Support intra-segment search in the query profiler with per-slice and per-partition breakdowns

[prudhvigodithi]

Description

Building on intra-segment search concurrency (#13542) and concurrent-search profiling (#14413), this PR attributes query-profiler timings per slice and per partition, resolving the slice-identification problem left open in #14413's review. #14413 keys leaf breakdowns by Thread, so when one thread runs several slices sequentially their timings merge into one bucket and for intra-segment search it cannot attribute timing to the doc-id-range partitions a segment is split into.

Change

• Reliably identifies slices via a counter assigned at the once-per-slice search(LeafReaderContextPartition[]) seam, independent of thread.
• Keys leaf timings per partition (sliceId, segmentOrd, minDocId, maxDocId), set at searchLeaf(...); both overrides delegate to super (no duplicated search logic).
• Single code path — no concurrent/non-concurrent class split; non-concurrent search is the single-slice degenerate case (one slice covering whole-segment partitions).
• Per-slice threadId/threadName/startTime show how the search parallelized, Thread object replaced by serializable id+name

Sample output

Verified locally by adding a temporary toString() (not included in this PR) and serializing getProfileResult() for a BooleanQuery(+foo:bar foo:baz) over a single segment split into two partitions [0,100) / [100,200) on a 2-thread executor.

[
   {
     "type": "BooleanQuery",
     "description": "+foo:bar foo:baz",
     "breakdown": { "create_weight": 1634167, "create_weight_count": 1 },
     "slices": [
       {
         "slice_id": 0,
         "thread_id": 22,
         "thread_name": "search-worker-caller",
         "partitions": [
           { "segment_ord": 0, "doc_range": [0, 100],
             "breakdown": { "build_scorer": 5185916, "next_doc_count": 101, "score_count": 100, "advance_count": 0 } }
         ]
       },
       {
         "slice_id": 1,
         "thread_id": 23,
         "thread_name": "search-worker-pool-3-thread-1",
         "partitions": [
           { "segment_ord": 0, "doc_range": [100, 200],
             "breakdown": { "build_scorer": 5183792, "next_doc_count": 100, "score_count": 100, "advance_count": 1 } }
         ]
       }
     ],
     "children": [
       {
         "type": "TermQuery", "description": "foo:bar",
         "breakdown": { "create_weight": 903875, "create_weight_count": 1 },
         "slices": [
           { "slice_id": 0, "thread_id": 22, "thread_name": "search-worker-caller",
             "partitions": [ { "segment_ord": 0, "doc_range": [0, 100],
               "breakdown": { "build_scorer": 1026292, "next_doc_count": 101, "score_count": 100 } } ] },
           { "slice_id": 1, "thread_id": 23, "thread_name": "search-worker-pool-3-thread-1",
             "partitions": [ { "segment_ord": 0, "doc_range": [100, 200],
               "breakdown": { "build_scorer": 1008001, "next_doc_count": 100, "score_count": 100 } } ] }
         ],
         "children": []
       },
       {
         "type": "TermQuery", "description": "foo:baz",
         "breakdown": { "create_weight": 52459, "create_weight_count": 1 },
         "slices": [
           { "slice_id": 0, "thread_id": 22, "thread_name": "search-worker-caller",
             "partitions": [ { "segment_ord": 0, "doc_range": [0, 100],
               "breakdown": { "build_scorer": 959, "next_doc_count": 0, "score_count": 0 } } ] },
           { "slice_id": 1, "thread_id": 23, "thread_name": "search-worker-pool-3-thread-1",
             "partitions": [ { "segment_ord": 0, "doc_range": [100, 200],
               "breakdown": { "build_scorer": 708, "next_doc_count": 0, "score_count": 0 } } ] }
         ],
         "children": []
       }
     ]
   }
 ]