You might get some mileage out of encoding what you can in the documents
and doing a standard fq clause on that part, and then have your post-filter
do the really wild stuff. But you're right, you have to be prepared for the
nightmare scenario of your sysadmin who has rights to see everything firin
: Actually, after thinking for a bit, it makes sense to apply the post
: filter everywhere, otherwise I wouldn't be able to know the number of
: results overall (something I unfortunately really need).
Not to mention things like facet counts, which need access to the full set
of matching documen
Actually, after thinking for a bit, it makes sense to apply the post
filter everywhere, otherwise I wouldn't be able to know the number of
results overall (something I unfortunately really need).
Anyways, thank you Timothy
Colin Hebert
On 28 February 2013 17:38, Colin Hebert wrote:
> I know tha
I know that the query selects everything, this is why I made this
request to test my solution.
If a user make a query with a very large amount of results with
paging, I expected the post filter to be executed only when necessary
(as it can be expensive).
Colin
On 28 February 2013 17:25, Timothy
Hi Colin,
Your query is *:* so that is every document. Try a query that only
matches a small subset and see if you get different results.
Cheers,
Tim
On Thu, Feb 28, 2013 at 8:17 AM, Colin Hebert wrote:
> Thank you Timothy,
>
> With the indication you gave me (and the help of this article
> htt
Thank you Timothy,
With the indication you gave me (and the help of this article
http://searchhub.org/2012/02/22/custom-security-filtering-in-solr/ ) I
managed to draft my own filter, but it seems that it doesn't work
quite as I expected.
Here is what I've done so far:
https://github.com/ColinHeb
Hi Colin,
I think a filter is definitely the way to go. Moreover, you should
look into Solr's PostFilter concept which is intended to work with
"expensive" filters. Have a look at Yonik's blog post on this topic:
http://yonik.com/posts/advanced-filter-caching-in-solr/
Cheers,
Tim
On Tue, Feb 26,
