Github user rtreffer commented on the pull request:
https://github.com/apache/spark/pull/6796#issuecomment-114835713
@liancheng I'll rebase on your branch, I really like the way you cleaned up
toPrimitiveDataType by using a fluent Types interface. This will make this
patch way easier.
Talking about testing/compatibility/interoperability, I have added a
hive-generated parquet file that I'd like to turn into a test case:
https://github.com/rtreffer/spark/tree/spark-4176-store-large-decimal-in-parquet/sql/core/src/test/resources/hive-decimal-parquet
There are some parquet files attached to tickets in jira, too.
Do you plan to convert those into tests?
Regarding FIXED_LENGTH_BYTE_ARRAY.... The overhead would decreases compared
to size. BINARY overhead would be <10% from ~DECIMAL(100) and <25% from
~DECIAL(40) (pre-compression). I'd expect DECIMAL(40) to use the full precision
only from time to time. But yeah, I've overlooked the 4 byte overhead at
https://github.com/Parquet/parquet-format/blob/master/Encodings.md and assumed
it would be less, FIXED_LENGTH_BYTE_ARRAY should be good for now (until s.o.
complains).
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