Error when saving as parquet to S3 from Spark

[Cosmin Cătălin Sanda <co...@gmail.com>]

After repartitioning a *DataFrame* in *Spark 1.3.0* I get a *.parquet*
exception
when saving to*Amazon's S3*. The data that I try to write is 10G.

logsForDate
    .repartition(10)
    .saveAsParquetFile(destination) // <-- Exception here

The exception I receive is:

java.io.IOException: The file being written is in an invalid state.
Probably caused by an error thrown previously. Current state: COLUMN
at parquet.hadoop.ParquetFileWriter$STATE.error(ParquetFileWriter.java:137)
at parquet.hadoop.ParquetFileWriter$STATE.startBlock(ParquetFileWriter.java:129)
at parquet.hadoop.ParquetFileWriter.startBlock(ParquetFileWriter.java:173)
at parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:152)
at parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:112)
at parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:73)
at org.apache.spark.sql.parquet.ParquetRelation2.org
<http://org.apache.spark.sql.parquet.parquetrelation2.org/>$apache$spark$sql$parquet$ParquetRelation2$$writeShard$1(newParquet.scala:635)
at org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:649)
at org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:649)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
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)

I would like to know what is the problem and how to solve it.
------------------------------------
*Cosmin Catalin SANDA*
Software Systems Engineer
Phone: +45.27.30.60.35