[jira] [Commented] (SPARK-17041) Columns in schema are no longer case sensitive when reading csv file

["Sean Owen (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-17041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15419133#comment-15419133 ] 

Sean Owen commented on SPARK-17041:
-----------------------------------

Behavior changes across major versions. I'm not sure this is a bug just because behavior is different.

> Columns in schema are no longer case sensitive when reading csv file
> --------------------------------------------------------------------
>
>                 Key: SPARK-17041
>                 URL: https://issues.apache.org/jira/browse/SPARK-17041
>             Project: Spark
>          Issue Type: Bug
>          Components: Input/Output
>    Affects Versions: 2.0.0
>            Reporter: Barry Becker
>
> It used to be (in spark 1.6.2) that I could read a csv file that had columns with  names that differed only by case. For example, one column may be "output" and another called "Output". Now (with spark 2.0.0) if I try to read such a file, I get an error like this:
> {code}
> org.apache.spark.sql.AnalysisException: Reference 'Output' is ambiguous, could be: Output#1263, Output#1295.;
> {code}
> The schema (dfSchema below) that I pass to the csv read looks like this:
> {code}
> StructType( StructField(Output,StringType,true), ... StructField(output,StringType,true), ...)
> {code}
> The code that does the read is this
> {code}
> sqlContext.read
>           .format("csv")
>           .option("header", "false") // Use first line of all files as header
>           .option("inferSchema", "false") // Automatically infer data types
>           .schema(dfSchema)
>           .csv(dataFile)
> {code}



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