Search_after With Collapse Pagination Alternative

We want to utilize the search_after pagination strategy rather than from-size pagination strategy as we understood that search_after has better performance for high pagination numbers.

At the same time, we do collapse our query results base on specific field. We are aware of the limitation that search_after can't be applied when collapse is utilized.

Question A: Based on, composite aggregation can be used as an alternative to from-size pagination - do I understand correctly that composite aggregation is used to retrieve page of "record ids", and second query is used to fetch records by ids returned from aggregation?

Question B: Are there other, performance wise better pagination approaches than from-size, that can be used together with field collapsing?

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No, the challenge with doing any form of distributed aggregation with deep pagination is getting remote shards to independently agree on which subset of terms (not docs/doc IDs) to focus on with each request.

For scenarios where you want to do deep pagination there's broadly 3 approaches:

  1. Composite agg - all shards work through results in order of a given grouping key (typically a field's terms e.g. customerID)).
  2. Terms agg with partitioning - each shard works on an algorithmically determined subset of terms (uses the same sort of hash+modulo N partitioning approach used to evenly and deterministically index docs across shards by id)
  3. Transforms API - fuses related docs together at index-time rather than the above query-time approaches.

This wizard can help walk through the options in more detail

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