Jim Huang created SPARK-31276:
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Summary: 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
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 same final DataFrame back to Driver's local file system
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 cluster 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 cluster 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.
Thanks.
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