, distinguished by a classifier. avro-mapred for the new Hadoop API uses the classifier "hadoop2". avro-mapred for the old Hadoop API uses no classifier.
> E.g. when reading avro files using
> {code}
> sc.newAPIHadoopFile[AvroKey[SomeClass]],NullWritable,AvroKeyInputFormat[SomeClass]]("hdfs://path/to/file.avro")
> {code}
> The following error occurs:
> {code}
> java.lang.IncompatibleClassChangeError: Found interface org.apache.hadoop.mapreduce.TaskAttemptContext, but class was expected
> at org.apache.avro.mapreduce.AvroKeyInputFormat.createRecordReader(AvroKeyInputFormat.java:47)
> at org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:111)
> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:99)
> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:61)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.rdd.FilteredRDD.compute(FilteredRDD.scala:34)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:158)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
> at org.apache.spark.scheduler.Task.run(Task.scala:51)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> {code}
> This error usually is a hint that there was a mix up of the old and the new Hadoop API. As a work-around, if avro-mapred for hadoop2 is "forced" to appear before the version that is bundled with Spark, reading avro files works fine.
> Also, if Spark is built using avro-mapred for hadoop2, it works fine as well.
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