mbrette commented on issue #12440:
URL: https://github.com/apache/lucene/issues/12440#issuecomment-1702371365

   An idea, instead of trying to merge the subgraph, is to do a union of 
subgraphs: 
   When we merge, we build a disconnected graph which is the union of all the 
segment graphs. 
   At search time, you explore each subgraph to come up with results.
   If we do this naively, this would be the same as parallel exploration of 
segments. 
   To improve this:
   When we search in this graph, we run a greedy search like we do today, with 
2 small tweaks: 
   * First you make sure that you include candidates from every subgraph. 
   * Second, you don't want the candidates list to be dominated by one subgraph 
(for ex because this is the one you start exploring), so you need a strategy to 
give a fair share for each subgraph. Maybe exploring not greedily by best 
score, but each subgraph in turn. Or maybe maintain your results and candidate 
lists such that the stopping criteria for adding candidates is not only based 
on a single best score for all the candidates, but also account on the best 
score from each subgraph.
   
   The advantages of that approach would be that: 
   * You can explore each subgraph in parallel, like you would do with many 
segments, except that it does not influence the segment strategy for the 
keyword indexes.
   * You can somewhat limit the increase in number of nodes you have to explore 
by having a stopping criteria that is cross-subgraph
   
   But of course, this may become bloated as we start to have many disconnected 
subgraphs. At some point you'll want to do a real merge.
   


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