You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Dongjoon Hyun (JIRA)" <ji...@apache.org> on 2017/10/11 05:37:00 UTC
[jira] [Updated] (SPARK-15474) ORC data source fails to write and
read back empty dataframe
[ https://issues.apache.org/jira/browse/SPARK-15474?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun updated SPARK-15474:
----------------------------------
Affects Version/s: 2.1.1
> 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, 2.1.1
> 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.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org