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From "shivusondur (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-25271) Creating parquet table with all the column null throws exception
Date Tue, 04 Sep 2018 14:26:01 GMT

    [ https://issues.apache.org/jira/browse/SPARK-25271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16603106#comment-16603106
] 

shivusondur commented on SPARK-25271:
-------------------------------------

After further analyzing the issue i got following details

In  SingleDirectoryWriteTask private class(org.apache.spark.sql.execution.datasources.FileFormatWriter
File) , currentWriter is  initialized with different outputWriter in spark-2.2.1 and spar-2.3.1,
as shown below. 


{code:java}
Spark-2.3.1= currentWriter is initilized with "HiveOutputWriter"
Spark-2.2.1= currentWriter is initilized with "ParquetOutputWriter"
{code}


So ParquetOutputWriter may be handling the null/empty values.

> Creating parquet table with all the column null throws exception
> ----------------------------------------------------------------
>
>                 Key: SPARK-25271
>                 URL: https://issues.apache.org/jira/browse/SPARK-25271
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.1
>            Reporter: shivusondur
>            Priority: Major
>
> {code:java}
>  1)cat /data/parquet.dat
> 1$abc2$pqr:3$xyz
> null{code}
>  
> {code:java}
> 2)spark.sql("create table vp_reader_temp (projects map<int, string>) ROW FORMAT
DELIMITED FIELDS TERMINATED BY ',' COLLECTION ITEMS TERMINATED BY ':' MAP KEYS TERMINATED
BY '$'")
> {code}
> {code:java}
> 3)spark.sql("
> LOAD DATA LOCAL INPATH '/data/parquet.dat' INTO TABLE vp_reader_temp")
> {code}
> {code:java}
> 4)spark.sql("create table vp_reader STORED AS PARQUET as select * from vp_reader_temp")
> {code}
> *Result :* Throwing exception (Working fine with spark 2.2.1)
> {code:java}
> java.lang.RuntimeException: Parquet record is malformed: empty fields are illegal, the
field should be ommited completely instead
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriter.write(DataWritableWriter.java:64)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriteSupport.write(DataWritableWriteSupport.java:59)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriteSupport.write(DataWritableWriteSupport.java:31)
> 	at org.apache.parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:123)
> 	at org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:180)
> 	at org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:46)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.ParquetRecordWriterWrapper.write(ParquetRecordWriterWrapper.java:112)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.ParquetRecordWriterWrapper.write(ParquetRecordWriterWrapper.java:125)
> 	at org.apache.spark.sql.hive.execution.HiveOutputWriter.write(HiveFileFormat.scala:149)
> 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:406)
> 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:283)
> 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:281)
> 	at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1438)
> 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:286)
> 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:211)
> 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:210)
> 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:109)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:349)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:745)
> Caused by: org.apache.parquet.io.ParquetEncodingException: empty fields are illegal,
the field should be ommited completely instead
> 	at org.apache.parquet.io.MessageColumnIO$MessageColumnIORecordConsumer.endField(MessageColumnIO.java:320)
> 	at org.apache.parquet.io.RecordConsumerLoggingWrapper.endField(RecordConsumerLoggingWrapper.java:165)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriter.writeMap(DataWritableWriter.java:241)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriter.writeValue(DataWritableWriter.java:116)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriter.writeGroupFields(DataWritableWriter.java:89)
> 	at org.apache.hadoop.hive.ql.io.parquet.write.DataWritableWriter.write(DataWritableWriter.java:60)
> 	... 21 more
> {code}



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