Details
-
Improvement
-
Status: Open
-
Major
-
Resolution: Unresolved
-
None
-
None
-
None
-
None
Description
This is a parent wrapper issue for a collection of small-ish, improvements that can be made to the StatsComponent and the FacetComponent to allow them to play nicer together and – in combination with eachother – provide more powerful combinations of features that will still work well in a SolrCloud setup.
The end goal, once all tasks are completed, is that it should be possible to specify some query params like...
stats.field={!tag=price_stats min=true max=true}product_price
stats.field={!tag=avg_rating mean=true}user_rating
facet.range={!tag=price_ranges stats=rating_stats facet.range.start=...}price
facet.pivot={!range=price_ranges stats=price_stats}store,category
And in the results you would get:
- the min & max product_price for all matching documents
- the mean user_rating for all matching documents
- range facet counts over the price field
- for each range bucket, in addition to the normal constraint count there would also be:
- the average user_rating for all documents in that range bucket.
- for each range bucket, in addition to the normal constraint count there would also be:
- pivot facets drilling down on all matching documents, first by store then by category
- for value/count node in the pivot tree, there would also be:
- the min & max product_price for all documents matching this pivot constraint
- range facet counts over the price field for documents matching this pivot constraint
- for each range bucket, in addition to the normal constraint count there would also be:
- the average user_rating for all documents in that range bucket.
- for each range bucket, in addition to the normal constraint count there would also be:
- for value/count node in the pivot tree, there would also be: