explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 0TkU : explain_pps_new

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

CTE Scan on uniform_papa (cost=8,736.210..8,737.250 rows=52 width=1,214) (actual rows= loops=)

2.          

CTE uniform_november

3. 0.000 0.000 ↓ 0.0

Result (cost=0.000..0.010 rows=1 width=44) (actual rows= loops=)

4.          

CTE lima_foxtrot_echo

5. 0.000 0.000 ↓ 0.0

Sort (cost=7,793.890..7,805.220 rows=4,530 width=292) (actual rows= loops=)

  • Sort Key: lima_four1.romeo_three616alpha, lima_four1.romeo_three617sierra_victor, lima_four1.romeo_three8071echo_papa, lima_four1.romeo_three8071kilo_papa_echo
6. 0.000 0.000 ↓ 0.0

WindowAgg (cost=0.000..7,518.800 rows=4,530 width=292) (actual rows= loops=)

7. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.000..7,450.850 rows=4,530 width=72) (actual rows= loops=)

  • Join Filter: ((lima_four1.romeo_three8118whiskey_six five_romeo NULL) OR (((lima_four1.romeo_three8118whiskey_six = whiskey_hotel.quebec_kilo) OR (lima_four1.romeo_three8118whiskey_six = whiskey_hotel.romeo_three8118seven) OR (lima_four1.romeo_three8118whiskey_six =
8. 0.000 0.000 ↓ 0.0

CTE Scan on uniform_november whiskey_hotel (cost=0.000..0.020 rows=1 width=42) (actual rows= loops=)

9. 0.000 0.000 ↓ 0.0

Seq Scan on three charlie_lima (cost=0.000..268.180 rows=9,818 width=72) (actual rows= loops=)

10.          

SubPlan (for Nested Loop)

11. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.290..3,913.170 rows=9,507 width=0) (actual rows= loops=)

12. 0.000 0.000 ↓ 0.0

Seq Scan on papa foxtrot_seven (cost=0.000..457.980 rows=9,760 width=37) (actual rows= loops=)

  • Filter: (oscar_seven = ANY (ARRAY[whiskey_hotel.quebec_kilo, whiskey_hotel.romeo_three8070five_tango, whiskey_hotel.romeo_three8070juliet, whiskey_hotel.romeo_three8070lima_mike, whiskey_hotel.romeo_three8070hotel_four, whiskey_hotel.romeo_three8070mike, whiskey_hotel.romeo_three8070oscar_oscar, whiskey_hotel.romeo_three8
13. 0.000 0.000 ↓ 0.0

Index Only Scan using romeo_papa on three tango_juliet (cost=0.290..0.340 rows=1 width=37) (actual rows= loops=)

  • Index Cond: ((romeo_three616alpha = foxtrot_seven.romeo_three616alpha) AND (romeo_three617sierra_victor = foxtrot_seven.romeo_three617sierra_victor) AND (romeo_three8071echo_papa = foxtrot_seven.romeo_three8071echo_papa) AND (romeo_three8071kilo_papa_romeo
14.          

CTE november

15. 0.000 0.000 ↓ 0.0

Sort (cost=149.090..150.220 rows=453 width=12) (actual rows= loops=)

  • Sort Key: lima_four2.hotel_seven
16. 0.000 0.000 ↓ 0.0

HashAggregate (cost=124.580..129.110 rows=453 width=12) (actual rows= loops=)

  • Group Key: lima_four2.hotel_seven, lima_four2.romeo_three8119tango_golf
17. 0.000 0.000 ↓ 0.0

CTE Scan on lima_foxtrot_echo quebec_zulu (cost=0.000..90.600 rows=4,530 width=10) (actual rows= loops=)

18.          

CTE lima_foxtrot_hotel

19. 0.000 0.000 ↓ 0.0

Limit (cost=508.370..649.770 rows=1 width=618) (actual rows= loops=)

20. 0.000 0.000 ↓ 0.0

Nested Loop (cost=508.370..649.770 rows=1 width=618) (actual rows= loops=)

  • Join Filter: ((yankee_india1.oscar_seven = tango_three1.quebec_kilo) OR (yankee_india1.oscar_seven = tango_three1.romeo_three8070five_tango) OR (yankee_india1.oscar_seven = tango_three1.romeo_three8070juliet) OR (yankee_india1.oscar_seven = tango_three1.romeo_three8070lima_mike)
21. 0.000 0.000 ↓ 0.0

Hash Join (cost=508.370..646.530 rows=1 width=126) (actual rows= loops=)

  • Hash Cond: ((lima_four3.romeo_three616alpha = yankee_india1.romeo_three616alpha) AND (lima_four3.romeo_three617sierra_victor = yankee_india1.romeo_three617sierra_victor) AND (lima_four3.romeo_three8071echo_papa = yankee_india1.romeo_three8071echo_papa) AND (quebec_three
22. 0.000 0.000 ↓ 0.0

CTE Scan on lima_foxtrot_echo golf_kilo (cost=0.000..90.600 rows=4,530 width=114) (actual rows= loops=)

23. 0.000 0.000 ↓ 0.0

Hash (cost=306.790..306.790 rows=10,079 width=118) (actual rows= loops=)

24. 0.000 0.000 ↓ 0.0

Seq Scan on papa delta (cost=0.000..306.790 rows=10,079 width=118) (actual rows= loops=)

25. 0.000 0.000 ↓ 0.0

CTE Scan on uniform_november victor (cost=0.000..0.020 rows=1 width=24) (actual rows= loops=)

26.          

SubPlan (for Nested Loop)

27. 0.000 0.000 ↓ 0.0

Seq Scan on two five_hotel (cost=0.000..1.140 rows=1 width=41) (actual rows= loops=)

  • Filter: (yankee_india1.oscar_seven = romeo_three8070sierra_five)
28. 0.000 0.000 ↓ 0.0

Seq Scan on six quebec_sierra (cost=0.000..1.020 rows=1 width=41) (actual rows= loops=)

  • Filter: (yankee_india1.romeo_three8080echo_four = romeo_three8080echo_four)
29. 0.000 0.000 ↓ 0.0

Seq Scan on golf_five hotel_quebec (cost=0.000..1.010 rows=1 width=41) (actual rows= loops=)

  • Filter: (((yankee_india1.romeo_three8097yankee_three)::text = (romeo_three8097yankee_three)::text) AND (yankee_india1.romeo_three8080echo_four = romeo_three8080echo_four))
30.          

CTE uniform_papa

31. 0.000 0.000 ↓ 0.0

GroupAggregate (cost=121.490..130.980 rows=52 width=1,218) (actual rows= loops=)

  • Group Key: lima_four4.romeo_three616alpha, lima_four4.romeo_three617sierra_victor, lima_four4.romeo_three8071echo_papa, lima_four4.romeo_three8071kilo_papa_echo, yankee_india2.bravo, yankee_india2.romeo_three8080echo_four, lima_four4.foxtrot_uniform, yankee_india2.echo_whiskey, yankee_india2
32. 0.000 0.000 ↓ 0.0

Sort (cost=121.490..121.620 rows=52 width=1,046) (actual rows= loops=)

  • Sort Key: lima_four4.romeo_three616alpha, lima_four4.romeo_three617sierra_victor, lima_four4.romeo_three8071echo_papa, lima_four4.romeo_three8071kilo_papa_echo, yankee_india2.bravo, yankee_india2.romeo_three8080echo_four, lima_four4.foxtrot_uniform, yankee_india2.echo_whiskey,
33. 0.000 0.000 ↓ 0.0

Hash Join (cost=108.170..120.010 rows=52 width=1,046) (actual rows= loops=)

  • Hash Cond: (india.hotel_seven = lima_four4.hotel_seven)
34. 0.000 0.000 ↓ 0.0

CTE Scan on november india (cost=0.000..9.060 rows=453 width=10) (actual rows= loops=)

35. 0.000 0.000 ↓ 0.0

Hash (cost=107.880..107.880 rows=23 width=1,060) (actual rows= loops=)

36. 0.000 0.000 ↓ 0.0

Hash Join (cost=0.060..107.880 rows=23 width=1,060) (actual rows= loops=)

  • Hash Cond: (lima_four4.hotel_seven = yankee_india2.hotel_seven)
37. 0.000 0.000 ↓ 0.0

CTE Scan on lima_foxtrot_echo echo_three (cost=0.000..90.600 rows=4,530 width=386) (actual rows= loops=)

38. 0.000 0.000 ↓ 0.0

Hash (cost=0.050..0.050 rows=1 width=674) (actual rows= loops=)

39. 0.000 0.000 ↓ 0.0

Nested Loop (cost=0.000..0.050 rows=1 width=674) (actual rows= loops=)

40. 0.000 0.000 ↓ 0.0

CTE Scan on uniform_november yankee_zulu (cost=0.000..0.020 rows=1 width=0) (actual rows= loops=)

41. 0.000 0.000 ↓ 0.0

CTE Scan on lima_foxtrot_hotel charlie_quebec (cost=0.000..0.020 rows=1 width=674) (actual rows= loops=)

42.          

SubPlan (for GroupAggregate)

43. 0.000 0.000 ↓ 0.0

Result (cost=0.000..0.010 rows=1 width=32) (actual rows= loops=)

44. 0.000 0.000 ↓ 0.0

Result (cost=0.000..0.010 rows=1 width=32) (actual rows= loops=)