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https://issues.apache.org/jira/browse/LUCENE-10054?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17402399#comment-17402399
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Mayya Sharipova commented on LUCENE-10054:
------------------------------------------

[~sokolov] Thanks your for your feedback. I've modified the diagram to expand 
all abbreviations.

 
{quote}I wonder if we'll need {{ep}} as a special case – it's really just the 
single node in the max level isn't it?
{quote}
Great comment, we don't need ep, I've removed it from the diagram.. Although 
the max level may contain several nodes, it is the first node in the max level 
that is served as the graph's entry point. 

 
{quote}Could you explain what is in each of the {{NodesLevelX}}? I guess it's a 
list of the ordinals in level 0 that are contained in the other level – but I 
wonder if we will need this
{quote}
I've expanded the explanation, but I think with need this info, as I can't see 
how we can find for each level the closest nodes to a query; these ordinals 
allow us to get the vector values for distance calculations. 

 
{quote}Should we implement the in-memory version before defining the 
serialization?
{quote}
 

Agree. Great suggestion.

 

> Handle hierarchy in HNSW graph
> ------------------------------
>
>                 Key: LUCENE-10054
>                 URL: https://issues.apache.org/jira/browse/LUCENE-10054
>             Project: Lucene - Core
>          Issue Type: Task
>            Reporter: Mayya Sharipova
>            Priority: Major
>          Time Spent: 0.5h
>  Remaining Estimate: 0h
>
> Currently HNSW graph is represented as a single layer graph. 
>  We would like to extend it to handle hierarchy as per 
> [discussion|https://issues.apache.org/jira/browse/LUCENE-9004?focusedCommentId=17393216&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-17393216].
>  
>  
> TODO tasks:
> - add multiple layers in the HnswGraph class
>  - modify the format in  Lucene90HnswVectorsWriter and 
> Lucene90HnswVectorsReader to handle multiple layers
> - modify graph construction and search algorithm to handle hierarchy
>  - run benchmarks



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