QUERY PLAN -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Aggregate (cost=252319.25..252319.26 rows=1 width=8) (actual time=2185.816..2200.051 rows=1 loops=1) Output: count(*) -> Subquery Scan on cool_cust (cost=149504.61..252278.56 rows=16276 width=0) (actual time=2169.488..2196.223 rows=93140 loops=1) Output: cool_cust.c_last_name, cool_cust.c_first_name, cool_cust.d_date -> HashSetOp Except (cost=149504.61..252115.80 rows=16276 width=144) (actual time=2169.487..2187.308 rows=93140 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, (0) -> Append (cost=149504.61..251941.76 rows=23205 width=144) (actual time=1712.746..2160.576 rows=117004 loops=1) -> Result (cost=149504.61..200338.87 rows=16276 width=144) (actual time=1712.746..1750.336 rows=93267 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, 0 -> HashSetOp Except (cost=149504.61..200176.11 rows=16276 width=144) (actual time=1712.744..1740.325 rows=93267 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, (0) -> Append (cost=149504.61..199992.99 rows=24415 width=144) (actual time=973.112..1698.406 rows=156635 loops=1) -> Subquery Scan on "*SELECT* 1" (cost=149504.61..149830.13 rows=16276 width=21) (actual time=973.111..1013.840 rows=93891 loops=1) Output: "*SELECT* 1".c_last_name, "*SELECT* 1".c_first_name, "*SELECT* 1".d_date, 0 -> Unique (cost=149504.61..149667.37 rows=16276 width=17) (actual time=973.109..1004.160 rows=93891 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date -> Sort (cost=149504.61..149545.30 rows=16276 width=17) (actual time=973.108..992.133 rows=94197 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: quicksort Memory: 7280kB -> Gather (cost=146575.70..148366.06 rows=16276 width=17) (actual time=820.555..850.480 rows=94197 loops=1) Output: customer.c_last_name, customer.c_first_name, date_dim.d_date Workers Planned: 1 Workers Launched: 1 -> HashAggregate (cost=145575.70..145738.46 rows=16276 width=17) (actual time=818.787..827.198 rows=47098 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: 5649kB Worker 0: actual time=817.326..826.427 rows=46986 loops=1 Batches: 1 Memory Usage: 5649kB -> Parallel Hash Join (cost=140703.75..145453.63 rows=16276 width=17) (actual time=608.035..706.762 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=606.747..705.672 rows=531889 loops=1 -> Parallel Seq Scan on public.customer (cost=0.00..3838.06 rows=84706 width=17) (actual time=0.009..7.236 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=0.010..7.344 rows=71598 loops=1 -> Parallel Hash (cost=140559.64..140559.64 rows=11529 width=8) (actual time=607.826..607.830 rows=546248 loops=2) Output: store_sales.ss_customer_sk, date_dim.d_date Buckets: 2097152 (originally 32768) Batches: 1 (originally 1) Memory Usage: 74272kB Worker 0: actual time=606.664..606.666 rows=546687 loops=1 -> Parallel Hash Join (cost=2570.12..140559.64 rows=11529 width=8) (actual time=5.418..506.881 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=4.257..506.966 rows=546687 loops=1 -> Parallel Seq Scan on public.store_sales (cost=0.00..131690.80 rows=2399380 width=8) (actual time=0.019..257.782 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=0.022..257.891 rows=2878318 loops=1 -> Parallel Hash (cost=2567.55..2567.55 rows=206 width=8) (actual time=5.371..5.371 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=4.204..4.205 rows=155 loops=1 -> Parallel Seq Scan on public.date_dim (cost=0.00..2567.55 rows=206 width=8) (actual time=2.189..5.321 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=1.028..4.157 rows=155 loops=1 -> Subquery Scan on "*SELECT* 2" (cost=49878.01..50040.79 rows=8139 width=21) (actual time=658.619..676.077 rows=62744 loops=1) Output: "*SELECT* 2".c_last_name, "*SELECT* 2".c_first_name, "*SELECT* 2".d_date, 1 -> Unique (cost=49878.01..49959.40 rows=8139 width=17) (actual time=658.617..669.592 rows=62744 loops=1) Output: customer_1.c_last_name, customer_1.c_first_name, date_dim_1.d_date -> Sort (cost=49878.01..49898.36 rows=8139 width=17) (actual time=658.616..661.616 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: quicksort Memory: 4341kB -> Gather (cost=48454.07..49349.36 rows=8139 width=17) (actual time=561.197..571.678 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=47454.07..47535.46 rows=8139 width=17) (actual time=535.356..541.636 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=509.782..515.593 rows=29639 loops=1 Batches: 1 Memory Usage: 3601kB -> Nested Loop (cost=0.85..47393.02 rows=8139 width=17) (actual time=1.863..466.491 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=0.549..444.467 rows=268480 loops=1 -> Nested Loop (cost=0.43..43793.90 rows=8139 width=8) (actual time=1.847..88.255 rows=285052 loops=2) Output: catalog_sales.cs_bill_customer_sk, date_dim_1.d_date Worker 0: actual time=0.527..85.258 rows=269122 loops=1 -> Parallel Seq Scan on public.date_dim date_dim_1 (cost=0.00..2567.55 rows=206 width=8) (actual time=1.809..3.772 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=0.489..4.356 rows=175 loops=1 -> Index Scan using idx_cs_sold_date_sk on public.catalog_sales (cost=0.43..184.53 rows=1560 width=8) (actual time=0.004..0.314 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..0.315 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=50558.61..51486.87 rows=6929 width=21) (actual time=308.103..403.898 rows=23737 loops=1) Output: "*SELECT* 3".c_last_name, "*SELECT* 3".c_first_name, "*SELECT* 3".d_date, 1 -> Unique (cost=50558.61..51417.58 rows=6929 width=17) (actual time=308.101..401.424 rows=23737 loops=1) Output: customer_2.c_last_name, customer_2.c_first_name, date_dim_2.d_date -> Gather Merge (cost=50558.61..51365.61 rows=6929 width=17) (actual time=308.100..370.805 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=49558.59..49565.81 rows=2887 width=17) (actual time=304.699..310.446 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: quicksort Memory: 7444kB Worker 0: actual time=304.767..309.513 rows=96821 loops=1 Sort Method: quicksort Memory: 7379kB Worker 1: actual time=301.512..309.827 rows=92877 loops=1 Sort Method: quicksort Memory: 7205kB -> Nested Loop (cost=2570.55..49392.65 rows=2887 width=17) (actual time=3.419..230.307 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=2.440..229.401 rows=96821 loops=1 Worker 1: actual time=2.704..230.216 rows=92877 loops=1 -> Parallel Hash Join (cost=2570.12..48102.45 rows=2887 width=8) (actual time=3.401..99.460 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=2.417..97.885 rows=96841 loops=1 Worker 1: actual time=2.685..97.490 rows=92890 loops=1 -> Parallel Seq Scan on public.web_sales (cost=0.00..43955.11 rows=600811 width=8) (actual time=0.016..53.317 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=0.019..52.418 rows=484786 loops=1 Worker 1: actual time=0.020..53.691 rows=460693 loops=1 -> Parallel Hash (cost=2567.55..2567.55 rows=206 width=8) (actual time=3.208..3.209 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=2.256..2.257 rows=152 loops=1 Worker 1: actual time=2.557..2.558 rows=76 loops=1 -> Parallel Seq Scan on public.date_dim date_dim_2 (cost=0.00..2567.55 rows=206 width=8) (actual time=1.291..3.153 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=0.329..2.197 rows=152 loops=1 Worker 1: actual time=0.643..2.497 rows=76 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=96841 Worker 1: actual time=0.001..0.001 rows=1 loops=92890 Planning Time: 3.013 ms Execution Time: 2203.990 ms (145 rows)