Optimise DisjunctionMaxBulkScorer

[iprithv]

Description:

Made two optimisations here:

1. Reuse inner LeafCollector : The anonymous LeafCollector was allocated inside the inner do-while loop for every sub-scorer in every window. Moved to a reusable field (innerCollector), eliminating per-window allocations and GC pressure. Measured 4.3x faster in allocation microbenchmark.

2. Inline score reset during replay : Replaced Arrays.fill(windowScores, 0f) (which zeros all 4096 entries unconditionally) with windowScores[doc] = 0f inline during the replay loop. Since the replay already reads windowScores[doc], the reset piggybacks on the same cache line access at near-zero cost.

Benchmark evidence (window=4096, 200k iterations, best of 3):

Matches/Window	OLD (replay + fill)	NEW (inline reset)	Speedup
10	272.0 ms	25.1 ms	10.83x
50	330.7 ms	84.7 ms	3.90x
100	405.3 ms	159.8 ms	2.54x
500	979.4 ms	742.4 ms	1.32x
1000	1683.7 ms	1443.8 ms	1.17x
4096 (full)	5521.0 ms	5352.8 ms	1.03x

Faster at ALL densities : never slower, even when fully saturated.

Precedent

For both I followed MaxScoreBulkScorer, which already uses selective score reset during its replay loop.

[iprithv]

@uschindler would be great if you could take a look at this, thanks!

[uschindler]

@uschindler would be great if you could take a look at this, thanks!

I can have a look, but I think @jpountz is the better one to look at this

Uwe

[github-actions]

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[iprithv]

sure thanks @uschindler, @jpountz, could you please help review this? Thanks!