This is strange.
1M unique facet terms and 10 terms per document -- sounds like this use case is
exactly where fc would be faster. But your results were the exact opposite.
What value for facet.limit did you set?
Was your 80/30 seconds query time spent mostly on returning the facet counts of
Thanks everyone for your help so far. I'm still trying to get to the bottom
of whether switching over to index-time boosts will give me a performance
improvement, and if so if it will be noticeable. This is all under the
assumption that I can achieve the scoring functionality that I need with
eit
On Fri, Jun 4, 2010 at 7:50 PM, Asif Rahman wrote:
> Perhaps I should have been more specific in my initial post. I'm doing
> date-based boosting on the documents in my index, so as to assign a higher
> score to more recent documents. Currently I'm using a boost function to
> achieve this. I'm
I know how to index a document with a boost but am still not sure whether
I'll see a search performance improvement with it. The initial decision to
use a boost function at search-time was made to preserve the flexibility to
tweak the function without having to a full reindex. I no longer need th
The documents full-text fields are 140 chars length (tweets).
Actually I had looked at those parameters and thought no change was
neccessary because the terms per document would be few and the unique term
count was nearly 1 M. I don't know exactly but average term count per
document text can be 10
You need to make each document added to the index a 1 to 1 mapping for each
company and consultant combo
text
1_1
Michael
Davis
AOL
2006-02-13T15:26:37Z
2008-02-13T15:26:37Z
1_4
Michael
Davis
Google
