explain.depesz.com

PostgreSQL's explain analyze made readable

Result: ZHgA

Settings
# exclusive inclusive rows x rows loops node
1. 1,077,160.483 1,514,770.493 ↓ 28,846,114.0 28,846,114 1

Sort (cost=30,002,062,880.21..30,002,062,880.21 rows=1 width=223) (actual time=1,347,099.982..1,514,770.493 rows=28,846,114 loops=1)

  • Output: ibsh.shipped_date, poh.po_nbr, ven.name, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibs_stat.description, inv.orig_qty, cs.description, ibsh.facility_id, ibsh.company_id, ibsd.container_nbr, ibs
  • Sort Key: ibsh.shipment_nbr, ctr.container_nbr
  • Sort Method: external merge Disk: 6249456kB
2. 7,332.181 437,610.010 ↓ 28,846,114.0 28,846,114 1

Hash Join (cost=20,001,536,542.10..20,002,062,880.20 rows=1 width=223) (actual time=140,503.182..437,610.010 rows=28,846,114 loops=1)

  • Output: ibsh.shipped_date, poh.po_nbr, ven.name, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibs_stat.description, inv.orig_qty, cs.description, ibsh.facility_id, ibsh.company_id, ibsd.container_nb
  • Hash Cond: (poh.status_id = pos.id)
3. 7,176.029 430,277.822 ↓ 28,846,114.0 28,846,114 1

Hash Join (cost=20,001,536,540.79..20,002,062,878.85 rows=1 width=227) (actual time=140,503.167..430,277.822 rows=28,846,114 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code, ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.
  • Hash Cond: (fcx_1.company_id = comp_2.id)
4. 7,295.938 423,095.506 ↓ 28,846,114.0 28,846,114 1

Hash Join (cost=20,001,536,536.44..20,002,062,874.47 rows=1 width=220) (actual time=140,496.870..423,095.506 rows=28,846,114 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code, ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsh.shipped_date, ibsh.shipment_nbr,
  • Hash Cond: (fcx_1.facility_id = fac_2.id)
5. 7,873.119 415,799.525 ↓ 5,769,222.8 28,846,114 1

Hash Join (cost=20,001,536,532.09..20,002,062,870.07 rows=5 width=217) (actual time=140,496.802..415,799.525 rows=28,846,114 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code, ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsh.shipped_date, ibsh.shipmen
  • Hash Cond: (poh.facility_company_xref_id = fcx_1.id)
6. 274,050.693 407,926.399 ↓ 5,769,222.8 28,846,114 1

Hash Join (cost=20,001,536,530.09..20,002,062,867.90 rows=5 width=209) (actual time=140,496.753..407,926.399 rows=28,846,114 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code, ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsh.shipped_date, ibsh.s
  • Hash Cond: (inv.container_id = ctr.id)
7. 12,620.451 108,195.590 ↓ 1.0 3,364,921 1

GroupAggregate (cost=10,001,450,070.13..10,001,864,509.26 rows=3,315,513 width=147) (actual time=91,483.024..108,195.590 rows=3,364,921 loops=1)

  • Output: inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.id, invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_
  • Group Key: inv.id, fac_3.code, inv_st.description, bn.batch_nbr, bn.expiry_date, invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_1.invn_attr_c, invn_attr_1.invn_attr_d, invn_attr_1
8. 76,920.927 95,575.139 ↓ 1.9 6,307,084 1

Sort (cost=10,001,450,070.13..10,001,458,358.92 rows=3,315,513 width=147) (actual time=91,482.845..95,575.139 rows=6,307,084 loops=1)

  • Output: inv.id, invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_1.invn_attr_c, invn_attr_1.invn_attr_d, invn_attr_1.invn_attr_e, invn_attr_1.invn_attr_f, invn_attr_1.invn_att
  • Sort Key: inv.id, fac_3.code, inv_st.description, bn.batch_nbr, bn.expiry_date, invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_1.invn_attr_c, invn_attr_1.invn_attr_d, invn_a
  • Sort Method: external merge Disk: 942280kB
9. 2,971.067 18,654.212 ↓ 1.9 6,307,084 1

Hash Left Join (cost=284,319.41..1,090,986.80 rows=3,315,513 width=147) (actual time=3,230.394..18,654.212 rows=6,307,084 loops=1)

  • Output: inv.id, invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_1.invn_attr_c, invn_attr_1.invn_attr_d, invn_attr_1.invn_attr_e, invn_attr_1.invn_attr_f, invn_attr_1.in
  • Hash Cond: (inv.batch_number_id = bn.id)
10. 4,220.105 15,609.520 ↓ 1.9 6,307,084 1

Hash Join (cost=282,957.66..949,613.59 rows=3,315,513 width=135) (actual time=3,156.745..15,609.520 rows=6,307,084 loops=1)

  • Output: inv.id, inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.item_id, inv.location_id, inv.manufact
  • Hash Cond: (inv.invn_attr_id = invn_attr_1.id)
11. 1,448.549 10,866.037 ↓ 1.9 6,307,084 1

Hash Join (cost=274,620.09..804,511.12 rows=3,315,513 width=113) (actual time=2,633.306..10,866.037 rows=6,307,084 loops=1)

  • Output: inv.id, inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.item_id, inv.location_id, inv.ma
  • Hash Cond: (inv.status_id = inv_st.id)
12. 1,694.228 9,417.481 ↓ 1.9 6,307,084 1

Hash Join (cost=274,618.91..692,611.37 rows=3,315,513 width=96) (actual time=2,633.273..9,417.481 rows=6,307,084 loops=1)

  • Output: inv.id, inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.item_id, inv.location_id,
  • Hash Cond: (inv.facility_id = fac_3.id)
13. 4,550.031 7,719.886 ↓ 1.9 6,307,084 1

Hash Right Join (cost=273,792.34..563,308.68 rows=3,315,513 width=89) (actual time=2,629.893..7,719.886 rows=6,307,084 loops=1)

  • Output: inv.id, inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.item_id, inv.locatio
  • Hash Cond: (al.from_inventory_id = inv.id)
14. 542.437 542.437 ↓ 1.0 3,125,138 1

Seq Scan on public.allocation al (cost=0.00..166,355.57 rows=3,079,019 width=12) (actual time=0.007..542.437 rows=3,125,138 loops=1)

  • Output: al.id, al.from_inventory_id, al.to_inventory_id, al.alloc_qty, al.status_id, al.order_dtl_id, al.create_ts, al.mod_ts, al.mod_user, al.type_id
15. 1,382.828 2,627.418 ↓ 1.0 3,364,921 1

Hash (cost=166,038.17..166,038.17 rows=3,315,513 width=81) (actual time=2,627.418..2,627.418 rows=3,364,921 loops=1)

  • Output: inv.id, inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.item_id, inv.l
  • Buckets: 524288 Batches: 1 Memory Usage: 410613kB
16. 1,244.590 1,244.590 ↓ 1.0 3,364,921 1

Seq Scan on public.inventory inv (cost=0.00..166,038.17 rows=3,315,513 width=81) (actual time=0.017..1,244.590 rows=3,364,921 loops=1)

  • Output: inv.id, inv.batch_number_id, inv.case_qty, inv.container_id, inv.create_ts, inv.curr_qty, inv.expiry_date, inv.facility_id, inv.item_id,
  • Filter: (inv.facility_id = ANY ('{3,1}'::integer[]))
17. 1.001 3.367 ↑ 1.0 5,289 1

Hash (cost=654.67..654.67 rows=5,289 width=11) (actual time=3.367..3.367 rows=5,289 loops=1)

  • Output: fac_3.code, fac_3.id
  • Buckets: 1024 Batches: 1 Memory Usage: 239kB
18. 2.366 2.366 ↑ 1.0 5,289 1

Seq Scan on public.facility fac_3 (cost=0.00..654.67 rows=5,289 width=11) (actual time=0.004..2.366 rows=5,289 loops=1)

  • Output: fac_3.code, fac_3.id
19. 0.001 0.007 ↑ 1.0 3 1

Hash (cost=1.09..1.09 rows=3 width=21) (actual time=0.007..0.007 rows=3 loops=1)

  • Output: inv_st.description, inv_st.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
20. 0.006 0.006 ↑ 1.0 3 1

Seq Scan on public.inventory_status inv_st (cost=0.00..1.09 rows=3 width=21) (actual time=0.005..0.006 rows=3 loops=1)

  • Output: inv_st.description, inv_st.id
21. 45.453 523.378 ↓ 1.0 110,285 1

Hash (cost=4,773.19..4,773.19 rows=109,673 width=30) (actual time=523.378..523.378 rows=110,285 loops=1)

  • Output: invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_1.invn_attr_c, invn_attr_1.invn_attr_d, invn_attr_1.invn_attr_e, invn_attr_1.invn_attr_f, invn_attr_
  • Buckets: 16384 Batches: 1 Memory Usage: 6877kB
22. 477.925 477.925 ↓ 1.0 110,285 1

Seq Scan on public.inventory_attribute invn_attr_1 (cost=0.00..4,773.19 rows=109,673 width=30) (actual time=0.009..477.925 rows=110,285 loops=1)

  • Output: invn_attr_1.invn_attr_a, invn_attr_1.invn_attr_b, invn_attr_1.invn_attr_c, invn_attr_1.invn_attr_d, invn_attr_1.invn_attr_e, invn_attr_1.invn_attr_f, invn
23. 3.470 73.625 ↑ 1.0 16,636 1

Hash (cost=821.08..821.08 rows=16,636 width=16) (actual time=73.625..73.625 rows=16,636 loops=1)

  • Output: bn.batch_nbr, bn.expiry_date, bn.id
  • Buckets: 2048 Batches: 1 Memory Usage: 801kB
24. 70.155 70.155 ↑ 1.0 16,636 1

Seq Scan on public.batch_number bn (cost=0.00..821.08 rows=16,636 width=16) (actual time=0.018..70.155 rows=16,636 loops=1)

  • Output: bn.batch_nbr, bn.expiry_date, bn.id
25. 16,271.410 25,680.116 ↓ 28,845,070.0 28,845,070 1

Hash (cost=10,000,086,459.92..10,000,086,459.92 rows=1 width=198) (actual time=25,680.116..25,680.116 rows=28,845,070 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code, ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsh.shipped_date,
  • Buckets: 1024 Batches: 8 (originally 1) Memory Usage: 1048577kB
26. 7,071.552 9,408.706 ↓ 28,845,070.0 28,845,070 1

Hash Join (cost=10,000,026,791.43..10,000,086,459.92 rows=1 width=198) (actual time=1,815.908..9,408.706 rows=28,845,070 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code, ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsh.shipped_
  • Hash Cond: (ctr.rcvd_shipment_id = ibsd.ib_shipment_id)
27. 99.534 521.718 ↓ 3,315.6 517,230 1

Hash Join (cost=147.61..59,815.45 rows=156 width=47) (actual time=0.451..521.718 rows=517,230 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, cs.description, fac.code
  • Hash Cond: (ctr.status_id = cs.id)
28. 148.891 422.178 ↓ 3,315.6 517,230 1

Hash Join (cost=145.48..59,808.06 rows=156 width=41) (actual time=0.433..422.178 rows=517,230 loops=1)

  • Output: ctr.facility_company_xref_id, ctr.container_nbr, ctr.type, ctr.rcvd_shipment_id, ctr.id, ctr.status_id, fac.code
  • Hash Cond: (ctr.facility_company_xref_id = fcx.id)
29. 272.881 272.881 ↓ 1.0 836,521 1

Seq Scan on public.container ctr (cost=0.00..55,012.74 rows=826,638 width=42) (actual time=0.009..272.881 rows=836,521 loops=1)

  • Output: ctr.id, ctr.facility_company_xref_id, ctr.container_nbr, ctr.status_id, ctr.curr_location_id, ctr.priority_date, ctr.type, ctr.pallet_id, ctr.rcvd_shipment_id,
  • Filter: (ctr.facility_company_xref_id = ANY ('{1,276}'::integer[]))
  • Rows Removed by Filter: 1
30. 0.000 0.406 ↑ 1.0 1 1

Hash (cost=145.45..145.45 rows=1 width=11) (actual time=0.406..0.406 rows=1 loops=1)

  • Output: fcx.id, fac.code
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
31. 0.103 0.406 ↑ 1.0 1 1

Hash Join (cost=6.23..145.45 rows=1 width=11) (actual time=0.061..0.406 rows=1 loops=1)

  • Output: fcx.id, fac.code
  • Hash Cond: (comp.id = fcx.company_id)
32. 0.283 0.283 ↑ 1.0 1,321 1

Index Only Scan using company_pkey on public.company comp (cost=0.28..134.51 rows=1,321 width=4) (actual time=0.028..0.283 rows=1,321 loops=1)

  • Output: comp.id
  • Heap Fetches: 0
33. 0.000 0.020 ↑ 1.0 1 1

Hash (cost=5.92..5.92 rows=1 width=15) (actual time=0.020..0.020 rows=1 loops=1)

  • Output: fcx.id, fcx.company_id, fac.code
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
34. 0.012 0.020 ↑ 1.0 1 1

Hash Join (cost=4.35..5.92 rows=1 width=15) (actual time=0.018..0.020 rows=1 loops=1)

  • Output: fcx.id, fcx.company_id, fac.code
  • Hash Cond: (fcx.facility_id = fac.id)
35. 0.002 0.002 ↑ 1.0 16 1

Seq Scan on public.facility_company_xref fcx (cost=0.00..1.48 rows=16 width=12) (actual time=0.001..0.002 rows=16 loops=1)

  • Output: fcx.id, fcx.facility_id, fcx.company_id, fcx.create_ts, fcx.mod_ts, fcx.mod_user, fcx.active_flg, fcx.create_user
36. 0.001 0.006 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=11) (actual time=0.006..0.006 rows=1 loops=1)

  • Output: fac.code, fac.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
37. 0.005 0.005 ↑ 1.0 1 1

Index Scan using facility_ukey on public.facility fac (cost=0.28..4.32 rows=1 width=11) (actual time=0.005..0.005 rows=1 loops=1)

  • Output: fac.code, fac.id
  • Index Cond: ((fac.code)::text = 'CD11'::text)
38. 0.003 0.006 ↑ 1.0 18 1

Hash (cost=1.54..1.54 rows=18 width=14) (actual time=0.006..0.006 rows=18 loops=1)

  • Output: cs.description, cs.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
39. 0.003 0.003 ↑ 1.0 18 1

Seq Scan on public.container_status cs (cost=0.00..1.54 rows=18 width=14) (actual time=0.002..0.003 rows=18 loops=1)

  • Output: cs.description, cs.id
40. 13.355 1,815.436 ↓ 7,583.3 22,750 1

Hash (cost=10,000,026,643.73..10,000,026,643.73 rows=3 width=155) (actual time=1,815.436..1,815.436 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facility
  • Buckets: 1024 Batches: 1 Memory Usage: 4062kB
41. 9.166 1,802.081 ↓ 7,583.3 22,750 1

Hash Right Join (cost=10,000,026,489.05..10,000,026,643.73 rows=3 width=155) (actual time=1,771.316..1,802.081 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.fa
  • Hash Cond: (ven.id = poh.vendor_id)
42. 42.383 42.383 ↑ 1.0 1,321 1

Seq Scan on public.company ven (cost=0.00..149.63 rows=1,321 width=27) (actual time=0.005..42.383 rows=1,321 loops=1)

  • Output: ven.id, ven.code, ven.name, ven.address_1, ven.address_2, ven.locality, ven.city, ven.state, ven.zip, ven.country, ven.univ_id_1, ven.create_ts, ven.mod_ts, ven
43. 10.201 1,750.532 ↓ 7,583.3 22,750 1

Hash (cost=10,000,026,488.96..10,000,026,488.96 rows=3 width=136) (actual time=1,750.532..1,750.532 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, i
  • Buckets: 1024 Batches: 1 Memory Usage: 3609kB
44. 7.835 1,740.331 ↓ 7,583.3 22,750 1

Hash Join (cost=10,000,026,337.84..10,000,026,488.96 rows=3 width=136) (actual time=1,686.784..1,740.331 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cn
  • Hash Cond: (poh.id = pod.purchase_order_id)
45. 45.799 45.799 ↓ 1.1 1,817 1

Seq Scan on public.purchase_order_hdr poh (cost=0.00..144.82 rows=1,653 width=38) (actual time=0.002..45.799 rows=1,817 loops=1)

  • Output: poh.id, poh.po_nbr, poh.facility_company_xref_id, poh.vendor_id, poh.status_id, poh.ord_date, poh.ref_nbr, poh.create_ts, poh.mod_ts, poh.mod_user,
  • Filter: (poh.facility_company_xref_id = ANY ('{1,276}'::integer[]))
46. 10.553 1,686.697 ↓ 7,583.3 22,750 1

Hash (cost=10,000,026,337.75..10,000,026,337.75 rows=3 width=114) (actual time=1,686.697..1,686.697 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_ship
  • Buckets: 1024 Batches: 1 Memory Usage: 3076kB
47. 16.465 1,676.144 ↓ 7,583.3 22,750 1

Hash Join (cost=10,000,025,262.47..10,000,026,337.75 rows=3 width=114) (actual time=1,422.055..1,676.144 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.ori
  • Hash Cond: (pod.id = ibsd.po_dtl_id)
48. 305.719 305.719 ↓ 1.0 16,261 1

Seq Scan on public.purchase_order_dtl pod (cost=0.00..1,014.39 rows=16,213 width=12) (actual time=26.110..305.719 rows=16,261 loops=1)

  • Output: pod.id, pod.purchase_order_id, pod.item_id, pod.orig_ord_qty, pod.ord_qty, pod.rcvd_qty, pod.shpd_qty, pod.create_ts, pod.mod_ts, pod.mo
49. 7.677 1,353.960 ↓ 5,687.5 22,750 1

Hash (cost=10,000,025,262.34..10,000,025,262.34 rows=4 width=102) (actual time=1,353.960..1,353.960 rows=22,750 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ib
  • Buckets: 1024 Batches: 1 Memory Usage: 2787kB
50. 6.425 1,346.283 ↓ 8,252.0 33,008 1

Hash Join (cost=10,000,019,988.81..10,000,025,262.34 rows=4 width=102) (actual time=1,268.979..1,346.283 rows=33,008 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_uni
  • Hash Cond: (ibsh.status_id = ibs_stat.id)
51. 9.816 1,339.852 ↓ 8,252.0 33,008 1

Nested Loop (cost=10,000,019,987.31..10,000,025,260.70 rows=4 width=91) (actual time=1,268.960..1,339.852 rows=33,008 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipp
52. 61.175 1,330.036 ↓ 8,252.0 33,008 1

Hash Join (cost=19,987.03..25,256.25 rows=4 width=80) (actual time=1,268.906..1,330.036 rows=33,008 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig
  • Hash Cond: (invn_attr.id = ibsd.invn_attr_id)
  • -> Index Only Scan using inventory_attribute_pkey on public.inventory_attribute invn_attr (cost=0.29..4446.85 rows=109673 wi
  • Output: invn_attr.id
  • Heap Fetches: 768
53. 13.114 1,268.861 ↓ 8,252.0 33,008 1

Hash (cost=19,986.61..19,986.61 rows=4 width=84) (actual time=1,268.861..1,268.861 rows=33,008 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsd.invn_attr_id, ibsh.shipped_date, ibs
  • Buckets: 1024 Batches: 1 Memory Usage: 3882kB
54. 1,214.326 1,255.747 ↓ 8,252.0 33,008 1

Hash Join (cost=376.60..19,986.61 rows=4 width=84) (actual time=118.015..1,255.747 rows=33,008 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id, ibsd.invn_attr_id, ibsh.shipped_dat
  • Hash Cond: (ibsd.ib_shipment_id = ibsh.id)
  • -> Seq Scan on public.ib_shipment_dtl ibsd (cost=0.00..18568.68 rows=276656 width=33) (actual time=0.001..1168.3
  • Output: ibsd.id, ibsd.ib_shipment_id, ibsd.item_id, ibsd.container_nbr, ibsd.shipped_qty, ibsd.received_qty,
55. 0.042 41.421 ↓ 156.0 156 1

Hash (cost=376.56..376.56 rows=1 width=51) (actual time=41.421..41.421 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facilit
  • Buckets: 1024 Batches: 1 Memory Usage: 13kB
56. 2.782 41.379 ↓ 156.0 156 1

Hash Join (cost=45.56..376.56 rows=1 width=51) (actual time=39.767..41.379 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.f
  • Hash Cond: (load.id = ibsh.load_id)
  • -> Index Only Scan using load_pkey on public.load (cost=0.28..311.51 rows=5265 width=4) (actual time
  • Output: load.id
  • Heap Fetches: 2372
57. 0.118 38.597 ↓ 156.0 156 1

Hash (cost=45.25..45.25 rows=1 width=55) (actual time=38.597..38.597 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs,
  • Buckets: 1024 Batches: 1 Memory Usage: 14kB
58. 38.456 38.479 ↓ 156.0 156 1

Hash Join (cost=4.63..45.25 rows=1 width=55) (actual time=22.783..38.479 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_c
  • Hash Cond: (ibsh.facility_id = fac_1.id)
  • -> Index Scan using ib_shipment_shipped_date_idx on public.ib_shipment ibsh (cost=0.28..
  • Output: ibsh.id, ibsh.facility_id, ibsh.shipment_nbr, ibsh.status_id, ibsh.ref_nbr,
  • Index Cond: (ibsh.shipped_date = '2019-04-29'::date)
  • Filter: ((ibsh.facility_id = ANY ('{3,1}'::integer[])) AND (ibsh.company_id = 1))
59. 0.023 0.023 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=11) (actual time=0.023..0.023 rows=1 loops=1)

  • Output: fac_1.code, fac_1.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
  • -> Index Scan using facility_ukey on public.facility fac_1 (cost=0.28..4.32 rows=1
  • Output: fac_1.code, fac_1.id
  • Index Cond: ((fac_1.code)::text = 'CD11'::text)
60. 0.000 0.000 ↑ 1.0 1 33,008

Materialize (cost=0.28..4.32 rows=1 width=15) (actual time=0.000..0.000 rows=1 loops=33,008)

  • Output: comp_1.code, comp_1.id
  • -> Index Scan using company_ukey1 on public.company comp_1 (cost=0.28..4.32 rows=1 width=15) (actual time=0.030..0.031 rows=
  • Output: comp_1.code, comp_1.id
  • Index Cond: ((comp_1.code)::text = '1000'::text)
  • Filter: (comp_1.id = 1)
61. 0.002 0.006 ↑ 1.0 8 1

Hash (cost=1.24..1.24 rows=8 width=19) (actual time=0.006..0.006 rows=8 loops=1)

  • Output: ibs_stat.description, ibs_stat.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
62. 0.004 0.004 ↑ 1.0 8 1

Seq Scan on public.ib_shipment_status ibs_stat (cost=0.00..1.24 rows=8 width=19) (actual time=0.003..0.004 rows=8 loops=1)

  • Output: ibs_stat.description, ibs_stat.id
63. 0.004 0.007 ↑ 1.0 16 1

Hash (cost=1.48..1.48 rows=16 width=12) (actual time=0.007..0.007 rows=16 loops=1)

  • Output: fcx_1.id, fcx_1.facility_id, fcx_1.company_id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
64. 0.003 0.003 ↑ 1.0 16 1

Seq Scan on public.facility_company_xref fcx_1 (cost=0.00..1.48 rows=16 width=12) (actual time=0.002..0.003 rows=16 loops=1)

  • Output: fcx_1.id, fcx_1.facility_id, fcx_1.company_id
65. 0.000 0.043 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=11) (actual time=0.043..0.043 rows=1 loops=1)

  • Output: fac_2.code, fac_2.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
66. 0.043 0.043 ↑ 1.0 1 1

Index Scan using facility_ukey on public.facility fac_2 (cost=0.28..4.32 rows=1 width=11) (actual time=0.042..0.043 rows=1 loops=1)

  • Output: fac_2.code, fac_2.id
  • Index Cond: ((fac_2.code)::text = 'CD11'::text)
67. 0.004 6.287 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=15) (actual time=6.287..6.287 rows=1 loops=1)

  • Output: comp_2.code, comp_2.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
68. 6.283 6.283 ↑ 1.0 1 1

Index Scan using company_ukey1 on public.company comp_2 (cost=0.28..4.32 rows=1 width=15) (actual time=6.281..6.283 rows=1 loops=1)

  • Output: comp_2.code, comp_2.id
  • Index Cond: ((comp_2.code)::text = '1000'::text)
69. 0.003 0.007 ↑ 1.0 5 1

Hash (cost=1.15..1.15 rows=5 width=4) (actual time=0.007..0.007 rows=5 loops=1)

  • Output: pos.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
70. 0.004 0.004 ↑ 1.0 5 1

Seq Scan on public.purchase_order_status pos (cost=0.00..1.15 rows=5 width=4) (actual time=0.003..0.004 rows=5 loops=1)

  • Output: pos.id