[SPARK-33726][SQL][2.4] Fix for Duplicate field names during Aggregation#31327
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[SPARK-33726][SQL][2.4] Fix for Duplicate field names during Aggregation#31327yliou wants to merge 1 commit intoapache:branch-2.4from
yliou wants to merge 1 commit intoapache:branch-2.4from
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The `RowBasedKeyValueBatch` has two different implementations depending on whether the aggregation key and value uses only fixed length data types (`FixedLengthRowBasedKeyValueBatch`) or not (`VariableLengthRowBasedKeyValueBatch`).
Before this PR the decision about the used implementation was based on by accessing the schema fields by their name.
But if two fields has the same name and one with variable length and the other with fixed length type (and all the other fields are with fixed length types) a bad decision could be made.
When `FixedLengthRowBasedKeyValueBatch` is chosen but there is a variable length field then an aggregation function could calculate with invalid values. This case is illustrated by the example used in the unit test:
`with T as (select id as a, -id as x from range(3)),
U as (select id as b, cast(id as string) as x from range(3))
select T.x, U.x, min(a) as ma, min(b) as mb from T join U on a=b group by U.x, T.x`
where the 'x' column in the left side of the join is a Long but on the right side is a String.
Fixes the issue where duplicate field name aggregation has null values in the dataframe.
No
Added UT, tested manually on spark shell.
Closes apache#30788 from yliou/SPARK-33726.
Authored-by: yliou <yliou@berkeley.edu>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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cc @cloud-fan |
dongjoon-hyun
changed the title
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Test build #134459 has finished for PR 31327 at commit
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Contributor
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retest this please |
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Test build #134505 has finished for PR 31327 at commit
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Contributor
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thanks, merging to 2.4! |
cloud-fan
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Jan 26, 2021
### What changes were proposed in this pull request?
The `RowBasedKeyValueBatch` has two different implementations depending on whether the aggregation key and value uses only fixed length data types (`FixedLengthRowBasedKeyValueBatch`) or not (`VariableLengthRowBasedKeyValueBatch`).
Before this PR the decision about the used implementation was based on by accessing the schema fields by their name.
But if two fields has the same name and one with variable length and the other with fixed length type (and all the other fields are with fixed length types) a bad decision could be made.
When `FixedLengthRowBasedKeyValueBatch` is chosen but there is a variable length field then an aggregation function could calculate with invalid values. This case is illustrated by the example used in the unit test:
`with T as (select id as a, -id as x from range(3)),
U as (select id as b, cast(id as string) as x from range(3))
select T.x, U.x, min(a) as ma, min(b) as mb from T join U on a=b group by U.x, T.x`
where the 'x' column in the left side of the join is a Long but on the right side is a String.
### Why are the changes needed?
Fixes the issue where duplicate field name aggregation has null values in the dataframe.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UT, tested manually on spark shell.
Closes #31327 from yliou/SPARK-33726_2.4.
Authored-by: yliou <yliou@berkeley.edu>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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What changes were proposed in this pull request?
The
RowBasedKeyValueBatchhas two different implementations depending on whether the aggregation key and value uses only fixed length data types (FixedLengthRowBasedKeyValueBatch) or not (VariableLengthRowBasedKeyValueBatch).Before this PR the decision about the used implementation was based on by accessing the schema fields by their name.
But if two fields has the same name and one with variable length and the other with fixed length type (and all the other fields are with fixed length types) a bad decision could be made.
When
FixedLengthRowBasedKeyValueBatchis chosen but there is a variable length field then an aggregation function could calculate with invalid values. This case is illustrated by the example used in the unit test:with T as (select id as a, -id as x from range(3)), U as (select id as b, cast(id as string) as x from range(3)) select T.x, U.x, min(a) as ma, min(b) as mb from T join U on a=b group by U.x, T.xwhere the 'x' column in the left side of the join is a Long but on the right side is a String.
Why are the changes needed?
Fixes the issue where duplicate field name aggregation has null values in the dataframe.
Does this PR introduce any user-facing change?
No
How was this patch tested?
Added UT, tested manually on spark shell.