Test histogram precision for ANALYZE, 2023

We need to test precision of histograms (both DOUBLE_PREC_HB and JSON_HB) with different analyze_sample_percentage settings.

Goals:

• Catch possible bugs, or just undesirable estimates.
• Validate analyze_sample_percentage=0 before making it the default.

Means:
Running full benchmarks is not a good way to achieve this:

• It is difficult to see if better query plans are caused by better/worse selectivity estimates.
• Benchmark queries do only a few requests to histogram data.

We reuse the approach from histogram-test [1] script:

• Get some dataset somewhere
• Collect histogram
• Run small test queries and see what estimates the optimizer gets from histogram code for various ranges.
  • ask for common/uncommon values
  • ask for wide/narrow intervals
  • etc

Things to check for

• Height-balanced histograms should not produce errors that are larger than bucket_size (right?)
  • But for DOUBLE_PREC_HB there is also an error due to imprecise storage of bucket endpoint. Not sure what are the bounds on that.

• Using sampling instead of the full dataset should not reduce the precision much.
  • what happens to n_distinct estimate?
  • Monitor disk space. Does it increase less with the percentage 0. How much less?

[1] https://github.com/spetrunia/histogram-test.