explain.depesz.com

PostgreSQL's explain analyze made readable

Result: 7Oc4

Settings
# exclusive inclusive rows x rows loops node
1. 1,079,029.840 1,866,671.229 ↓ 28,843,846.0 28,843,846 1

Sort (cost=10,001,501,605.35..10,001,501,605.36 rows=1 width=223) (actual time=1,685,196.026..1,866,671.229 rows=28,843,846 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, ibsd.item_
  • Sort Key: ibsh.shipment_nbr, ctr.container_nbr
  • Sort Method: external merge Disk: 6249000kB
2. 7,205.798 787,641.389 ↓ 28,843,846.0 28,843,846 1

Hash Join (cost=10,001,220,512.09..10,001,501,605.34 rows=1 width=223) (actual time=46,506.147..787,641.389 rows=28,843,846 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, ibsd
  • Hash Cond: (poh.status_id = pos.id)
3. 7,092.197 780,435.580 ↓ 28,843,846.0 28,843,846 1

Hash Join (cost=10,001,220,510.78..10,001,501,604.00 rows=1 width=227) (actual time=46,506.120..780,435.580 rows=28,843,846 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.orig_sh
  • Hash Cond: (fcx_1.company_id = comp_2.id)
4. 7,042.695 773,343.333 ↓ 28,843,846.0 28,843,846 1

Hash Join (cost=10,001,220,506.43..10,001,501,599.62 rows=1 width=220) (actual time=46,506.058..773,343.333 rows=28,843,846 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.o
  • Hash Cond: (fcx_1.facility_id = fac_2.id)
5. 7,891.527 766,300.611 ↓ 7,210,961.5 28,843,846 1

Hash Join (cost=10,001,220,502.08..10,001,501,595.22 rows=4 width=217) (actual time=46,506.018..766,300.611 rows=28,843,846 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: (poh.facility_company_xref_id = fcx_1.id)
6. 704,954.006 758,409.074 ↓ 7,210,961.5 28,843,846 1

Hash Join (cost=10,001,220,500.08..10,001,501,593.08 rows=4 width=209) (actual time=46,505.993..758,409.074 rows=28,843,846 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
  • Hash Cond: (inv.container_id = ctr.id)
7. 15,814.440 30,508.229 ↓ 1.1 3,190,932 1

HashAggregate (cost=1,103,345.40..1,290,740.66 rows=2,776,226 width=147) (actual time=23,558.446..30,508.229 rows=3,190,932 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_1.invn_
  • 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.invn_a
8. 2,417.365 14,693.789 ↓ 2.2 5,984,307 1

Hash Left Join (cost=258,535.15..950,652.97 rows=2,776,226 width=147) (actual time=2,422.366..14,693.789 rows=5,984,307 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.manufacture_date, inv.mod_t
  • Hash Cond: (inv.batch_number_id = bn.id)
9. 3,195.982 12,269.284 ↓ 2.2 5,984,307 1

Hash Join (cost=257,190.40..832,109.30 rows=2,776,226 width=135) (actual time=2,415.201..12,269.284 rows=5,984,307 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.manufacture_date, inv
  • Hash Cond: (inv.invn_attr_id = invn_attr_1.id)
10. 1,393.425 9,007.686 ↓ 2.2 5,984,307 1

Hash Join (cost=249,203.65..713,073.51 rows=2,776,226 width=113) (actual time=2,349.500..9,007.686 rows=5,984,307 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.manufacture_dat
  • Hash Cond: (inv.status_id = inv_st.id)
11. 1,604.826 7,614.256 ↓ 2.2 5,984,307 1

Hash Join (cost=249,202.46..619,374.69 rows=2,776,226 width=96) (actual time=2,349.478..7,614.256 rows=5,984,307 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.manufactu
  • Hash Cond: (inv.facility_id = fac_3.id)
12. 3,132.556 6,006.299 ↓ 2.2 5,984,307 1

Hash Right Join (cost=248,375.90..510,969.37 rows=2,776,226 width=89) (actual time=2,346.334..6,006.299 rows=5,984,307 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.man
  • Hash Cond: (al.from_inventory_id = inv.id)
13. 529.472 529.472 ↓ 1.0 2,965,771 1

Seq Scan on public.allocation al (cost=0.00..159,337.08 rows=2,942,636 width=12) (actual time=0.007..529.472 rows=2,965,771 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, al.wave_id,
14. 1,143.073 2,344.271 ↓ 1.1 3,190,932 1

Hash (cost=158,148.55..158,148.55 rows=2,776,226 width=81) (actual time=2,344.271..2,344.271 rows=3,190,932 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, i
  • Buckets: 524288 Batches: 1 Memory Usage: 389304kB
15. 1,201.198 1,201.198 ↓ 1.1 3,190,932 1

Seq Scan on public.inventory inv (cost=0.00..158,148.55 rows=2,776,226 width=81) (actual time=0.022..1,201.198 rows=3,190,932 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
  • Filter: (inv.facility_id = ANY ('{3,1}'::integer[]))
16. 0.893 3.131 ↑ 1.0 5,289 1

Hash (cost=654.67..654.67 rows=5,289 width=11) (actual time=3.131..3.131 rows=5,289 loops=1)

  • Output: fac_3.code, fac_3.id
  • Buckets: 1024 Batches: 1 Memory Usage: 239kB
17. 2.238 2.238 ↑ 1.0 5,289 1

Seq Scan on public.facility fac_3 (cost=0.00..654.67 rows=5,289 width=11) (actual time=0.003..2.238 rows=5,289 loops=1)

  • Output: fac_3.code, fac_3.id
18. 0.001 0.005 ↑ 1.0 3 1

Hash (cost=1.09..1.09 rows=3 width=21) (actual time=0.005..0.005 rows=3 loops=1)

  • Output: inv_st.description, inv_st.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
19. 0.004 0.004 ↑ 1.0 3 1

Seq Scan on public.inventory_status inv_st (cost=0.00..1.09 rows=3 width=21) (actual time=0.003..0.004 rows=3 loops=1)

  • Output: inv_st.description, inv_st.id
20. 34.290 65.616 ↑ 1.0 104,988 1

Hash (cost=4,574.64..4,574.64 rows=104,988 width=30) (actual time=65.616..65.616 rows=104,988 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_1.invn_attr_g
  • Buckets: 16384 Batches: 1 Memory Usage: 6546kB
21. 31.326 31.326 ↑ 1.0 104,988 1

Seq Scan on public.inventory_attribute invn_attr_1 (cost=0.00..4,574.64 rows=104,988 width=30) (actual time=0.010..31.326 rows=104,988 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_1.invn_
22. 3.152 7.140 ↑ 1.0 16,364 1

Hash (cost=812.92..812.92 rows=16,364 width=16) (actual time=7.140..7.140 rows=16,364 loops=1)

  • Output: bn.batch_nbr, bn.expiry_date, bn.id
  • Buckets: 2048 Batches: 1 Memory Usage: 788kB
23. 3.988 3.988 ↑ 1.0 16,364 1

Seq Scan on public.batch_number bn (cost=0.00..812.92 rows=16,364 width=16) (actual time=0.020..3.988 rows=16,364 loops=1)

  • Output: bn.batch_nbr, bn.expiry_date, bn.id
24. 15,168.337 22,946.839 ↓ 28,842,802.0 28,842,802 1

Hash (cost=10,000,117,154.65..10,000,117,154.65 rows=1 width=198) (actual time=22,946.839..22,946.839 rows=28,842,802 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.sh
  • Buckets: 1024 Batches: 8 (originally 1) Memory Usage: 1048577kB
25. 6,994.641 7,778.502 ↓ 28,842,802.0 28,842,802 1

Hash Join (cost=10,000,060,807.17..10,000,117,154.65 rows=1 width=198) (actual time=327.321..7,778.502 rows=28,842,802 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, i
  • Hash Cond: (ctr.rcvd_shipment_id = ibsd.ib_shipment_id)
26. 91.452 456.686 ↓ 4,279.6 487,880 1

Hash Join (cost=8.51..56,355.53 rows=114 width=47) (actual time=0.129..456.686 rows=487,880 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)
27. 139.577 365.220 ↓ 4,279.6 487,880 1

Hash Join (cost=6.38..56,349.56 rows=114 width=41) (actual time=0.108..365.220 rows=487,880 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)
28. 225.562 225.562 ↓ 1.3 792,319 1

Seq Scan on public.container ctr (cost=0.00..52,950.92 rows=603,066 width=42) (actual time=0.013..225.562 rows=792,319 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, ctr.rcv
  • Filter: (ctr.facility_company_xref_id = ANY ('{1,276}'::integer[]))
  • Rows Removed by Filter: 1
29. 0.001 0.081 ↑ 1.0 1 1

Hash (cost=6.35..6.35 rows=1 width=11) (actual time=0.081..0.081 rows=1 loops=1)

  • Output: fcx.id, fac.code
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
30. 0.006 0.080 ↑ 1.0 1 1

Merge Join (cost=6.21..6.35 rows=1 width=11) (actual time=0.079..0.080 rows=1 loops=1)

  • Output: fcx.id, fac.code
  • Merge Cond: (fcx.company_id = comp.id)
31. 0.013 0.045 ↑ 1.0 1 1

Sort (cost=5.93..5.94 rows=1 width=15) (actual time=0.044..0.045 rows=1 loops=1)

  • Output: fcx.id, fcx.company_id, fac.code
  • Sort Key: fcx.company_id
  • Sort Method: quicksort Memory: 25kB
32. 0.009 0.032 ↑ 1.0 1 1

Hash Join (cost=4.35..5.92 rows=1 width=15) (actual time=0.029..0.032 rows=1 loops=1)

  • Output: fcx.id, fcx.company_id, fac.code
  • Hash Cond: (fcx.facility_id = fac.id)
33. 0.004 0.004 ↑ 1.0 16 1

Seq Scan on public.facility_company_xref fcx (cost=0.00..1.48 rows=16 width=12) (actual time=0.002..0.004 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
34. 0.000 0.019 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=11) (actual time=0.019..0.019 rows=1 loops=1)

  • Output: fac.code, fac.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
35. 0.019 0.019 ↑ 1.0 1 1

Index Scan using facility_ukey on public.facility fac (cost=0.28..4.32 rows=1 width=11) (actual time=0.018..0.019 rows=1 loops=1)

  • Output: fac.code, fac.id
  • Index Cond: ((fac.code)::text = 'CD11'::text)
36. 0.029 0.029 ↑ 440.3 3 1

Index Only Scan using company_pkey on public.company comp (cost=0.28..134.51 rows=1,321 width=4) (actual time=0.029..0.029 rows=3 loops=1)

  • Output: comp.id
  • Heap Fetches: 0
37. 0.003 0.014 ↑ 1.0 18 1

Hash (cost=1.54..1.54 rows=18 width=14) (actual time=0.014..0.014 rows=18 loops=1)

  • Output: cs.description, cs.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
38. 0.011 0.011 ↑ 1.0 18 1

Seq Scan on public.container_status cs (cost=0.00..1.54 rows=18 width=14) (actual time=0.008..0.011 rows=18 loops=1)

  • Output: cs.description, cs.id
39. 8.640 327.175 ↓ 7,583.3 22,750 1

Hash (cost=10,000,060,798.56..10,000,060,798.56 rows=3 width=155) (actual time=327.175..327.175 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_id, ib
  • Buckets: 1024 Batches: 1 Memory Usage: 4062kB
40. 5.724 318.535 ↓ 7,583.3 22,750 1

Hash Right Join (cost=10,000,060,643.88..10,000,060,798.56 rows=3 width=155) (actual time=312.501..318.535 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_
  • Hash Cond: (ven.id = poh.vendor_id)
41. 0.404 0.404 ↑ 1.0 1,321 1

Seq Scan on public.company ven (cost=0.00..149.63 rows=1,321 width=27) (actual time=0.002..0.404 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.mod_us
42. 8.197 312.407 ↓ 7,583.3 22,750 1

Hash (cost=10,000,060,643.79..10,000,060,643.79 rows=3 width=136) (actual time=312.407..312.407 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.fac
  • Buckets: 1024 Batches: 1 Memory Usage: 3609kB
43. 5.335 304.210 ↓ 7,583.3 22,750 1

Hash Join (cost=10,000,060,495.37..10,000,060,643.79 rows=3 width=136) (actual time=298.403..304.210 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, ib
  • Hash Cond: (poh.id = pod.purchase_order_id)
44. 0.513 0.513 ↓ 1.1 1,737 1

Seq Scan on public.purchase_order_hdr poh (cost=0.00..142.39 rows=1,583 width=38) (actual time=0.009..0.513 rows=1,737 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, poh.del
  • Filter: (poh.facility_company_xref_id = ANY ('{1,276}'::integer[]))
45. 7.256 298.362 ↓ 7,583.3 22,750 1

Hash (cost=10,000,060,495.28..10,000,060,495.28 rows=3 width=114) (actual time=298.362..298.362 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_cnt
  • Buckets: 1024 Batches: 1 Memory Usage: 3076kB
46. 10.698 291.106 ↓ 7,583.3 22,750 1

Hash Join (cost=10,000,059,605.02..10,000,060,495.28 rows=3 width=114) (actual time=276.974..291.106 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_shipp
  • Hash Cond: (pod.id = ibsd.po_dtl_id)
47. 3.913 3.913 ↓ 1.0 15,464 1

Seq Scan on public.purchase_order_dtl pod (cost=0.00..832.26 rows=15,442 width=12) (actual time=0.012..3.913 rows=15,464 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.mod_user,
48. 5.791 276.495 ↓ 5,687.5 22,750 1

Hash (cost=10,000,059,604.89..10,000,059,604.89 rows=4 width=102) (actual time=276.495..276.495 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
  • Buckets: 1024 Batches: 1 Memory Usage: 2787kB
49. 10.069 270.704 ↓ 8,252.0 33,008 1

Nested Loop (cost=10,000,058,319.08..10,000,059,604.89 rows=4 width=102) (actual time=252.286..270.704 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_units, ibs
50. 12.662 260.635 ↓ 8,252.0 33,008 1

Merge Join (cost=58,318.81..59,600.44 rows=4 width=91) (actual time=252.255..260.635 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_unit
  • Merge Cond: (ibsh.id = ibsd.ib_shipment_id)
51. 0.064 1.314 ↓ 156.0 156 1

Sort (cost=238.62..238.63 rows=1 width=62) (actual time=1.303..1.314 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facility_id, ibsh.company_id, ib
  • Sort Key: ibsh.id
  • Sort Method: quicksort Memory: 46kB
52. 0.036 1.250 ↓ 156.0 156 1

Hash Join (cost=50.67..238.61 rows=1 width=62) (actual time=1.095..1.250 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facility_id, ibsh.company_
  • Hash Cond: (ibsh.status_id = ibs_stat.id)
53. 0.904 1.208 ↓ 156.0 156 1

Merge Join (cost=49.17..237.08 rows=1 width=51) (actual time=1.080..1.208 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facility_id, ibsh.co
  • Merge Cond: (ibsh.load_id = load.id)
  • -> Index Only Scan using load_pkey on public.load (cost=0.28..180.74 rows=3156 width=4) (actual time=0.019..0.755 rows=
54. 0.069 0.304 ↓ 156.0 156 1

Sort (cost=48.89..48.89 rows=1 width=55) (actual time=0.296..0.304 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facility_id, i
  • Sort Key: ibsh.load_id
  • Sort Method: quicksort Memory: 46kB
  • Output: load.id
  • Heap Fetches: 1564
55. 0.224 0.235 ↓ 156.0 156 1

Hash Join (cost=4.63..48.88 rows=1 width=55) (actual time=0.036..0.235 rows=156 loops=1)

  • Output: ibsh.shipped_date, ibsh.shipment_nbr, ibsh.orig_shipped_units, ibsh.orig_shipped_cntrs, ibsh.facility
  • Hash Cond: (ibsh.facility_id = fac_1.id)
  • -> Index Scan using ib_shipment_shipped_date_idx on public.ib_shipment ibsh (cost=0.28..43.94 rows=149 widt
  • Output: ibsh.id, ibsh.facility_id, ibsh.shipment_nbr, ibsh.status_id, ibsh.ref_nbr, ibsh.create_ts, ibs
  • Index Cond: (ibsh.shipped_date = '2019-04-29'::date)
  • Filter: ((ibsh.facility_id = ANY ('{3,1}'::integer[])) AND (ibsh.company_id = 1))
56. 0.011 0.011 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=11) (actual time=0.011..0.011 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 width=11) (actual
  • Output: fac_1.code, fac_1.id
  • Index Cond: ((fac_1.code)::text = 'CD11'::text)
57. 0.006 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
  • -> Seq Scan on public.ib_shipment_status ibs_stat (cost=0.00..1.24 rows=8 width=19) (actual time=0.003..0.005 rows=8 lo
  • Output: ibs_stat.description, ibs_stat.id
58. 67.070 246.659 ↑ 2.1 120,343 1

Sort (cost=58,080.19..58,719.05 rows=255,545 width=29) (actual time=237.857..246.659 rows=120,343 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id
  • Sort Key: ibsd.ib_shipment_id
  • Sort Method: quicksort Memory: 26172kB
59. 155.227 179.589 ↓ 1.0 256,485 1

Hash Join (cost=7,664.98..35,128.13 rows=255,545 width=29) (actual time=24.430..179.589 rows=256,485 loops=1)

  • Output: ibsd.container_nbr, ibsd.item_id, ibsd.po_dtl_id, ibsd.ib_shipment_id
  • Hash Cond: (ibsd.invn_attr_id = invn_attr.id)
  • -> Seq Scan on public.ib_shipment_dtl ibsd (cost=0.00..17241.35 rows=255545 width=33) (actual time=0.005..46.223 rows=256485
  • Output: ibsd.id, ibsd.ib_shipment_id, ibsd.item_id, ibsd.container_nbr, ibsd.shipped_qty, ibsd.received_qty, ibsd.pre_rec
60. 24.362 24.362 ↑ 1.0 104,988 1

Hash (cost=4,252.87..4,252.87 rows=104,988 width=4) (actual time=24.362..24.362 rows=104,988 loops=1)

  • Output: invn_attr.id
  • Buckets: 16384 Batches: 1 Memory Usage: 3691kB
  • -> Index Only Scan using inventory_attribute_pkey on public.inventory_attribute invn_attr (cost=0.29..4252.87 rows=1049
  • Output: invn_attr.id
  • Heap Fetches: 0
61. 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
62. 0.027 0.027 ↑ 1.0 1 1

Index Scan using company_ukey1 on public.company comp_1 (cost=0.28..4.32 rows=1 width=15) (actual time=0.026..0.027 rows=1 loops=1)

  • Output: comp_1.code, comp_1.id
  • Index Cond: ((comp_1.code)::text = '1000'::text)
  • Filter: (comp_1.id = 1)
63. 0.005 0.010 ↑ 1.0 16 1

Hash (cost=1.48..1.48 rows=16 width=12) (actual time=0.010..0.010 rows=16 loops=1)

  • Output: fcx_1.id, fcx_1.facility_id, fcx_1.company_id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
64. 0.005 0.005 ↑ 1.0 16 1

Seq Scan on public.facility_company_xref fcx_1 (cost=0.00..1.48 rows=16 width=12) (actual time=0.003..0.005 rows=16 loops=1)

  • Output: fcx_1.id, fcx_1.facility_id, fcx_1.company_id
65. 0.001 0.027 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=11) (actual time=0.027..0.027 rows=1 loops=1)

  • Output: fac_2.code, fac_2.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
66. 0.026 0.026 ↑ 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=0.026..0.026 rows=1 loops=1)

  • Output: fac_2.code, fac_2.id
  • Index Cond: ((fac_2.code)::text = 'CD11'::text)
67. 0.001 0.050 ↑ 1.0 1 1

Hash (cost=4.32..4.32 rows=1 width=15) (actual time=0.050..0.050 rows=1 loops=1)

  • Output: comp_2.code, comp_2.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
68. 0.049 0.049 ↑ 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=0.049..0.049 rows=1 loops=1)

  • Output: comp_2.code, comp_2.id
  • Index Cond: ((comp_2.code)::text = '1000'::text)
69. 0.004 0.011 ↑ 1.0 5 1

Hash (cost=1.15..1.15 rows=5 width=4) (actual time=0.011..0.011 rows=5 loops=1)

  • Output: pos.id
  • Buckets: 1024 Batches: 1 Memory Usage: 1kB
70. 0.007 0.007 ↑ 1.0 5 1

Seq Scan on public.purchase_order_status pos (cost=0.00..1.15 rows=5 width=4) (actual time=0.007..0.007 rows=5 loops=1)

  • Output: pos.id