means you are looking for data within a certain range. To implement
this index structures like R-Trees help, because they make it a lot
easier to think in "boxes". GeoSort is just to sort the data in
relation to a given point in a 2D environment. So you always have to
compute the distance from the given point to the locations of the
documents. I think this is the only possibly approach?
Am 15.07.2008 um 10:05 schrieb Karl Wettin:
15 jul 2008 kl. 09.50 skrev Sascha Fahl:
handle geo-positioning problems. You might want to take a look at
them if that is features you are looking for. I suppose the code in
the book is mearly an example to show how to implement a custom
sort, but I didn't read it so I'm just guessing here.
karl
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Sascha FahlI read the chapter about custom sort methods and hacked around with
the GeoSort. Are there ways to improve the algorithm? Espacially
calculating the distance for ALL documents in the index is a bad
idea because only the distance for hitted documents are of
interest. That could save lots of time because the number of hits
compared to all documents in an index usually is pretty small.
GeoLucene and LocalLucene are both branches of Lucene hacked tothe GeoSort. Are there ways to improve the algorithm? Espacially
calculating the distance for ALL documents in the index is a bad
idea because only the distance for hitted documents are of
interest. That could save lots of time because the number of hits
compared to all documents in an index usually is pretty small.
handle geo-positioning problems. You might want to take a look at
them if that is features you are looking for. I suppose the code in
the book is mearly an example to show how to implement a custom
sort, but I didn't read it so I'm just guessing here.
karl
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Softwareenticklung
evenity GmbH
Zu den Mühlen 19
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Mail: sascha@evenity.net
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