Optimize RowNumberReader to be 8x faster

[Samyak2]

Which issue does this PR close?

• Closes None

Rationale for this change

We internally found RowNumberReader to be a hot path in some of our queries. Flamegraphs showed ~70% of the cpu time taken by methods in RowNumberReader.

These can be made an order of magnitude faster (benchmarks below).

What changes are included in this PR?

• Instead of storing an iterator over individual row numbers, we now store a vec of ranges.
  • These ranges are not materialized into a fully array until needed.
• read_records was previously linear in terms of number of rows read.
  • Now it's close to constant since one batch (8192 rows) usually is satisfied by one row range (which comes from a row group).
  • Same for skip_records
• consume_batch is still linear in terms of rows, but it is faster since it can pre-allocate the output vec.
  • Previously, the Flatten iter would have prevented it pre-allocating (it's not an ExactSizeIterator).

Are these changes tested?

• Yes, added more unit tests
• I have some benchmarks at Add micro-benchmark for RowNumberReader Samyak2/arrow-rs#1, but they need RowNumberReader to be pub, so I've not included them here

Before:

Benchmarking row_number_read_consume: Warming up for 3.0000 s
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 7.0s, enable flat sampling, or reduce sample count to 50.
row_number_read_consume time:   [1.3915 ms 1.3967 ms 1.4035 ms]
Found 11 outliers among 100 measurements (11.00%)
  1 (1.00%) low severe
  1 (1.00%) low mild
  5 (5.00%) high mild
  4 (4.00%) high severe

row_number_skip_and_read
                        time:   [716.61 µs 718.14 µs 719.91 µs]
Found 6 outliers among 100 measurements (6.00%)
  1 (1.00%) low severe
  1 (1.00%) low mild
  3 (3.00%) high mild
  1 (1.00%) high severe

After:

row_number_read_consume time:   [159.00 µs 160.81 µs 162.68 µs]
                        change: [−88.900% −88.721% −88.505%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
  1 (1.00%) low mild
  2 (2.00%) high mild

row_number_skip_and_read
                        time:   [79.057 µs 79.924 µs 80.846 µs]
                        change: [−89.025% −88.865% −88.712%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
  2 (2.00%) high mild

Ranging from 8.6x to 8.9x faster!

Are there any user-facing changes?

No