Update precombine benchmark to better represent varied workloads

[lukecwik]

1. Represent more data distributions (hot key, uniform, normal, unique)
2. Run longer allowing the JIT to function
3. Have a random ordering of data
4. Use a blackhole to prevent to the JIT from optimizing away the data

Updated benchmark numbers are (note that I renamed the class before running):

Benchmark                       (distribution)  (globallyWindowed)   Mode  Cnt   Score   Error  Units
CombinerTableBenchmark.combine         uniform                true  thrpt   15  12.838 ± 0.314  ops/s
CombinerTableBenchmark.combine         uniform               false  thrpt   15   5.633 ± 0.283  ops/s
CombinerTableBenchmark.combine          normal                true  thrpt   15   6.869 ± 0.196  ops/s
CombinerTableBenchmark.combine          normal               false  thrpt   15   4.165 ± 0.271  ops/s
CombinerTableBenchmark.combine          hotKey                true  thrpt   15  13.697 ± 0.320  ops/s
CombinerTableBenchmark.combine          hotKey               false  thrpt   15   6.143 ± 0.458  ops/s
CombinerTableBenchmark.combine      uniqueKeys                true  thrpt   15   2.346 ± 0.063  ops/s
CombinerTableBenchmark.combine      uniqueKeys               false  thrpt   15   1.676 ± 0.055  ops/s

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[lukecwik]

R: @bhisevishal

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control

[bhisevishal]

Thanks @lukecwik Looks good. Is it possible to have muti threaded benchmark as well.

[lukecwik]

Thanks @lukecwik Looks good. Is it possible to have muti threaded benchmark as well.

I'm not sure it will provide much value but you can always configure the benchmark with the additional flag -t 4 for running it concurrently with 4 threads or add the annotation @Threads(4) to the benchmark itself (example).

Note that this benchmark only checks the combiner table and doesn't represent a full transform graph.