There’s a lot of confusion about using points-based fields for faceting, see:
https://issues.apache.org/jira/browse/SOLR-13227 for instance.
Two options you might try:
1> copyField to a string field and facet on that (won’t work, of course, for
any kind of interval/range facet)
2> use the deprecated Trie field instead. You could use the copyField to a Trie
field for this too.
Best,
Erick
> On Jun 11, 2020, at 9:39 AM, James Bodkin <james.bod...@loveholidays.com>
> wrote:
>
> We’ve been running a load test against our index and have noticed that the
> facet queries are significantly slower than we would like.
> Currently these types of queries are taking several seconds to execute and
> are wondering if it would be possible to speed these up.
> Repeating the same query over and over does not improve the response time so
> does not appear to utilise any caching.
> Ideally we would like to be targeting a response time around tens or hundreds
> of milliseconds if possible.
>
> An example query that is taking around 2-3 seconds to execute is:
>
> q=*.*
> facet=true
> facet.field=D_UserRatingGte
> facet.mincount=1
> facet.limit=-1
> rows=0
>
> "response":{"numFound":18979503,"start":0,"maxScore":1.0,"docs":[]}
> "facet_counts":{
> "facet_queries":{},
> "facet_fields":{
> "D_UserRatingGte":[
> "1575",16614238,
> "1576",16614238,
> "1577",16614238,
> "1578",16065938,
> "1579",12079545,
> "1580",458799]},
> "facet_ranges":{},
> "facet_intervals":{},
> "facet_heatmaps":{}}}
>
> I have also tried the equivalent query using the JSON Facet API with the same
> outcome of slow response time.
> Additionally I have tried changing the facet method (on both facet apis) with
> the same outcome of slow response time.
>
> The underlying field for the above query is configured as a
> solr.IntPointField with docValues, indexed and multiValued set to true.
> The index has just under 19 million documents and the physical size on disk
> is 10.95GB. The index is read-only and consists of 4 segments with 0
> deletions.
> We’re running standalone Solr 8.3.1 with a 8GB Heap and the underlying Google
> Cloud Virtual Machine in our load test environment has 6 vCPUs, 32G RAM and
> 100GB SSD.
>
> Would anyone be able to point me in a direction to either improve the
> performance or understand the current performance is expected?
>
> Kind Regards,
>
> James Bodkin
