IHEII/sr_tpcds_exec huggingface dataset:
Query Q46 (degree of parallelism: 8)

select  c_last_name
       ,c_first_name
       ,ca_city
       ,bought_city
       ,ss_ticket_number
       ,amt,profit 
 from
   (select ss_ticket_number
          ,ss_customer_sk
          ,ca_city bought_city
          ,sum(ss_coupon_amt) amt
          ,sum(ss_net_profit) profit
    from store_sales,date_dim,store,household_demographics,customer_address 
    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 store_sales.ss_addr_sk = customer_address.ca_address_sk
    and (household_demographics.hd_dep_count = 4 or
         household_demographics.hd_vehicle_count= 3)
    and date_dim.d_dow in (6,0)
    and date_dim.d_year in (1999,1999+1,1999+2) 
    and store.s_city in ('Fairview','Midway','Fairview','Fairview','Fairview') 
    group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr
    where ss_customer_sk = c_customer_sk
      and customer.c_current_addr_sk = current_addr.ca_address_sk
      and current_addr.ca_city <> bought_city
  order by c_last_name
          ,c_first_name
          ,ca_city
          ,bought_city
          ,ss_ticket_number
  limit 100;

Measured execution times:
4000MB: 1640
4000MB-sp(lt0.2/ts5/min10/max100): 1633
8000MB: 1631
8000MB-sp(lt0.2/ts5/min10/max100): 1661
Query Q47 (degree of parallelism: 2)

with v1 as(
 select i_category, i_brand,
        s_store_name, s_company_name,
        d_year, 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, d_year)
          avg_monthly_sales,
        rank() over
          (partition by i_category, i_brand,
                     s_store_name, s_company_name
           order by d_year, d_moy) rn
 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 = 1999 or
         ( d_year = 1999-1 and d_moy =12) or
         ( d_year = 1999+1 and d_moy =1)
       )
 group by i_category, i_brand,
          s_store_name, s_company_name,
          d_year, d_moy),
 v2 as(
 select v1.i_category, v1.i_brand, v1.s_store_name, v1.s_company_name
        ,v1.d_year, v1.d_moy
        ,v1.avg_monthly_sales
        ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
 from v1, v1 v1_lag, v1 v1_lead
 where v1.i_category = v1_lag.i_category and
       v1.i_category = v1_lead.i_category and
       v1.i_brand = v1_lag.i_brand and
       v1.i_brand = v1_lead.i_brand and
       v1.s_store_name = v1_lag.s_store_name and
       v1.s_store_name = v1_lead.s_store_name and
       v1.s_company_name = v1_lag.s_company_name and
       v1.s_company_name = v1_lead.s_company_name and
       v1.rn = v1_lag.rn + 1 and
       v1.rn = v1_lead.rn - 1)
  select  *
 from v2
 where  d_year = 1999 and    
        avg_monthly_sales > 0 and
        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 100;

Measured execution times:
4000MB: 5098
4000MB-sp(lt0.2/ts5/min10/max100): 5135
8000MB: 5206
8000MB-sp(lt0.2/ts5/min10/max100): 5169
Query Q47 (degree of parallelism: 4)

with v1 as(
 select i_category, i_brand,
        s_store_name, s_company_name,
        d_year, 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, d_year)
          avg_monthly_sales,
        rank() over
          (partition by i_category, i_brand,
                     s_store_name, s_company_name
           order by d_year, d_moy) rn
 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 = 1999 or
         ( d_year = 1999-1 and d_moy =12) or
         ( d_year = 1999+1 and d_moy =1)
       )
 group by i_category, i_brand,
          s_store_name, s_company_name,
          d_year, d_moy),
 v2 as(
 select v1.i_category, v1.i_brand, v1.s_store_name, v1.s_company_name
        ,v1.d_year, v1.d_moy
        ,v1.avg_monthly_sales
        ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
 from v1, v1 v1_lag, v1 v1_lead
 where v1.i_category = v1_lag.i_category and
       v1.i_category = v1_lead.i_category and
       v1.i_brand = v1_lag.i_brand and
       v1.i_brand = v1_lead.i_brand and
       v1.s_store_name = v1_lag.s_store_name and
       v1.s_store_name = v1_lead.s_store_name and
       v1.s_company_name = v1_lag.s_company_name and
       v1.s_company_name = v1_lead.s_company_name and
       v1.rn = v1_lag.rn + 1 and
       v1.rn = v1_lead.rn - 1)
  select  *
 from v2
 where  d_year = 1999 and    
        avg_monthly_sales > 0 and
        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 100;

Measured execution times:
4000MB: 3120
4000MB-sp(lt0.2/ts5/min10/max100): 3182
8000MB: 3123
8000MB-sp(lt0.2/ts5/min10/max100): 3149
Query Q47 (degree of parallelism: 8)

with v1 as(
 select i_category, i_brand,
        s_store_name, s_company_name,
        d_year, 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, d_year)
          avg_monthly_sales,
        rank() over
          (partition by i_category, i_brand,
                     s_store_name, s_company_name
           order by d_year, d_moy) rn
 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 = 1999 or
         ( d_year = 1999-1 and d_moy =12) or
         ( d_year = 1999+1 and d_moy =1)
       )
 group by i_category, i_brand,
          s_store_name, s_company_name,
          d_year, d_moy),
 v2 as(
 select v1.i_category, v1.i_brand, v1.s_store_name, v1.s_company_name
        ,v1.d_year, v1.d_moy
        ,v1.avg_monthly_sales
        ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
 from v1, v1 v1_lag, v1 v1_lead
 where v1.i_category = v1_lag.i_category and
       v1.i_category = v1_lead.i_category and
       v1.i_brand = v1_lag.i_brand and
       v1.i_brand = v1_lead.i_brand and
       v1.s_store_name = v1_lag.s_store_name and
       v1.s_store_name = v1_lead.s_store_name and
       v1.s_company_name = v1_lag.s_company_name and
       v1.s_company_name = v1_lead.s_company_name and
       v1.rn = v1_lag.rn + 1 and
       v1.rn = v1_lead.rn - 1)
  select  *
 from v2
 where  d_year = 1999 and    
        avg_monthly_sales > 0 and
        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 100;

Measured execution times:
4000MB: 2385
4000MB-sp(lt0.2/ts5/min10/max100): 2367
8000MB: 2408
8000MB-sp(lt0.2/ts5/min10/max100): 2405
Query Q48 (degree of parallelism: 2)

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 = 'M'
   and 
   cd_education_status = '4 yr 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 = '2 yr Degree'
   and 
   ss_sales_price between 50.00 and 100.00   
  )
 or 
 (
  cd_demo_sk = ss_cdemo_sk
  and 
   cd_marital_status = 'S'
   and 
   cd_education_status = 'College'
   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 ('CO', 'OH', 'TX')
  and ss_net_profit between 0 and 2000  
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('OR', 'MN', 'KY')
  and ss_net_profit between 150 and 3000 
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('VA', 'CA', 'MS')
  and ss_net_profit between 50 and 25000 
  )
 )
;

Measured execution times:
4000MB: 1940
4000MB-sp(lt0.2/ts5/min10/max100): 1944
8000MB: 1913
8000MB-sp(lt0.2/ts5/min10/max100): 1974
Query Q48 (degree of parallelism: 4)

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 = 'M'
   and 
   cd_education_status = '4 yr 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 = '2 yr Degree'
   and 
   ss_sales_price between 50.00 and 100.00   
  )
 or 
 (
  cd_demo_sk = ss_cdemo_sk
  and 
   cd_marital_status = 'S'
   and 
   cd_education_status = 'College'
   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 ('CO', 'OH', 'TX')
  and ss_net_profit between 0 and 2000  
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('OR', 'MN', 'KY')
  and ss_net_profit between 150 and 3000 
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('VA', 'CA', 'MS')
  and ss_net_profit between 50 and 25000 
  )
 )
;

Measured execution times:
4000MB: 1345
4000MB-sp(lt0.2/ts5/min10/max100): 1346
8000MB: 1325
8000MB-sp(lt0.2/ts5/min10/max100): 1310
Query Q48 (degree of parallelism: 8)

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 = 'M'
   and 
   cd_education_status = '4 yr 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 = '2 yr Degree'
   and 
   ss_sales_price between 50.00 and 100.00   
  )
 or 
 (
  cd_demo_sk = ss_cdemo_sk
  and 
   cd_marital_status = 'S'
   and 
   cd_education_status = 'College'
   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 ('CO', 'OH', 'TX')
  and ss_net_profit between 0 and 2000  
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('OR', 'MN', 'KY')
  and ss_net_profit between 150 and 3000 
  )
 or
  (ss_addr_sk = ca_address_sk
  and
  ca_country = 'United States'
  and
  ca_state in ('VA', 'CA', 'MS')
  and ss_net_profit between 50 and 25000 
  )
 )
;

Measured execution times:
4000MB: 1323
4000MB-sp(lt0.2/ts5/min10/max100): 1348
8000MB: 1311
8000MB-sp(lt0.2/ts5/min10/max100): 1302
Query Q50 (degree of parallelism: 2)

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 "30 days" 
  ,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 "31-60 days" 
  ,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 "61-90 days" 
  ,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 "91-120 days" 
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk  > 120) then 1 else 0 end)  as ">120 days" 
from
   store_sales
  ,store_returns
  ,store
  ,date_dim d1
  ,date_dim d2
where
    d2.d_year = 2001
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 100;

Measured execution times:
4000MB: 2394
4000MB-sp(lt0.2/ts5/min10/max100): 2439
8000MB: 2430
8000MB-sp(lt0.2/ts5/min10/max100): 2420
Query Q50 (degree of parallelism: 4)

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 "30 days" 
  ,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 "31-60 days" 
  ,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 "61-90 days" 
  ,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 "91-120 days" 
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk  > 120) then 1 else 0 end)  as ">120 days" 
from
   store_sales
  ,store_returns
  ,store
  ,date_dim d1
  ,date_dim d2
where
    d2.d_year = 2001
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 100;

Measured execution times:
4000MB: 1643
4000MB-sp(lt0.2/ts5/min10/max100): 1631
8000MB: 1635
8000MB-sp(lt0.2/ts5/min10/max100): 1629
Query Q50 (degree of parallelism: 8)

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 "30 days" 
  ,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 "31-60 days" 
  ,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 "61-90 days" 
  ,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 "91-120 days" 
  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk  > 120) then 1 else 0 end)  as ">120 days" 
from
   store_sales
  ,store_returns
  ,store
  ,date_dim d1
  ,date_dim d2
where
    d2.d_year = 2001
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 100;

Measured execution times:
4000MB: 1519
4000MB-sp(lt0.2/ts5/min10/max100): 1529
8000MB: 1533
8000MB-sp(lt0.2/ts5/min10/max100): 1518
Query Q51 (degree of parallelism: 2)

WITH web_v1 as (
select
  ws_item_sk item_sk, d_date,
  sum(sum(ws_sales_price))
      over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from web_sales
    ,date_dim
where ws_sold_date_sk=d_date_sk
  and d_month_seq between 1200 and 1200+11
  and ws_item_sk is not NULL
group by ws_item_sk, d_date),
store_v1 as (
select
  ss_item_sk item_sk, d_date,
  sum(sum(ss_sales_price))
      over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from store_sales
    ,date_dim
where ss_sold_date_sk=d_date_sk
  and d_month_seq between 1200 and 1200+11
  and ss_item_sk is not NULL
group by ss_item_sk, d_date)
 select  *
from (select item_sk
     ,d_date
     ,web_sales
     ,store_sales
     ,max(web_sales)
         over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
     ,max(store_sales)
         over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
     from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
                 ,case when web.d_date is not null then web.d_date else store.d_date end d_date
                 ,web.cume_sales web_sales
                 ,store.cume_sales store_sales
           from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
                                                          and web.d_date = store.d_date)
          )x )y
where web_cumulative > store_cumulative
order by item_sk
        ,d_date
limit 100;

Measured execution times:
4000MB: 8946
4000MB-sp(lt0.2/ts5/min10/max100): -
8000MB: 8999
8000MB-sp(lt0.2/ts5/min10/max100): 9114
Query Q51 (degree of parallelism: 4)

WITH web_v1 as (
select
  ws_item_sk item_sk, d_date,
  sum(sum(ws_sales_price))
      over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from web_sales
    ,date_dim
where ws_sold_date_sk=d_date_sk
  and d_month_seq between 1200 and 1200+11
  and ws_item_sk is not NULL
group by ws_item_sk, d_date),
store_v1 as (
select
  ss_item_sk item_sk, d_date,
  sum(sum(ss_sales_price))
      over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from store_sales
    ,date_dim
where ss_sold_date_sk=d_date_sk
  and d_month_seq between 1200 and 1200+11
  and ss_item_sk is not NULL
group by ss_item_sk, d_date)
 select  *
from (select item_sk
     ,d_date
     ,web_sales
     ,store_sales
     ,max(web_sales)
         over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
     ,max(store_sales)
         over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
     from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
                 ,case when web.d_date is not null then web.d_date else store.d_date end d_date
                 ,web.cume_sales web_sales
                 ,store.cume_sales store_sales
           from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
                                                          and web.d_date = store.d_date)
          )x )y
where web_cumulative > store_cumulative
order by item_sk
        ,d_date
limit 100;

Measured execution times:
4000MB: 5615
4000MB-sp(lt0.2/ts5/min10/max100): -
8000MB: 5953
8000MB-sp(lt0.2/ts5/min10/max100): 6940
Query Q51 (degree of parallelism: 8)

WITH web_v1 as (
select
  ws_item_sk item_sk, d_date,
  sum(sum(ws_sales_price))
      over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from web_sales
    ,date_dim
where ws_sold_date_sk=d_date_sk
  and d_month_seq between 1200 and 1200+11
  and ws_item_sk is not NULL
group by ws_item_sk, d_date),
store_v1 as (
select
  ss_item_sk item_sk, d_date,
  sum(sum(ss_sales_price))
      over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from store_sales
    ,date_dim
where ss_sold_date_sk=d_date_sk
  and d_month_seq between 1200 and 1200+11
  and ss_item_sk is not NULL
group by ss_item_sk, d_date)
 select  *
from (select item_sk
     ,d_date
     ,web_sales
     ,store_sales
     ,max(web_sales)
         over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
     ,max(store_sales)
         over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
     from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
                 ,case when web.d_date is not null then web.d_date else store.d_date end d_date
                 ,web.cume_sales web_sales
                 ,store.cume_sales store_sales
           from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
                                                          and web.d_date = store.d_date)
          )x )y
where web_cumulative > store_cumulative
order by item_sk
        ,d_date
limit 100;

Measured execution times:
4000MB: -
4000MB-sp(lt0.2/ts5/min10/max100): -
8000MB: 4386
8000MB-sp(lt0.2/ts5/min10/max100): 4465
Query Q52 (degree of parallelism: 2)

select  dt.d_year
 	,item.i_brand_id brand_id
 	,item.i_brand brand
 	,sum(ss_ext_sales_price) ext_price
 from date_dim dt
     ,store_sales
     ,item
 where dt.d_date_sk = store_sales.ss_sold_date_sk
    and store_sales.ss_item_sk = item.i_item_sk
    and item.i_manager_id = 1
    and dt.d_moy=11
    and dt.d_year=2000
 group by dt.d_year
 	,item.i_brand
 	,item.i_brand_id
 order by dt.d_year
 	,ext_price desc
 	,brand_id
limit 100 ;

Measured execution times:
4000MB: 1247
4000MB-sp(lt0.2/ts5/min10/max100): 1253
8000MB: 1266
8000MB-sp(lt0.2/ts5/min10/max100): 1253
Query Q52 (degree of parallelism: 4)

select  dt.d_year
 	,item.i_brand_id brand_id
 	,item.i_brand brand
 	,sum(ss_ext_sales_price) ext_price
 from date_dim dt
     ,store_sales
     ,item
 where dt.d_date_sk = store_sales.ss_sold_date_sk
    and store_sales.ss_item_sk = item.i_item_sk
    and item.i_manager_id = 1
    and dt.d_moy=11
    and dt.d_year=2000
 group by dt.d_year
 	,item.i_brand
 	,item.i_brand_id
 order by dt.d_year
 	,ext_price desc
 	,brand_id
limit 100 ;

Measured execution times:
4000MB: 731
4000MB-sp(lt0.2/ts5/min10/max100): 777
8000MB: 741
8000MB-sp(lt0.2/ts5/min10/max100): 737
Query Q52 (degree of parallelism: 8)

select  dt.d_year
 	,item.i_brand_id brand_id
 	,item.i_brand brand
 	,sum(ss_ext_sales_price) ext_price
 from date_dim dt
     ,store_sales
     ,item
 where dt.d_date_sk = store_sales.ss_sold_date_sk
    and store_sales.ss_item_sk = item.i_item_sk
    and item.i_manager_id = 1
    and dt.d_moy=11
    and dt.d_year=2000
 group by dt.d_year
 	,item.i_brand
 	,item.i_brand_id
 order by dt.d_year
 	,ext_price desc
 	,brand_id
limit 100 ;

Measured execution times:
4000MB: 626
4000MB-sp(lt0.2/ts5/min10/max100): 654
8000MB: 621
8000MB-sp(lt0.2/ts5/min10/max100): 643