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From "Dongjoon Hyun (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-24204) Verify a write schema in Json/Orc/ParquetFileFormat
Date Thu, 10 May 2018 16:27:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-24204?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Dongjoon Hyun updated SPARK-24204:
----------------------------------
    Summary: Verify a write schema in Json/Orc/ParquetFileFormat  (was: Verify a write schema
in Orc/ParquetFileFormat)

> Verify a write schema in Json/Orc/ParquetFileFormat
> ---------------------------------------------------
>
>                 Key: SPARK-24204
>                 URL: https://issues.apache.org/jira/browse/SPARK-24204
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Takeshi Yamamuro
>            Priority: Minor
>
> The native orc file format throws an exception with a meaningless message in executor-sides
when unsupported types passed;
> {code}
> scala> val rdd = spark.sparkContext.parallelize(List(Row(1, null), Row(2, null)))
> scala> val schema = StructType(StructField("a", IntegerType) :: StructField("b", NullType)
:: Nil)
> scala> val df = spark.createDataFrame(rdd, schema)
> scala> df.write.orc("/tmp/orc")
> java.lang.IllegalArgumentException: Can't parse category at 'struct<a:int,b:null^>'
>         at org.apache.orc.TypeDescription.parseCategory(TypeDescription.java:223)
>         at org.apache.orc.TypeDescription.parseType(TypeDescription.java:332)
>         at org.apache.orc.TypeDescription.parseStruct(TypeDescription.java:327)
>         at org.apache.orc.TypeDescription.parseType(TypeDescription.java:385)
>         at org.apache.orc.TypeDescription.fromString(TypeDescription.java:406)
>         at org.apache.spark.sql.execution.datasources.orc.OrcSerializer.org$apache$spark$sql$execution$datasources$orc$OrcSerializer$$createOrcValue(OrcSerializ
> er.scala:226)
>         at org.apache.spark.sql.execution.datasources.orc.OrcSerializer.<init>(OrcSerializer.scala:36)
>         at org.apache.spark.sql.execution.datasources.orc.OrcOutputWriter.<init>(OrcOutputWriter.scala:36)
>         at org.apache.spark.sql.execution.datasources.orc.OrcFileFormat$$anon$1.newInstance(OrcFileFormat.scala:108)
>         at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.newOutputWriter(FileFormatWriter.scala:376)
>         at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:387)
>         at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply
> (FileFormatWriter.scala:278)
> {code}
> It seems to be better to verify a write schema in a driver side for users along with
the CSV fromat;
> https://github.com/apache/spark/blob/76ecd095024a658bf68e5db658e4416565b30c17/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala#L65



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