All Downloads are FREE. Search and download functionalities are using the official Maven repository.

tpcds.query66.sql Maven / Gradle / Ivy

There is a newer version: 1.2.23
Show newest version
select w_warehouse_name
     , w_warehouse_sq_ft
     , w_city
     , w_county
     , w_state
     , w_country
     , ship_carriers
     , year
     , sum (jan_sales) as jan_sales
     , sum (feb_sales) as feb_sales
     , sum (mar_sales) as mar_sales
     , sum (apr_sales) as apr_sales
     , sum (may_sales) as may_sales
     , sum (jun_sales) as jun_sales
     , sum (jul_sales) as jul_sales
     , sum (aug_sales) as aug_sales
     , sum (sep_sales) as sep_sales
     , sum (oct_sales) as oct_sales
     , sum (nov_sales) as nov_sales
     , sum (dec_sales) as dec_sales
     , sum (jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
     , sum (feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
     , sum (mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
     , sum (apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
     , sum (may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
     , sum (jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
     , sum (jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
     , sum (aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
     , sum (sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
     , sum (oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
     , sum (nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
     , sum (dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
     , sum (jan_net) as jan_net
     , sum (feb_net) as feb_net
     , sum (mar_net) as mar_net
     , sum (apr_net) as apr_net
     , sum (may_net) as may_net
     , sum (jun_net) as jun_net
     , sum (jul_net) as jul_net
     , sum (aug_net) as aug_net
     , sum (sep_net) as sep_net
     , sum (oct_net) as oct_net
     , sum (nov_net) as nov_net
     , sum (dec_net) as dec_net
from (
    select
    w_warehouse_name
        , w_warehouse_sq_ft
        , w_city
        , w_county
        , w_state
        , w_country
        , concat('DHL', ',', 'BARIAN') as ship_carriers
        , d_year as year
        , sum (case when d_moy = 1
    then ws_ext_sales_price* ws_quantity else 0 end) as jan_sales
        , sum (case when d_moy = 2
    then ws_ext_sales_price* ws_quantity else 0 end) as feb_sales
        , sum (case when d_moy = 3
    then ws_ext_sales_price* ws_quantity else 0 end) as mar_sales
        , sum (case when d_moy = 4
    then ws_ext_sales_price* ws_quantity else 0 end) as apr_sales
        , sum (case when d_moy = 5
    then ws_ext_sales_price* ws_quantity else 0 end) as may_sales
        , sum (case when d_moy = 6
    then ws_ext_sales_price* ws_quantity else 0 end) as jun_sales
        , sum (case when d_moy = 7
    then ws_ext_sales_price* ws_quantity else 0 end) as jul_sales
        , sum (case when d_moy = 8
    then ws_ext_sales_price* ws_quantity else 0 end) as aug_sales
        , sum (case when d_moy = 9
    then ws_ext_sales_price* ws_quantity else 0 end) as sep_sales
        , sum (case when d_moy = 10
    then ws_ext_sales_price* ws_quantity else 0 end) as oct_sales
        , sum (case when d_moy = 11
    then ws_ext_sales_price* ws_quantity else 0 end) as nov_sales
        , sum (case when d_moy = 12
    then ws_ext_sales_price* ws_quantity else 0 end) as dec_sales
        , sum (case when d_moy = 1
    then ws_net_paid * ws_quantity else 0 end) as jan_net
        , sum (case when d_moy = 2
    then ws_net_paid * ws_quantity else 0 end) as feb_net
        , sum (case when d_moy = 3
    then ws_net_paid * ws_quantity else 0 end) as mar_net
        , sum (case when d_moy = 4
    then ws_net_paid * ws_quantity else 0 end) as apr_net
        , sum (case when d_moy = 5
    then ws_net_paid * ws_quantity else 0 end) as may_net
        , sum (case when d_moy = 6
    then ws_net_paid * ws_quantity else 0 end) as jun_net
        , sum (case when d_moy = 7
    then ws_net_paid * ws_quantity else 0 end) as jul_net
        , sum (case when d_moy = 8
    then ws_net_paid * ws_quantity else 0 end) as aug_net
        , sum (case when d_moy = 9
    then ws_net_paid * ws_quantity else 0 end) as sep_net
        , sum (case when d_moy = 10
    then ws_net_paid * ws_quantity else 0 end) as oct_net
        , sum (case when d_moy = 11
    then ws_net_paid * ws_quantity else 0 end) as nov_net
        , sum (case when d_moy = 12
    then ws_net_paid * ws_quantity else 0 end) as dec_net
    from
    web_sales
        , warehouse
        , date_dim
        , time_dim
        , ship_mode
    where
    ws_warehouse_sk = w_warehouse_sk
    and ws_sold_date_sk = d_date_sk
    and ws_sold_time_sk = t_time_sk
    and ws_ship_mode_sk = sm_ship_mode_sk
    and d_year = 2001
    and t_time between 30838 and 30838+28800
    and sm_carrier in ('DHL', 'BARIAN')
    group by
    w_warehouse_name
        , w_warehouse_sq_ft
        , w_city
        , w_county
        , w_state
        , w_country
        , d_year
    union all
    select
    w_warehouse_name
        , w_warehouse_sq_ft
        , w_city
        , w_county
        , w_state
        , w_country
        , concat('DHL', ',', 'BARIAN') as ship_carriers
        , d_year as year
        , sum (case when d_moy = 1
    then cs_sales_price* cs_quantity else 0 end) as jan_sales
        , sum (case when d_moy = 2
    then cs_sales_price* cs_quantity else 0 end) as feb_sales
        , sum (case when d_moy = 3
    then cs_sales_price* cs_quantity else 0 end) as mar_sales
        , sum (case when d_moy = 4
    then cs_sales_price* cs_quantity else 0 end) as apr_sales
        , sum (case when d_moy = 5
    then cs_sales_price* cs_quantity else 0 end) as may_sales
        , sum (case when d_moy = 6
    then cs_sales_price* cs_quantity else 0 end) as jun_sales
        , sum (case when d_moy = 7
    then cs_sales_price* cs_quantity else 0 end) as jul_sales
        , sum (case when d_moy = 8
    then cs_sales_price* cs_quantity else 0 end) as aug_sales
        , sum (case when d_moy = 9
    then cs_sales_price* cs_quantity else 0 end) as sep_sales
        , sum (case when d_moy = 10
    then cs_sales_price* cs_quantity else 0 end) as oct_sales
        , sum (case when d_moy = 11
    then cs_sales_price* cs_quantity else 0 end) as nov_sales
        , sum (case when d_moy = 12
    then cs_sales_price* cs_quantity else 0 end) as dec_sales
        , sum (case when d_moy = 1
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as jan_net
        , sum (case when d_moy = 2
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as feb_net
        , sum (case when d_moy = 3
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as mar_net
        , sum (case when d_moy = 4
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as apr_net
        , sum (case when d_moy = 5
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as may_net
        , sum (case when d_moy = 6
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as jun_net
        , sum (case when d_moy = 7
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as jul_net
        , sum (case when d_moy = 8
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as aug_net
        , sum (case when d_moy = 9
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as sep_net
        , sum (case when d_moy = 10
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as oct_net
        , sum (case when d_moy = 11
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as nov_net
        , sum (case when d_moy = 12
    then cs_net_paid_inc_tax * cs_quantity else 0 end) as dec_net
    from
    catalog_sales
        , warehouse
        , date_dim
        , time_dim
        , ship_mode
    where
    cs_warehouse_sk = w_warehouse_sk
    and cs_sold_date_sk = d_date_sk
    and cs_sold_time_sk = t_time_sk
    and cs_ship_mode_sk = sm_ship_mode_sk
    and d_year = 2001
    and t_time between 30838 AND 30838+28800
    and sm_carrier in ('DHL', 'BARIAN')
    group by
    w_warehouse_name
        , w_warehouse_sq_ft
        , w_city
        , w_county
        , w_state
        , w_country
        , d_year
    ) x
group by
    w_warehouse_name
        , w_warehouse_sq_ft
        , w_city
        , w_county
        , w_state
        , w_country
        , ship_carriers
        , year
order by w_warehouse_name
    limit 100




© 2015 - 2024 Weber Informatics LLC | Privacy Policy