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https://issues.apache.org/jira/browse/SPARK-19340?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15836489#comment-15836489
]
Reza Safi commented on SPARK-19340:
-----------------------------------
[~hyukjin.kwon] I updated the description and the way to reproduce. If you run:
val
df=spark.read.option("header","false").csv("/Users/reza/test/test{00-1}.txt"),
you are right the issue is not just about csv. but if you run:
{noformat}
val df=spark.read.option("header","false").csv("/Users/reza/test/*.txt")
{noformat}
you will get the exception as I mentioned in the updated description. However
running this will be successful:
{noformat}
val df=spark.read.option("header","false").text("/Users/reza/test/*.txt")
{noformat}
> 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
>
> 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/rezasafi/bck/sp2/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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