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feat: correlation support #456
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #456 +/- ##
============================================
- Coverage 34.02% 34.02% -0.01%
- Complexity 857 859 +2
============================================
Files 116 116
Lines 38565 38671 +106
Branches 8517 8564 +47
============================================
+ Hits 13120 13156 +36
- Misses 22691 22753 +62
- Partials 2754 2762 +8 ☔ View full report in Codecov by Sentry. |
.setCorrelation(corrBuilder) | ||
.build()) | ||
} else { | ||
None |
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Should we add withInfo()
?
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Yes, I forgot this. Added.
sql(s"insert into $table values(1, 4, 1), (2, 5, 1), (3, 6, 2)") | ||
val expectedNumOfCometAggregates = 2 | ||
|
||
sql("SELECT corr(col1, col2) FROM test GROUP BY col3").show |
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nit: we can reuse s$table
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Done.
@@ -1212,6 +1212,157 @@ class CometAggregateSuite extends CometTestBase with AdaptiveSparkPlanHelper { | |||
} | |||
} | |||
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test("correlation") { | |||
withSQLConf(CometConf.COMET_EXEC_SHUFFLE_ENABLED.key -> "true") { | |||
Seq(false).foreach { cometColumnShuffleEnabled => |
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Is it intentional that we only test for cometColumnShuffleEnabled==false
? I have similar questions for parquet.enable.dictionary
and nullOnDivideByZero
, where we also iterate over a single boolean and don't test both for true and false.
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Should be both true
and false
. I removed one of them so it's easier for me to debug. Forgot to put back.
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LGTM
Merged. Thanks @huaxingao @andygrove @kazuyukitanimura |
Thanks @viirya @andygrove @kazuyukitanimura |
* feat: correlation support * fmt * remove un-used import * address comments * address comment --------- Co-authored-by: Huaxin Gao <huaxin.gao@apple.com> (cherry picked from commit 6d23e28)
Which issue does this PR close?
Supports
CORR
The implementation mostly is the same as the DataFusion's implementation. The reason
we have our own implementation is that DataFusion has UInt64 for state_field count,
while Spark has Double for count. Also adding null_on_divide_by_zero
to be consistent with Spark's implementation.
Closes #.
Rationale for this change
What changes are included in this PR?
How are these changes tested?