explain.depesz.com

A tool for finding a real cause for slow queries.

Result: 4ys

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# exclusive inclusive rows x rows loops node
1. 6,799.920 54,725.740 ↑ 1.0 1,000,000 1

Limit (cost=85,847.22..152,506.52 rows=1,000,000 width=28) (actual time=25,229.844..54,725.740 rows=1,000,000 loops=1)

2. 9,440.504 47,925.820 ↑ 64.3 1,000,000 1

Hash Join (cost=85,847.22..4,371,045.75 rows=64,285,080 width=28) (actual time=25,229.834..47,925.820 rows=1,000,000 loops=1)

  • Hash Cond: (i.fk_weather_station_id = ws.id)
3. 7,782.931 38,476.645 ↑ 64.3 1,000,000 1

Hash Join (cost=85,811.37..2,683,526.55 rows=64,285,080 width=24) (actual time=25,220.950..38,476.645 rows=1,000,000 loops=1)

  • Hash Cond: (v.id = i.id)
4. 5,476.440 5,476.440 ↑ 64.3 1,000,000 1

Seq Scan on native_weather_data_value v (cost=0.00..1,312,013.58 rows=64,285,080 width=12) (actual time=0.023..5,476.440 rows=1,000,000 loops=1)

  • Filter: (((value)::text <> '-'::text) AND ((value)::text ~ '^[-0-9.]+$'::text))
5. 12,765.638 25,217.274 ↑ 1.0 2,972,372 1

Hash (cost=48,656.72..48,656.72 rows=2,972,372 width=16) (actual time=25,217.274..25,217.274 rows=2,972,372 loops=1)

  • Buckets: 524288 Batches: 1 Memory Usage: 139330kB
6. 12,451.636 12,451.636 ↑ 1.0 2,972,372 1

Seq Scan on native_weather_data_index i (cost=0.00..48,656.72 rows=2,972,372 width=16) (actual time=6.689..12,451.636 rows=2,972,372 loops=1)

7. 4.375 8.671 ↑ 1.0 1,149 1

Hash (cost=21.49..21.49 rows=1,149 width=4) (actual time=8.671..8.671 rows=1,149 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 41kB
8. 4.296 4.296 ↑ 1.0 1,149 1

Seq Scan on weather_station ws (cost=0.00..21.49 rows=1,149 width=4) (actual time=0.010..4.296 rows=1,149 loops=1)