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Rewrite AVG(expr) --> SUM(expr) / COUNT(expr) when components can be shared
#25536
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9acbb37
feat: decompose shared float64 avg aggregates
wudidapaopao aaae196
Merge remote-tracking branch 'origin/main' into avg-simplify-sum-count
wudidapaopao 749751c
Merge remote-tracking branch 'origin/main' into avg-simplify-sum-count
wudidapaopao 5fc8c93
Merge remote-tracking branch 'origin/main' into avg-simplify-sum-count
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I wonder if you considered using the existing
simplifymethod:https://docs.rs/datafusion/latest/datafusion/logical_expr/trait.AggregateUDFImpl.html#method.simplify
If you changed the avg udf to simplify to
sum/countthe existing common subexpr eliminate path probably will already avoid the recomputation.Also it woudl allow us to delete the actual AVG accumulators (rather than having a special case like this) 🤔
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Thanks, I considered using
simplify. I think we should retain the AVG accumulator and only decomposeAVGwhen its generatedSUMorCOUNTcan be shared. If implemented insimplify, every AVG would be unconditionally rewritten intoSUM/COUNT.Benchmark: 20 million random non-null
Int64rows, single-threaded.SELECT AVG(x) FROM tSELECT SUM(CAST(x AS DOUBLE)), AVG(x) FROM tSELECT SUM(CAST(x AS DOUBLE)), AVG(x), SUM(CAST(y AS DOUBLE)), AVG(y), SUM(CAST(z AS DOUBLE)), AVG(z) FROM tThere was a problem hiding this comment.
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Given the internal avg implementation basically has a sum and count accumulator, I am surprised at these numbers. Can you profile them and find out why there is a performance difference?
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Thanks for pointing this out. I found that
COUNT(*)materializes a fullInt64Arrayfor each batch. I will optimize this in a separate PR, then continue this PR.