Hi Nicholas,
Given that boosting is generally inherently fuzzy / inexact thing, you can
likely get away with using simpler calculations. dist() can do the
Euclidean distance (i.e. the Pythagorean theorem). If your data is in just
one region of the world, you can project your data into a 2-D plan
Yes, I did. But instead of sorting by geodist(), I use function query to
boost by distance. That's why I noticed the heavy calculation happened in
the processing.
Example:
bf=recip(geodist(), 50, 5)
Basically, I think the boost function will iterate all the results, and
calculate the distance.
On Mon, May 13, 2013 at 1:12 PM, Nicholas Ding wrote:
> I'm using geodist() in a recip boost function. I noticed a performance
> impact to the response time. I did a profiling session, the geodist()
> calculation took 30% of CPU time.
Are you also using an "fq" with geofilt to narrow down the num
