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https://issues.apache.org/jira/browse/LUCENE-4272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13537395#comment-13537395
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Shai Erera commented on LUCENE-4272:
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bq. Especially the impact on mean average precision.
I'll focus on performance first because I think that we should give a good
solution for DOCS_ONLY type of fields.
Also, constructing a test which can reliably check the effect on MAP is not
trivial. Maybe if e.g. I replace the entire content field, or some part of it.
But, to measure MAP I'd need to use the TREC (GOV, GOV2) collection, for which
I have judgements. But then I believe I'm the only one that can run the test?
Unless anyone else has access to that collection? Do you know of any other open
collection with judgements that I can use?
Not saying that it's not important to measure, but to me that comes second in
the list, at least for the first step of field updates.
> another idea for updatable fields
> ---------------------------------
>
> Key: LUCENE-4272
> URL: https://issues.apache.org/jira/browse/LUCENE-4272
> Project: Lucene - Core
> Issue Type: New Feature
> Reporter: Robert Muir
>
> I've been reviewing the ideas for updatable fields and have an alternative
> proposal that I think would address my biggest concern:
> * not slowing down searching
> When I look at what Solr and Elasticsearch do here, by basically reindexing
> from stored fields, I think they solve a lot of the problem: users don't have
> to "rebuild" their document from scratch just to update one tiny piece.
> But I think we can do this more efficiently: by avoiding reindexing of the
> unaffected fields.
> The basic idea is that we would require term vectors for this approach (as
> the already store a serialized indexed version of the doc), and so we could
> just take the other pieces from the existing vectors for the doc.
> I think we would have to extend vectors to also store the norm (so we dont
> recompute that), and payloads, but it seems feasible at a glance.
> I dont think we should discard the idea because vectors are slow/big today,
> this seems like something we could fix.
> Personally I like the idea of not slowing down search performance to solve
> the problem, I think we should really start from that angle and work towards
> making the indexing side more efficient, not vice-versa.
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