Spark: Remove hasExtraFilterColumns #1004
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@rdsr, this affects the work you're doing for ORC identity projections. @samarthjain, this hopefully makes the vectorized read path a bit easier. |
This was referenced May 5, 2020
Contributor
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+1 LGTM, you might want to file an issue for ORC to support the constant projection because I assume ORC will still pay the additional copy cost. |
Contributor
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Ratandeep is already working on constant projection in #989. |
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I'm not sure why CI didn't run, but I tested locally to verify this change and everything passes. I'm going to merge this. |
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Spark has special handling in the read path for extra filter columns -- columns that are referenced by a filter expression but not in the schema for rows returned to Spark. This path requires copying rows before returning to Spark to match the expected schema without the filter columns, and uses Spark's
UnsafeProjection.This handling isn't needed because the source can tell Spark the schema that it will project. So if Spark requests columns, the data source can return a schema with more columns, as long as the reader passes them back in
readSchema. Using this simplifies the logic in the reader and allows us to get rid of another case that doesn't need a full copy.