Implement a series of microbenchmarks giving a good picture of the performance of hash join implemented in Arrow across different set of dimensions.
Compare the performance against some other product(s).
Add scripts for generating useful visual reports giving a good picture of the costs of hash join.

Examples of dimensions to explore in microbenchmarks:

• number of duplicate keys on build side
• relative size of build side to probe side
• selectivity of the join
• number of key columns
• number of payload columns
• filtering performance for semi- and anti- joins
• dense integer key vs sparse integer key vs string key
• build size
• scaling of build, filtering, probe
• inner vs left outer, inner vs right outer
• left semi vs right semi, left anti vs right anti, left outer vs right outer
• non-uniform key distribution
• monotonic key values in input, partitioned key values in input (with and without per batch min-max metadata)
• chain of multiple hash joins
• overhead of Bloom filter for non-selective Bloom filter

Reporter: Michal Nowakiewicz / @michalursa
Assignee: Sasha Krassovsky / @save-buffer

Related issues:

• [C++][Compute] Hash Join performance improvement (is a child of)

PRs and other links:

• GitHub Pull Request #11876

_{Note: This issue was originally created as ARROW-14479. Please see the migration documentation for further details.}