explain.depesz.com

A tool for finding a real cause for slow queries.

Result: 0Ee

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# exclusive inclusive rows x rows loops node
1. 6799.920 54725.740 ↑ 1.0 1000000 1

Limit (cost=85847.22..152506.52 rows=1000000 width=28) (actual time=25229.844..54725.740 rows=1000000 loops=1)

2. 9440.504 47925.820 ↑ 64.3 1000000 1

Hash Join (cost=85847.22..4371045.75 rows=64285080 width=28) (actual time=25229.834..47925.820 rows=1000000 loops=1)

  • Hash Cond: (i.fk_weather_station_id = ws.id)
3. 7782.931 38476.645 ↑ 64.3 1000000 1

Hash Join (cost=85811.37..2683526.55 rows=64285080 width=24) (actual time=25220.950..38476.645 rows=1000000 loops=1)

  • Hash Cond: (v.id = i.id)
4. 5476.440 5476.440 ↑ 64.3 1000000 1

Seq Scan on native_weather_data_value v (cost=0.00..1312013.58 rows=64285080 width=12) (actual time=0.023..5476.440 rows=1000000 loops=1)

  • Filter: (((value)::text <> '-'::text) AND ((value)::text ~ '^[-0-9.]+$'::text))
5. 12765.638 25217.274 ↑ 1.0 2972372 1

Hash (cost=48656.72..48656.72 rows=2972372 width=16) (actual time=25217.274..25217.274 rows=2972372 loops=1)

  • Buckets: 524288 Batches: 1 Memory Usage: 139330kB
6. 12451.636 12451.636 ↑ 1.0 2972372 1

Seq Scan on native_weather_data_index i (cost=0.00..48656.72 rows=2972372 width=16) (actual time=6.689..12451.636 rows=2972372 loops=1)

7. 4.375 8.671 ↑ 1.0 1149 1

Hash (cost=21.49..21.49 rows=1149 width=4) (actual time=8.671..8.671 rows=1149 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 41kB
8. 4.296 4.296 ↑ 1.0 1149 1

Seq Scan on weather_station ws (cost=0.00..21.49 rows=1149 width=4) (actual time=0.010..4.296 rows=1149 loops=1)