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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2018/02/09 14:49:00 UTC
[jira] [Commented] (SPARK-23371) Parquet Footer data is wrong on
window in parquet format partition table
[ https://issues.apache.org/jira/browse/SPARK-23371?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16358488#comment-16358488 ]
Sean Owen commented on SPARK-23371:
-----------------------------------
It sounds like you have multiple versions of Parquet on your classpath, or at least, you're writing with a new version and reading with an old version? that's not going to work. This does not look like a Spark problem.
> Parquet Footer data is wrong on window in parquet format partition table
> -------------------------------------------------------------------------
>
> Key: SPARK-23371
> URL: https://issues.apache.org/jira/browse/SPARK-23371
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.1.1, 2.1.2
> Reporter: pin_zhang
> Priority: Major
>
> On window
> Run SQL in spark shell
> spark.sql("create table part_test (id string )partitioned by( index int) stored as parquet")
> spark.sql("insert into part_test partition (index =1) values ('1')")
> Get exception when query spark.sql("select * from part_test ").show()
> For the parquet.Version in parquet-hadoop-bundle-1.6.0.jar cannot load the version info in spark on window. Classloader try to get version in the parquet-format-2.3.0-incubating.jar
> 18/02/09 16:58:48 WARN CorruptStatistics: Ignoring statistics because created_by
> could not be parsed (see PARQUET-251): parquet-mr
> org.apache.parquet.VersionParser$VersionParseException: Could not parse created_
> by: parquet-mr using format: (.+) version ((.*) )?(build ?(.*))
> at org.apache.parquet.VersionParser.parse(VersionParser.java:112)
> at org.apache.parquet.CorruptStatistics.shouldIgnoreStatistics(CorruptSt
> atistics.java:60)
> at org.apache.parquet.format.converter.ParquetMetadataConverter.fromParq
> uetStatistics(ParquetMetadataConverter.java:263)
> at org.apache.parquet.hadoop.ParquetFileReader$Chunk.readAllPages(Parque
> tFileReader.java:583)
> at org.apache.parquet.hadoop.ParquetFileReader.readNextRowGroup(ParquetF
> ileReader.java:513)
> at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetR
> ecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:270)
> at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetR
> ecordReader.nextBatch(VectorizedParquetRecordReader.java:225)
> at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetR
> ecordReader.nextKeyValue(VectorizedParquetRecordReader.java:137)
> at org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNe
> xt(RecordReaderIterator.scala:39)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNex
> t(FileScanRDD.scala:109)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIt
> erator(FileScanRDD.scala:184)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNex
> t(FileScanRDD.scala:109)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIte
> rator.scan_nextBatch$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIte
> rator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRo
> wIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon
> $1.hasNext(WholeStageCodegenExec.scala:377)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.s
> cala:231)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.s
> cala:225)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$ap
> ply$25.apply(RDD.scala:827)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$ap
> ply$25.apply(RDD.scala:827)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:
> 38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:325)
> 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)
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