We monitor the response time (pingdom) of the page that uses these
boosting parameters. Since the addition of these boosting parameters and
an additional field to search on (which I will create a thread on it in
the mailing list), the page average response time has increased by 1-2
seconds.
Before worrying about it too much, exactly _how_ much has
the performance changed?
I’ve just been in too many situations where there’s
no objective measure of performance before and after, just
someone saying “it seems slower” and had those performance
changes disappear when a rigorous test is
Hi Derek,
Ah, then my reply was completely off :)
I don’t really see a better way. Maybe other than changing termfreq to field,
if the numeric field has docValues? That may be faster, but I don’t know for
sure.
Best regards,
Radu
--
Sematext Cloud - Full Stack Observability -
Hi Radu
Apologies for not making myself clear.
I would like to know if there is a more simple or efficient way to craft
the boosting parameters based on the requirements.
For example, I am using 'if', 'map' and 'termfreq' functions in the bf
parameters.
Is there a more efficient or simple
Hi Derek,
It’s hard to tell whether your boosts can be made better without knowing your
data and what users expect of it. Which is a problem in itself.
I would suggest gathering judgements, like if a user queries for X, what doc
IDs do you expect to get back?
Once you have enough of these
Hi
I have added the following boosting requirements to the search query of
a page. Feedback from monitoring team is that the overall response of
the page has increased since then.
I am trying to find out if the added boosting parameters (below) could
have contributed to the increased.
The
