explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 6huQ : Optimization for: Optimization for: Optimization for: Optimization for: plan #vOOL; plan #AU1g; plan #v3gH; plan #D3Wj

Settings

Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.013 0.565 ↑ 1.0 1 1

Subquery Scan on results (cost=100.67..100.70 rows=1 width=96) (actual time=0.555..0.565 rows=1 loops=1)

2. 0.092 0.552 ↑ 1.0 1 1

CTE Scan on candidates (cost=100.67..100.69 rows=1 width=98) (actual time=0.551..0.552 rows=1 loops=1)

  • Filter: ($5 = special_airport)
  • Rows Removed by Filter: 1
3.          

CTE candidates

4. 0.375 0.375 ↓ 2.0 2 1

Index Scan using travel_cancellation_option_ma_partner_id_site_id_country_fa_idx on travel_cancellation_option_mapping tcom (cost=0.41..83.40 rows=1 width=133) (actual time=0.068..0.375 rows=2 loops=1)

  • Index Cond: ((partner_id = '1'::text) AND (site_id = '1'::text) AND (country = 'JP'::text) AND (fare_class = 'SuperValue'::text) AND ((currency)::text = 'JPY'::text) AND (price_band_1_item_count = 1) AND (price_band_2_item_count = 1))
  • Filter: ((20000.0 <@ price_band_1_range) AND (10000.0 <@ price_band_2_range) AND ((allowed_airports IS NULL) OR ('{NRT,OKA}'::text[] <@ allowed_airports)))
  • Rows Removed by Filter: 10
5.          

Initplan (forCTE Scan)

6. 0.026 0.460 ↑ 1.0 1 1

Aggregate (cost=17.25..17.27 rows=1 width=1) (actual time=0.459..0.460 rows=1 loops=1)

7. 0.010 0.434 ↓ 2.0 2 1

Nested Loop (cost=0.55..17.25 rows=1 width=33) (actual time=0.027..0.434 rows=2 loops=1)

8. 0.312 0.312 ↓ 2.0 2 1

CTE Scan on candidates candidates_1 (cost=0.00..0.02 rows=1 width=32) (actual time=0.000..0.312 rows=2 loops=1)

9. 0.018 0.112 ↑ 2.0 1 2

Nested Loop (cost=0.55..17.21 rows=2 width=66) (actual time=0.053..0.056 rows=1 loops=2)

10. 0.006 0.006 ↑ 1.0 2 2

Values Scan on "*VALUES*" (cost=0.00..0.03 rows=2 width=40) (actual time=0.002..0.003 rows=2 loops=2)

11. 0.088 0.088 ↓ 0.0 0 4

Index Scan using special_airports_mapping_id_code_start_day_start_month_end__idx on special_airports sa (cost=0.55..8.58 rows=1 width=86) (actual time=0.022..0.022 rows=0 loops=4)

  • Index Cond: ((mapping_id = candidates_1.id) AND (code = "*VALUES*".column1) AND (start_day <= "*VALUES*".column2) AND (start_month <= "*VALUES*".column3) AND (end_day >= "*VALUES*".column2) AND (end_month >= "*VALUES*".column3))