LUCENE-10297: Speed up medium cardinality fields with readLongs and SIMD

[gf2121]

We introduced a bitset optimization for extremly low cardinality fields in https://issues.apache.org/jira/browse/LUCENE-10233, but medium cardinality fields (like 32/128) can rarely trigger this optimization, I'm trying to find out a way to speed up them.

In apache/lucene-solr#1538, we made some effort to use readLELongs to speed up BKD id blocks, but did not get a obvious gain on this approach. I think the reason could probably be that we were trying to optimize the unsorted situation (typically happens for high cardinality fields) and the bottleneck of queries on high cardinality fields is visitDocValues but not readDocIds.

However, medium cardinality fields may be tempted for this optimization because they need to read lots of ids for each term. The basic idea is that we can compute the delta of the sorted ids and encode/decode them like what we do in StoredFieldsInts. I benchmarked the optimization by mocking some random longPoint and querying them with PointInSetQuery. As expected, the medium cardinality fields got spped up and high cardinality fields get even results.

Benchmark Result

doc count	field cardinality	query point	baseline(ms)	candidate(ms)	diff percentage	baseline(QPS)	candidate(QPS)	diff percentage
100000000	32	1	19	16	-15.79%	52.63	62.5	18.75%
100000000	32	2	34	14	-58.82%	29.41	71.43	142.86%
100000000	32	4	76	22	-71.05%	13.16	45.45	245.45%
100000000	32	8	139	42	-69.78%	7.19	23.81	230.95%
100000000	32	16	279	82	-70.61%	3.58	12.2	240.24%
100000000	128	1	17	11	-35.29%	58.82	90.91	54.55%
100000000	128	8	75	23	-69.33%	13.33	43.48	226.09%
100000000	128	16	126	25	-80.16%	7.94	40	404.00%
100000000	128	32	245	50	-79.59%	4.08	20	390.00%
100000000	128	64	528	97	-81.63%	1.89	10.31	444.33%
100000000	1024	1	3	2	-33.33%	333.33	500	50.00%
100000000	1024	8	13	8	-38.46%	76.92	125	62.50%
100000000	1024	32	31	19	-38.71%	32.26	52.63	63.16%
100000000	1024	128	120	67	-44.17%	8.33	14.93	79.10%
100000000	1024	512	480	133	-72.29%	2.08	7.52	260.90%
100000000	8192	1	3	3	0.00%	333.33	333.33	0.00%
100000000	8192	16	18	15	-16.67%	55.56	66.67	20.00%
100000000	8192	64	19	14	-26.32%	52.63	71.43	35.71%
100000000	8192	512	69	43	-37.68%	14.49	23.26	60.47%
100000000	8192	2048	236	134	-43.22%	4.24	7.46	76.12%
100000000	1048576	1	3	2	-33.33%	333.33	500	50.00%
100000000	1048576	16	18	19	5.56%	55.56	52.63	-5.26%
100000000	1048576	64	17	17	0.00%	58.82	58.82	0.00%
100000000	1048576	512	34	32	-5.88%	29.41	31.25	6.25%
100000000	1048576	2048	89	93	4.49%	11.24	10.75	-4.30%

[gf2121]

This is the benchmark script, i post it here in case someone would like to play with it. I'll delete this file later.