Filed SPARK-2446
2014-07-15 16:17 GMT+08:00 Michael Armbrust <mich...@databricks.com>:
> 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
>>>>
>>>>
>>>
>>
>
