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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2017/10/09 13:31:00 UTC
[jira] [Commented] (SPARK-22225) wholeTextFilesIterators
[ 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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