theirix opened a new pull request, #21383:
URL: https://github.com/apache/datafusion/pull/21383
## Which issue does this PR close?
- Closes #.
## Rationale for this change
A minor refactoring of `first_last.rs` to improve performance (up to 32%)
and address naming concerns in TODOs.
## What changes are included in this PR?
- Optimise memory allocation in `take_state` - no need to copy vectors and
buffers
- Optimise extracting single elements
- Pre-compute common data for sorting
- Rename structs and functions as recommended in TODOs - a majority of
changes in this PR
- Add benchmark. It's pretty complicated to test aggregates with grouping,
since many operations are stateful, so I introduced end-to-end `evaluate` test
(to actually test taking state) and `convert_to_state` (as in other benches)
## Are these changes tested?
- Existing unit and integration tests
- A new bench has a meaningful result
Improvements: up to 32%
Raw bench result:
<details>
first_value convert_to_state nulls=0%, filter=false
time: [98.086 µs 99.014 µs 100.25 µs]
change: [−15.400% −13.532% −11.559%] (p = 0.00 <
0.05)
Performance has improved.
Found 17 outliers among 100 measurements (17.00%)
4 (4.00%) low mild
3 (3.00%) high mild
10 (10.00%) high severe
Benchmarking first_value evaluate_bench nulls=0%, filter=false, first(2):
Collecting 100 samples in estimated 7.1575 s (10k ite
first_value evaluate_bench nulls=0%, filter=false, first(2)
time: [54.938 µs 55.482 µs 56.060 µs]
change: [−38.163% −36.295% −34.463%] (p = 0.00 <
0.05)
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
5 (5.00%) high mild
4 (4.00%) high severe
Benchmarking first_value evaluate_bench nulls=0%, filter=false, all:
Collecting 100 samples in estimated 7.0741 s (10k iteratio
first_value evaluate_bench nulls=0%, filter=false, all
time: [50.624 µs 51.092 µs 51.612 µs]
change: [−17.955% −16.332% −14.593%] (p = 0.00 <
0.05)
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
5 (5.00%) high mild
4 (4.00%) high severe
first_value convert_to_state nulls=0%, filter=true
time: [2.0647 µs 2.0881 µs 2.1148 µs]
change: [−7.6314% −6.2174% −4.8530%] (p = 0.00 <
0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
2 (2.00%) high mild
6 (6.00%) high severe
Benchmarking first_value evaluate_bench nulls=0%, filter=true, first(2):
Collecting 100 samples in estimated 9.6354 s (10k iter
first_value evaluate_bench nulls=0%, filter=true, first(2)
time: [54.708 µs 55.240 µs 55.805 µs]
change: [−27.249% −24.755% −22.195%] (p = 0.00 <
0.05)
Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
3 (3.00%) high mild
2 (2.00%) high severe
Benchmarking first_value evaluate_bench nulls=0%, filter=true, all:
Collecting 100 samples in estimated 9.6394 s (10k iteration
first_value evaluate_bench nulls=0%, filter=true, all
time: [50.540 µs 50.963 µs 51.424 µs]
change: [−6.8346% −3.9146% −0.8864%] (p = 0.01 <
0.05)
Change within noise threshold.
Found 4 outliers among 100 measurements (4.00%)
1 (1.00%) high mild
3 (3.00%) high severe
Benchmarking first_value convert_to_state nulls=90%, filter=false:
Collecting 100 samples in estimated 5.0440 s (50k iterations
first_value convert_to_state nulls=90%, filter=false
time: [98.054 µs 98.996 µs 100.10 µs]
change: [−3.4798% −2.2129% −1.0173%] (p = 0.00 <
0.05)
Performance has improved.
Found 19 outliers among 100 measurements (19.00%)
1 (1.00%) low severe
8 (8.00%) low mild
2 (2.00%) high mild
8 (8.00%) high severe
Benchmarking first_value evaluate_bench nulls=90%, filter=false, first(2):
Collecting 100 samples in estimated 8.5385 s (10k it
first_value evaluate_bench nulls=90%, filter=false, first(2)
time: [53.780 µs 54.673 µs 55.639 µs]
change: [−17.702% −15.978% −14.173%] (p = 0.00 <
0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
1 (1.00%) low mild
5 (5.00%) high mild
2 (2.00%) high severe
Benchmarking first_value evaluate_bench nulls=90%, filter=false, all:
Collecting 100 samples in estimated 8.2692 s (10k iterati
first_value evaluate_bench nulls=90%, filter=false, all
time: [49.851 µs 50.289 µs 50.755 µs]
change: [−4.8554% −3.1896% −1.3951%] (p = 0.00 <
0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
3 (3.00%) low severe
2 (2.00%) high mild
3 (3.00%) high severe
Benchmarking first_value convert_to_state nulls=90%, filter=true: Collecting
100 samples in estimated 5.0077 s (2.4M iterations
first_value convert_to_state nulls=90%, filter=true
time: [2.0339 µs 2.0465 µs 2.0603 µs]
change: [−1.8037% −0.7068% +0.3821%] (p = 0.22 >
0.05)
No change in performance detected.
Found 8 outliers among 100 measurements (8.00%)
2 (2.00%) low mild
3 (3.00%) high mild
3 (3.00%) high severe
Benchmarking first_value evaluate_bench nulls=90%, filter=true, first(2):
Collecting 100 samples in estimated 9.7925 s (10k ite
first_value evaluate_bench nulls=90%, filter=true, first(2)
time: [54.544 µs 55.119 µs 55.720 µs]
change: [−15.717% −13.982% −12.279%] (p = 0.00 <
0.05)
Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
1 (1.00%) low mild
1 (1.00%) high severe
Benchmarking first_value evaluate_bench nulls=90%, filter=true, all:
Collecting 100 samples in estimated 9.7401 s (10k iteratio
first_value evaluate_bench nulls=90%, filter=true, all
time: [50.126 µs 50.886 µs 51.703 µs]
change: [+0.8379% +4.1713% +7.1024%] (p = 0.00 <
0.05)
Change within noise threshold.
Found 9 outliers among 100 measurements (9.00%)
6 (6.00%) high mild
3 (3.00%) high severe
last_value convert_to_state nulls=0%, filter=false
time: [97.957 µs 98.314 µs 98.692 µs]
change: [−2.8086% −2.0315% −1.2541%] (p = 0.00 <
0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
7 (7.00%) high mild
3 (3.00%) high severe
Benchmarking last_value evaluate_bench nulls=0%, filter=false, first(2):
Collecting 100 samples in estimated 7.0582 s (10k iter
last_value evaluate_bench nulls=0%, filter=false, first(2)
time: [52.692 µs 53.414 µs 54.144 µs]
change: [−22.228% −20.636% −19.153%] (p = 0.00 <
0.05)
Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
1 (1.00%) low mild
2 (2.00%) high mild
2 (2.00%) high severe
Benchmarking last_value evaluate_bench nulls=0%, filter=false, all:
Collecting 100 samples in estimated 6.9411 s (10k iteration
last_value evaluate_bench nulls=0%, filter=false, all
time: [49.781 µs 50.226 µs 50.793 µs]
change: [−1.9658% −0.1634% +1.5825%] (p = 0.86 >
0.05)
No change in performance detected.
Found 11 outliers among 100 measurements (11.00%)
1 (1.00%) low mild
6 (6.00%) high mild
4 (4.00%) high severe
last_value convert_to_state nulls=0%, filter=true
time: [2.0639 µs 2.0781 µs 2.0949 µs]
change: [−0.7535% +0.4491% +1.6752%] (p = 0.47 >
0.05)
No change in performance detected.
Found 11 outliers among 100 measurements (11.00%)
3 (3.00%) low mild
4 (4.00%) high mild
4 (4.00%) high severe
Benchmarking last_value evaluate_bench nulls=0%, filter=true, first(2):
Collecting 100 samples in estimated 9.8040 s (10k itera
last_value evaluate_bench nulls=0%, filter=true, first(2)
time: [53.779 µs 54.311 µs 54.868 µs]
change: [−15.863% −14.071% −12.391%] (p = 0.00 <
0.05)
Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
4 (4.00%) high mild
3 (3.00%) high severe
Benchmarking last_value evaluate_bench nulls=0%, filter=true, all:
Collecting 100 samples in estimated 9.6860 s (10k iterations
last_value evaluate_bench nulls=0%, filter=true, all
time: [50.276 µs 50.794 µs 51.429 µs]
change: [−1.6780% +0.0697% +1.9541%] (p = 0.94 >
0.05)
No change in performance detected.
Found 6 outliers among 100 measurements (6.00%)
2 (2.00%) high mild
4 (4.00%) high severe
last_value convert_to_state nulls=90%, filter=false
time: [97.508 µs 98.412 µs 99.486 µs]
change: [−1.2994% −0.3404% +0.8319%] (p = 0.52 >
0.05)
No change in performance detected.
Found 9 outliers among 100 measurements (9.00%)
2 (2.00%) low mild
3 (3.00%) high mild
4 (4.00%) high severe
Benchmarking last_value evaluate_bench nulls=90%, filter=false, first(2):
Collecting 100 samples in estimated 8.9282 s (10k ite
last_value evaluate_bench nulls=90%, filter=false, first(2)
time: [54.064 µs 54.748 µs 55.433 µs]
change: [−15.790% −13.678% −11.790%] (p = 0.00 <
0.05)
Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
3 (3.00%) low mild
1 (1.00%) high mild
1 (1.00%) high severe
Benchmarking last_value evaluate_bench nulls=90%, filter=false, all:
Collecting 100 samples in estimated 9.2411 s (10k iteratio
last_value evaluate_bench nulls=90%, filter=false, all
time: [49.964 µs 50.731 µs 51.630 µs]
change: [−2.4530% −0.2470% +1.8407%] (p = 0.82 >
0.05)
No change in performance detected.
Found 9 outliers among 100 measurements (9.00%)
8 (8.00%) high mild
1 (1.00%) high severe
last_value convert_to_state nulls=90%, filter=true
time: [2.0660 µs 2.0874 µs 2.1139 µs]
change: [−3.2299% −1.8585% −0.5850%] (p = 0.01 <
0.05)
Change within noise threshold.
Found 10 outliers among 100 measurements (10.00%)
4 (4.00%) high mild
6 (6.00%) high severe
Benchmarking last_value evaluate_bench nulls=90%, filter=true, first(2):
Warming up for 3.0000 s
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase
target time to 5.6s, enable flat sampling, or reduce sample count to 60.
Benchmarking last_value evaluate_bench nulls=90%, filter=true, first(2):
Collecting 100 samples in estimated 5.6274 s (5050 ite
last_value evaluate_bench nulls=90%, filter=true, first(2)
time: [53.565 µs 54.399 µs 55.381 µs]
change: [−18.757% −16.680% −14.334%] (p = 0.00 <
0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
8 (8.00%) high mild
Benchmarking last_value evaluate_bench nulls=90%, filter=true, all: Warming
up for 3.0000 s
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase
target time to 5.3s, enable flat sampling, or reduce sample count to 60.
Benchmarking last_value evaluate_bench nulls=90%, filter=true, all:
Collecting 100 samples in estimated 5.3402 s (5050 iteratio
last_value evaluate_bench nulls=90%, filter=true, all
time: [49.473 µs 50.055 µs 50.743 µs]
change: [−41.448% −32.836% −24.471%] (p = 0.00 <
0.05)
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
5 (5.00%) high mild
4 (4.00%) high severe
cargo bench --bench first_last -- --baseline main-first_last3 810.16s user
14.72s system 135% cpu 10:09.30 total
</details>
## Are there any user-facing changes?
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