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https://issues.apache.org/jira/browse/SPARK-22225?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16198287#comment-16198287
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Sean Owen commented on SPARK-22225:
-----------------------------------
I tend to agree that this is already available from binaryFiles as it gives you
a stream on the input file. That's not a textual representation but of course
you just apply a Reader to it. The given use case was XML files earlier, and
those libraries are happy to operate on a stream. It's not crazy to have a
convenience method that applies a BufferedReader to an InputStream but it hides
virtually no complexity.
> 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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