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https://issues.apache.org/jira/browse/SPARK-10185?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Davies Liu resolved SPARK-10185.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8416
[https://github.com/apache/spark/pull/8416]
> Spark SQL does not handle comma separates paths on Hadoop FileSystem
> --------------------------------------------------------------------
>
> Key: SPARK-10185
> URL: https://issues.apache.org/jira/browse/SPARK-10185
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1
> Reporter: koert kuipers
> Fix For: 1.6.0
>
>
> Spark SQL uses a Map[String, String] for data source settings. As a
> consequence the only way to pass in multiple paths (something that hadoop
> file input format supports) is to do pass in a comma separated list. For
> example:
> sqlContext.format("json").load("dir1,dir22")
> or
> sqlContext.format("json").option("path", "dir1,dir2").load
> However in this case ResolvedDataSource does not handle the comma delimited
> paths correctly for a HadoopFsRelationProvider. It treats the multiple comma
> delimited paths as single path.
> For example if i pass in for path "dir1,dir2" it will make dir1 qualified but
> ignore dir2 (presumably because it simply treats it as part of dir1). If
> globs are involved then it simply always returns an empty array of paths
> (because the glob with comma in it doesn’t match anything).
> I think its important to handle commas to pass in multiple paths, since the
> framework does not provide an alternative. In some cases like parquet the
> code simply bypasses ResolvedDataSource to support multiple paths but to me
> this is a workaround that should be discouraged.
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