ARROW-10015: [Rust] Simd aggregate kernels

[jhorstmann]

Built on top of ARROW-10040 (#8262)

Benchmarks (run on a Ryzen 3700U laptop with some thermal problems)

Current master without simd:

$ cargo bench --bench aggregate_kernels
sum 512 time: [3.9652 us 3.9722 us 3.9819 us] change: [-0.2270% -0.0896% +0.0672%] (p = 0.23 > 0.05)
No change in performance detected.
Found 14 outliers among 100 measurements (14.00%)
4 (4.00%) high mild
10 (10.00%) high severe
sum nulls 512 time: [9.4577 us 9.4796 us 9.5112 us] change: [+2.9175% +3.1309% +3.3937%] (p = 0.00 < 0.05)
Performance has regressed.
Found 4 outliers among 100 measurements (4.00%)
1 (1.00%) high mild
3 (3.00%) high severe

This branch without simd (speedup probably due to accessing the data via a slice):

sum 512 time: [1.1066 us 1.1113 us 1.1168 us] change: [-72.648% -72.480% -72.310%] (p = 0.00 < 0.05)
Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
7 (7.00%) high mild
6 (6.00%) high severe
sum nulls 512 time: [1.3279 us 1.3364 us 1.3469 us] change: [-86.326% -86.209% -86.085%] (p = 0.00 < 0.05)
Performance has improved.
Found 20 outliers among 100 measurements (20.00%)
4 (4.00%) high mild
16 (16.00%) high severe

This branch with simd:

sum 512 time: [108.58 ns 109.47 ns 110.57 ns] change: [-90.164% -90.033% -89.850%] (p = 0.00 < 0.05)
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
1 (1.00%) high mild
10 (10.00%) high severe
sum nulls 512 time: [249.95 ns 250.50 ns 251.06 ns] change: [-81.420% -81.281% -81.157%] (p = 0.00 < 0.05)
Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
3 (3.00%) high mild
1 (1.00%) high severe

[github-actions]

https://issues.apache.org/jira/browse/ARROW-10015

[jorgecarleitao]

This is really exciting!!

Just to check my understanding, we are talking 9.48 us vs 250 ns when we use this branch with SIMD vs current master without SIMD, which corresponds to a 36x overall improvement. Did you ran the current master with SIMD (to compare them with the same feature gate)?

I will start by reviewing the other branch first.

fyi @andygrove@alamb , this may have "some" impact on the query benchmarks of DataFusion.

[alamb]

I personally think this looks really nice. I didn't examine the entire implementation in detail but I can if that is needed. Nice work @jhorstmann

[alamb]

I am curious (for my own future edification) if this change actually improves performance or if it was just a code cleanup

[jhorstmann]

If I remember correctly, there might have been an issue a bit further down where it previously used the len (in bytes) of the null buffer but after the refactoring needs the length of the array. I don't remember if I did this for consistency or if it caused a test failure.

[alamb]

💯 for improved naming

[alamb]

I wonder too now that you know lots about what bitwise_bin_op_helper does, if you might be able to add a summary in the comments

Like

/// This function creates a new Buffer view aligned on ....fn bitwise_bin_op_helper<F>(

[jhorstmann]

Rebased after merge of ARROW-10040 (#8262)

[andygrove]

I'm planning on running TPC-H benchmarks later today with and without this patch.

[andygrove]

cargo run --release --bin tpch -- --debug --iterations 3 --path /mnt/tpch/s100/parquet --format parquet --query 1 --batch-size 4096 --concurrency 24

Master branch:

Query 1 iteration 0 took 14574 ms
Query 1 iteration 1 took 14623 ms
Query 1 iteration 2 took 14985 ms

This PR:

Query 1 iteration 0 took 14253 ms
Query 1 iteration 1 took 14112 ms
Query 1 iteration 2 took 14290 ms

I also verified that the query produced the same results, so LGTM.

[jhorstmann]

@andygrove seems there is a lot else going on in that query and the sum aggregation is just a small part. I'll try to setup the benchmarks myself and have a look. Would be interesting to compare a similar query without the grouping, filtering and sorting.