Internal geo distance calculation in Elastic Search

Hi all,

       I am new to this group and new to Elastic Search as well. I had 

been using geo location facilities of Elastic Search and I wondered how
internally does the Elastic Search calculates distances between two points
on earth. I heard about great circle distance which calculates distances
like a crow fly ignoring the roads and other aspects. Does Elastic Search
uses same kind of technique or does it have a separate technique. ?

Thanks & Regards,
Mohit Golchha

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If you go here:

http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/query-dsl-geo-distance-filter.html

You can see the distance_type parameter which specifies the different types
of calculations you can do with this filter.

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I have a related question, I know that it supports arc (better precision),
sloppy_arc(faster but less precise) or plane (fastest)
which one of these distance types is better if I want to show the results
to the user considering driving distance between two points?

On Wednesday, February 19, 2014 8:54:20 AM UTC-6, Binh Ly wrote:

If you go here:

Elasticsearch Platform — Find real-time answers at scale | Elastic

You can see the distance_type parameter which specifies the different
types of calculations you can do with this filter.

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arc and sloppy_arc use the haversine formula while plane computes distances
as if the earth was a plane.

Although plane is the fastest option, it only has good accuracy if you are
not too far from the equator and if your points are close to each other.

The difference between arc and sloppy_arc is that sloppy_arc uses
implementations of cosinus and arcsinus that trade accuracy for speed
(based on tables of values and taylor series). In my opinion, you would
almost always want to use sloppy_arc as it is significantly faster than arc
while the error is small enough to not be an issue for user experience.
Actually, the main reason why we didn't remove the arc distance computation
implementation is to be able to make sure, in case of weird distances, that
the error is not due to the sloppyness of the distance computation function.

Please note that even arc has accuracy issues because it assumes that the
earth is round (although it is an ellipsoid) but the future release of
Lucene is going to take this better into account so this will benefit
Elasticsearch as well ([LUCENE-5271] A slightly more accurate SloppyMath distance - ASF JIRA).

On Wed, Feb 19, 2014 at 4:03 PM, Hariharan Vadivelu hariinfo@gmail.comwrote:

I have a related question, I know that it supports arc (better
precision), sloppy_arc(faster but less precise) or plane (fastest)
which one of these distance types is better if I want to show the results
to the user considering driving distance between two points?

On Wednesday, February 19, 2014 8:54:20 AM UTC-6, Binh Ly wrote:

If you go here:

Elasticsearch Platform — Find real-time answers at scale | Elastic
reference/current/query-dsl-geo-distance-filter.html

You can see the distance_type parameter which specifies the different
types of calculations you can do with this filter.

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Adrien Grand

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