explain.depesz.com

PostgreSQL's explain analyze made readable

Result: c0h : Optimization for: plan #jKY1

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Optimization path:

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.000 0.210 ↑ 1.0 1 1

Subquery Scan on results (cost=58.53..58.56 rows=1 width=96) (actual time=0.210..0.210 rows=1 loops=1)

2. 0.052 0.210 ↑ 1.0 1 1

CTE Scan on candidates (cost=58.53..58.55 rows=1 width=98) (actual time=0.210..0.210 rows=1 loops=1)

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

CTE candidates

4. 0.162 0.162 ↓ 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=0.28..41.55 rows=1 width=133) (actual time=0.051..0.162 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 ('20000'::numeric >= price_band_1_price_start) AND ('20000'::numeric <= price_band_1_price_end) AND (price_band_2_item_count = 1) AND ('10000'::numeric >= price_band_2_price_start) AND ('10000'::numeric <= price_band_2_price_end))
  • Filter: ((allowed_airports IS NULL) OR ('{NRT,OKA}'::text[] <@ allowed_airports))
5.          

Initplan (forCTE Scan)

6. 0.006 0.158 ↑ 1.0 1 1

Aggregate (cost=16.97..16.99 rows=1 width=1) (actual time=0.157..0.158 rows=1 loops=1)

7. 0.002 0.152 ↓ 2.0 2 1

Nested Loop (cost=0.41..16.97 rows=1 width=33) (actual time=0.026..0.152 rows=2 loops=1)

8. 0.112 0.112 ↓ 2.0 2 1

CTE Scan on candidates candidates_1 (cost=0.00..0.02 rows=1 width=32) (actual time=0.000..0.112 rows=2 loops=1)

9. 0.006 0.038 ↑ 2.0 1 2

Nested Loop (cost=0.41..16.93 rows=2 width=66) (actual time=0.018..0.019 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. 0.028 0.028 ↓ 0.0 0 4

Index Scan using special_airports_mapping_id_code_start_day_start_month_end__idx on special_airports sa (cost=0.41..8.44 rows=1 width=86) (actual time=0.007..0.007 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))