Hi Mikhail,
thanks, JSON facet domains may actually be the key! Something like (when a
user from group1 is searching):
1. Facet on price_group1
2. Facet on price for all results that do not have price_group1 field using
JSON facet domain
3. Sum up the facet counts
Best,
Georg
Mikhail Khludnev
Exclude users' products, calculate default price facet, then facet only
user's products (in a main query) and sum facet counts. It's probably can
be done with switching domains in json facets.
On Tue, Apr 4, 2017 at 5:43 PM, Georg Sorst wrote:
> Hi Mikhail,
>
> copying the default field was my f
Hi Mikhail,
copying the default field was my first attempt as well - however, the
system in total has over 50.000 users which may have an individual price on
every product (even though they usually don't). Still, with the copying
approach this results in every document having 50.000 price fields.
Hello Georg,
You can probably use {!frange} and and a few facet.query enumerating price
ranges, but probably it's easier to just copy default price across all
empty price groups in index time.
On Tue, Apr 4, 2017 at 1:14 PM, Georg Sorst wrote:
> Hi list!
>
> My documents are eCommerce items. T
Hi list!
My documents are eCommerce items. They may have a special price for a
certain group of users, but not for other groups of users; in that case the
default price should be used. So the documents look like something like
this:
item:
id: 1
price_default: 11.5
price_group1: 11.2
item:
