planner: improve row count estimation of IndexJoin's inner scan #12085
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## master #12085 +/- ##
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Coverage ? 81.3048%
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Files ? 452
Lines ? 96886
Branches ? 0
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Hits ? 78773
Misses ? 12460
Partials ? 5653 |
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@@ Benchmark Diff @@
================================================================================
--- tidb: 5c18c5df97d935398ea1b44098a0db3171999466
+++ tidb: 7278ab07104a307f04e72e21d02f6528f8591013
tikv: ff82aa9eba331585aec1c6cdf9e1584512bccb34
pd: ce060a9aeb66d6bbb39159243b879740dffae041
================================================================================
test-1: < oltp_insert >
* QPS : 21141.44 ± 1.5888% (std=240.80) delta: -0.08%
* AvgMs : 12.10 ± 1.6193% (std=0.14) delta: 0.08%
* PercentileMs99 : 42.92 ± 1.0903% (std=0.38) delta: 1.46%
test-2: < oltp_update_non_index >
* QPS : 29436.80 ± 0.2322% (std=47.10) delta: -0.10%
* AvgMs : 8.69 ± 0.2071% (std=0.01) delta: 0.09%
* PercentileMs99 : 30.59 ± 1.0788% (std=0.27) delta: 1.09%
test-3: < oltp_read_write >
* QPS : 37051.41 ± 0.3770% (std=80.95) delta: 0.32%
* AvgMs : 138.73 ± 0.3792% (std=0.31) delta: -0.32%
* PercentileMs99 : 257.95 ± 0.0000% (std=0.00) delta: 0.00%
test-4: < oltp_point_select >
* QPS : 74734.42 ± 3.2705% (std=1572.71) delta: -0.30%
* AvgMs : 3.43 ± 3.0940% (std=0.07) delta: 0.40%
* PercentileMs99 : 7.43 ± 0.0000% (std=0.00) delta: 0.00%
test-5: < oltp_update_index >
* QPS : 16880.32 ± 0.5051% (std=62.94) delta: 0.29%
* AvgMs : 15.16 ± 0.5012% (std=0.06) delta: -0.29%
* PercentileMs99 : 48.34 ± 0.0000% (std=0.00) delta: 0.00%
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What problem does this PR solve?
Currently, the row count estimation of IndexJoin's inner child is not that accurate because:
Count / NDV, if the index used is composite index, and the join key only covers the prefix of the index, the row count would be smaller than the real countWhat is changed and how it works?
Initially, I considered comparing histograms of both child plans to compute an overlapping ratio and using it for row count estimation, but found that it was trivial to handle the mismatch between the data types, and it was hard to compute overlap for composite index cases.
Alternatively, I choose to reuse the estimated row count of join result after evaluating join equal conditions, because
leftCnt * rightCnt / max(leftNDV, rightNDV)has already taken the overlap into account more or less, and this approach can give more consistent row count estimations for join operator and its children.Check List
Tests
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