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From "Reza Safi (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-19340) Opening a file in CSV format will result in an exception if the filename contains special characters
Date Tue, 24 Jan 2017 19:46:26 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19340?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Reza Safi updated SPARK-19340:
------------------------------
    Priority: Minor  (was: Major)

> Opening a file in CSV format will result in an exception if the filename contains special
characters
> ----------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-19340
>                 URL: https://issues.apache.org/jira/browse/SPARK-19340
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0, 2.0.1, 2.1.0, 2.2.0
>            Reporter: Reza Safi
>            Priority: Minor
>
> If you want to open a file that its name is like  {noformat} "*{*}*.*" {noformat} or
{noformat} "*[*]*.*" {noformat} using CSV format, you will get the "org.apache.spark.sql.AnalysisException:
Path does not exist" whether the file is a local file or on hdfs.
> This bug can be reproduced on master and all other Spark 2 branches.
> To reproduce:
> # Create a file like "test{00-1}.txt" on a local directory (like in /Users/reza/test/test{00-1}.txt)
> # Run spark-shell
> # Execute this command:
> val df=spark.read.option("header","false").csv("/Users/reza/test/*.txt")
> You will see the following stack trace:
> {noformat}
> org.apache.spark.sql.AnalysisException: Path does not exist: file:/Users/reza/test/test\{00-01\}.txt;
>   at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:367)
>   at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:360)
>   at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
>   at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
>   at scala.collection.immutable.List.foreach(List.scala:381)
>   at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
>   at scala.collection.immutable.List.flatMap(List.scala:344)
>   at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:360)
>   at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.readText(CSVFileFormat.scala:208)
>   at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:63)
>   at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$7.apply(DataSource.scala:174)
>   at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$7.apply(DataSource.scala:174)
>   at scala.Option.orElse(Option.scala:289)
>   at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:173)
>   at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:377)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:158)
>   at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:423)
>   at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:360)
>   ... 48 elided
> {noformat}



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