Yeah, two of the reasons why the built-in in-memory columnar storage
doesn't achieve comparable compression ratio as Parquet are:
1. The in-memory columnar representation doesn't handle nested types. So
array/map/struct values are not compressed.
2. Parquet may use more than one kind of compression methods to compress
a single column. For example, dictionary + RLE.
Cheng
On 9/2/15 3:58 PM, Nitin Goyal wrote:
I think spark sql's in-memory columnar cache already does compression. Check
out classes in following path :-
https://github.com/apache/spark/tree/master/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression
Although compression ratio is not as good as Parquet.
Thanks
-Nitin
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