Re: Improve PostGIS performance with 62 million rows?

On Jan 5, 2017, at 8:50 AM, Paul Ramsey <pramsey(at)cleverelephant(dot)ca> wrote:
>
> The index filters using bounding boxes. A long, diagonal route will have a large bounding box, relative to the area you actually care about (within a narrow strip of the route). Use ST_Segmentize() to add points to your route, ST_DumpPoints() to dump those out as point and ST_MakeLine to generate new lines from those points, each line very short. The maximum index effectiveness will come when your line length is close to your buffer width.
>
> P

Ok, I think I understand the concept. So attempting to follow your advice, I modified the query to be:

SELECT elevation
FROM data
WHERE
ST_DWithin(
location,
(SELECT ST_MakeLine(geom)::geography as split_line
FROM (SELECT
(ST_DumpPoints(
ST_Segmentize(
ST_GeographyFromText('SRID=4326;LINESTRING(-150.008056 61.179167,-156.77 71.285833)'),
600
)::geometry
)).geom
) s1),
600
)
ORDER BY elevation DESC limit 1;

It took some fiddling to find a syntax that Postgresql would accept, but eventually that's what I came up with. Unfortunately, far from improving performance, it killed it - in running the query, it went from 22 seconds to several minutes (EXPLAIn ANALYZE has yet to return a result). Looking at the query execution plan shows, at least partially, why:

QUERY PLAN
------------------------------------------------------------------------------
Limit (cost=17119748.98..17119748.98 rows=1 width=4)
InitPlan 1 (returns $0)
-> Aggregate (cost=17.76..17.77 rows=1 width=32)
-> Result (cost=0.00..5.25 rows=1000 width=32)
-> Sort (cost=17119731.21..17171983.43 rows=20900890 width=4)
Sort Key: data.elevation DESC
-> Seq Scan on data (cost=0.00..17015226.76 rows=20900890 width=4)
Filter: st_dwithin(location, $0, '600'::double precision)
(8 rows)

So apparently it is now doing a sequential scan on data rather than using the index. And, of course, sorting 20 million rows is not trivial either. Did I do something wrong with forming the query?

-----------------------------------------------
Israel Brewster
Systems Analyst II
Ravn Alaska
5245 Airport Industrial Rd
Fairbanks, AK 99709
(907) 450-7293
-----------------------------------------------

>
> On Thu, Jan 5, 2017 at 9:45 AM, Israel Brewster <israel(at)ravnalaska(dot)net <mailto:israel(at)ravnalaska(dot)net>> wrote:
> I have a database (PostgreSQL 9.6.1) containing 62,702,675 rows of latitude (numeric), longitude(numeric), elevation(integer) data, along with a PostGIS (2.3.0) geometry column (location), running on a CentOS 6.8 box with 64GB RAM and a RAID10 SSD data drive. I'm trying to get the maximum elevation along a path, for which purpose I've come up with the following query (for one particular path example):
>
> SELECT elevation FROM data WHERE ST_DWithin(location, ST_GeographyFromText('SRID=4326;LINESTRING(-150.008056 61.179167,-156.77 71.285833)'), 600) ORDER BY elevation LIMIT 1;
>
> The EXPLAIN ANALYZE output of this particular query (https://explain.depesz.com/s/heZ <https://explain.depesz.com/s/heZ>) shows:
>
> QUERY PLAN
> ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
> Limit (cost=4.83..4.83 rows=1 width=4) (actual time=22653.840..22653.842 rows=1 loops=1)
> -> Sort (cost=4.83..4.83 rows=1 width=4) (actual time=22653.837..22653.837 rows=1 loops=1)
> Sort Key: elevation DESC
> Sort Method: top-N heapsort Memory: 25kB
> -> Index Scan using location_gix on data (cost=0.42..4.82 rows=1 width=4) (actual time=15.786..22652.041 rows=11081 loops=1)
> Index Cond: (location && '0102000020E6100000020000002C11A8FE41C062C0DFC2BAF1EE964E40713D0AD7A39863C086C77E164BD25140'::geography)
> Filter: (('0102000020E6100000020000002C11A8FE41C062C0DFC2BAF1EE964E40713D0AD7A39863C086C77E164BD25140'::geography && _st_expand(location, '600'::double precision)) AND _st_dwithin(location, '0102000020E6100000020000002C11A8FE41C062C0DFC2BAF1EE964E40713D0AD7A39863C086C77E164BD25140'::geography, '600'::double precision, true))
> Rows Removed by Filter: 4934534
> Planning time: 0.741 ms
> Execution time: 22653.906 ms
> (10 rows)
>
> So it is using the index properly, but still takes a good 22 seconds to run, most of which appears to be in the Index Scan.
>
> Is there any way to improve this, or is this going to be about as good as it gets with the number of rows being dealt with? I was planning to use this for a real-time display - punch in a couple of points, get some information about the route between, including maximum elevation - but with it taking 22 seconds for the longer routes at least, that doesn't make for the best user experience.
>
> It's perhaps worth noting that the example above is most likely a worst case scenario. I would expect the vast majority of routes to be significantly shorter, and I want to say the shorter routes query much faster [testing needed]. That said, the faster the better, even for short routes :-)
> -----------------------------------------------
> Israel Brewster
> Systems Analyst II
> Ravn Alaska
> 5245 Airport Industrial Rd
> Fairbanks, AK 99709
> (907) 450-7293 <tel:(907)%20450-7293>
> -----------------------------------------------
>
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