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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2020/03/31 04:47:00 UTC
[jira] [Resolved] (SPARK-31276) Contrived working example that
works with multiple URI file storages for Spark cluster mode
[ https://issues.apache.org/jira/browse/SPARK-31276?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-31276.
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Resolution: Won't Fix
> 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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