Reputation: 452
I am trying to run a spatial query between two tables. Table one (prism_ppt_monthly - see below for details) is monthly precipitation data. Table two (usgs_basin_boundary - see below for details) are polygons of hydrologic basin boundaries.
I would like to create a time series of the total precipitation for each basin. I have a query that will do that (see below for details), but for a single calculation it takes nearly 4.75 seconds. Considering I have 1440 months of precipitation data and nearly 40 basins, this query would take: 4.75 sec * 1440 * 40 = 77 hours.
Below is the info on the query and tables. I have spatial indexes on each table (gist) and have VACUUM ANALYZED each table. Any ideas on how I might be able to speed this thing up would be greatly appreciated!!!
QUERY:
EXPLAIN ANALYZE
SELECT filename,date_from,date_to,site_no,sqmi,(ST_SummaryStats(rast)).* FROM prism_ppt_monthly, usgs_basin_boundary WHERE ST_Intersects(rast,ST_Transform(geom,4269)) LIMIT 1;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=65964.53..66000.10 rows=1 width=81) (actual time=4764.969..4764.972 rows=1 loops=1)
-> Nested Loop (cost=65964.53..66782.60 rows=23 width=81) (actual time=4764.963..4764.963 rows=1 loops=1)
Join Filter: _st_intersects(st_transform(usgs_basin_boundary.geom, 4269), prism_ppt_monthly.rast, NULL::integer)
-> Hash Semi Join (cost=65964.53..66610.73 rows=47 width=126256) (actual time=4587.961..4587.961 rows=1 loops=1)
Hash Cond: ((usgs_basin_boundary.site_no)::text = df_flow.code)
-> Seq Scan on usgs_basin_boundary (cost=0.00..639.09 rows=2509 width=126256) (actual time=0.007..1.279 rows=595 loops=1)
-> Hash (cost=65963.94..65963.94 rows=47 width=9) (actual time=4585.313..4585.313 rows=47 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 2kB
-> HashAggregate (cost=65963.00..65963.47 rows=47 width=9) (actual time=4585.126..4585.215 rows=47 loops=1)
-> Seq Scan on df_flow (cost=0.00..63244.20 rows=1087520 width=9) (actual time=5.826..2367.593 rows=1087520 loops=1)
-> Index Scan using prism_ppt_monthly_rast_gist on prism_ppt_monthly (cost=0.00..0.40 rows=1 width=64) (actual time=0.034..0.034 rows=1 loops=1)
Index Cond: ((rast)::geometry && st_transform(usgs_basin_boundary.geom, 4269))
Total runtime: 4765.151 ms
TABLE 1:
\d+ prism_ppt_monthly
Table "public.prism_ppt_monthly"
Column | Type | Modifiers | Storage | Description
-----------+---------+-----------------------------------------------------------------+----------+-------------
rid | integer | not null default nextval('prism_ppt_monthly_rid_seq'::regclass) | plain |
rast | raster | | extended |
filename | text | | extended |
date_from | date | | plain |
date_to | date | | plain |
Indexes:
"prism_ppt_monthly_pkey" PRIMARY KEY, btree (rid)
"prism_ppt_monthly_rast_gist" gist (st_convexhull(rast))
Check constraints:
"enforce_height_rast" CHECK (st_height(rast) = 621)
"enforce_max_extent_rast" CHECK (st_coveredby(st_convexhull(rast), '0103000020AD10000001000000050000005555555555415FC01E01000000F8484060A9AAAAAA9E50C01E01000000F8484060A9AAAAAA9E50C0F5FFFFFFFF0F38405555555555415FC0F5FFFFFFFF0F38405555555555415FC01E01000000F84840'::geometry))
"enforce_nodata_values_rast" CHECK (_raster_constraint_nodata_values(rast)::numeric(16,10)[] = '{-9999}'::numeric(16,10)[])
"enforce_num_bands_rast" CHECK (st_numbands(rast) = 1)
"enforce_out_db_rast" CHECK (_raster_constraint_out_db(rast) = '{f}'::boolean[])
"enforce_pixel_types_rast" CHECK (_raster_constraint_pixel_types(rast) = '{32BF}'::text[])
"enforce_same_alignment_rast" CHECK (st_samealignment(rast, '0100000000365755555555A53F365755555555A5BF5555555555415FC01E01000000F8484000000000000000000000000000000000AD10000001000100'::raster))
"enforce_scalex_rast" CHECK (st_scalex(rast)::numeric(16,10) = 0.04166666666667::numeric(16,10))
"enforce_scaley_rast" CHECK (st_scaley(rast)::numeric(16,10) = (-0.04166666666667)::numeric(16,10))
"enforce_srid_rast" CHECK (st_srid(rast) = 4269)
"enforce_width_rast" CHECK (st_width(rast) = 1405)
Has OIDs: no
TABLE 2:
\d+ usgs_basin_boundary
Table "public.usgs_basin_boundary"
Column | Type | Modifiers | Storage | Description
----------+-----------------------------+-------------------------------------------------------------------+----------+-------------
gid | integer | not null default nextval('usgs_basin_boundary_gid_seq'::regclass) | plain |
site_no | character varying(15) | | extended |
sqmi | numeric | | main |
abs_diff | numeric | | main |
geom | geometry(MultiPolygon,5070) | | main |
Indexes:
"usgs_basin_boundary_pkey" PRIMARY KEY, btree (gid)
"usgs_basin_boundary_shape_gist" gist (geom)
Has OIDs: no
Upvotes: 2
Views: 1282
Reputation: 1380
It won't solve all your Problems, but I just stumbled upon something in your query:
SELECT (...) WHERE ST_Intersects(rast,ST_Transform(geom,4269)) LIMIT 1;
The important part is this one:
ST_Transform(geom,4269)
You are projecting a geometry right in the middle of your query. While this is certainly possible, it might not be good practice. You could project 'geom' beforehand to 'SRID:4269' into another table. After that you just access the transformed geometry from your other table.
After transforming the geom into a new table, you may also want to create an index on that table. This just might improve performance a bit.
Upvotes: 0
Reputation: 16477
The index on usgs_basin_boundary.geom
is not used because you're calling ST_Transform(geom,4269)
You should create an index on the result of the transform (as mentioned in the manual)
CREATE INDEX jkb_usgs_basin_boundary_geom_t_4269
ON usgs_basin_boundary
USING gist
(ST_Transform(geom,4269))
Upvotes: 1