[ 
https://issues.apache.org/jira/browse/SPARK-3039?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14238197#comment-14238197
 ] 

Derrick Burns edited comment on SPARK-3039 at 12/8/14 6:29 PM:
---------------------------------------------------------------

Spark 1.1.1/Hadoop 1.0.4 built using maven with:

{code:xml}
      <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.10</artifactId>
        <version>1.1.1</version>
      </dependency>
      <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.10</artifactId>
        <version>1.1.1</version>
      </dependency>
      <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-mllib_2.10</artifactId>
        <version>1.1.1</version>
      </dependency>
{code}

The code is rather trivial:

{code}
    val sc = new SparkContext(sparkConf)
    val sqlContext = new org.apache.spark.sql.SQLContext(sc)
    val tweets = sqlContext.jsonFile(path).cache()
    tweets.saveAsParquetFile("tweets.parquet")
{code}

Here is the stack trace:

{code}
java.lang.IncompatibleClassChangeError: Found class 
org.apache.hadoop.mapreduce.TaskAttemptContext, but interface was expected
        at 
org.apache.spark.sql.parquet.AppendingParquetOutputFormat.getDefaultWorkFile(ParquetTableOperations.scala:334)
        at 
parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:251)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:300)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:744)
14/12/08 10:21:06 ERROR executor.ExecutorUncaughtExceptionHandler: Uncaught 
exception in thread Thread[Executor task launch worker-0,5,main]
java.lang.IncompatibleClassChangeError: Found class 
org.apache.hadoop.mapreduce.TaskAttemptContext, but interface was expected
        at 
org.apache.spark.sql.parquet.AppendingParquetOutputFormat.getDefaultWorkFile(ParquetTableOperations.scala:334)
        at 
parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:251)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:300)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
        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}



was (Author: derrickburns):
Spark 1.1.1/Hadoop 1.0.4 built using maven with:

{code:xml}
      <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.10</artifactId>
        <version>1.1.1</version>
      </dependency>
      <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.10</artifactId>
        <version>1.1.1</version>
      </dependency>
      <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-mllib_2.10</artifactId>
        <version>1.1.1</version>
      </dependency>
{code}

Here is the stack trace:

{code}
java.lang.IncompatibleClassChangeError: Found class 
org.apache.hadoop.mapreduce.TaskAttemptContext, but interface was expected
        at 
org.apache.spark.sql.parquet.AppendingParquetOutputFormat.getDefaultWorkFile(ParquetTableOperations.scala:334)
        at 
parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:251)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:300)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:744)
14/12/08 10:21:06 ERROR executor.ExecutorUncaughtExceptionHandler: Uncaught 
exception in thread Thread[Executor task launch worker-0,5,main]
java.lang.IncompatibleClassChangeError: Found class 
org.apache.hadoop.mapreduce.TaskAttemptContext, but interface was expected
        at 
org.apache.spark.sql.parquet.AppendingParquetOutputFormat.getDefaultWorkFile(ParquetTableOperations.scala:334)
        at 
parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:251)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable.org$apache$spark$sql$parquet$InsertIntoParquetTable$$writeShard$1(ParquetTableOperations.scala:300)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at 
org.apache.spark.sql.parquet.InsertIntoParquetTable$$anonfun$saveAsHadoopFile$1.apply(ParquetTableOperations.scala:318)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
        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}


> 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
>            Assignee: Bertrand Bossy
>             Fix For: 1.2.0
>
>
> 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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