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Dongjoon Hyun commented on SPARK-17041: --------------------------------------- Since I don't have the exact script of your situation, it might be different. But, Spark 2.0 supports `case sensitive` of course with SQL configuration. In the above, `sql("set spark.sql.caseSensitive=true")`. Could you confirm on your site, [~barrybecker4]? > 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} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org