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From Danny Yates <>
Subject Can Spark benefit from Hive-like partitions?
Date Mon, 26 Jan 2015 13:40:41 GMT

I've got a bunch of data stored in S3 under directories like this:


In Hive, if I issue a query WHERE y=2015 AND m=01, I get the benefit that
it only scans the necessary directories for files to read.

As far as I can tell from searching and reading the docs, the right way of
loading this data into Spark is to use sc.textFile("s3n://blah/*/*/*/")

1) Is there any way in Spark to access y, m and d as fields? In Hive, you
declare them in the schema, but you don't put them in the CSV files - their
values are extracted from the path.
2) Is there any way to get Spark to use the y, m and d fields to minimise
the files it transfers from S3?



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