Compact more aggressively in TopK based upon memory usage

[cetra3]

Which issue does this PR close?

Sort of addresses #19386

Rationale for this change

Compaction in TopK values currently uses some hard set heuristics to decide when to compact. Instead we can use the memory size of the batches as a bound.

What changes are included in this PR?

Adjusts TopK compaction to compact more aggressively, based upon memory size.

Are these changes tested?

Yes and a test has been added.

Are there any user-facing changes?

No

Benchmarks

I'm struggling (in this PR and other PRs...) to get some good reliable benchmarks through.

However with this one it seems like it's mostly the same speed as main or a little faster in some cases:

+ critcmp main topk_memory_batch
group                                                             main                                   topk_memory_batch
-----                                                             ----                                   -----------------
aggregate 10000000 time-series rows                               1.05     45.5±2.13ms        ? ?/sec    1.00     43.5±2.09ms        ? ?/sec
aggregate 10000000 worst-case rows                                1.06     43.9±1.12ms        ? ?/sec    1.00     41.5±1.03ms        ? ?/sec
distinct 10000000 rows asc [TopK]                                 1.00      4.3±0.25ms        ? ?/sec    1.00      4.3±0.07ms        ? ?/sec
distinct 10000000 rows asc [no TopK]                              1.00     42.9±1.83ms        ? ?/sec    1.06     45.5±1.65ms        ? ?/sec
distinct 10000000 rows desc [TopK]                                1.00      4.3±0.07ms        ? ?/sec    1.01      4.3±0.06ms        ? ?/sec
distinct 10000000 rows desc [no TopK]                             1.00     42.4±1.48ms        ? ?/sec    1.05     44.7±1.88ms        ? ?/sec
top k=10 aggregate 10000000 time-series rows                      1.13     10.6±0.54ms        ? ?/sec    1.00      9.4±0.64ms        ? ?/sec
top k=10 aggregate 10000000 time-series rows [Utf8View]           1.08     11.0±0.65ms        ? ?/sec    1.00     10.2±0.48ms        ? ?/sec
top k=10 aggregate 10000000 worst-case rows                       1.04     16.8±1.47ms        ? ?/sec    1.00     16.1±1.44ms        ? ?/sec
top k=10 aggregate 10000000 worst-case rows [Utf8View]            1.10     17.9±1.51ms        ? ?/sec    1.00     16.2±1.16ms        ? ?/sec
top k=10 string aggregate 10000000 time-series rows [Utf8View]    1.11      9.1±0.36ms        ? ?/sec    1.00      8.2±0.35ms        ? ?/sec
top k=10 string aggregate 10000000 time-series rows [Utf8]        1.12      7.8±0.48ms        ? ?/sec    1.00      6.9±0.26ms        ? ?/sec
top k=10 string aggregate 10000000 worst-case rows [Utf8View]     1.06      8.6±0.21ms        ? ?/sec    1.00      8.1±0.20ms        ? ?/sec
top k=10 string aggregate 10000000 worst-case rows [Utf8]         1.07      7.4±0.17ms        ? ?/sec    1.00      6.9±0.13ms        ? ?/sec

[Dandandan]

run benchmarks