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From "Nicholas Chammas (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-15474) ORC data source fails to write and read back empty dataframe
Date Fri, 03 Mar 2017 04:08:45 GMT

    [ https://issues.apache.org/jira/browse/SPARK-15474?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15893703#comment-15893703
] 

Nicholas Chammas commented on SPARK-15474:
------------------------------------------

cc [~owen.omalley]

>  ORC data source fails to write and read back empty dataframe
> -------------------------------------------------------------
>
>                 Key: SPARK-15474
>                 URL: https://issues.apache.org/jira/browse/SPARK-15474
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Hyukjin Kwon
>
> Currently ORC data source fails to write and read empty data.
> The code below:
> {code}
> val emptyDf = spark.range(10).limit(0)
> emptyDf.write
>   .format("orc")
>   .save(path.getCanonicalPath)
> val copyEmptyDf = spark.read
>   .format("orc")
>   .load(path.getCanonicalPath)
> copyEmptyDf.show()
> {code}
> throws an exception below:
> {code}
> Unable to infer schema for ORC at /private/var/folders/9j/gf_c342d7d150mwrxvkqnc180000gn/T/spark-5b7aa45b-a37d-43e9-975e-a15b36b370da.
It must be specified manually;
> org.apache.spark.sql.AnalysisException: Unable to infer schema for ORC at /private/var/folders/9j/gf_c342d7d150mwrxvkqnc180000gn/T/spark-5b7aa45b-a37d-43e9-975e-a15b36b370da.
It must be specified manually;
> 	at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$16.apply(DataSource.scala:352)
> 	at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$16.apply(DataSource.scala:352)
> 	at scala.Option.getOrElse(Option.scala:121)
> 	at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:351)
> 	at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:130)
> 	at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:140)
> 	at org.apache.spark.sql.sources.HadoopFsRelationTest$$anonfun$32$$anonfun$apply$mcV$sp$47.apply(HadoopFsRelationTest.scala:892)
> 	at org.apache.spark.sql.sources.HadoopFsRelationTest$$anonfun$32$$anonfun$apply$mcV$sp$47.apply(HadoopFsRelationTest.scala:884)
> 	at org.apache.spark.sql.test.SQLTestUtils$class.withTempPath(SQLTestUtils.scala:114)
> {code}
> Note that this is a different case with the data below
> {code}
> val emptyDf = spark.createDataFrame(spark.sparkContext.emptyRDD[Row], schema)
> {code}
> In this case, any writer is not initialised and created. (no calls of {{WriterContainer.writeRows()}}.
> For Parquet and JSON, it works but ORC does not.



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