tpcds_ch-Multi-table_queries.sql

1、
select i_item_id, 
        avg(cs_quantity) agg1,
        avg(cs_list_price) agg2,
        avg(cs_coupon_amt) agg3,
        avg(cs_sales_price) agg4 
 from catalog_sales, customer_demographics, date_dim, item, promotion
 where cs_sold_date_sk = d_date_sk and
       cs_item_sk = i_item_sk and
       cs_bill_cdemo_sk = cd_demo_sk and
       cs_promo_sk = p_promo_sk and
       cd_gender = 'M' and 
       cd_marital_status = 'D' and
       cd_education_status = 'Advanced Degree' and
       (p_channel_email = 'N' or p_channel_event = 'N') and
       d_year = 1998 
 group by i_item_id
 order by i_item_id
 limit 10;

2、
select i_brand_id brand_id, i_brand brand,
  sum(ss_ext_sales_price) ext_price
 from date_dim, store_sales, item
 where d_date_sk = ss_sold_date_sk
  and ss_item_sk = i_item_sk
  and i_manager_id=25
  and d_moy=11
  and d_year=2002
 group by i_brand, i_brand_id
 order by ext_price desc, i_brand_id
 limit 10;

3、
select channel, col_name, d_year, d_qoy, i_category, COUNT(*) sales_cnt, SUM(ext_sales_price) sales_amt FROM (
        SELECT 'store' as channel, 'ss_promo_sk' col_name, d_year, d_qoy, i_category, ss_ext_sales_price ext_sales_price
         FROM store_sales, item, date_dim
         WHERE ss_promo_sk IS NULL
           AND ss_sold_date_sk=d_date_sk
           AND ss_item_sk=i_item_sk
        UNION ALL
        SELECT 'web' as channel, 'ws_ship_customer_sk' col_name, d_year, d_qoy, i_category, ws_ext_sales_price ext_sales_price
         FROM web_sales, item, date_dim
         WHERE ws_ship_customer_sk IS NULL
           AND ws_sold_date_sk=d_date_sk
           AND ws_item_sk=i_item_sk
        UNION ALL
        SELECT 'catalog' as channel, 'cs_bill_hdemo_sk' col_name, d_year, d_qoy, i_category, cs_ext_sales_price ext_sales_price
         FROM catalog_sales, item, date_dim
         WHERE cs_bill_hdemo_sk IS NULL
           AND cs_sold_date_sk=d_date_sk
           AND cs_item_sk=i_item_sk) foo
GROUP BY channel, col_name, d_year, d_qoy, i_category
ORDER BY channel, col_name, d_year, d_qoy, i_category
limit 10;

4、
select avg(ss_quantity)
       ,avg(ss_ext_sales_price)
       ,avg(ss_ext_wholesale_cost)
       ,sum(ss_ext_wholesale_cost)
 from store_sales
     ,store
     ,customer_demographics
     ,household_demographics
     ,customer_address
     ,date_dim
 where s_store_sk = ss_store_sk
 and  ss_sold_date_sk = d_date_sk and d_year = 2001
 and((ss_hdemo_sk=hd_demo_sk
  and cd_demo_sk = ss_cdemo_sk
  and cd_marital_status = 'U'
  and cd_education_status = 'Secondary'
  and ss_sales_price between 100.00 and 150.00
  and hd_dep_count = 3   
     )or
     (ss_hdemo_sk=hd_demo_sk
  and cd_demo_sk = ss_cdemo_sk
  and cd_marital_status = 'S'
  and cd_education_status = 'Advanced Degree'
  and ss_sales_price between 50.00 and 100.00   
  and hd_dep_count = 1
     ) or 
     (ss_hdemo_sk=hd_demo_sk
  and cd_demo_sk = ss_cdemo_sk
  and cd_marital_status = 'M'
  and cd_education_status = 'College'
  and ss_sales_price between 150.00 and 200.00 
  and hd_dep_count = 1  
     ))
 and((ss_addr_sk = ca_address_sk
  and ca_country = 'United States'
  and ca_state in ('AK', 'TX', 'WV')
  and ss_net_profit between 100 and 200  
     ) or
     (ss_addr_sk = ca_address_sk
  and ca_country = 'United States'
  and ca_state in ('MT', 'NC', 'IN')
  and ss_net_profit between 150 and 300  
     ) or
     (ss_addr_sk = ca_address_sk
  and ca_country = 'United States'
  and ca_state in ('MI', 'MO', 'KY')
  and ss_net_profit between 50 and 250  
     ))
	 limit 10;


5、
select c_last_name
       ,c_first_name
       ,c_salutation
       ,c_preferred_cust_flag 
       ,ss_ticket_number
       ,cnt from
   (select ss_ticket_number
          ,ss_customer_sk
          ,count(*) cnt
    from store_sales,date_dim,store,household_demographics
    where store_sales.ss_sold_date_sk = date_dim.d_date_sk
    and store_sales.ss_store_sk = store.s_store_sk  
    and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
    and date_dim.d_dom between 1 and 2 
    and (household_demographics.hd_buy_potential = '>10000' or
         household_demographics.hd_buy_potential = '5001-10000')
    and household_demographics.hd_vehicle_count > 0
    and case when household_demographics.hd_vehicle_count > 0 then 
             household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1
    and date_dim.d_year in (1999,1999+1,1999+2)
    and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County')
    group by ss_ticket_number,ss_customer_sk) dj,customer
    where ss_customer_sk = c_customer_sk
      and cnt between 1 and 5
    order by cnt desc, c_last_name asc;


6 select 
  c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit
  from
   (select ss_ticket_number
          ,ss_customer_sk
          ,store.s_city
          ,sum(ss_coupon_amt) amt
          ,sum(ss_net_profit) profit
    from store_sales,date_dim,store,household_demographics
    where store_sales.ss_sold_date_sk = date_dim.d_date_sk
    and store_sales.ss_store_sk = store.s_store_sk  
    and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
    and (household_demographics.hd_dep_count = 1 or household_demographics.hd_vehicle_count > -1)
    and date_dim.d_dow = 1
    and date_dim.d_year in (2000,2000+1,2000+2) 
    and store.s_number_employees between 200 and 295
    group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer
    where ss_customer_sk = c_customer_sk
 order by c_last_name,c_first_name,substr(s_city,1,30), profit
 limit 10
;

7、
select sum (ss_quantity)
 from store_sales, store, customer_demographics, customer_address, date_dim
 where s_store_sk = ss_store_sk
 and  ss_sold_date_sk = d_date_sk and d_year = 2000
 and  
 (
  (
   cd_demo_sk = ss_cdemo_sk
   and 
   cd_marital_status = 'S'
   and 
   cd_education_status = 'Advanced Degree'
   and 
   ss_sales_price between 100.00 and 150.00  
   )
 or
  (
  cd_demo_sk = ss_cdemo_sk
   and 
   cd_marital_status = 'D'
   and 
   cd_education_status = '4 yr Degree'
   and 
   ss_sales_price between 50.00 and 100.00   
  )
 or 
 (
  cd_demo_sk = ss_cdemo_sk
  and 
   cd_marital_status = 'U'
   and 
   cd_education_status = 'Secondary'
   and 
   ss_sales_price between 150.00 and 200.00  
 )
 )
 and
 (
  (
  ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('MN', 'TN', 'IL')
  and ss_net_profit between 0 and 2000  
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('TX', 'OR', 'ID')
  and ss_net_profit between 150 and 3000 
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('MI', 'AL', 'RI')
  and ss_net_profit between 50 and 25000 
  )
 )
;

8 select  i_item_id, 
        avg(cs_quantity) agg1,
        avg(cs_list_price) agg2,
        avg(cs_coupon_amt) agg3,
        avg(cs_sales_price) agg4 
 from catalog_sales, customer_demographics, date_dim, item, promotion
 where cs_sold_date_sk = d_date_sk and
       cs_item_sk = i_item_sk and
       cs_bill_cdemo_sk = cd_demo_sk and
       cs_promo_sk = p_promo_sk and
       cd_gender = 'M' and 
       cd_marital_status = 'D' and
       cd_education_status = 'Advanced Degree' and
       (p_channel_email = 'N' or p_channel_event = 'N') and
       d_year = 1998 
 group by i_item_id
 order by i_item_id
 limit 10
 ;
 
9、
select distinct(i_product_name)
 from item i1
 where i_manufact_id between 761 and 761+40 
   and (select count(*) as item_cnt
        from item
        where (i_manufact = i1.i_manufact and
        ((i_category = 'Women' and 
        (i_color = 'midnight' or i_color = 'gainsboro') and 
        (i_units = 'Box' or i_units = 'Carton') and
        (i_size = 'small' or i_size = 'large')
        ) or
        (i_category = 'Women' and
        (i_color = 'magenta' or i_color = 'chocolate') and
        (i_units = 'Lb' or i_units = 'Bunch') and
        (i_size = 'petite' or i_size = 'medium')
        ) or
        (i_category = 'Men' and
        (i_color = 'chartreuse' or i_color = 'chiffon') and
        (i_units = 'Tbl' or i_units = 'Dozen') and
        (i_size = 'economy' or i_size = 'extra large')
        ) or
        (i_category = 'Men' and
        (i_color = 'coral' or i_color = 'pale') and
        (i_units = 'Ton' or i_units = 'Bundle') and
        (i_size = 'small' or i_size = 'large')
        ))) or
       (i_manufact = i1.i_manufact and
        ((i_category = 'Women' and 
        (i_color = 'burnished' or i_color = 'plum') and 
        (i_units = 'Oz' or i_units = 'Each') and
        (i_size = 'small' or i_size = 'large')
        ) or
        (i_category = 'Women' and
        (i_color = 'misty' or i_color = 'mint') and
        (i_units = 'Ounce' or i_units = 'Tsp') and
        (i_size = 'petite' or i_size = 'medium')
        ) or
        (i_category = 'Men' and
        (i_color = 'dark' or i_color = 'olive') and
        (i_units = 'Dram' or i_units = 'Gross') and
        (i_size = 'economy' or i_size = 'extra large')
        ) or
        (i_category = 'Men' and
        (i_color = 'cornflower' or i_color = 'hot') and
        (i_units = 'Gram' or i_units = 'N/A') and
        (i_size = 'small' or i_size = 'large')
        )))) > 0
 order by i_product_name
 limit 10
 ;

10、
select *
from(
select i_category, i_class, i_brand,
       s_store_name, s_company_name,
       d_moy,
       sum(ss_sales_price) sum_sales,
       avg(sum(ss_sales_price)) over
         (partition by i_category, i_brand, s_store_name, s_company_name)
         avg_monthly_sales
from item, store_sales, date_dim, store
where ss_item_sk = i_item_sk and
      ss_sold_date_sk = d_date_sk and
      ss_store_sk = s_store_sk and
      d_year in (1998) and
        ((i_category in ('Electronics','Men','Books') and
          i_class in ('cameras','shirts','entertainments')
         )
      or (i_category in ('Music','Women','Jewelry') and
          i_class in ('classical','dresses','estate') 
        ))
group by i_category, i_class, i_brand,
         s_store_name, s_company_name, d_moy) tmp1
where case when (avg_monthly_sales <> 0) then (abs(sum_sales - avg_monthly_sales) / avg_monthly_sales) else null end > 0.1
order by sum_sales - avg_monthly_sales, s_store_name
limit 10
;

 11 select sum (ss_quantity)
 from store_sales, store, customer_demographics, customer_address, date_dim
 where s_store_sk = ss_store_sk
 and  ss_sold_date_sk = d_date_sk and d_year = 2000
 and  
 (
  (
   cd_demo_sk = ss_cdemo_sk
   and 
   cd_marital_status = 'S'
   and 
   cd_education_status = 'Advanced Degree'
   and 
   ss_sales_price between 100.00 and 150.00  
   )
 or
  (
  cd_demo_sk = ss_cdemo_sk
   and 
   cd_marital_status = 'D'
   and 
   cd_education_status = '4 yr Degree'
   and 
   ss_sales_price between 50.00 and 100.00   
  )
 or 
 (
  cd_demo_sk = ss_cdemo_sk
  and 
   cd_marital_status = 'U'
   and 
   cd_education_status = 'Secondary'
   and 
   ss_sales_price between 150.00 and 200.00  
 )
 )
 and
 (
  (
  ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('MN', 'TN', 'IL')
  and ss_net_profit between 0 and 2000  
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('TX', 'OR', 'ID')
  and ss_net_profit between 150 and 3000 
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('MI', 'AL', 'RI')
  and ss_net_profit between 50 and 25000 
  )
 )
;
12 
select 
	s_store_name,
	i_item_desc,
	sc.revenue,
	i_current_price,
	i_wholesale_cost,
	i_brand
 from store, item,
     (select ss_store_sk, avg(revenue) as ave
 	from
 	    (select  ss_store_sk, ss_item_sk, 
 		     sum(ss_sales_price) as revenue
 		from store_sales, date_dim
 		where ss_sold_date_sk = d_date_sk and d_month_seq between 1177 and 1177+11
 		group by ss_store_sk, ss_item_sk) sa
 	group by ss_store_sk) sb,
    (select  ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue
		from store_sales, date_dim
		where ss_sold_date_sk = d_date_sk and d_month_seq between 1177 and 1177+11
		group by ss_store_sk, ss_item_sk) sc
 where sb.ss_store_sk = sc.ss_store_sk and 
       sc.revenue <= 0.1 * sb.ave and
       s_store_sk = sc.ss_store_sk and
       i_item_sk = sc.ss_item_sk
 order by s_store_name, i_item_desc
 limit 10
;

select s_store_name,i_item_desc,sc.revenue,i_current_price,i_wholesale_cost,i_brand from store, item,(select ss_store_sk, avg(revenue) as ave from(select  ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue from store_sales, date_dim where ss_sold_date_sk = d_date_sk and d_month_seq between 1177 and 1177+11 group by ss_store_sk, ss_item_sk) sa group by ss_store_sk) sb,(select  ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue from store_sales, date_dim where ss_sold_date_sk = d_date_sk and d_month_seq between 1177 and 1177+11 group by ss_store_sk, ss_item_sk) sc where sb.ss_store_sk = sc.ss_store_sk and sc.revenue <= 0.1 * sb.ave and s_store_sk = sc.ss_store_sk and i_item_sk = sc.ss_item_sk order by s_store_name, i_item_desc limit 10;


13
select  *
from
 (select count(*) h8_30_to_9
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk   
     and ss_hdemo_sk = household_demographics.hd_demo_sk 
     and ss_store_sk = s_store_sk
     and time_dim.t_hour = 8
     and time_dim.t_minute >= 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2)) 
     and store.s_store_name = 'ese') s1,
 (select count(*) h9_to_9_30 
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk 
     and time_dim.t_hour = 9 
     and time_dim.t_minute < 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s2,
 (select count(*) h9_30_to_10 
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk
     and time_dim.t_hour = 9
     and time_dim.t_minute >= 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s3,
 (select count(*) h10_to_10_30
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk
     and time_dim.t_hour = 10 
     and time_dim.t_minute < 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s4,
 (select count(*) h10_30_to_11
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk
     and time_dim.t_hour = 10 
     and time_dim.t_minute >= 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s5,
 (select count(*) h11_to_11_30
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk 
     and time_dim.t_hour = 11
     and time_dim.t_minute < 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s6,
 (select count(*) h11_30_to_12
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk
     and time_dim.t_hour = 11
     and time_dim.t_minute >= 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s7,
 (select count(*) h12_to_12_30
 from store_sales, household_demographics , time_dim, store
 where ss_sold_time_sk = time_dim.t_time_sk
     and ss_hdemo_sk = household_demographics.hd_demo_sk
     and ss_store_sk = s_store_sk
     and time_dim.t_hour = 12
     and time_dim.t_minute < 30
     and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
     and store.s_store_name = 'ese') s8
;

select  * from(select count(*) h8_30_to_9 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk   and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 8 and time_dim.t_minute >= 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2)) and store.s_store_name = 'ese') s1,(select count(*) h9_to_9_30 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk  and time_dim.t_hour = 9 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or(household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))and store.s_store_name = 'ese') s2,(select count(*) h9_30_to_10 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 9  and time_dim.t_minute >= 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or(household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))and store.s_store_name = 'ese') s3,(select count(*) h10_to_10_30 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 10 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or(household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))and store.s_store_name = 'ese') s4,(select count(*) h10_30_to_11 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 10 and time_dim.t_minute >= 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or(household_demographics.hd_dep_count = 4 and  household_demographics.hd_vehicle_count<=4+2))and store.s_store_name = 'ese') s5,(select count(*) h11_to_11_30 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 11 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or(household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))and store.s_store_name = 'ese') s6,(select count(*) h11_30_to_12 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 11  and time_dim.t_minute >= 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or  (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or(household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2)) and store.s_store_name = 'ese') s7,(select count(*) h12_to_12_30 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 12 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2)) and store.s_store_name = 'ese') s8;

14、
 select count(*) from store_sales,household_demographics ,time_dim, store where ss_sold_time_sk 
 = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk 
 and time_dim.t_hour = 8 and time_dim.t_minute >= 30 and household_demographics.hd_dep_count = 5 and 
 store.s_store_name = 'ese' order by count(*);


15
select 
   s_store_name
  ,s_company_id
  ,s_street_number
  ,s_street_name
  ,s_street_type
  ,s_suite_number
  ,s_city
  ,s_county
  ,s_state
  ,s_zip
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end)  as a
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and 
                 (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end )  as b
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and 
                 (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end)  as c
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and
                 (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end)  as d
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk  > 120) then 1 else 0 end)  as e 
from
   store_sales
  ,store_returns
  ,store
  ,date_dim d1
  ,date_dim d2
where
    d2.d_year = 2000
and d2.d_moy  = 8
and ss_ticket_number = sr_ticket_number
and ss_item_sk = sr_item_sk
and ss_sold_date_sk   = d1.d_date_sk
and sr_returned_date_sk   = d2.d_date_sk
and ss_customer_sk = sr_customer_sk
and ss_store_sk = s_store_sk
group by
   s_store_name
  ,s_company_id
  ,s_street_number
  ,s_street_name
  ,s_street_type
  ,s_suite_number
  ,s_city
  ,s_county
  ,s_state
  ,s_zip
order by s_store_name
        ,s_company_id
        ,s_street_number
        ,s_street_name
        ,s_street_type
        ,s_suite_number
        ,s_city
        ,s_county
        ,s_state
        ,s_zip
limit 10 
;

Multiple table queries used in bench-marking TPCDS on clickhouse
you can find the complete blog post @ https://aavin.dev/tpcds-benchmark-on-clickhouse-part1/