Oh, maybe not. Please file another JIRA.
On Tue, Jul 15, 2014 at 12:34 AM, Pei-Lun Lee <pl...@appier.com> wrote:
> Hi Michael,
>
> Good to know it is being handled. I tried master branch (9fe693b5) and got
> another error:
>
> scala> sqlContext.parquetFile("/tmp/foo")
> java.lang.RuntimeException: Unsupported parquet datatype optional
> fixed_len_byte_array(4) b
> at scala.sys.package$.error(package.scala:27)
> at
> org.apache.spark.sql.parquet.ParquetTypesConverter$.toPrimitiveDataType(ParquetTypes.scala:58)
> at
> org.apache.spark.sql.parquet.ParquetTypesConverter$.toDataType(ParquetTypes.scala:109)
> at
> org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$convertToAttributes$1.apply(ParquetTypes.scala:282)
> at
> org.apache.spark.sql.parquet.ParquetTypesConverter$$anonfun$convertToAttributes$1.apply(ParquetTypes.scala:279)
> ......
>
> The avro schema I used is something like:
>
> protocol Test {
> fixed Bytes4(4);
>
> record User {
> string name;
> int age;
> union {null, int} i;
> union {null, int} j;
> union {null, Bytes4} b;
> union {null, bytes} c;
> union {null, int} d;
> }
> }
>
> Is this case included in SPARK-2446
> <https://issues.apache.org/jira/browse/SPARK-2446>?
>
>
> 2014-07-15 3:54 GMT+08:00 Michael Armbrust <mich...@databricks.com>:
>
> This is not supported yet, but there is a PR open to fix it:
>> https://issues.apache.org/jira/browse/SPARK-2446
>>
>>
>> On Mon, Jul 14, 2014 at 4:17 AM, Pei-Lun Lee <pl...@appier.com> wrote:
>>
>>> Hi,
>>>
>>> I am using spark-sql 1.0.1 to load parquet files generated from method
>>> described in:
>>>
>>> https://gist.github.com/massie/7224868
>>>
>>>
>>> When I try to submit a select query with columns of type fixed length
>>> byte array, the following error pops up:
>>>
>>>
>>> 14/07/14 11:09:14 INFO scheduler.DAGScheduler: Failed to run take at
>>> basicOperators.scala:100
>>> org.apache.spark.SparkDriverExecutionException: Execution error
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.runLocallyWithinThread(DAGScheduler.scala:581)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anon$1.run(DAGScheduler.scala:559)
>>> Caused by: parquet.io.ParquetDecodingException: Can not read value at 0
>>> in block -1 in file s3n://foo/bar/part-r-00000.snappy.parquet
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:177)
>>> at
>>> parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:130)
>>> at
>>> org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:122)
>>> at
>>> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
>>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
>>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
>>> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
>>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>>> at
>>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
>>> at
>>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
>>> at
>>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
>>> at scala.collection.TraversableOnce$class.to
>>> (TraversableOnce.scala:273)
>>> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
>>> at
>>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
>>> at
>>> scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
>>> at
>>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
>>> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
>>> at org.apache.spark.rdd.RDD$$anonfun$27.apply(RDD.scala:989)
>>> at org.apache.spark.rdd.RDD$$anonfun$27.apply(RDD.scala:989)
>>> at
>>> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1083)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.runLocallyWithinThread(DAGScheduler.scala:574)
>>> ... 1 more
>>> Caused by: java.lang.ClassCastException: Expected instance of primitive
>>> converter but got
>>> "org.apache.spark.sql.parquet.CatalystNativeArrayConverter"
>>> at
>>> parquet.io.api.Converter.asPrimitiveConverter(Converter.java:30)
>>> at
>>> parquet.io.RecordReaderImplementation.<init>(RecordReaderImplementation.java:264)
>>> at
>>> parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:60)
>>> at
>>> parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:74)
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:110)
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:172)
>>> ... 24 more
>>>
>>>
>>> Is fixed length byte array supposed to work in this version? I noticed
>>> that other array types like int or string already work.
>>>
>>> Thanks,
>>> --
>>> Pei-Lun
>>>
>>>
>>
>
