explain.depesz.com

PostgreSQL's explain analyze made readable

Result: AU1g : Optimization for: plan #vOOL

Settings

Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.001 0.754 ↑ 1.0 1 1

Subquery Scan on results (cost=261.30..261.33 rows=1 width=96) (actual time=0.753..0.754 rows=1 loops=1)

2. 0.083 0.753 ↑ 1.0 1 1

CTE Scan on candidates (cost=261.30..261.32 rows=1 width=98) (actual time=0.752..0.753 rows=1 loops=1)

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

CTE candidates

4. 0.696 0.696 ↓ 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..244.03 rows=1 width=133) (actual time=0.077..0.696 rows=2 loops=1)

  • Index Cond: ((price_band_2_item_count = 1) AND (price_band_2_price_start < '10000'::numeric) AND (price_band_2_price_end >= '10000'::numeric) AND (price_band_1_item_count = 1) AND (price_band_1_price_start < '20000'::numeric) AND (price_band_1_price_end >= '20000'::numeric) AND (partner_id = '1'::text) AND (site_id = '1'::text) AND (country = 'JP'::text) AND (fare_class = 'SuperValue'::text) AND ((currency)::text = 'JPY'::text))
  • Filter: ((allowed_airports IS NULL) OR ('{NRT,OKA}'::text[] <@ allowed_airports))
5.          

Initplan (forCTE Scan)

6. 0.004 0.670 ↑ 1.0 1 1

Aggregate (cost=17.25..17.27 rows=1 width=1) (actual time=0.670..0.670 rows=1 loops=1)

7. 0.000 0.666 ↓ 2.0 2 1

Nested Loop (cost=0.55..17.25 rows=1 width=33) (actual time=0.027..0.666 rows=2 loops=1)

8. 0.622 0.622 ↓ 2.0 2 1

CTE Scan on candidates candidates_1 (cost=0.00..0.02 rows=1 width=32) (actual time=0.001..0.622 rows=2 loops=1)

9. 0.004 0.044 ↑ 2.0 1 2

Nested Loop (cost=0.55..17.21 rows=2 width=66) (actual time=0.021..0.022 rows=1 loops=2)

10. 0.004 0.004 ↑ 1.0 2 2

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

11. 0.036 0.036 ↓ 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=0.009..0.009 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))
Planning time : 0.547 ms
Execution time : 0.825 ms