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From "Hyukjin Kwon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-21820) csv option "multiLine" as "true" not parsing windows line feed (CR LF) properly
Date Wed, 23 Aug 2017 13:57:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-21820?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16138379#comment-16138379
] 

Hyukjin Kwon commented on SPARK-21820:
--------------------------------------

I investigated this newline stuff few times before. For example, https://github.com/apache/spark/pull/18304#discussion_r122142421.

> csv option "multiLine" as "true" not parsing windows line feed (CR LF) properly
> -------------------------------------------------------------------------------
>
>                 Key: SPARK-21820
>                 URL: https://issues.apache.org/jira/browse/SPARK-21820
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.2.0
>            Reporter: Kumaresh C R
>              Labels: features
>         Attachments: windows_CRLF.csv
>
>
> With multiLine=true, windows CR LF is not getting parsed properly. If i make multiLine=false,
it parses properly. Could you please help here ?
> Attached the CSV used in the below commands for your reference.
> scala> val csvFile = spark.read.format("com.databricks.spark.csv").option("header",
"true").option("inferSchema", "true").option("parserLib", "univocity").load("/home/kumar/Desktop/windows_CRLF.csv");
> csvFile: org.apache.spark.sql.DataFrame = [Sales_Dollars: int, Created_Date: string ...
1 more field]
> scala> csvFile.schema.fieldNames
> res0: Array[String] = Array(Sales_Dollars, Created_Date, Order_Delivered)
> scala> val csvFile = spark.read.format("com.databricks.spark.csv").option("header",
"true").option("inferSchema", "true").option("parserLib", "univocity").option("multiLine","true").load("/home/kumar/Desktop/windows_CRLF.csv");
> csvFile: org.apache.spark.sql.DataFrame = [Sales_Dollars: int, Created_Date: string ...
1 more field]
> scala> csvFile.schema.fieldNames
> ")s1: Array[String] = Array(Sales_Dollars, Created_Date, "Order_Delivered



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