zhaih opened a new pull request, #15184:
URL: https://github.com/apache/lucene/pull/15184

   ### Description
   As title, add more comments about concurrency, and also removes 
   `addGraphNode(int node, UpdateableRandomVectorScorer scorer)` and ensure all 
`addGraphNode(int node)` call will not recreate a new scorer.
   
   ### Test
   Did run benchmark on 100d vectors, didn't find any regression
   
   #### candidate runs
   single thread
   ```
   recall  latency(ms)  netCPU  avgCpuCount    nDoc  topK  fanout  maxConn  
beamWidth  quantized  index(s)  index_docs/s  force_merge(s)  num_segments  
index_size(MB)  vec_disk(MB)  vec_RAM(MB)  indexType
    0.804        0.230   0.225        0.978  500000   100      50       64      
  250         no     14.07      35549.24           57.87             1          
216.95       190.735      190.735       HNSW
   ```
   multi thread
   ```
   recall  latency(ms)  netCPU  avgCpuCount    nDoc  topK  fanout  maxConn  
beamWidth  quantized  index(s)  index_docs/s  force_merge(s)  num_segments  
index_size(MB)  vec_disk(MB)  vec_RAM(MB)  indexType
    0.835        0.244   0.239        0.980  500000   100      50       64      
  250         no     14.05      35584.66           18.36             1          
220.28       190.735      190.735       HNSW
   ```
   
   #### baseline runs
   single thread
   ```
   recall  latency(ms)  netCPU  avgCpuCount    nDoc  topK  fanout  maxConn  
beamWidth  quantized  index(s)  index_docs/s  force_merge(s)  num_segments  
index_size(MB)  vec_disk(MB)  vec_RAM(MB)  indexType
    0.805        0.230   0.226        0.983  500000   100      50       64      
  250         no     13.96      35808.92           57.34             1          
216.93       190.735      190.735       HNSW
   ```
   
   multi thread
   ```
   recall  latency(ms)  netCPU  avgCpuCount    nDoc  topK  fanout  maxConn  
beamWidth  quantized  index(s)  index_docs/s  force_merge(s)  num_segments  
index_size(MB)  vec_disk(MB)  vec_RAM(MB)  indexType
    0.834        0.252   0.248        0.984  500000   100      50       64      
  250         no     14.32      34916.20           18.31             1          
220.28       190.735      190.735       HNSW
   ```


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