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https://issues.apache.org/jira/browse/SPARK-31276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17074677#comment-17074677
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Jim Huang edited comment on SPARK-31276 at 4/3/20, 3:51 PM:
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Clarified the question with more succinct scenario that describe the the
challenge of URI not being able to differentiate between driver vs executor.
was (Author: jimhuang):
Clarify the question with more succinct scenario that describe the the
challenge of URI not being able to differentiate between driver vs executor.
> Contrived working example that works with multiple URI file storages for
> Spark cluster mode
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-31276
> URL: https://issues.apache.org/jira/browse/SPARK-31276
> Project: Spark
> Issue Type: Wish
> Components: Examples
> Affects Versions: 2.4.5
> Reporter: Jim Huang
> Priority: Major
>
> This Spark SQL Guide --> Data sources --> Generic Load/Save Functions
> [https://spark.apache.org/docs/latest/sql-data-sources-load-save-functions.html]
> described a very simple "local file system load of an example file".
>
> I am looking for an example that demonstrates a workflow that exercises
> different file systems. For example,
> # Driver loads an input file from local file system
> # Add a simple column using lit() and stores that DataFrame in cluster mode
> to HDFS
> # Write that a small limited subset of that DataFrame back to Driver's local
> file system. (This is to avoid the anti-pattern of writing large file and
> out of the scope for this example. The small limited DataFrame would be some
> basic statistics, not the actual complete dataset.)
>
> The examples I found on the internet only uses simple paths without the
> explicit URI prefixes.
> Without the explicit URI prefixes, the "filepath" inherits how Spark (mode)
> was called, local stand alone vs YARN client mode. So a "filepath" will be
> read/write locally (file system) vs cluster mode HDFS, without these explicit
> URIs.
> There are situations were a Spark program needs to deal with both local file
> system and YARN client mode (big data) in the same Spark application, like
> producing a summary table stored on the local file system of the driver at
> the end.
> If there are any existing alternatives Spark documentation that provides
> examples that traverse through the different URIs in Spark YARN client mode
> or a better or smarter Spark pattern or API that is more suited for this, I
> am happy to accept that as well. Thanks!
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