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https://issues.apache.org/jira/browse/SPARK-11844?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17344105#comment-17344105
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Sungwon commented on SPARK-11844:
---------------------------------
I'm in agreement with your intuition that S3aOutputStream may be closing
without raising an underlying exception.
I've primarily seen this issue only when writing large parquet files (tends to
be bigger than 1 or 2Gb), and have confirmed that these files are corrupt upon
read through spark / parquet reader.
And interestingly enough, Hadoop 2.9 has a similar issue with their
S3aInputStream, just that it actually throws an exception and closes the
stream. The root cause in the inputstream is that the S3Client object gets
GC'ed prematurely even when the file read is still happening. I'm curious if
something similar is happening with S3aOutputStream, but instead of detecting
the exception of closing the stream, it is actually continuing the write and
closing it without an exception.
[https://stackoverflow.com/questions/22673698/local-variable-in-method-being-garbage-collected-before-method-exits-java
]
[https://github.com/apache/hadoop/blob/rel/release-2.9.0/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3a/S3AFileSystem.java]
> can not read class org.apache.parquet.format.PageHeader: don't know what
> type: 13
> ---------------------------------------------------------------------------------
>
> Key: SPARK-11844
> URL: https://issues.apache.org/jira/browse/SPARK-11844
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Yin Huai
> Priority: Minor
> Labels: bulk-closed
>
> I got the following error once when I was running a query
> {code}
> java.io.IOException: can not read class org.apache.parquet.format.PageHeader:
> don't know what type: 13
> at org.apache.parquet.format.Util.read(Util.java:216)
> at org.apache.parquet.format.Util.readPageHeader(Util.java:65)
> at
> org.apache.parquet.hadoop.ParquetFileReader$Chunk.readPageHeader(ParquetFileReader.java:534)
> at
> org.apache.parquet.hadoop.ParquetFileReader$Chunk.readAllPages(ParquetFileReader.java:546)
> at
> org.apache.parquet.hadoop.ParquetFileReader.readNextRowGroup(ParquetFileReader.java:496)
> at
> org.apache.parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:127)
> at
> org.apache.parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:208)
> at
> org.apache.parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:201)
> at
> org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.hasNext(SqlNewHadoopRDD.scala:168)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.sql.execution.joins.HashJoin$$anon$1.hasNext(HashJoin.scala:77)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.sql.execution.joins.HashJoin$$anon$1.hasNext(HashJoin.scala:77)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.sql.execution.joins.HashJoin$$anon$1.hasNext(HashJoin.scala:77)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.sql.execution.joins.HashJoin$$anon$1.hasNext(HashJoin.scala:77)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:88)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:86)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:704)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:704)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: parquet.org.apache.thrift.protocol.TProtocolException: don't know
> what type: 13
> at
> parquet.org.apache.thrift.protocol.TCompactProtocol.getTType(TCompactProtocol.java:806)
> at
> parquet.org.apache.thrift.protocol.TCompactProtocol.readFieldBegin(TCompactProtocol.java:500)
> at
> org.apache.parquet.format.InterningProtocol.readFieldBegin(InterningProtocol.java:158)
> at
> parquet.org.apache.thrift.protocol.TProtocolUtil.skip(TProtocolUtil.java:108)
> {code}
> The next retry was good. Right now, seems not critical. But, let's still
> track it in case we see it in future.
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