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https://issues.apache.org/jira/browse/SOLR-13807?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael Gibney updated SOLR-13807:
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Description:
Solr does not have a facet count cache; so for _every_ request, term facets are
recalculated for _every_ (facet) field, by iterating over _every_ field value
for _every_ doc in the result domain, and incrementing the associated count.
As a result, subsequent requests end up redoing a lot of the same work,
including all associated object allocation, GC, etc. This situation could
benefit from integrated caching.
Because of the domain-based, serial/iterative nature of term facet calculation,
latency is proportional to the size of the result domain. Consequently, one
common/clear manifestation of this issue is high latency for faceting over an
unrestricted domain (e.g., {{*:*}}), as might be observed on a top-level
landing page that exposes facets. This type of "static" case is often mitigated
by external (to Solr) caching, either with a caching layer between Solr and a
front-end application, or within a front-end application, or even with a
caching layer between the end user and a front-end application.
But in addition to the overhead of handling this caching elsewhere in the stack
(or, for a new user, even being aware of this as a potential issue to
mitigate), any external caching mitigation is really only appropriate for
relatively static cases like the "landing page" example described above. A
Solr-internal facet count cache (analogous to the {{filterCache}}) would
provide the following additional benefits:
# ease of use/out-of-the-box configuration to address a common performance
concern
# compact (specifically caching count arrays, without the extra baggage that
accompanies a naive external caching approach)
# NRT-friendly (could be implemented to be segment-aware)
# modular, capable of reusing the same cached values in conjunction with
variant requests over the same result domain (this would support common use
cases like paging, but also potentially more interesting direct uses of
facets).
# could be used for distributed refinement (i.e., if facet counts over a given
domain are cached, a refinement request could simply look up the ordinal value
for each enumerated term and directly grab the count out of the count array
that was cached during the first phase of facet calculation)
# composable (e.g., in aggregate functions that calculate values based on
facet counts across different domains, like SKG/relatedness – see SOLR-13132)
was:
Solr does not have a facet count cache; so for _every_ request, term facets are
recalculated for _every_ (facet) field, by iterating over _every_ field value
for _every_ doc in the result domain, and incrementing the associated count.
This redoes a lot of work, including all associated object allocation, GC,
etc., and could benefit greatly from integrated caching.
Because of the domain-based, serial/iterative nature of term facet calculation,
latency is proportional to the size of the result domain. Consequently, one
common/clear manifestation of this issue is high latency for faceting over an
unrestricted domain (e.g., {{*:*}}), as might be observed on a top-level
landing page that exposes facets. This type of "static" case is often mitigated
by external (to Solr) caching, either with a caching layer between Solr and a
front-end application, or within a front-end application, or even with a
caching layer between the end user and a front-end application.
But in addition to the overhead of handling this caching elsewhere in the stack
(or, for a new user, even being aware of this as a potential issue to
mitigate), any external caching mitigation is really only appropriate for
relatively static cases like the "landing page" example described above. A
Solr-internal facet count cache (analogous to the {{filterCache}}) would
provide the following additional benefits:
# ease of use/out-of-the-box configuration to address a common performance
concern
# compact (specifically caching count arrays, without the extra baggage that
accompanies a naive external caching approach)
# NRT-friendly (could be implemented to be segment-aware)
# modular, capable of reusing the same cached values in conjunction with
variant requests over the same result domain (this would support common use
cases like paging, but also potentially more interesting direct uses of
facets).
# could be used for distributed refinement (i.e., if facet counts over a given
domain are cached, a refinement request could simply look up the ordinal value
for each enumerated term and directly grab the count out of the count array
that was cached during the first phase of facet calculation)
# composable (e.g., in aggregate functions that calculate values based on
facet counts across different domains, like SKG/relatedness – see SOLR-13132)
> Caching for term facet counts
> -----------------------------
>
> Key: SOLR-13807
> URL: https://issues.apache.org/jira/browse/SOLR-13807
> Project: Solr
> Issue Type: New Feature
> Security Level: Public(Default Security Level. Issues are Public)
> Components: Facet Module
> Affects Versions: master (9.0), 8.2
> Reporter: Michael Gibney
> Priority: Minor
>
> Solr does not have a facet count cache; so for _every_ request, term facets
> are recalculated for _every_ (facet) field, by iterating over _every_ field
> value for _every_ doc in the result domain, and incrementing the associated
> count.
> As a result, subsequent requests end up redoing a lot of the same work,
> including all associated object allocation, GC, etc. This situation could
> benefit from integrated caching.
> Because of the domain-based, serial/iterative nature of term facet
> calculation, latency is proportional to the size of the result domain.
> Consequently, one common/clear manifestation of this issue is high latency
> for faceting over an unrestricted domain (e.g., {{*:*}}), as might be
> observed on a top-level landing page that exposes facets. This type of
> "static" case is often mitigated by external (to Solr) caching, either with a
> caching layer between Solr and a front-end application, or within a front-end
> application, or even with a caching layer between the end user and a
> front-end application.
> But in addition to the overhead of handling this caching elsewhere in the
> stack (or, for a new user, even being aware of this as a potential issue to
> mitigate), any external caching mitigation is really only appropriate for
> relatively static cases like the "landing page" example described above. A
> Solr-internal facet count cache (analogous to the {{filterCache}}) would
> provide the following additional benefits:
> # ease of use/out-of-the-box configuration to address a common performance
> concern
> # compact (specifically caching count arrays, without the extra baggage that
> accompanies a naive external caching approach)
> # NRT-friendly (could be implemented to be segment-aware)
> # modular, capable of reusing the same cached values in conjunction with
> variant requests over the same result domain (this would support common use
> cases like paging, but also potentially more interesting direct uses of
> facets).
> # could be used for distributed refinement (i.e., if facet counts over a
> given domain are cached, a refinement request could simply look up the
> ordinal value for each enumerated term and directly grab the count out of the
> count array that was cached during the first phase of facet calculation)
> # composable (e.g., in aggregate functions that calculate values based on
> facet counts across different domains, like SKG/relatedness – see SOLR-13132)
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