[jira] [Created] (SPARK-7565) Broken maps in jsonRDD

["Paul Colomiets (JIRA)" <ji...@apache.org>]

Paul Colomiets created SPARK-7565:
-------------------------------------

             Summary: Broken maps in jsonRDD
                 Key: SPARK-7565
                 URL: https://issues.apache.org/jira/browse/SPARK-7565
             Project: Spark
          Issue Type: Bug
    Affects Versions: 1.4.0
            Reporter: Paul Colomiets


When I use the following JSON:
{code}
{"obj": {"a": "hello"}}
{code}

And load it with the following python code:
{code}
tf = sc.textFile('test.json')
v = sqlContext.jsonRDD(tf, StructType([StructField("obj", MapType(StringType(), StringType()), True)]))
v.save('test.parquet', mode='overwrite')
{code}

I get the following error in spark master branch:
{code}
Py4JJavaError: An error occurred while calling o78.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 5.0 failed 1 times, most recent failure: Lost task 1.0 in stage 5.0 (TID 11, localhost): java.lang.ClassCastException: java.lang.String cannot be cast to org.apache.spark.sql.types.UTF8String
        at org.apache.spark.sql.parquet.RowWriteSupport.writePrimitive(ParquetTableSupport.scala:201)
        at org.apache.spark.sql.parquet.RowWriteSupport.writeValue(ParquetTableSupport.scala:192)
        at org.apache.spark.sql.parquet.RowWriteSupport$$anonfun$writeMap$2.apply(ParquetTableSupport.scala:284)
        at org.apache.spark.sql.parquet.RowWriteSupport$$anonfun$writeMap$2.apply(ParquetTableSupport.scala:281)
        at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
        at scala.collection.immutable.Map$Map1.foreach(Map.scala:109)
        at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
        at org.apache.spark.sql.parquet.RowWriteSupport.writeMap(ParquetTableSupport.scala:281)
        at org.apache.spark.sql.parquet.RowWriteSupport.writeValue(ParquetTableSupport.scala:186)
        at org.apache.spark.sql.parquet.RowWriteSupport.write(ParquetTableSupport.scala:171)
        at org.apache.spark.sql.parquet.RowWriteSupport.write(ParquetTableSupport.scala:134)
        at parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:120)
        at parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:81)
        at parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:37)
        at org.apache.spark.sql.parquet.ParquetRelation2.org$apache$spark$sql$parquet$ParquetRelation2$$writeShard$1(newParquet.scala:699)
        at org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:717)
        at org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:717)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
        at org.apache.spark.scheduler.Task.run(Task.scala:70)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
        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:745)

{code}

This worked well in spark 1.3



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