explain.depesz.com

PostgreSQL's explain analyze made readable

Result: XiS

Settings
# exclusive inclusive rows x rows loops node
1. 690.672 8,860.366 ↑ 1.0 423,444 1

Hash Left Join (cost=146,720.63..517,444.45 rows=423,444 width=928) (actual time=2,577.203..8,860.366 rows=423,444 loops=1)

  • Hash Cond: (events_staffing_days_positions.staffing_positions_id = staffing_positions.id)
2. 264.535 8,169.567 ↑ 1.0 423,444 1

Hash Left Join (cost=146,710.12..503,159.79 rows=423,444 width=766) (actual time=2,577.049..8,169.567 rows=423,444 loops=1)

  • Hash Cond: ((claim_types.id = claim_types_programs.claim_types_id) AND (programs.id = claim_types_programs.programs_id))
3. 1,040.762 7,901.527 ↑ 1.0 423,444 1

Hash Join (cost=146,451.97..468,707.20 rows=423,444 width=737) (actual time=2,573.523..7,901.527 rows=423,444 loops=1)

  • Hash Cond: (claims_1.events_id = events_venues.events_id)
4. 1,223.373 4,915.127 ↑ 1.0 423,444 1

Hash Left Join (cost=52,737.75..286,047.62 rows=423,444 width=717) (actual time=618.858..4,915.127 rows=423,444 loops=1)

  • Hash Cond: (claims_1.events_staffing_days_positions_id = events_staffing_days_positions.id)
5. 270.432 3,098.384 ↑ 1.0 423,444 1

Hash Join (cost=2,964.86..149,241.72 rows=423,444 width=713) (actual time=24.692..3,098.384 rows=423,444 loops=1)

  • Hash Cond: (events.programs_id = programs.id)
6. 267.814 2,827.591 ↑ 1.0 423,444 1

Hash Join (cost=2,923.71..143,378.23 rows=423,444 width=677) (actual time=24.326..2,827.591 rows=423,444 loops=1)

  • Hash Cond: (claims_1.payroll_periods_id = payroll_periods.id)
7. 231.043 2,559.725 ↑ 1.0 423,444 1

Hash Join (cost=2,918.01..137,550.17 rows=423,444 width=669) (actual time=24.271..2,559.725 rows=423,444 loops=1)

  • Hash Cond: (claims_1.claim_statuses_id = claim_statuses.id)
8. 261.252 2,328.676 ↑ 1.0 423,444 1

Hash Join (cost=2,916.88..131,726.68 rows=423,444 width=605) (actual time=24.256..2,328.676 rows=423,444 loops=1)

  • Hash Cond: (claims_1.staffing_users_id = staffing_users.id)
9. 248.887 2,043.389 ↑ 1.0 423,444 1

Hash Join (cost=75.79..123,063.24 rows=423,444 width=591) (actual time=0.175..2,043.389 rows=423,444 loops=1)

  • Hash Cond: (claims_1.claim_types_id = claim_types.id)
10. 550.681 1,794.467 ↑ 1.0 423,444 1

Merge Join (cost=72.85..117,237.94 rows=423,444 width=523) (actual time=0.136..1,794.467 rows=423,444 loops=1)

  • Merge Cond: (claims_1.events_id = events.id)
11. 446.968 446.968 ↑ 1.0 423,444 1

Index Scan using claims_events_id_idx on claims claims_1 (cost=0.42..43,146.11 rows=423,444 width=466) (actual time=0.007..446.968 rows=423,444 loops=1)

12. 796.818 796.818 ↓ 1.2 1,230,104 1

Index Scan using events_pkey on events (cost=0.43..66,221.03 rows=1,058,835 width=57) (actual time=0.006..796.818 rows=1,230,104 loops=1)

13. 0.006 0.035 ↑ 1.0 32 1

Hash (cost=2.54..2.54 rows=32 width=68) (actual time=0.035..0.035 rows=32 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 10kB
14. 0.014 0.029 ↑ 1.0 32 1

Hash Join (cost=1.07..2.54 rows=32 width=68) (actual time=0.012..0.029 rows=32 loops=1)

  • Hash Cond: (claim_types.claim_categories_id = claim_categories.id)
15. 0.010 0.010 ↑ 1.0 32 1

Seq Scan on claim_types (cost=0.00..1.32 rows=32 width=40) (actual time=0.004..0.010 rows=32 loops=1)

16. 0.002 0.005 ↑ 1.0 3 1

Hash (cost=1.03..1.03 rows=3 width=36) (actual time=0.005..0.005 rows=3 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
17. 0.003 0.003 ↑ 1.0 3 1

Seq Scan on claim_categories (cost=0.00..1.03 rows=3 width=36) (actual time=0.003..0.003 rows=3 loops=1)

18. 11.645 24.035 ↑ 1.0 42,004 1

Hash (cost=2,316.04..2,316.04 rows=42,004 width=18) (actual time=24.035..24.035 rows=42,004 loops=1)

  • Buckets: 65536 Batches: 1 Memory Usage: 2667kB
19. 12.390 12.390 ↑ 1.0 42,004 1

Seq Scan on staffing_users (cost=0.00..2,316.04 rows=42,004 width=18) (actual time=0.005..12.390 rows=42,004 loops=1)

20. 0.002 0.006 ↑ 1.0 6 1

Hash (cost=1.06..1.06 rows=6 width=68) (actual time=0.006..0.006 rows=6 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 9kB
21. 0.004 0.004 ↑ 1.0 6 1

Seq Scan on claim_statuses (cost=0.00..1.06 rows=6 width=68) (actual time=0.004..0.004 rows=6 loops=1)

22. 0.027 0.052 ↑ 1.0 120 1

Hash (cost=4.20..4.20 rows=120 width=12) (actual time=0.052..0.052 rows=120 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
23. 0.025 0.025 ↑ 1.0 120 1

Seq Scan on payroll_periods (cost=0.00..4.20 rows=120 width=12) (actual time=0.005..0.025 rows=120 loops=1)

24. 0.142 0.361 ↑ 1.0 673 1

Hash (cost=32.73..32.73 rows=673 width=36) (actual time=0.361..0.361 rows=673 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 56kB
25. 0.219 0.219 ↑ 1.0 673 1

Seq Scan on programs (cost=0.00..32.73 rows=673 width=36) (actual time=0.010..0.219 rows=673 loops=1)

26. 311.392 593.370 ↑ 1.0 1,100,884 1

Hash (cost=31,710.84..31,710.84 rows=1,100,884 width=8) (actual time=593.370..593.370 rows=1,100,884 loops=1)

  • Buckets: 131072 Batches: 16 Memory Usage: 3723kB
27. 281.978 281.978 ↑ 1.0 1,100,884 1

Seq Scan on events_staffing_days_positions (cost=0.00..31,710.84 rows=1,100,884 width=8) (actual time=0.009..281.978 rows=1,100,884 loops=1)

28. 371.307 1,945.638 ↑ 1.0 1,059,209 1

Hash (cost=74,267.10..74,267.10 rows=1,059,210 width=24) (actual time=1,945.638..1,945.638 rows=1,059,209 loops=1)

  • Buckets: 65536 Batches: 32 Memory Usage: 2253kB
29. 756.827 1,574.331 ↑ 1.0 1,059,209 1

Hash Join (cost=33,199.87..74,267.10 rows=1,059,210 width=24) (actual time=549.375..1,574.331 rows=1,059,209 loops=1)

  • Hash Cond: (events_venues.venues_profiles_id = venues_profiles.id)
30. 268.238 268.238 ↑ 1.0 1,059,210 1

Seq Scan on events_venues (cost=0.00..17,244.10 rows=1,059,210 width=8) (actual time=0.009..268.238 rows=1,059,210 loops=1)

31. 73.775 549.266 ↑ 1.0 167,589 1

Hash (cost=30,120.27..30,120.27 rows=167,728 width=20) (actual time=549.266..549.266 rows=167,589 loops=1)

  • Buckets: 65536 Batches: 4 Memory Usage: 2735kB
32. 263.228 475.491 ↑ 1.0 167,589 1

Hash Join (cost=5,875.88..30,120.27 rows=167,728 width=20) (actual time=102.765..475.491 rows=167,589 loops=1)

  • Hash Cond: (venues.id = venues_profiles.venues_id)
33. 109.691 109.691 ↑ 1.0 415,935 1

Seq Scan on venues (cost=0.00..15,475.35 rows=415,935 width=20) (actual time=0.008..109.691 rows=415,935 loops=1)

34. 67.731 102.572 ↑ 1.0 167,728 1

Hash (cost=3,123.28..3,123.28 rows=167,728 width=8) (actual time=102.572..102.572 rows=167,728 loops=1)

  • Buckets: 131072 Batches: 4 Memory Usage: 2655kB
35. 34.841 34.841 ↑ 1.0 167,728 1

Seq Scan on venues_profiles (cost=0.00..3,123.28 rows=167,728 width=8) (actual time=0.007..34.841 rows=167,728 loops=1)

36. 1.717 3.505 ↑ 1.0 7,006 1

Hash (cost=153.06..153.06 rows=7,006 width=45) (actual time=3.505..3.505 rows=7,006 loops=1)

  • Buckets: 8192 Batches: 1 Memory Usage: 438kB
37. 1.788 1.788 ↑ 1.0 7,006 1

Seq Scan on claim_types_programs (cost=0.00..153.06 rows=7,006 width=45) (actual time=0.007..1.788 rows=7,006 loops=1)

38. 0.060 0.127 ↑ 1.0 289 1

Hash (cost=6.89..6.89 rows=289 width=26) (actual time=0.127..0.127 rows=289 loops=1)

  • Buckets: 1024 Batches: 1 Memory Usage: 25kB
39. 0.067 0.067 ↑ 1.0 289 1

Seq Scan on staffing_positions (cost=0.00..6.89 rows=289 width=26) (actual time=0.013..0.067 rows=289 loops=1)