У меня есть следующий запрос, который занимает вечность (несколько дней), если вы можете предоставить какую-либо помощь по его улучшению, было бы замечательно. Сервер имеет 2 процессора xeon e5-2630 v3 (8 ядер, 16 потоков каждый) с 128ГБ ОЗУ и SSD-диск, postgres 11.
SELECT distinct on (location_signals.p_key) ooh_data.*,
location_signals."Lat" AS did_lat, location_signals."Lon" As did_lon, location_signals.device,
location_signals.timestamp AS did_timestamp, location_signals.p_key AS did_p_key
FROM ooh_data ,
location_signals
WHERE ST_DWithin(
ST_SetSRID(ST_MakePoint(ooh_data.offset_lon, ooh_data.offset_lat), 4326)::geography,
ST_SetSRID(ST_MakePoint(location_signals."Lon", location_signals."Lat"), 4326)::geography,
100
)
ORDER BY location_signals.p_key;
location_signals содержит 300 миллионов записей, а ooh_data имеет 6000 записей
. Вот объяснение, значительно ограничив выбор:
explain analyse SELECT distinct on (location_signals.p_key) ooh_data.*
FROM ooh_data ,
location_signals
WHERE ST_DWithin(
ST_SetSRID(ST_MakePoint(ooh_data.offset_lon, ooh_data.offset_lat), 4326)::geography,
ST_SetSRID(ST_MakePoint(location_signals."Lon", location_signals."Lat"), 4326)::geography,
100
)
AND ooh_data.p_key > 5700
AND location_signals.timestamp > '2019-05-31 23:57:00'
ORDER BY location_signals.p_key;
результат:
QUERY PLAN
Unique (cost=100551.80..100551.80 rows=1 width=84) (actual time=305.190..305.193 rows=2 loops=1)
-> Sort (cost=100551.80..100551.80 rows=1 width=84) (actual time=305.189..305.190 rows=3 loops=1)
Sort Key: location_signals.p_key
Sort Method: quicksort Memory: 25kB
-> Gather (cost=1029.18..100551.79 rows=1 width=84) (actual time=305.180..310.644 rows=3 loops=1)
Workers Planned: 1
Workers Launched: 1
-> Nested Loop (cost=29.18..99551.69 rows=1 width=84) (actual time=195.851..277.511 rows=2 loops=2)
Join Filter: (((st_setsrid(st_makepoint(ooh_data.offset_lon, ooh_data.offset_lat), 4326))::geography && _st_expand((st_setsrid(st_makepoint(location_signals."Lon", location_signals."Lat"), 4326))::geography, '100'::double precision)) AND ((st_setsrid(st_makepoint(location_signals."Lon", location_signals."Lat"), 4326))::geography && _st_expand((st_setsrid(st_makepoint(ooh_data.offset_lon, ooh_data.offset_lat), 4326))::geography, '100'::double precision)) AND _st_dwithin((st_setsrid(st_makepoint(ooh_data.offset_lon, ooh_data.offset_lat), 4326))::geography, (st_setsrid(st_makepoint(location_signals."Lon", location_signals."Lat"), 4326))::geography, '100'::double precision, true))
Rows Removed by Join Filter: 139156
-> Parallel Bitmap Heap Scan on location_signals (cost=28.89..2814.14 rows=1482 width=24) (actual time=1.144..10.886 rows=1288 loops=2)
Recheck Cond: ("timestamp" > '2019-05-31 23:57:00'::timestamp without time zone)
Heap Blocks: exact=1396
-> Bitmap Index Scan on idx_timestamp (cost=0.00..28.27 rows=2519 width=0) (actual time=1.355..1.356 rows=2577 loops=1)
Index Cond: ("timestamp" > '2019-05-31 23:57:00'::timestamp without time zone)
-> Index Scan using ooh_data_pkey on ooh_data (cost=0.28..5.35 rows=107 width=76) (actual time=0.004..0.025 rows=108 loops=2577)
Index Cond: (p_key > 5700)
Planning Time: 0.424 ms
Execution Time: 310.738 ms
благодарю за любую помощь, спасибо