QUERY PLAN -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Aggregate (cost=251725.01..251725.02 rows=1 width=8) (actual time=2617.632..2636.767 rows=1 loops=1) Output: count(*) -> Subquery Scan on cool_cust (cost=147576.79..251684.78 rows=16091 width=0) (actual time=2601.794..2633.189 rows=93140 loops=1) Output: cool_cust.c_last_name, cool_cust.c_first_name, cool_cust.d_date -> HashSetOp Except (cost=147576.79..251523.87 rows=16091 width=144) (actual time=2601.792..2624.473 rows=93140 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, (0) -> Append (cost=147576.79..251360.38 rows=21799 width=144) (actual time=2213.850..2598.501 rows=117004 loops=1) -> Result (cost=147576.79..199922.27 rows=16091 width=144) (actual time=2213.850..2255.342 rows=93267 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, 0 -> HashSetOp Except (cost=147576.79..199761.36 rows=16091 width=144) (actual time=2213.848..2245.447 rows=93267 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, (0) -> Append (cost=147576.79..199580.33 rows=24137 width=144) (actual time=1126.490..2203.619 rows=156635 loops=1) -> Subquery Scan on "*SELECT* 1" (cost=147576.79..149829.53 rows=16091 width=21) (actual time=1126.489..1366.751 rows=93891 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, 0 -> Unique (cost=147576.79..149668.62 rows=16091 width=17) (actual time=1126.487..1356.938 rows=93891 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date -> Gather Merge (cost=147576.79..149547.94 rows=16091 width=17) (actual time=1126.487..1345.253 rows=94204 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Workers Planned: 1 Workers Launched: 1 -> Unique (cost=146576.78..146737.69 rows=16091 width=17) (actual time=1124.426..1306.532 rows=47102 loops=2) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Worker 0: actual time=1122.677..1304.272 rows=47025 loops=1 -> Sort (cost=146576.78..146617.01 rows=16091 width=17) (actual time=1124.424..1245.110 rows=533434 loops=2) 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: 15176kB Worker 0: actual time=1122.675..1241.764 rows=532473 loops=1 Sort Method: external merge Disk: 15136kB -> Parallel Hash Join (cost=140703.38..145452.51 rows=16091 width=17) (actual time=644.066..761.474 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=647.901..758.829 rows=532473 loops=1 -> Parallel Seq Scan on public.customer (cost=0.00..3838.06 rows=84706 width=17) (actual time=0.009..6.282 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..6.398 rows=71611 loops=1 -> Parallel Hash (cost=140560.90..140560.90 rows=11398 width=8) (actual time=617.582..617.586 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=616.651..616.654 rows=547248 loops=1 -> Parallel Hash Join (cost=2570.10..140560.90 rows=11398 width=8) (actual time=5.390..508.118 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=4.456..507.951 rows=547248 loops=1 -> Parallel Seq Scan on public.store_sales (cost=0.00..131691.82 rows=2399482 width=8) (actual time=0.018..260.792 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=0.020..261.441 rows=2887593 loops=1 -> Parallel Hash (cost=2567.55..2567.55 rows=204 width=8) (actual time=5.352..5.353 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=4.409..4.410 rows=152 loops=1 -> Parallel Seq Scan on public.date_dim (cost=0.00..2567.55 rows=204 width=8) (actual time=2.560..5.299 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=1.621..4.358 rows=152 loops=1 -> Subquery Scan on "*SELECT* 2" (cost=48503.68..49630.12 rows=8046 width=21) (actual time=700.050..828.388 rows=62744 loops=1) Output: "*SELECT* 2".c_last_name, "*SELECT* 2".c_first_name, "*SELECT* 2".d_date, 1 -> Unique (cost=48503.68..49549.66 rows=8046 width=17) (actual time=700.047..821.836 rows=62744 loops=1) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date -> Gather Merge (cost=48503.68..49489.31 rows=8046 width=17) (actual time=700.047..814.136 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 -> Unique (cost=47503.67..47584.13 rows=8046 width=17) (actual time=666.348..763.403 rows=31372 loops=2) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date Worker 0: actual time=632.937..724.548 rows=29426 loops=1 -> Sort (cost=47503.67..47523.78 rows=8046 width=17) (actual time=666.347..730.336 rows=284349 loops=2) 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: 8576kB Worker 0: actual time=632.936..692.503 rows=266513 loops=1 Sort Method: external merge Disk: 7576kB -> Nested Loop (cost=0.85..46981.72 rows=8046 width=17) (actual time=1.852..454.111 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=0.681..433.435 rows=266513 loops=1 -> Nested Loop (cost=0.43..43423.72 rows=8046 width=8) (actual time=1.829..88.512 rows=285052 loops=2) Output: catalog_sales.cs_bill_customer_sk, date_dim_1.d_date Worker 0: actual time=0.648..85.747 rows=267146 loops=1 -> Parallel Seq Scan on public.date_dim date_dim_1 (cost=0.00..2567.55 rows=204 width=8) (actual time=1.789..3.883 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=0.597..4.725 rows=172 loops=1 -> Index Scan using idx_cs_sold_date_sk on public.catalog_sales (cost=0.43..184.68 rows=1560 width=8) (actual time=0.004..0.317 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=0.004..0.323 rows=1553 loops=172 -> 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=267146 -> Subquery Scan on "*SELECT* 3" (cost=50541.84..51329.11 rows=5708 width=21) (actual time=302.042..336.820 rows=23737 loops=1) Output: "*SELECT* 3".c_last_name, "*SELECT* 3".c_first_name, "*SELECT* 3".d_date, 1 -> Unique (cost=50541.84..51272.03 rows=5708 width=17) (actual time=302.039..334.329 rows=23737 loops=1) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date -> Gather Merge (cost=50541.84..51229.22 rows=5708 width=17) (actual time=302.039..331.296 rows=24128 loops=1) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date Workers Planned: 2 Workers Launched: 2 -> Unique (cost=49541.81..49570.35 rows=2854 width=17) (actual time=298.771..320.560 rows=8043 loops=3) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date Worker 0: actual time=297.820..319.743 rows=7997 loops=1 Worker 1: actual time=296.746..318.198 rows=7891 loops=1 -> Sort (cost=49541.81..49548.95 rows=2854 width=17) (actual time=298.770..309.603 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: 2792kB Worker 0: actual time=297.818..308.737 rows=95675 loops=1 Sort Method: external merge Disk: 2720kB Worker 1: actual time=296.745..307.315 rows=93910 loops=1 Sort Method: external merge Disk: 2664kB -> Nested Loop (cost=2570.52..49378.01 rows=2854 width=17) (actual time=3.209..230.291 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=2.294..228.843 rows=95675 loops=1 Worker 1: actual time=2.670..230.164 rows=93910 loops=1 -> Parallel Hash Join (cost=2570.10..48102.56 rows=2854 width=8) (actual time=3.191..99.159 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=2.270..97.201 rows=95690 loops=1 Worker 1: actual time=2.653..98.648 rows=93924 loops=1 -> Parallel Seq Scan on public.web_sales (cost=0.00..43955.21 rows=600821 width=8) (actual time=0.017..53.280 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=0.023..52.210 rows=480453 loops=1 Worker 1: actual time=0.020..54.103 rows=473734 loops=1 -> Parallel Hash (cost=2567.55..2567.55 rows=204 width=8) (actual time=3.032..3.032 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=2.170..2.171 rows=76 loops=1 Worker 1: actual time=2.559..2.560 rows=96 loops=1 -> Parallel Seq Scan on public.date_dim date_dim_2 (cost=0.00..2567.55 rows=204 width=8) (actual time=1.329..2.976 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=0.464..2.104 rows=76 loops=1 Worker 1: actual time=0.857..2.506 rows=96 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=95690 Worker 1: actual time=0.001..0.001 rows=1 loops=93924 Planning Time: 2.926 ms Execution Time: 2642.408 ms (147 rows)