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Is that a scalable solution? I suppose I'm asking whether:
zombodb in effect evaluates that filtered queryset, then sends a list of ids to ElasticSearch in order to filter the potential results (not scalable, as the size of the search query then grows with the number of Pizza*s in the database), or
does some magic (which in my mind is like creating an effective additional column of relevance which the normal filtered query is then ordered by) such that neither the search query size nor the index complexity increases with the number of things that you filter/exclude?
I'm a bit more used to django-haystack, where in order to achieve this kind of filtering scalably you'd have to have a thing you want to filter against in the search index itself. Excited by the potential of zombodb but needed to check this!
Suggestion
Please could the documentation here include a slightly more in depth note about how those filters are achieved and if it's scalable?
The text was updated successfully, but these errors were encountered:
zombodb in effect evaluates that filtered queryset, then sends a list of ids to ElasticSearch in order to filter the potential results
In fact it's the opposite. The 'name:Hut' search is executed on ElasticSearch side. Then the results are filtered with the additional SQL filters (WHERE). Note results can be limited to avoid heavy ES searches.
Haystack and basically every other search tool I've checked will suffer from similar problems: you need a list of ids to combine SQL filtering with searching (on a separate Search Engine).
But be aware nothing prevents you to ensure you're using only ElasticSearch for searches and completely avoid the use of SQL WHERE / .filter. In fact, that's recommended per docs:
It’s fine to call filter/exclude/etc. before and after search. If possible, the best would be using only a Elasticsearch query.
For that, you just need to use filter everything with the ES syntax. Try the dsl_search method.
However, I agree that's not clear enough, so I think we should separate that into a new warning explaning better what's going on behind the scenes. I'll leave this issue open due to that.
Description
Say we filter the queryset as shown in the docs
Is that a scalable solution? I suppose I'm asking whether:
relevance
which the normal filtered query is then ordered by) such that neither the search query size nor the index complexity increases with the number of things that you filter/exclude?I'm a bit more used to django-haystack, where in order to achieve this kind of filtering scalably you'd have to have a thing you want to filter against in the search index itself. Excited by the potential of zombodb but needed to check this!
Suggestion
Please could the documentation here include a slightly more in depth note about how those filters are achieved and if it's scalable?
The text was updated successfully, but these errors were encountered: