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From "Hyukjin Kwon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-22225) wholeTextFilesIterators
Date Mon, 09 Oct 2017 13:31:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-22225?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16196952#comment-16196952
] 

Hyukjin Kwon commented on SPARK-22225:
--------------------------------------

Couldn't we do this via {{sc.binaryFiles}} or {{spark.format("text").read("...").selectExpr("value",
"input_file_name()")}}.

For the latter, there is a JIRA for the delimiter support - SPARK-21289.

> wholeTextFilesIterators
> -----------------------
>
>                 Key: SPARK-22225
>                 URL: https://issues.apache.org/jira/browse/SPARK-22225
>             Project: Spark
>          Issue Type: New Feature
>          Components: Spark Core
>    Affects Versions: 2.2.0
>            Reporter: sam
>
> It is a very common use case to want to preserve a path -> file mapping in an RDD,
or read an entire file in one go.  Especially for unstructured data and ETL.
> Currently wholeTextFiles is the goto method for this, but it read the entire file into
memory, which is sometimes an issue (see SPARK-18965).  It also precludes the option to lazily
process files.
> It would be nice to have a method with the following signature:
> {code}
> def wholeTextFilesIterators(
>     path: String,
>     minPartitions: Int = defaultMinPartitions,
>     delimiter: String = "\n"): RDD[(String, Iterator[String])]
> {code}
> Where each `Iterator[String]` is a lazy file iterator where each string is delimited
by the `delimiter` field.



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