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PostgreSQL's explain analyze made readable

Result: Eh2Q : Optimization for: plan #347v

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Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

GroupAggregate (cost=11,982.59..37,593.15 rows=10,102 width=204) (actual rows= loops=)

  • Group Key: cities.id
2. 0.000 0.000 ↓ 0.0

Sort (cost=11,982.59..12,039.91 rows=22,928 width=156) (actual rows= loops=)

  • Sort Key: cities.id
3. 0.000 0.000 ↓ 0.0

Hash Join (cost=8,877.05..10,322.05 rows=22,928 width=156) (actual rows= loops=)

  • Hash Cond: (city_provider_source.provider_id = providers.id)
4. 0.000 0.000 ↓ 0.0

Hash Join (cost=8,865.36..10,246.77 rows=22,928 width=153) (actual rows= loops=)

  • Hash Cond: (city_provider_source.city_id = cities.id)
5. 0.000 0.000 ↓ 0.0

Seq Scan on city_provider_source (cost=0.00..1,200.83 rows=68,783 width=17) (actual rows= loops=)

6. 0.000 0.000 ↓ 0.0

Hash (cost=8,739.09..8,739.09 rows=10,102 width=140) (actual rows= loops=)

7. 0.000 0.000 ↓ 0.0

Seq Scan on cities (cost=0.00..8,739.09 rows=10,102 width=140) (actual rows= loops=)

  • Filter: (_st_distance((bbox)::geography, '0101000020E610000000000000800F3640F4E942B024854740'::geography, '0'::double precision, true) < '1000000'::double precision)
8. 0.000 0.000 ↓ 0.0

Hash (cost=10.75..10.75 rows=75 width=11) (actual rows= loops=)

9. 0.000 0.000 ↓ 0.0

Seq Scan on providers (cost=0.00..10.75 rows=75 width=11) (actual rows= loops=)