explain.depesz.com

PostgreSQL's explain analyze made readable

Result: Gtir

Settings
# exclusive inclusive rows x rows loops node
1. 37.403 8,255.159 ↓ 19.0 19 1

Hash Join (cost=7,357.78..472,987.61 rows=1 width=3,802) (actual time=5,500.121..8,255.159 rows=19 loops=1)

  • Hash Cond: (this_.auctionid = tender_lots.tender_lot_id)
2. 121.494 8,216.821 ↑ 3.0 31,570 1

Nested Loop Left Join (cost=7,313.64..472,589.04 rows=94,488 width=1,675) (actual time=486.557..8,216.821 rows=31,570 loops=1)

3. 79.130 613.237 ↓ 1.0 31,570 1

Hash Left Join (cost=7,303.84..17,391.67 rows=31,496 width=614) (actual time=486.407..613.237 rows=31,570 loops=1)

  • Hash Cond: (this_.bidderempid = persons.person_id)
4. 47.754 47.754 ↓ 1.0 31,570 1

Index Scan using lot_bids_active_winner on lot_bids this_ (cost=0.42..9,655.19 rows=31,496 width=270) (actual time=0.011..47.754 rows=31,570 loops=1)

  • Index Cond: ((isactive = true) AND (iswinner = true))
  • Filter: (iswinner AND isactive)
5. 90.251 486.353 ↑ 1.0 73,520 1

Hash (cost=6,384.41..6,384.41 rows=73,520 width=344) (actual time=486.352..486.353 rows=73,520 loops=1)

  • Buckets: 131,072 Batches: 1 Memory Usage: 28,279kB
6. 162.704 396.102 ↑ 1.0 73,520 1

Hash Join (cost=2,114.20..6,384.41 rows=73,520 width=344) (actual time=155.788..396.102 rows=73,520 loops=1)

  • Hash Cond: (persons.person_id = users.person_id)
7. 77.663 77.663 ↑ 1.0 73,521 1

Seq Scan on persons (cost=0.00..4,077.21 rows=73,521 width=332) (actual time=0.011..77.663 rows=73,521 loops=1)

8. 80.082 155.735 ↑ 1.0 73,520 1

Hash (cost=1,195.20..1,195.20 rows=73,520 width=16) (actual time=155.734..155.735 rows=73,520 loops=1)

  • Buckets: 131,072 Batches: 1 Memory Usage: 4,661kB
9. 75.653 75.653 ↑ 1.0 73,520 1

Seq Scan on users (cost=0.00..1,195.20 rows=73,520 width=16) (actual time=0.009..75.653 rows=73,520 loops=1)

10. 189.420 7,482.090 ↑ 3.0 1 31,570

Nested Loop Left Join (cost=9.80..14.42 rows=3 width=1,061) (actual time=0.224..0.237 rows=1 loops=31,570)

11. 189.420 1,420.650 ↑ 1.0 1 31,570

Nested Loop Left Join (cost=1.02..5.43 rows=1 width=1,049) (actual time=0.036..0.045 rows=1 loops=31,570)

12. 189.420 441.980 ↑ 1.0 1 31,570

Nested Loop (cost=0.58..0.74 rows=1 width=511) (actual time=0.008..0.014 rows=1 loops=31,570)

13. 126.280 126.280 ↑ 1.0 1 31,570

Index Scan using companies_pkey on companies (cost=0.29..0.38 rows=1 width=190) (actual time=0.003..0.004 rows=1 loops=31,570)

  • Index Cond: (this_.biddercompid = company_id)
14. 126.280 126.280 ↑ 1.0 1 31,570

Index Scan using companies_data_company_id_idx on companies_data (cost=0.29..0.35 rows=1 width=325) (actual time=0.002..0.004 rows=1 loops=31,570)

  • Index Cond: (company_id = companies.company_id)
15. 284.130 789.250 ↑ 1.0 1 31,570

Limit (cost=0.44..4.67 rows=1 width=538) (actual time=0.024..0.025 rows=1 loops=31,570)

16. 113.880 505.120 ↑ 3.0 1 31,570

Nested Loop (cost=0.44..13.13 rows=3 width=538) (actual time=0.016..0.016 rows=1 loops=31,570)

  • Join Filter: (comp_address.countryid = utl_countries.countryid)
  • Rows Removed by Join Filter: 0
17. 63.140 63.140 ↑ 44.0 1 31,570

Seq Scan on utl_countries (cost=0.00..1.44 rows=44 width=520) (actual time=0.002..0.002 rows=1 loops=31,570)

18. 75.540 328.100 ↑ 3.0 1 32,810

Materialize (cost=0.44..9.72 rows=3 width=26) (actual time=0.010..0.010 rows=1 loops=32,810)

19. 93.280 252.560 ↑ 3.0 1 31,570

Nested Loop (cost=0.44..9.70 rows=3 width=26) (actual time=0.008..0.008 rows=1 loops=31,570)

20. 94.710 94.710 ↑ 3.0 1 31,570

Index Scan using comp_address_compid_iswithdrawn_idx on comp_address (cost=0.29..3.70 rows=3 width=8) (actual time=0.003..0.003 rows=1 loops=31,570)

  • Index Cond: ((compid = companies.company_id) AND (iswithdrawn = false))
  • Filter: (NOT iswithdrawn)
21. 64.570 64.570 ↑ 1.0 1 32,285

Index Scan using utl_cities_pkey on utl_cities (cost=0.15..2.00 rows=1 width=26) (actual time=0.002..0.002 rows=1 loops=32,285)

  • Index Cond: (cityid = comp_address.cityid)
22. 157.850 5,872.020 ↑ 3.0 1 31,570

GroupAggregate (cost=8.78..8.93 rows=3 width=44) (actual time=0.185..0.186 rows=1 loops=31,570)

  • Group Key: a.total_count
23. 157.850 5,714.170 ↑ 3.0 1 31,570

Sort (cost=8.78..8.79 rows=3 width=44) (actual time=0.180..0.181 rows=1 loops=31,570)

  • Sort Key: a.total_count
  • Sort Method: quicksort Memory: 25kB
24. 126.280 5,556.320 ↑ 3.0 1 31,570

Subquery Scan on a (cost=8.66..8.76 rows=3 width=44) (actual time=0.173..0.176 rows=1 loops=31,570)

25. 189.420 5,430.040 ↑ 3.0 1 31,570

WindowAgg (cost=8.66..8.73 rows=3 width=44) (actual time=0.170..0.172 rows=1 loops=31,570)

26. 1,452.220 5,240.620 ↑ 3.0 1 31,570

HashAggregate (cost=8.66..8.69 rows=3 width=12) (actual time=0.165..0.166 rows=1 loops=31,570)

  • Group Key: ratings2.value
27. 2,304.610 3,788.400 ↓ 6.0 36 31,570

Nested Loop (cost=0.41..8.62 rows=6 width=4) (actual time=0.009..0.120 rows=36 loops=31,570)

28. 94.710 94.710 ↑ 1.0 1 31,570

Seq Scan on rating_statuss (cost=0.00..1.04 rows=1 width=4) (actual time=0.002..0.003 rows=1 loops=31,570)

  • Filter: ((rating_status_constant)::text = 'RATE_MARK_SET'::text)
  • Rows Removed by Filter: 2
29. 1,389.080 1,389.080 ↓ 6.0 36 31,570

Index Only Scan using ix_ratings2 on ratings2 (cost=0.41..7.52 rows=6 width=8) (actual time=0.003..0.044 rows=36 loops=31,570)

  • Index Cond: ((objectcompid = companies.company_id) AND (ratingstatuslid = rating_statuss.rating_status_id))
  • Heap Fetches: 1,135,028
30. 0.037 0.935 ↓ 19.0 19 1

Hash (cost=44.13..44.13 rows=1 width=2,384) (actual time=0.934..0.935 rows=19 loops=1)

  • Buckets: 1,024 Batches: 1 Memory Usage: 47kB
31. 0.091 0.898 ↓ 19.0 19 1

Nested Loop (cost=2.57..44.13 rows=1 width=2,384) (actual time=0.065..0.898 rows=19 loops=1)

  • Join Filter: (tender_lots.tender_lot_state_id = tender_lot_states.tender_lot_state_id)
  • Rows Removed by Join Filter: 50
32. 0.007 0.028 ↑ 1.0 1 1

Sort (cost=1.16..1.16 rows=1 width=821) (actual time=0.026..0.028 rows=1 loops=1)

  • Sort Key: (((tender_lot_states.tender_lot_state_old_data ->> 'order'::text))::integer)
  • Sort Method: quicksort Memory: 25kB
33. 0.021 0.021 ↑ 1.0 1 1

Seq Scan on tender_lot_states (cost=0.00..1.15 rows=1 width=821) (actual time=0.019..0.021 rows=1 loops=1)

  • Filter: ((tender_lot_state_old_constant)::text = '7'::text)
  • Rows Removed by Filter: 10
34. 0.214 0.779 ↓ 34.5 69 1

Nested Loop (cost=1.42..42.94 rows=2 width=1,632) (actual time=0.034..0.779 rows=69 loops=1)

35. 0.161 0.358 ↓ 34.5 69 1

Nested Loop (cost=1.00..41.76 rows=2 width=581) (actual time=0.025..0.358 rows=69 loops=1)

36. 0.016 0.041 ↓ 6.0 6 1

Nested Loop (cost=0.58..40.68 rows=1 width=13) (actual time=0.016..0.041 rows=6 loops=1)

37. 0.009 0.009 ↑ 1.0 1 1

Index Scan using users_company_id_idx on users users_1 (cost=0.29..2.51 rows=1 width=12) (actual time=0.007..0.009 rows=1 loops=1)

  • Index Cond: (company_id = 34,609)
38. 0.016 0.016 ↑ 6.0 6 1

Index Scan using tenders_new_user_id_idx on tenders_new (cost=0.29..37.81 rows=36 width=9) (actual time=0.005..0.016 rows=6 loops=1)

  • Index Cond: (user_id = users_1.user_id)
39. 0.156 0.156 ↓ 2.0 12 6

Index Scan using tender_lot_search_index_tender on tender_lots (cost=0.42..1.02 rows=6 width=572) (actual time=0.004..0.026 rows=12 loops=6)

  • Index Cond: (tender_id = tenders_new.tender_id)
40. 0.207 0.207 ↑ 1.0 1 69

Index Scan using tender_lot_data_tender_lot_id_idx on tender_lot_data (cost=0.42..0.59 rows=1 width=1,051) (actual time=0.003..0.003 rows=1 loops=69)

  • Index Cond: (tender_lot_id = tender_lots.tender_lot_id)
Planning time : 1.929 ms
Execution time : 8,255.474 ms