[
https://issues.apache.org/jira/browse/SPARK-5508?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14368493#comment-14368493
]
Yin Huai commented on SPARK-5508:
---------------------------------
I tried the following snippet in sparkShell
{code}
import sqlContext._
jsonRDD(sc.parallelize("""{"a":[1,2,3,4]}""" :: Nil)).registerTempTable("jt")
sql("set spark.sql.parquet.useDataSourceApi=false")
sql("create table jt_hive_parquet stored as parquet as select * from jt")
sql("set spark.sql.parquet.useDataSourceApi=true")
table("jt_hive_parquet").show
{code}
Seems the array value is null.
A workaround of this is set the following and then use HiveTableScan to read
the data.
{code}
sql("set spark.sql.parquet.useDataSourceApi=false")
sql("set spark.sql.hive.convertMetastoreParquet=false")
{code}
The array will be correctly read.
The metadata dump and file dump of the file is
{code}
creator: parquet-mr version 1.6.0rc3 (build
d4d5a07ec9bd262ca1e93c309f1d7d4a74ebda4c)
file schema: hive_schema
--------------------------------------------------------------------------------
a: OPTIONAL F:1
.bag: REPEATED F:1
..array_element: OPTIONAL INT64 R:1 D:3
row group 1: RC:1 TS:86 OFFSET:4
--------------------------------------------------------------------------------
a:
.bag:
..array_element: INT64 UNCOMPRESSED DO:0 FPO:4 SZ:86/86/1.00 VC:4 ENC:RLE,PLAIN
{code}
{code}
row group 0
--------------------------------------------------------------------------------
a:
.bag:
..array_element: INT64 UNCOMPRESSED DO:0 FPO:4 SZ:86/86/1.00 VC:4 ENC:RLE,PLAIN
a.bag.array_element TV=4 RL=1 DL=3
----------------------------------------------------------------------------
page 0: DLE:RLE RLE:RLE VLE:PLAIN SZ:45 VC:4
INT64 a.bag.array_element
--------------------------------------------------------------------------------
*** row group 1 of 1, values 1 to 4 ***
value 1: R:0 D:3 V:1
value 2: R:1 D:3 V:2
value 3: R:1 D:3 V:3
value 4: R:1 D:3 V:4
{code}
The metadata dump and file dump of a data source parquet file (generated
through Parquet2Relation2) is
{code}
creator: parquet-mr version 1.6.0rc3 (build
d4d5a07ec9bd262ca1e93c309f1d7d4a74ebda4c)
extra: org.apache.spark.sql.parquet.row.metadata =
{"type":"struct","fields":[{"name":"a","type":{"type":"array","elementType":"long","containsNull":true},"nullable":true,"metadata":{}}]}
file schema: root
--------------------------------------------------------------------------------
a: OPTIONAL F:1
.bag: REPEATED F:1
..array: OPTIONAL INT64 R:1 D:3
row group 1: RC:1 TS:86 OFFSET:4
--------------------------------------------------------------------------------
a:
.bag:
..array: INT64 UNCOMPRESSED DO:0 FPO:4 SZ:86/86/1.00 VC:4 ENC:PLAIN,RLE
{code}
{code}
row group 0
--------------------------------------------------------------------------------
a:
.bag:
..array: INT64 UNCOMPRESSED DO:0 FPO:4 SZ:86/86/1.00 VC:4 ENC:PLAIN,RLE
a.bag.array TV=4 RL=1 DL=3
----------------------------------------------------------------------------
page 0: DLE:RLE RLE:RLE VLE:PLAIN SZ:45 VC:4
INT64 a.bag.array
--------------------------------------------------------------------------------
*** row group 1 of 1, values 1 to 4 ***
value 1: R:0 D:3 V:1
value 2: R:1 D:3 V:2
value 3: R:1 D:3 V:3
value 4: R:1 D:3 V:4
{code}
> Arrays and Maps stored with Hive Parquet Serde may not be able to read by the
> Parquet support in the Data Souce API
> -------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-5508
> URL: https://issues.apache.org/jira/browse/SPARK-5508
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.2.1
> Environment: mesos, cdh
> Reporter: Ayoub Benali
> Labels: hivecontext, parquet
>
> When the table is saved as parquet, we cannot query a field which is an array
> of struct after an INSERT statement, like show bellow:
> {noformat}
> scala> val data1="""{
> | "timestamp": 1422435598,
> | "data_array": [
> | {
> | "field1": 1,
> | "field2": 2
> | }
> | ]
> | }"""
> scala> val data2="""{
> | "timestamp": 1422435598,
> | "data_array": [
> | {
> | "field1": 3,
> | "field2": 4
> | }
> | ]
> scala> val jsonRDD = sc.makeRDD(data1 :: data2 :: Nil)
> scala> val rdd = hiveContext.jsonRDD(jsonRDD)
> scala> rdd.printSchema
> root
> |-- data_array: array (nullable = true)
> | |-- element: struct (containsNull = false)
> | | |-- field1: integer (nullable = true)
> | | |-- field2: integer (nullable = true)
> |-- timestamp: integer (nullable = true)
> scala> rdd.registerTempTable("tmp_table")
> scala> hiveContext.sql("select data.field1 from tmp_table LATERAL VIEW
> explode(data_array) nestedStuff AS data").collect
> res3: Array[org.apache.spark.sql.Row] = Array([1], [3])
> scala> hiveContext.sql("SET hive.exec.dynamic.partition = true")
> scala> hiveContext.sql("SET hive.exec.dynamic.partition.mode = nonstrict")
> scala> hiveContext.sql("set parquet.compression=GZIP")
> scala> hiveContext.setConf("spark.sql.parquet.binaryAsString", "true")
> scala> hiveContext.sql("create external table if not exists
> persisted_table(data_array ARRAY <STRUCT<field1: INT, field2: INT>>,
> timestamp INT) STORED AS PARQUET Location 'hdfs://****/test_table'")
> scala> hiveContext.sql("insert into table persisted_table select * from
> tmp_table").collect
> scala> hiveContext.sql("select data.field1 from persisted_table LATERAL VIEW
> explode(data_array) nestedStuff AS data").collect
> parquet.io.ParquetDecodingException: Can not read value at 0 in block -1 in
> file hdfs://*****/test_table/part-00001
> at
> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:213)
> at
> parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:204)
> at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:145)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at org.apache.spark.rdd.RDD$$anonfun$17.apply(RDD.scala:797)
> at org.apache.spark.rdd.RDD$$anonfun$17.apply(RDD.scala:797)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1353)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1353)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
> 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)
> Caused by: java.lang.IndexOutOfBoundsException: Index: 0, Size: 0
> at java.util.ArrayList.rangeCheck(ArrayList.java:635)
> at java.util.ArrayList.get(ArrayList.java:411)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.PrimitiveColumnIO.getFirst(PrimitiveColumnIO.java:99)
> at parquet.io.PrimitiveColumnIO.isFirst(PrimitiveColumnIO.java:94)
> at
> parquet.io.RecordReaderImplementation.<init>(RecordReaderImplementation.java:274)
> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:131)
> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:96)
> at
> parquet.filter2.compat.FilterCompat$NoOpFilter.accept(FilterCompat.java:136)
> at parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:96)
> at
> parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:126)
> at
> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:193)
> ... 28 more
> 15/01/30 16:49:55 INFO TaskSetManager: Starting task 1.1 in stage 3.0 (TID
> 12, ****, NODE_LOCAL, 1610 bytes)
> 15/01/30 16:49:55 INFO TaskSetManager: Lost task 1.1 in stage 3.0 (TID 12) on
> executor ****: parquet.io.ParquetDecodingException (Can not read value at 0
> in block -1 in file hdfs://*****/test_table/part-00001) [duplicate 1]
> 15/01/30 16:49:55 INFO TaskSetManager: Starting task 1.2 in stage 3.0 (TID
> 13, ****, NODE_LOCAL, 1610 bytes)
> 15/01/30 16:49:55 WARN TaskSetManager: Lost task 2.0 in stage 3.0 (TID 11,
> ****): parquet.io.ParquetDecodingException: Can not read value at 0 in block
> -1 in file hdfs://*****/test_table/part-00002
> at
> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:213)
> at
> parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:204)
> at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:145)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$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$$anonfun$17.apply(RDD.scala:797)
> at org.apache.spark.rdd.RDD$$anonfun$17.apply(RDD.scala:797)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1353)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1353)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
> 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)
> Caused by: java.lang.IndexOutOfBoundsException: Index: 0, Size: 0
> at java.util.ArrayList.rangeCheck(ArrayList.java:635)
> at java.util.ArrayList.get(ArrayList.java:411)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.PrimitiveColumnIO.getFirst(PrimitiveColumnIO.java:99)
> at parquet.io.PrimitiveColumnIO.isFirst(PrimitiveColumnIO.java:94)
> at
> parquet.io.RecordReaderImplementation.<init>(RecordReaderImplementation.java:274)
> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:131)
> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:96)
> at
> parquet.filter2.compat.FilterCompat$NoOpFilter.accept(FilterCompat.java:136)
> at parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:96)
> at
> parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:126)
> at
> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:193)
> ... 28 more
> 15/01/30 16:49:55 INFO TaskSetManager: Starting task 2.1 in stage 3.0 (TID
> 14, ****, NODE_LOCAL, 1610 bytes)
> 15/01/30 16:49:55 INFO TaskSetManager: Lost task 1.2 in stage 3.0 (TID 13) on
> executor ****: parquet.io.ParquetDecodingException (Can not read value at 0
> in block -1 in file hdfs://*****/test_table/part-00001) [duplicate 2]
> 15/01/30 16:49:55 INFO TaskSetManager: Starting task 1.3 in stage 3.0 (TID
> 15, ****, NODE_LOCAL, 1610 bytes)
> 15/01/30 16:49:55 INFO TaskSetManager: Lost task 1.3 in stage 3.0 (TID 15) on
> executor ****: parquet.io.ParquetDecodingException (Can not read value at 0
> in block -1 in file hdfs://*****/test_table/part-00001) [duplicate 3]
> 15/01/30 16:49:55 ERROR TaskSetManager: Task 1 in stage 3.0 failed 4 times;
> aborting job
> 15/01/30 16:49:55 INFO TaskSchedulerImpl: Cancelling stage 3
> 15/01/30 16:49:55 INFO TaskSchedulerImpl: Stage 3 was cancelled
> 15/01/30 16:49:55 INFO TaskSetManager: Lost task 2.1 in stage 3.0 (TID 14) on
> executor ****: parquet.io.ParquetDecodingException (Can not read value at 0
> in block -1 in file hdfs://*****/test_table/part-00002) [duplicate 1]
> 15/01/30 16:49:55 INFO TaskSchedulerImpl: Removed TaskSet 3.0, whose tasks
> have all completed, from pool
> 15/01/30 16:49:55 INFO DAGScheduler: Job 3 failed: collect at
> SparkPlan.scala:84, took 1.259053 s
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in
> stage 3.0 failed 4 times, most recent failure: Lost task 1.3 in stage 3.0
> (TID 15, ****): parquet.io.ParquetDecodingException: Can not read value at 0
> in block -1 in file hdfs://*****/test_table/part-00001
> at
> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:213)
> at
> parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:204)
> at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:145)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at org.apache.spark.rdd.RDD$$anonfun$17.apply(RDD.scala:797)
> at org.apache.spark.rdd.RDD$$anonfun$17.apply(RDD.scala:797)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1353)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1353)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> Caused by: java.lang.IndexOutOfBoundsException: Index: 0, Size: 0
> at java.util.ArrayList.rangeCheck(ArrayList.java:635)
> at java.util.ArrayList.get(ArrayList.java:411)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.GroupColumnIO.getFirst(GroupColumnIO.java:99)
> at parquet.io.PrimitiveColumnIO.getFirst(PrimitiveColumnIO.java:99)
> at parquet.io.PrimitiveColumnIO.isFirst(PrimitiveColumnIO.java:94)
> at
> parquet.io.RecordReaderImplementation.<init>(RecordReaderImplementation.java:274)
> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:131)
> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:96)
> at
> parquet.filter2.compat.FilterCompat$NoOpFilter.accept(FilterCompat.java:136)
> at parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:96)
> at
> parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:126)
> at
> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:193)
> ... 28 more
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
> at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
> at akka.actor.ActorCell.invoke(ActorCell.scala:487)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
> at akka.dispatch.Mailbox.run(Mailbox.scala:220)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at
> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> {noformat}
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