explain.depesz.com

A tool for finding a real cause for slow queries.

Result: KE8

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# exclusive inclusive rows x rows loops node
1. 3.233 3627.180 ↑ 2.4 469 1

Limit (cost=7364.69..7384.10 rows=1109 width=48) (actual time=3622.157..3627.180 rows=469 loops=1)

2. 645.297 3623.947 ↑ 2.4 469 1

HashAggregate (cost=7364.69..7384.10 rows=1109 width=48) (actual time=3622.148..3623.947 rows=469 loops=1)

3. 531.729 2978.650 ↓ 4.7 66122 1

Merge Join (cost=6163.19..6522.65 rows=14034 width=48) (actual time=2207.216..2978.650 rows=66122 loops=1)

  • Merge Cond: (((weather_station.id)::bigint) = ((core.post_proc_result.fk_weather_station_id)::bigint))
4. 7.922 13.103 ↑ 1.5 784 1

Sort (cost=82.71..85.58 rows=1148 width=27) (actual time=10.425..13.103 rows=784 loops=1)

  • Sort Key: ((weather_station.id)::bigint)
  • Sort Method: quicksort Memory: 140kB
5. 5.181 5.181 ↑ 1.0 1126 1

Seq Scan on weather_station (cost=0.00..24.36 rows=1148 width=27) (actual time=0.015..5.181 rows=1126 loops=1)

  • Filter: ((friendly_name)::text <> ''::text)
6. 501.405 2433.818 ↓ 28.1 68789 1

Sort (cost=6080.48..6086.59 rows=2445 width=33) (actual time=2196.766..2433.818 rows=68789 loops=1)

  • Sort Key: ((core.post_proc_result.fk_weather_station_id)::bigint)
  • Sort Method: quicksort Memory: 8447kB
7. 267.655 1932.413 ↓ 28.1 68789 1

Hash Join (cost=5884.58..5942.88 rows=2445 width=33) (actual time=1660.685..1932.413 rows=68789 loops=1)

  • Hash Cond: ((geo_location.id)::bigint = core.post_proc_result.fk_weather_station_id)
8. 4.114 4.114 ↑ 1.0 1149 1

Seq Scan on geo_location (cost=0.00..19.49 rows=1149 width=21) (actual time=0.011..4.114 rows=1149 loops=1)

9. 267.038 1660.644 ↓ 66.7 68789 1

Hash (cost=5871.68..5871.68 rows=1032 width=28) (actual time=1660.644..1660.644 rows=68789 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 4031kB
10. 275.066 1393.606 ↓ 66.7 68789 1

Hash Join (cost=4897.42..5871.68 rows=1032 width=28) (actual time=1115.949..1393.606 rows=68789 loops=1)

  • Hash Cond: ((((core.post_proc_result.fk_weather_parameter_id)::bigint) = core.post_proc_result.fk_weather_parameter_id) AND (((core.post_proc_result.fk_weather_station_id)::bigint) = core.post_proc_result.fk_weather_station_id))
11. 267.068 533.690 ↑ 2.0 719 1

HashAggregate (cost=2362.72..2388.19 rows=1455 width=8) (actual time=531.057..533.690 rows=719 loops=1)

12. 266.622 266.622 ↑ 1.0 68789 1

Seq Scan on post_proc_result (cost=0.00..1846.81 rows=68789 width=8) (actual time=0.012..266.622 rows=68789 loops=1)

13. 287.075 584.850 ↑ 1.0 68789 1

Hash (cost=1502.86..1502.86 rows=68789 width=16) (actual time=584.850..584.850 rows=68789 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 3225kB
14. 297.775 297.775 ↑ 1.0 68789 1

Seq Scan on post_proc_result (cost=0.00..1502.86 rows=68789 width=16) (actual time=0.014..297.775 rows=68789 loops=1)

  • Filter: (calc_type = 'avg'::bpchar)