Hi. > cube and earthdistance regression tests fail.
Code updated to work with current HEAD. Also added tests to cover new functionality. > Do you have any benchmarks ? This patch just introduces functionality of calculating distances between cubes, so this code don't interfere much with kNN search speed. I think it's better to publish such benchmarks in neighbor patch about split algorithm. Anyway, we can compare kNN with b-tree and full scan: create table test(a1 float, a2 float, a3 float); insert into test (select 100*random(), 100*random(), 100*random() from generate_series(1,1000000) as s(a)); create index on test using gist(cube(array[a1,a2,a3])); select * from test order by a1 limit 15; -- 227.658 ms select * from test order by cube(array[a1,a2,a3])->1 limit 15; -- 1.275 ms create index on test(a1); select * from test order by a1 limit 15; -- 0.103 ms As we can see, kNN ordering 10 times slower than B-tree (on silly request for R-Tree, just as example), but still 100+ times faster than full scan on this table. Stas. On Sep 25, 2013, at 5:25 PM, Peter Eisentraut <pete...@gmx.net> wrote: > On 9/22/13 7:38 PM, Stas Kelvich wrote: >> Here is the patch that introduces kNN search for cubes with euclidean, >> taxicab and chebyshev distances. > > cube and earthdistance regression tests fail.
distances.patch
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