lucene-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Yonik Seeley (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SOLR-9142) JSON Facet, add hash table method for terms
Date Thu, 01 Sep 2016 01:50:21 GMT

    [ https://issues.apache.org/jira/browse/SOLR-9142?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15454007#comment-15454007
] 

Yonik Seeley commented on SOLR-9142:
------------------------------------

Thanks David, good improvements!

bq. DocSet is not necessarily an ordered set – so says it's javadocs. Yet our collecting
code assumes it is! For large ones it is but HashDocSet it won't be.
I think HashDocSet (as well as DocList) should be moved out of the DocSet hierarchy.  HashDocSet
is currently only used as a utility class internal to certain faceting methods.
Perhaps we could use the "Bits" interface instead when we want/require a fast random access
set.

I was surprised this adds a method (dvhash).  Although perhaps convenient for testing things
out, it would be tedious in production since the best method will depend on the domain size,
which will often not be known ahead of time by the user.  For the normal "dv" method, we should
definitely make it pick hashing when the domain is much smaller than the number of unique
terms in the field.  We already do stuff like this in the DV faceting to pick whether we accumulate
global ords, or accumulate local (per-seg) ords first and then do a mapping at the end to
global ords.


> JSON Facet, add hash table method for terms
> -------------------------------------------
>
>                 Key: SOLR-9142
>                 URL: https://issues.apache.org/jira/browse/SOLR-9142
>             Project: Solr
>          Issue Type: Improvement
>          Components: Facet Module
>            Reporter: Varun Thacker
>            Assignee: David Smiley
>             Fix For: 6.3
>
>         Attachments: SOLR_9412_FacetFieldProcessorByHashDV.patch, SOLR_9412_FacetFieldProcessorByHashDV.patch,
SOLR_9412_FacetFieldProcessorByHashDV.patch, SOLR_9412_FacetFieldProcessorByHashDV.patch,
SOLR_9412_FacetFieldProcessorByHashDV.patch
>
>
> I indexed a dataset of 2M docs
> {{top_facet_s}} has a cardinality of 1000 which is the top level facet.
> For nested facets it has two fields {{sub_facet_unique_s}} and {{sub_facet_unique_td}}
which are string and double and have cardinality 2M
> The nested query for the double field returns in the 1s mark always. The nested query
for the string field takes roughly 10s to execute.
> {code:title=nested string facet|borderStyle=solid}
> q=*:*&rows=0&json.facet=
> 	{
> 		"top_facet_s": {
> 			"type": "terms",
> 			"limit": -1,
> 			"field": "top_facet_s",
> 			"mincount": 1,
> 			"excludeTags": "ANY",
> 			"facet": {
> 				"sub_facet_unique_s": {
> 					"type": "terms",
> 					"limit": 1,
> 					"field": "sub_facet_unique_s",
> 					"mincount": 1
> 				}
> 			}
> 		}
> 	}
> {code}
> {code:title=nested double facet|borderStyle=solid}
> q=*:*&rows=0&json.facet=
> 	{
> 		"top_facet_s": {
> 			"type": "terms",
> 			"limit": -1,
> 			"field": "top_facet_s",
> 			"mincount": 1,
> 			"excludeTags": "ANY",
> 			"facet": {
> 				"sub_facet_unique_s": {
> 					"type": "terms",
> 					"limit": 1,
> 					"field": "sub_facet_unique_td",
> 					"mincount": 1
> 				}
> 			}
> 		}
> 	}
> {code}
> I tried to dig deeper to understand why are string nested faceting that slow compared
to numeric field
> Since the top facet has a cardinality of 1000 we have to calculate sub facets on each
of them. Now the key difference was in the implementation of the two .
> For the string field, In {{FacetField#getFieldCacheCounts}} we call {{createCollectAcc}}
with nDocs=0 and numSlots=2M . This then initializes an array of 2M. So we create a 2M array
1000 times for this one query which from what I understand makes this query slow.
> For numeric fields {{FacetFieldProcessorNumeric#calcFacets}} uses a CountSlotAcc which
doesn't assign a huge array. In this query it calls {{createCollectAcc}} with numDocs=2k and
numSlots=1024 .
> In string faceting, we create the 2M array because the cardinality is 2M and we use the
array position as the ordinal and value as the count. If we could improve on this it would
speed things up significantly? For sub-facets we know the maximum cardinality can be at max
the top level bucket count.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: dev-unsubscribe@lucene.apache.org
For additional commands, e-mail: dev-help@lucene.apache.org


Mime
View raw message