Separating Benchmarks for physical sorted union over large columns in SQL planner based on Datatype #18599
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Omega359
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Nov 11, 2025
| let array_data: Vec<T::Native> = (0..num_rows) | ||
| .map(|j| { | ||
| let value = (j as u64) * 100 + (i as u64); | ||
| <T::Native as NumCast>::from(value).unwrap_or_else(|| { |
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This is neat, first I've seen NumCast before. I'll have to remember this!
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LGTM, thanks! |
alamb
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Nov 11, 2025
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Thank you @logan-keede and @Omega359 -- this looks great to me too
I also tried running it via
cargo bench --bench sql_planner -- physical_sorted_union_order_byAnd as you pointed out, int64 takes more than 10x the time of uint64. Very nice find
Gnuplot not found, using plotters backend
physical_sorted_union_order_by_10_int64
time: [2.6344 ms 2.6446 ms 2.6559 ms]
Found 12 outliers among 100 measurements (12.00%)
7 (7.00%) high mild
5 (5.00%) high severe
Benchmarking physical_sorted_union_order_by_50_int64: Warming up for 3.0000 s
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 7.9s, or reduce sample count to 60.
physical_sorted_union_order_by_50_int64
time: [79.580 ms 80.020 ms 80.510 ms]
Found 11 outliers among 100 measurements (11.00%)
10 (10.00%) high mild
1 (1.00%) high severe
physical_sorted_union_order_by_10_uint64
time: [5.8978 ms 5.9296 ms 5.9655 ms]
Found 12 outliers among 100 measurements (12.00%)
7 (7.00%) high mild
5 (5.00%) high severe
Benchmarking physical_sorted_union_order_by_50_uint64: Warming up for 3.0000 s
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 17.0s, or reduce sample count to 20.
physical_sorted_union_order_by_50_uint64
time: [168.75 ms 169.33 ms 169.99 ms]
Found 9 outliers among 100 measurements (9.00%)
4 (4.00%) high mild
5 (5.00%) high severe
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I merged up from main and pushed a commit to resolve the CI fmt failure |
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Thanks again @logan-keede and @Omega359 |
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Which issue does this PR close?
Rationale for this change
Logical Plan for datatype Int64 and UInt64 differs, UInt64 Logical Plan's Union are wrapped up in Projection, and EliminateNestedUnion OptimezerRule is not applied leading to significantly longer execution time.
What changes are included in this PR?
Separating Benchmarks based on datatype, converting a datatype specific function to a generic one.
Are these changes tested?
Yes.
Are there any user-facing changes?
No, benchmarks only.