QUERY PLAN -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Aggregate (cost=254949.93..254949.94 rows=1 width=8) (actual time=2242.324..2259.657 rows=1 loops=1) Output: count(*) -> Subquery Scan on cool_cust (cost=149622.00..254907.85 rows=16834 width=0) (actual time=2226.567..2256.123 rows=93140 loops=1) Output: cool_cust.c_last_name, cool_cust.c_first_name, cool_cust.d_date -> HashSetOp Except (cost=149622.00..254739.51 rows=16834 width=144) (actual time=2226.566..2247.422 rows=93140 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, (0) -> Append (cost=149622.00..254559.51 rows=23999 width=144) (actual time=1771.245..2221.971 rows=117004 loops=1) -> Result (cost=149622.00..202870.82 rows=16834 width=144) (actual time=1771.245..1810.319 rows=93267 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, 0 -> HashSetOp Except (cost=149622.00..202702.48 rows=16834 width=144) (actual time=1771.244..1800.321 rows=93267 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, (0) -> Append (cost=149622.00..202513.10 rows=25251 width=144) (actual time=1018.607..1759.828 rows=156635 loops=1) -> Subquery Scan on "*SELECT* 1" (cost=149622.00..149958.68 rows=16834 width=21) (actual time=1018.606..1074.468 rows=93891 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, 0 -> Unique (cost=149622.00..149790.34 rows=16834 width=17) (actual time=1018.604..1064.790 rows=93891 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date -> Sort (cost=149622.00..149664.09 rows=16834 width=17) (actual time=1018.603..1052.591 rows=94199 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Sort Key: customer.c_last_name, customer.c_first_name, date_dim.d_date Sort Method: external merge Disk: 2696kB -> Gather (cost=146588.59..148440.33 rows=16834 width=17) (actual time=880.899..913.978 rows=94199 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Workers Planned: 1 Workers Launched: 1 -> HashAggregate (cost=145588.59..145756.93 rows=16834 width=17) (actual time=879.119..887.352 rows=47100 loops=2) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Group Key: customer.c_last_name, customer.c_first_name, date_dim.d_date Batches: 1 Memory Usage: 4625kB Worker 0: actual time=877.609..886.041 rows=44455 loops=1 Batches: 1 Memory Usage: 4369kB -> Parallel Hash Join (cost=140710.34..145462.34 rows=16834 width=17) (actual time=644.707..767.476 rows=533434 loops=2) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Hash Cond: (customer.c_customer_sk = store_sales.ss_customer_sk) Worker 0: actual time=650.882..772.536 rows=503226 loops=1 -> Parallel Seq Scan on public.customer (cost=0.00..3838.06 rows=84706 width=17) (actual time=0.009..6.004 rows=72000 loops=2) Output: customer.c_customer_sk, customer.c_customer_id, customer.c_current_cdemo_sk, customer.c_current_hdemo_sk, customer.c_current_addr_sk, customer.c_first_shipto_date_sk, customer.c_first_sales_date_sk, customer.c_salutation, customer.c_first_name, customer.c_last_name, customer.c_preferred_cust_flag, customer.c_birth_day, customer.c_birth_month, customer.c_birth_year, customer.c_birth_country, customer.c_login, customer.c_email_address, customer.c_last_review_date_sk Worker 0: actual time=0.009..6.171 rows=70942 loops=1 -> Parallel Hash (cost=140561.29..140561.29 rows=11924 width=8) (actual time=615.499..615.504 rows=546248 loops=2) Output: store_sales.ss_customer_sk, date_dim.d_date Buckets: 262144 (originally 32768) Batches: 8 (originally 1) Memory Usage: 7360kB Worker 0: actual time=614.329..614.333 rows=542130 loops=1 -> Parallel Hash Join (cost=2570.23..140561.29 rows=11924 width=8) (actual time=5.364..506.303 rows=546248 loops=2) Output: store_sales.ss_customer_sk, date_dim.d_date Inner Unique: true Hash Cond: (store_sales.ss_sold_date_sk = date_dim.d_date_sk) Worker 0: actual time=4.176..503.249 rows=542130 loops=1 -> Parallel Seq Scan on public.store_sales (cost=0.00..131692.02 rows=2399502 width=8) (actual time=0.017..258.551 rows=2879322 loops=2) Output: store_sales.ss_sold_date_sk, store_sales.ss_sold_time_sk, store_sales.ss_item_sk, store_sales.ss_customer_sk, store_sales.ss_cdemo_sk, store_sales.ss_hdemo_sk, store_sales.ss_addr_sk, store_sales.ss_store_sk, store_sales.ss_promo_sk, store_sales.ss_ticket_number, store_sales.ss_quantity, store_sales.ss_wholesale_cost, store_sales.ss_list_price, store_sales.ss_sales_price, store_sales.ss_ext_discount_amt, store_sales.ss_ext_sales_price, store_sales.ss_ext_wholesale_cost, store_sales.ss_ext_list_price, store_sales.ss_ext_tax, store_sales.ss_coupon_amt, store_sales.ss_net_paid, store_sales.ss_net_paid_inc_tax, store_sales.ss_net_profit Worker 0: actual time=0.021..258.112 rows=2861258 loops=1 -> Parallel Hash (cost=2567.55..2567.55 rows=214 width=8) (actual time=5.302..5.303 rows=182 loops=2) Output: date_dim.d_date, date_dim.d_date_sk Buckets: 1024 Batches: 1 Memory Usage: 72kB Worker 0: actual time=4.121..4.122 rows=172 loops=1 -> Parallel Seq Scan on public.date_dim (cost=0.00..2567.55 rows=214 width=8) (actual time=2.697..5.256 rows=182 loops=2) Output: date_dim.d_date, date_dim.d_date_sk Filter: ((date_dim.d_month_seq >= 1176) AND (date_dim.d_month_seq <= 1187)) Rows Removed by Filter: 36342 Worker 0: actual time=1.520..4.075 rows=172 loops=1 -> Subquery Scan on "*SELECT* 2" (cost=52259.82..52428.16 rows=8417 width=21) (actual time=653.640..676.879 rows=62744 loops=1) Output: "*SELECT* 2".c_last_name, "*SELECT* 2".c_first_name, "*SELECT* 2".d_date, 1 -> Unique (cost=52259.82..52343.99 rows=8417 width=17) (actual time=653.639..670.405 rows=62744 loops=1) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date -> Sort (cost=52259.82..52280.86 rows=8417 width=17) (actual time=653.637..662.428 rows=62744 loops=1) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Sort Key: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Sort Method: external merge Disk: 1800kB -> Gather (cost=50785.20..51711.07 rows=8417 width=17) (actual time=562.158..571.737 rows=62744 loops=1) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Workers Planned: 1 Workers Launched: 1 -> HashAggregate (cost=49785.20..49869.37 rows=8417 width=17) (actual time=538.263..544.336 rows=31372 loops=2) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Group Key: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Batches: 1 Memory Usage: 3601kB Worker 0: actual time=514.615..520.864 rows=29639 loops=1 Batches: 1 Memory Usage: 3601kB -> Nested Loop (cost=0.85..49722.07 rows=8417 width=17) (actual time=2.049..469.747 rows=284349 loops=2) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Inner Unique: true Worker 0: actual time=0.961..449.691 rows=268480 loops=1 -> Nested Loop (cost=0.43..46000.01 rows=8417 width=8) (actual time=2.029..93.688 rows=285052 loops=2) Output: catalog_sales.cs_bill_customer_sk, date_dim_1.d_date Worker 0: actual time=0.932..90.920 rows=269122 loops=1 -> Parallel Seq Scan on public.date_dim date_dim_1 (cost=0.00..2567.55 rows=214 width=8) (actual time=1.983..4.233 rows=182 loops=2) Output: date_dim_1.d_date_sk, date_dim_1.d_date_id, date_dim_1.d_date, date_dim_1.d_month_seq, date_dim_1.d_week_seq, date_dim_1.d_quarter_seq, date_dim_1.d_year, date_dim_1.d_dow, date_dim_1.d_moy, date_dim_1.d_dom, date_dim_1.d_qoy, date_dim_1.d_fy_year, date_dim_1.d_fy_quarter_seq, date_dim_1.d_fy_week_seq, date_dim_1.d_day_name, date_dim_1.d_quarter_name, date_dim_1.d_holiday, date_dim_1.d_weekend, date_dim_1.d_following_holiday, date_dim_1.d_first_dom, date_dim_1.d_last_dom, date_dim_1.d_same_day_ly, date_dim_1.d_same_day_lq, date_dim_1.d_current_day, date_dim_1.d_current_week, date_dim_1.d_current_month, date_dim_1.d_current_quarter, date_dim_1.d_current_year Filter: ((date_dim_1.d_month_seq >= 1176) AND (date_dim_1.d_month_seq <= 1187)) Rows Removed by Filter: 36342 Worker 0: actual time=0.886..5.324 rows=175 loops=1 -> Index Scan using idx_cs_sold_date_sk on public.catalog_sales (cost=0.43..187.36 rows=1560 width=8) (actual time=0.004..0.341 rows=1562 loops=365) Output: catalog_sales.cs_sold_date_sk, catalog_sales.cs_sold_time_sk, catalog_sales.cs_ship_date_sk, catalog_sales.cs_bill_customer_sk, catalog_sales.cs_bill_cdemo_sk, catalog_sales.cs_bill_hdemo_sk, catalog_sales.cs_bill_addr_sk, catalog_sales.cs_ship_customer_sk, catalog_sales.cs_ship_cdemo_sk, catalog_sales.cs_ship_hdemo_sk, catalog_sales.cs_ship_addr_sk, catalog_sales.cs_call_center_sk, catalog_sales.cs_catalog_page_sk, catalog_sales.cs_ship_mode_sk, catalog_sales.cs_warehouse_sk, catalog_sales.cs_item_sk, catalog_sales.cs_promo_sk, catalog_sales.cs_order_number, catalog_sales.cs_quantity, catalog_sales.cs_wholesale_cost, catalog_sales.cs_list_price, catalog_sales.cs_sales_price, catalog_sales.cs_ext_discount_amt, catalog_sales.cs_ext_sales_price, catalog_sales.cs_ext_wholesale_cost, catalog_sales.cs_ext_list_price, catalog_sales.cs_ext_tax, catalog_sales.cs_coupon_amt, catalog_sales.cs_ext_ship_cost, catalog_sales.cs_net_paid, catalog_sales.cs_net_paid_inc_tax, catalog_sales.cs_net_paid_inc_ship, catalog_sales.cs_net_paid_inc_ship_tax, catalog_sales.cs_net_profit Index Cond: (catalog_sales.cs_sold_date_sk = date_dim_1.d_date_sk) Worker 0: actual time=0.005..0.342 rows=1538 loops=175 -> Index Scan using customer_pkey on public.customer customer_1 (cost=0.42..0.44 rows=1 width=17) (actual time=0.001..0.001 rows=1 loops=570105) Output: customer_1.c_customer_sk, customer_1.c_customer_id, customer_1.c_current_cdemo_sk, customer_1.c_current_hdemo_sk, customer_1.c_current_addr_sk, customer_1.c_first_shipto_date_sk, customer_1.c_first_sales_date_sk, customer_1.c_salutation, customer_1.c_first_name, customer_1.c_last_name, customer_1.c_preferred_cust_flag, customer_1.c_birth_day, customer_1.c_birth_month, customer_1.c_birth_year, customer_1.c_birth_country, customer_1.c_login, customer_1.c_email_address, customer_1.c_last_review_date_sk Index Cond: (customer_1.c_customer_sk = catalog_sales.cs_bill_customer_sk) Worker 0: actual time=0.001..0.001 rows=1 loops=269122 -> Subquery Scan on "*SELECT* 3" (cost=50608.83..51568.70 rows=7165 width=21) (actual time=302.571..405.305 rows=23737 loops=1) Output: "*SELECT* 3".c_last_name, "*SELECT* 3".c_first_name, "*SELECT* 3".d_date, 1 -> Unique (cost=50608.83..51497.05 rows=7165 width=17) (actual time=302.568..402.818 rows=23737 loops=1) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date -> Gather Merge (cost=50608.83..51443.31 rows=7165 width=17) (actual time=302.567..372.246 rows=287761 loops=1) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date Workers Planned: 2 Workers Launched: 2 -> Sort (cost=49608.81..49616.27 rows=2985 width=17) (actual time=298.204..310.075 rows=95920 loops=3) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date Sort Key: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date Sort Method: external merge Disk: 2824kB Worker 0: actual time=297.401..308.205 rows=96226 loops=1 Sort Method: external merge Disk: 2736kB Worker 1: actual time=294.914..308.683 rows=92128 loops=1 Sort Method: external merge Disk: 2624kB -> Nested Loop (cost=2570.65..49436.52 rows=2985 width=17) (actual time=3.205..229.192 rows=95920 loops=3) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date Inner Unique: true Worker 0: actual time=2.263..227.978 rows=96226 loops=1 Worker 1: actual time=2.608..228.161 rows=92128 loops=1 -> Parallel Hash Join (cost=2570.23..48102.52 rows=2985 width=8) (actual time=3.186..100.585 rows=95936 loops=3) Output: web_sales.ws_bill_customer_sk, date_dim_2.d_date Inner Unique: true Hash Cond: (web_sales.ws_sold_date_sk = date_dim_2.d_date_sk) Worker 0: actual time=2.240..100.451 rows=96240 loops=1 Worker 1: actual time=2.587..98.637 rows=92152 loops=1 -> Parallel Seq Scan on public.web_sales (cost=0.00..43955.08 rows=600808 width=8) (actual time=0.017..53.842 rows=480649 loops=3) Output: web_sales.ws_sold_date_sk, web_sales.ws_sold_time_sk, web_sales.ws_ship_date_sk, web_sales.ws_item_sk, web_sales.ws_bill_customer_sk, web_sales.ws_bill_cdemo_sk, web_sales.ws_bill_hdemo_sk, web_sales.ws_bill_addr_sk, web_sales.ws_ship_customer_sk, web_sales.ws_ship_cdemo_sk, web_sales.ws_ship_hdemo_sk, web_sales.ws_ship_addr_sk, web_sales.ws_web_page_sk, web_sales.ws_web_site_sk, web_sales.ws_ship_mode_sk, web_sales.ws_warehouse_sk, web_sales.ws_promo_sk, web_sales.ws_order_number, web_sales.ws_quantity, web_sales.ws_wholesale_cost, web_sales.ws_list_price, web_sales.ws_sales_price, web_sales.ws_ext_discount_amt, web_sales.ws_ext_sales_price, web_sales.ws_ext_wholesale_cost, web_sales.ws_ext_list_price, web_sales.ws_ext_tax, web_sales.ws_coupon_amt, web_sales.ws_ext_ship_cost, web_sales.ws_net_paid, web_sales.ws_net_paid_inc_tax, web_sales.ws_net_paid_inc_ship, web_sales.ws_net_paid_inc_ship_tax, web_sales.ws_net_profit Worker 0: actual time=0.021..53.860 rows=486377 loops=1 Worker 1: actual time=0.022..54.070 rows=460098 loops=1 -> Parallel Hash (cost=2567.55..2567.55 rows=214 width=8) (actual time=3.007..3.008 rows=122 loops=3) Output: date_dim_2.d_date, date_dim_2.d_date_sk Buckets: 1024 Batches: 1 Memory Usage: 104kB Worker 0: actual time=2.123..2.123 rows=76 loops=1 Worker 1: actual time=2.433..2.434 rows=114 loops=1 -> Parallel Seq Scan on public.date_dim date_dim_2 (cost=0.00..2567.55 rows=214 width=8) (actual time=1.326..2.956 rows=122 loops=3) Output: date_dim_2.d_date, date_dim_2.d_date_sk Filter: ((date_dim_2.d_month_seq >= 1176) AND (date_dim_2.d_month_seq <= 1187)) Rows Removed by Filter: 24228 Worker 0: actual time=0.438..2.064 rows=76 loops=1 Worker 1: actual time=0.751..2.375 rows=114 loops=1 -> Index Scan using customer_pkey on public.customer customer_2 (cost=0.42..0.45 rows=1 width=17) (actual time=0.001..0.001 rows=1 loops=287809) Output: customer_2.c_customer_sk, customer_2.c_customer_id, customer_2.c_current_cdemo_sk, customer_2.c_current_hdemo_sk, customer_2.c_current_addr_sk, customer_2.c_first_shipto_date_sk, customer_2.c_first_sales_date_sk, customer_2.c_salutation, customer_2.c_first_name, customer_2.c_last_name, customer_2.c_preferred_cust_flag, customer_2.c_birth_day, customer_2.c_birth_month, customer_2.c_birth_year, customer_2.c_birth_country, customer_2.c_login, customer_2.c_email_address, customer_2.c_last_review_date_sk Index Cond: (customer_2.c_customer_sk = web_sales.ws_bill_customer_sk) Worker 0: actual time=0.001..0.001 rows=1 loops=96240 Worker 1: actual time=0.001..0.001 rows=1 loops=92152 Planning Time: 3.040 ms Execution Time: 2262.778 ms (145 rows)