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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2186) Rework CSV import to support very wide files
Date Thu, 09 Feb 2017 07:57:42 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2186?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15859179#comment-15859179

ASF GitHub Bot commented on FLINK-2186:

Github user ex00 commented on a diff in the pull request:

    --- Diff: flink-scala/src/main/scala/org/apache/flink/api/scala/ExecutionEnvironment.scala
    @@ -348,6 +349,47 @@ class ExecutionEnvironment(javaEnv: JavaEnv) {
         wrap(new DataSource[T](javaEnv, inputFormat, typeInfo, getCallLocationName()))
    +  def readCsvFileAsRow[T : ClassTag : TypeInformation](
    --- End diff --
    Could you add scaladoc for method?  may do not understand, what is ```additionalTypes```

> Rework CSV import to support very wide files
> --------------------------------------------
>                 Key: FLINK-2186
>                 URL: https://issues.apache.org/jira/browse/FLINK-2186
>             Project: Flink
>          Issue Type: Improvement
>          Components: Machine Learning Library, Scala API
>            Reporter: Theodore Vasiloudis
>            Assignee: Anton Solovev
> In the current readVcsFile implementation, importing CSV files with many columns can
become from cumbersome to impossible.
> For example to import an 11 column file we need to write:
> {code}
> val cancer = env.readCsvFile[(String, String, String, String, String, String, String,
String, String, String, String)]("/path/to/breast-cancer-wisconsin.data")
> {code}
> For many use cases in Machine Learning we might have CSV files with thousands or millions
of columns that we want to import as vectors.
> In that case using the current readCsvFile method becomes impossible.
> We therefore need to rework the current function, or create a new one that will allow
us to import CSV files with an arbitrary number of columns.

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