GH-36297: [C++][Parquet] Benchmark for non-binary dict encoding

[mapleFU]

Rationale for this change

Add benchmark for non-binary dict encoding

What changes are included in this PR?

Add benchmark BM_DictEncodingInt64

Are these changes tested?

no need

Are there any user-facing changes?

no

• Closes: [C++][Parquet] Benchmark Dict Encoding for non-binary types #36297

[github-actions]

⚠️ GitHub issue #36297 has been automatically assigned in GitHub to PR creator.

[mapleFU]

@pitrou Would you mind take a look? Or here are already some benchmarks here?

[pitrou]

Why not, but is this useful? Is dictionary encoding often used with integers?

[mapleFU]

Hmm sometimes we use dictionary with integer, and I found that there're not benchmark for it. So add this benchmark.

[pitrou]

Are there decoding benchmarks already?

[mapleFU]

@pitrou Seems that we already have some decode test before. But they only test one value, see DecodeDict. I've unify the EncodeDict as same as DecodeDict

[pitrou]

Thanks @mapleFU ! A couple other suggestions.

[pitrou]

Can you also add a SetItemsProcessed here and possibly in other benchmark functions?

[pitrou]

And by the way:

Suggested change

	state.SetBytesProcessed(state.iterations() * state.range(0) * sizeof(T));
	state.SetBytesProcessed(state.iterations() * num_values * sizeof(T));

[pitrou]

You addressed only one comment here.

[mapleFU]

Sorry for missing the message, I've fixed it and paste the result

[mapleFU]

Comment fixed

[mapleFU]

M1 MacOS, clang++13.0, Release(O2):

BM_DictDecodingInt64_repeats/1024                                     1016 ns         1013 ns       694975 bytes_per_second=7.53056G/s items_per_second=1010.73M/s
BM_DictDecodingInt64_repeats/4096                                     1373 ns         1369 ns       480367 bytes_per_second=22.2907G/s items_per_second=2.99181G/s
BM_DictDecodingInt64_repeats/32768                                    4692 ns         4672 ns       141777 bytes_per_second=52.2591G/s items_per_second=7.0141G/s
BM_DictDecodingInt64_repeats/65536                                    8837 ns         8828 ns        71320 bytes_per_second=55.3124G/s items_per_second=7.42391G/s
BM_DictEncodingInt64_repeats/1024                                     6120 ns         5971 ns       117212 bytes_per_second=1.27764G/s items_per_second=171.482M/s
BM_DictEncodingInt64_repeats/4096                                    23239 ns        23204 ns        30078 bytes_per_second=1.31518G/s items_per_second=176.52M/s
BM_DictEncodingInt64_repeats/32768                                  192336 ns       185895 ns         3687 bytes_per_second=1.31332G/s items_per_second=176.271M/s
BM_DictEncodingInt64_repeats/65536                                  386575 ns       371757 ns         1870 bytes_per_second=1.31344G/s items_per_second=176.287M/s
BM_DictDecodingInt64_literals/1024                                    2027 ns         1862 ns       376684 bytes_per_second=4.09711G/s items_per_second=549.904M/s
BM_DictDecodingInt64_literals/4096                                    5082 ns         4902 ns       143489 bytes_per_second=6.22589G/s items_per_second=835.625M/s
BM_DictDecodingInt64_literals/32768                                  68385 ns        59901 ns        12076 bytes_per_second=4.07575G/s items_per_second=547.038M/s
BM_DictDecodingInt64_literals/65536                                 114003 ns       111464 ns         6023 bytes_per_second=4.38064G/s items_per_second=587.959M/s
BM_DictEncodingInt64_literals/1024                                    7405 ns         7394 ns        94886 bytes_per_second=1056.53M/s items_per_second=138.482M/s
BM_DictEncodingInt64_literals/4096                                   30762 ns        30462 ns        23066 bytes_per_second=1025.87M/s items_per_second=134.463M/s
BM_DictEncodingInt64_literals/32768                                 267431 ns       267176 ns         2494 bytes_per_second=935.713M/s items_per_second=122.646M/s
BM_DictEncodingInt64_literals/65536                                 581665 ns       580486 ns         1139 bytes_per_second=861.347M/s items_per_second=112.898M/s

[conbench-apache-arrow]

Conbench analyzed the 6 benchmark runs on commit 4198aacf.

There were 8 benchmark results indicating a performance regression:

• Commit Run on arm64-t4g-linux-compute at 2023-06-27 21:08:26Z

  • params=threads:4/task_cost:100000/real_time, source=cpp-micro, suite=arrow-thread-pool-benchmark

• Commit Run on arm64-m6g-linux-compute at 2023-06-27 21:03:58Z

  • params=/ConvertToSparseCOOTensorInt32, source=cpp-micro, suite=arrow-tensor-conversion-benchmark

• and 6 more (see the report linked below)

The full Conbench report has more details.