TPC-DS是事务处理性能委员会（ Transaction ProcessingPerformance Council ）制定的基准程序之一。TPC-DS测试涉及24张表，工作负载包含99个SQL，主要目的是评价特定查询的决策支持能力，详情参考：TPCDS
下面详细介绍使用AnalyticDB for PostgreSQL 6.0 进行TPC-DS 1TB数据的测试步骤：
1、开通一个ECS实例
准备一台ECS（建议规格：ecs.g6.4xlarge规格、CentOS系统、ESSD 2T数据盘，建议与AnalyticDB for PostgreSQL 6.0 实例用相同region和VPC网络），用于1T数据生成、数据上传/入库、客户端测试。
2、开通一个AnalyticDB for PostgreSQL 6.0 实例
2.1、AnalyticDB for PostgreSQL 6.0 规格选择
推荐选择性价比适中的两种规格：
• ADB PG 6.0 SSD存储+单节点4核+实例节点数16
• ADB PG 6.0 SSD存储+单节点4核+实例节点数32
参考配置如下图。建议与ECS实例用相同区域和VPC网络。
2.2、开通外网，修改白名单，创建数据库账号
进入阿里云分析型数据库PostgreSQL产品页，进入分析型数据库PostgreSQL版控制台，找到已开通的AnalyticDB for PostgreSQL 6.0 实例。点击“实例名链接”进入详情页，参考下图位置，修改配置项使ECS实例能够连接到ADB PG实例。
3、生成TPC-DS 1T数据
3.1、clone并编译TPC-DS dbgen代码
git clone https://github.com/gregrahn/tpcds-kit.git
cd tpcds-kit/tools
make OS=LINUX3.2、生成1TB数据
./dsdgen -TERMINATE N -SCALE 10003.3、各个数据表的数据量
| 表名 | 数据条数 |
|---|---|
| customer_address | 6000000 |
| customer_demographics | 1920800 |
| date_dim | 73049 |
| warehouse | 20 |
| ship_mode | 20 |
| time_dim | 86400 |
| reason | 65 |
| income_band | 20 |
| item | 300000 |
| store | 1002 |
| call_center | 42 |
| customer | 12000000 |
| web_site | 54 |
| store_returns | 287999764 |
| household_demographics | 7200 |
| web_page | 3000 |
| promotion | 1500 |
| catalog_page | 30000 |
| inventory | 783000000 |
| catalog_returns | 143996756 |
| web_returns | 71997522 |
| web_sales | 720000376 |
| catalog_sales | 1439980416 |
| store_sales | 2879987999 |
4、向数据库中建表
在ECS机器上检查是否存在PSQL命令，如果没有，安装PSQL客户端：
sudo yum install postgresql准备TPC-DS涉及到的24张表创建SQL，建表语句参考如下：
create table dbgen_version
(
dv_version varchar(16) ,
dv_create_date date ,
dv_create_time time ,
dv_cmdline_args varchar(200)
);
create table customer_address
(
ca_address_sk integer not null,
ca_address_id char(16) not null,
ca_street_number char(10) ,
ca_street_name varchar(60) ,
ca_street_type char(15) ,
ca_suite_number char(10) ,
ca_city varchar(60) ,
ca_county varchar(30) ,
ca_state char(2) ,
ca_zip char(10) ,
ca_country varchar(20) ,
ca_gmt_offset decimal(5,2) ,
ca_location_type char(20)
)
with (orientation=column, appendonly=true)
distributed by (ca_address_sk);
create table customer_demographics
(
cd_demo_sk integer not null,
cd_gender char(1) ,
cd_marital_status char(1) ,
cd_education_status char(20) ,
cd_purchase_estimate integer ,
cd_credit_rating char(10) ,
cd_dep_count integer ,
cd_dep_employed_count integer ,
cd_dep_college_count integer
)
with (orientation=column, appendonly=true)
distributed by (cd_demo_sk);
create table date_dim
(
d_date_sk integer not null,
d_date_id char(16) not null,
d_date date ,
d_month_seq integer ,
d_week_seq integer ,
d_quarter_seq integer ,
d_year integer ,
d_dow integer ,
d_moy integer ,
d_dom integer ,
d_qoy integer ,
d_fy_year integer ,
d_fy_quarter_seq integer ,
d_fy_week_seq integer ,
d_day_name char(9) ,
d_quarter_name char(6) ,
d_holiday char(1) ,
d_weekend char(1) ,
d_following_holiday char(1) ,
d_first_dom integer ,
d_last_dom integer ,
d_same_day_ly integer ,
d_same_day_lq integer ,
d_current_day char(1) ,
d_current_week char(1) ,
d_current_month char(1) ,
d_current_quarter char(1) ,
d_current_year char(1)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table warehouse
(
w_warehouse_sk integer not null,
w_warehouse_id char(16) not null,
w_warehouse_name varchar(20) ,
w_warehouse_sq_ft integer ,
w_street_number char(10) ,
w_street_name varchar(60) ,
w_street_type char(15) ,
w_suite_number char(10) ,
w_city varchar(60) ,
w_county varchar(30) ,
w_state char(2) ,
w_zip char(10) ,
w_country varchar(20) ,
w_gmt_offset decimal(5,2)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table ship_mode
(
sm_ship_mode_sk integer not null,
sm_ship_mode_id char(16) not null,
sm_type char(30) ,
sm_code char(10) ,
sm_carrier char(20) ,
sm_contract char(20)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table time_dim
(
t_time_sk integer not null,
t_time_id char(16) not null,
t_time integer ,
t_hour integer ,
t_minute integer ,
t_second integer ,
t_am_pm char(2) ,
t_shift char(20) ,
t_sub_shift char(20) ,
t_meal_time char(20)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table reason
(
r_reason_sk integer not null,
r_reason_id char(16) not null,
r_reason_desc char(100)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table income_band
(
ib_income_band_sk integer not null,
ib_lower_bound integer ,
ib_upper_bound integer
)
with (orientation=column, appendonly=true)
distributed replicated;
create table item
(
i_item_sk integer not null,
i_item_id char(16) not null,
i_rec_start_date date ,
i_rec_end_date date ,
i_item_desc varchar(200) ,
i_current_price decimal(7,2) ,
i_wholesale_cost decimal(7,2) ,
i_brand_id integer ,
i_brand char(50) ,
i_class_id integer ,
i_class char(50) ,
i_category_id integer ,
i_category char(50) ,
i_manufact_id integer ,
i_manufact char(50) ,
i_size char(20) ,
i_formulation char(20) ,
i_color char(20) ,
i_units char(10) ,
i_container char(10) ,
i_manager_id integer ,
i_product_name char(50)
)
with (orientation=column, appendonly=true)
distributed by (i_item_sk);
create table store
(
s_store_sk integer not null,
s_store_id char(16) not null,
s_rec_start_date date ,
s_rec_end_date date ,
s_closed_date_sk integer ,
s_store_name varchar(50) ,
s_number_employees integer ,
s_floor_space integer ,
s_hours char(20) ,
s_manager varchar(40) ,
s_market_id integer ,
s_geography_class varchar(100) ,
s_market_desc varchar(100) ,
s_market_manager varchar(40) ,
s_division_id integer ,
s_division_name varchar(50) ,
s_company_id integer ,
s_company_name varchar(50) ,
s_street_number varchar(10) ,
s_street_name varchar(60) ,
s_street_type char(15) ,
s_suite_number char(10) ,
s_city varchar(60) ,
s_county varchar(30) ,
s_state char(2) ,
s_zip char(10) ,
s_country varchar(20) ,
s_gmt_offset decimal(5,2) ,
s_tax_precentage decimal(5,2)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table call_center
(
cc_call_center_sk integer not null,
cc_call_center_id char(16) not null,
cc_rec_start_date date ,
cc_rec_end_date date ,
cc_closed_date_sk integer ,
cc_open_date_sk integer ,
cc_name varchar(50) ,
cc_class varchar(50) ,
cc_employees integer ,
cc_sq_ft integer ,
cc_hours char(20) ,
cc_manager varchar(40) ,
cc_mkt_id integer ,
cc_mkt_class char(50) ,
cc_mkt_desc varchar(100) ,
cc_market_manager varchar(40) ,
cc_division integer ,
cc_division_name varchar(50) ,
cc_company integer ,
cc_company_name char(50) ,
cc_street_number char(10) ,
cc_street_name varchar(60) ,
cc_street_type char(15) ,
cc_suite_number char(10) ,
cc_city varchar(60) ,
cc_county varchar(30) ,
cc_state char(2) ,
cc_zip char(10) ,
cc_country varchar(20) ,
cc_gmt_offset decimal(5,2) ,
cc_tax_percentage decimal(5,2)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table customer
(
c_customer_sk integer not null,
c_customer_id char(16) not null,
c_current_cdemo_sk integer ,
c_current_hdemo_sk integer ,
c_current_addr_sk integer ,
c_first_shipto_date_sk integer ,
c_first_sales_date_sk integer ,
c_salutation char(10) ,
c_first_name char(20) ,
c_last_name char(30) ,
c_preferred_cust_flag char(1) ,
c_birth_day integer ,
c_birth_month integer ,
c_birth_year integer ,
c_birth_country varchar(20) ,
c_login char(13) ,
c_email_address char(50) ,
c_last_review_date char(10)
)
with (orientation=column, appendonly=true)
distributed by (c_customer_sk);
create table web_site
(
web_site_sk integer not null,
web_site_id char(16) not null,
web_rec_start_date date ,
web_rec_end_date date ,
web_name varchar(50) ,
web_open_date_sk integer ,
web_close_date_sk integer ,
web_class varchar(50) ,
web_manager varchar(40) ,
web_mkt_id integer ,
web_mkt_class varchar(50) ,
web_mkt_desc varchar(100) ,
web_market_manager varchar(40) ,
web_company_id integer ,
web_company_name char(50) ,
web_street_number char(10) ,
web_street_name varchar(60) ,
web_street_type char(15) ,
web_suite_number char(10) ,
web_city varchar(60) ,
web_county varchar(30) ,
web_state char(2) ,
web_zip char(10) ,
web_country varchar(20) ,
web_gmt_offset decimal(5,2) ,
web_tax_percentage decimal(5,2)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table store_returns
(
sr_returned_date_sk integer ,
sr_return_time_sk integer ,
sr_item_sk integer not null,
sr_customer_sk integer ,
sr_cdemo_sk integer ,
sr_hdemo_sk integer ,
sr_addr_sk integer ,
sr_store_sk integer ,
sr_reason_sk integer ,
sr_ticket_number bigint not null,
sr_return_quantity integer ,
sr_return_amt decimal(7,2) ,
sr_return_tax decimal(7,2) ,
sr_return_amt_inc_tax decimal(7,2) ,
sr_fee decimal(7,2) ,
sr_return_ship_cost decimal(7,2) ,
sr_refunded_cash decimal(7,2) ,
sr_reversed_charge decimal(7,2) ,
sr_store_credit decimal(7,2) ,
sr_net_loss decimal(7,2)
)
with (orientation=column, appendonly=true)
distributed by (sr_item_sk, sr_ticket_number)
partition by range (sr_returned_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (100),
default partition others
);
create table household_demographics
(
hd_demo_sk integer not null,
hd_income_band_sk integer ,
hd_buy_potential char(15) ,
hd_dep_count integer ,
hd_vehicle_count integer
)
with (orientation=column, appendonly=true)
distributed replicated;
create table web_page
(
wp_web_page_sk integer not null,
wp_web_page_id char(16) not null,
wp_rec_start_date date ,
wp_rec_end_date date ,
wp_creation_date_sk integer ,
wp_access_date_sk integer ,
wp_autogen_flag char(1) ,
wp_customer_sk integer ,
wp_url varchar(100) ,
wp_type char(50) ,
wp_char_count integer ,
wp_link_count integer ,
wp_image_count integer ,
wp_max_ad_count integer
)
with (orientation=column, appendonly=true)
distributed replicated;
create table promotion
(
p_promo_sk integer not null,
p_promo_id char(16) not null,
p_start_date_sk integer ,
p_end_date_sk integer ,
p_item_sk integer ,
p_cost decimal(15,2) ,
p_response_target integer ,
p_promo_name char(50) ,
p_channel_dmail char(1) ,
p_channel_email char(1) ,
p_channel_catalog char(1) ,
p_channel_tv char(1) ,
p_channel_radio char(1) ,
p_channel_press char(1) ,
p_channel_event char(1) ,
p_channel_demo char(1) ,
p_channel_details varchar(100) ,
p_purpose char(15) ,
p_discount_active char(1)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table catalog_page
(
cp_catalog_page_sk integer not null,
cp_catalog_page_id char(16) not null,
cp_start_date_sk integer ,
cp_end_date_sk integer ,
cp_department varchar(50) ,
cp_catalog_number integer ,
cp_catalog_page_number integer ,
cp_description varchar(100) ,
cp_type varchar(100)
)
with (orientation=column, appendonly=true)
distributed replicated;
create table inventory
(
inv_date_sk integer not null,
inv_item_sk integer not null,
inv_warehouse_sk integer not null,
inv_quantity_on_hand integer
)
with (orientation=column, appendonly=true, compresslevel=1)
distributed by (inv_date_sk, inv_item_sk, inv_warehouse_sk)
partition by range (inv_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (100),
default partition others
);
create table catalog_returns
(
cr_returned_date_sk integer ,
cr_returned_time_sk integer ,
cr_item_sk integer not null,
cr_refunded_customer_sk integer ,
cr_refunded_cdemo_sk integer ,
cr_refunded_hdemo_sk integer ,
cr_refunded_addr_sk integer ,
cr_returning_customer_sk integer ,
cr_returning_cdemo_sk integer ,
cr_returning_hdemo_sk integer ,
cr_returning_addr_sk integer ,
cr_call_center_sk integer ,
cr_catalog_page_sk integer ,
cr_ship_mode_sk integer ,
cr_warehouse_sk integer ,
cr_reason_sk integer ,
cr_order_number bigint not null,
cr_return_quantity integer ,
cr_return_amount decimal(7,2) ,
cr_return_tax decimal(7,2) ,
cr_return_amt_inc_tax decimal(7,2) ,
cr_fee decimal(7,2) ,
cr_return_ship_cost decimal(7,2) ,
cr_refunded_cash decimal(7,2) ,
cr_reversed_charge decimal(7,2) ,
cr_store_credit decimal(7,2) ,
cr_net_loss decimal(7,2)
)
with (orientation=column, appendonly=true)
distributed by (cr_item_sk, cr_order_number)
partition by range (cr_returned_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (8),
default partition others
);
create table web_returns
(
wr_returned_date_sk integer ,
wr_returned_time_sk integer ,
wr_item_sk integer not null,
wr_refunded_customer_sk integer ,
wr_refunded_cdemo_sk integer ,
wr_refunded_hdemo_sk integer ,
wr_refunded_addr_sk integer ,
wr_returning_customer_sk integer ,
wr_returning_cdemo_sk integer ,
wr_returning_hdemo_sk integer ,
wr_returning_addr_sk integer ,
wr_web_page_sk integer ,
wr_reason_sk integer ,
wr_order_number bigint not null,
wr_return_quantity integer ,
wr_return_amt decimal(7,2) ,
wr_return_tax decimal(7,2) ,
wr_return_amt_inc_tax decimal(7,2) ,
wr_fee decimal(7,2) ,
wr_return_ship_cost decimal(7,2) ,
wr_refunded_cash decimal(7,2) ,
wr_reversed_charge decimal(7,2) ,
wr_account_credit decimal(7,2) ,
wr_net_loss decimal(7,2)
)
with (orientation=column, appendonly=true)
distributed by (wr_item_sk, wr_order_number)
partition by range (wr_returned_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (180),
default partition others
);
create table web_sales
(
ws_sold_date_sk integer ,
ws_sold_time_sk integer ,
ws_ship_date_sk integer ,
ws_item_sk integer not null,
ws_bill_customer_sk integer ,
ws_bill_cdemo_sk integer ,
ws_bill_hdemo_sk integer ,
ws_bill_addr_sk integer ,
ws_ship_customer_sk integer ,
ws_ship_cdemo_sk integer ,
ws_ship_hdemo_sk integer ,
ws_ship_addr_sk integer ,
ws_web_page_sk integer ,
ws_web_site_sk integer ,
ws_ship_mode_sk integer ,
ws_warehouse_sk integer ,
ws_promo_sk integer ,
ws_order_number bigint not null,
ws_quantity integer ,
ws_wholesale_cost decimal(7,2) ,
ws_list_price decimal(7,2) ,
ws_sales_price decimal(7,2) ,
ws_ext_discount_amt decimal(7,2) ,
ws_ext_sales_price decimal(7,2) ,
ws_ext_wholesale_cost decimal(7,2) ,
ws_ext_list_price decimal(7,2) ,
ws_ext_tax decimal(7,2) ,
ws_coupon_amt decimal(7,2) ,
ws_ext_ship_cost decimal(7,2) ,
ws_net_paid decimal(7,2) ,
ws_net_paid_inc_tax decimal(7,2) ,
ws_net_paid_inc_ship decimal(7,2) ,
ws_net_paid_inc_ship_tax decimal(7,2) ,
ws_net_profit decimal(7,2)
)
with (orientation=column, appendonly=true, compresslevel=1)
distributed by (ws_item_sk, ws_order_number)
partition by range (ws_sold_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (40),
default partition others
);
create table catalog_sales
(
cs_sold_date_sk integer ,
cs_sold_time_sk integer ,
cs_ship_date_sk integer ,
cs_bill_customer_sk integer ,
cs_bill_cdemo_sk integer ,
cs_bill_hdemo_sk integer ,
cs_bill_addr_sk integer ,
cs_ship_customer_sk integer ,
cs_ship_cdemo_sk integer ,
cs_ship_hdemo_sk integer ,
cs_ship_addr_sk integer ,
cs_call_center_sk integer ,
cs_catalog_page_sk integer ,
cs_ship_mode_sk integer ,
cs_warehouse_sk integer ,
cs_item_sk integer not null,
cs_promo_sk integer ,
cs_order_number bigint not null,
cs_quantity integer ,
cs_wholesale_cost decimal(7,2) ,
cs_list_price decimal(7,2) ,
cs_sales_price decimal(7,2) ,
cs_ext_discount_amt decimal(7,2) ,
cs_ext_sales_price decimal(7,2) ,
cs_ext_wholesale_cost decimal(7,2) ,
cs_ext_list_price decimal(7,2) ,
cs_ext_tax decimal(7,2) ,
cs_coupon_amt decimal(7,2) ,
cs_ext_ship_cost decimal(7,2) ,
cs_net_paid decimal(7,2) ,
cs_net_paid_inc_tax decimal(7,2) ,
cs_net_paid_inc_ship decimal(7,2) ,
cs_net_paid_inc_ship_tax decimal(7,2) ,
cs_net_profit decimal(7,2)
)
with (orientation=column, appendonly=true, compresslevel=1)
distributed by (cs_item_sk, cs_order_number)
partition by range (cs_sold_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (28),
default partition others
);
create table store_sales
(
ss_sold_date_sk integer ,
ss_sold_time_sk integer ,
ss_item_sk integer not null,
ss_customer_sk integer ,
ss_cdemo_sk integer ,
ss_hdemo_sk integer ,
ss_addr_sk integer ,
ss_store_sk integer ,
ss_promo_sk integer ,
ss_ticket_number bigint not null,
ss_quantity integer ,
ss_wholesale_cost decimal(7,2) ,
ss_list_price decimal(7,2) ,
ss_sales_price decimal(7,2) ,
ss_ext_discount_amt decimal(7,2) ,
ss_ext_sales_price decimal(7,2) ,
ss_ext_wholesale_cost decimal(7,2) ,
ss_ext_list_price decimal(7,2) ,
ss_ext_tax decimal(7,2) ,
ss_coupon_amt decimal(7,2) ,
ss_net_paid decimal(7,2) ,
ss_net_paid_inc_tax decimal(7,2) ,
ss_net_profit decimal(7,2)
)
with (orientation=column, appendonly=true, compresslevel=1)
distributed by (ss_item_sk, ss_ticket_number)
partition by range (ss_sold_date_sk)
(
start(2450815) INCLUSIVE end(2453005) INCLUSIVE every (10),
default partition others
);列存表适合向量计算、JIT架构。对大批量数据的访问和统计，效率更高。因此建表语句中使用了
• 所有表均为列存表
• 7个大表建分区表
• 3个*_sales表及inventory表压缩级别为1，其他压缩级别为0
将上述建表语句存储为一个建表SQL脚本文件，可以批量创建TPC-DS数据表，执行方式如下：
export PGPASSWORD=<数据库账号密码>
psql -h <ADB PG实例内网或外网地址> -p 3432 -U <数据库账号> -f <创建表的SQL脚本文件路径>5、导入数据
通过copy命令可以从文件中导入数据到ADB PG数据表中，可以根据实际情况设置分隔符和其他格式：
\COPY dbgen_version from 'dbgen_version.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY customer_address from 'customer_address.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY customer_demographics from 'customer_demographics.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY date_dim from 'date_dim.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY warehouse from 'warehouse.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY ship_mode from 'ship_mode.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY time_dim from 'time_dim.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY reason from 'reason.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY income_band from 'income_band.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY item from 'item.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY store from 'store.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY call_center from 'call_center.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY customer from 'customer.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY web_site from 'web_site.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY store_returns from 'store_returns.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY household_demographics from 'household_demographics.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY web_page from 'web_page.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY promotion from 'promotion.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY catalog_page from 'catalog_page.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY inventory from 'inventory.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY catalog_returns from 'catalog_returns.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY web_returns from 'web_returns.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY web_sales from 'web_sales.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY catalog_sales from 'catalog_sales.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;
\COPY store_sales from 'store_sales.dat' with DELIMITER '|' NULL '' SEGMENT REJECT LIMIT 10000 ROWS;导入过程中可能会遇到无法识别的特殊字符导致copy命令中断，这种情况一般是由于外部文件的字符编码无法识别，可以参考以下命令将文件编码改为UTF-8，再重新进行导入：
iconv -f GBK -t UTF-8 customer.dat -o tcustomer.dat6、查询执行阶段
6.1、收集统计信息
analyze customer_address;
analyze customer_demographics;
analyze date_dim;
analyze warehouse;
analyze ship_mode;
analyze time_dim;
analyze reason;
analyze income_band;
analyze item;
analyze store;
analyze call_center;
analyze customer;
analyze web_site;
analyze store_returns;
analyze household_demographics;
analyze web_page;
analyze promotion;
analyze catalog_page;
analyze inventory;
analyze catalog_returns;
analyze web_returns;
analyze web_sales;
analyze catalog_sales;
analyze store_sales;6.2、集群参数配置
为了获取极致的性能，建议对相关参数按以下推荐值修改。其中有些参数用户无法自行设置，请联系ADB PG值班人员进行修改。
| 推荐参数配置 | 参数含义 | 设置方式 |
|---|---|---|
| set optimizer = on | 使用ORCA优化器 | session级别，在query文件开头添加即可。 |
| set statement_mem = 16777216 | 设置每个查询可使用内存大小为16G | session级别，在query文件开头添加即可。 |
| set max_statement_mem = 20971520 | 设置每个查询最大可使用内存大小为20G | 需要联系ADBPG值班人员修改，修改时需要重启。 |
| set gp_workfile_limit_per_segment = 0 | 不限制下盘文件大小 | 需要联系ADBPG值班人员修改，修改时需要重启。 |
如果使用本文所提供的99条TPC-DS SQL，请在每个Query文件开始处添加想要增加的配置，这里以第一个查询文件 q1.sql为例：
set optimizer = on;
set statement_mem = 16777216;
with customer_total_return as
(select sr_customer_sk as ctr_customer_sk
,sr_store_sk as ctr_store_sk
,sum(SR_FEE) as ctr_total_return
from store_returns
,date_dim
where sr_returned_date_sk = d_date_sk
and d_year =2000
group by sr_customer_sk
,sr_store_sk)
select c_customer_id
from customer_total_return ctr1
,store
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_store_sk = ctr2.ctr_store_sk)
and s_store_sk = ctr1.ctr_store_sk
and s_state = 'SD'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id
limit 100;6.3、执行查询
使用如下shell脚本测试，也可以通过psql等其他客户端逐条执行查询SQL。具体的99条SQL语句见本文最后。
total_cost=0
for i in {1..99}
do
echo "begin run Q${i}, query/q$i.sql , `date`"
begin_time=`date +%s.%N`
#psql -h ${实例连接地址} -p ${端口号} -U ${数据库用户} -f query/q${i}.sql > ./log/log_q${i}.out
rc=$?
end_time=`date +%s.%N`
cost=`echo "$end_time-$begin_time"|bc`
total_cost=`echo "$total_cost+$cost"|bc`
if [ $rc -ne 0 ] ; then
printf "run Q%s fail, cost: %.2f, totalCost: %.2f, `date`\n" $i $cost $total_cost
else
printf "run Q%s succ, cost: %.2f, totalCost: %.2f, `date`\n" $i $cost $total_cost
fi
done7、测试结果
| 查询 | 4c32G SSD节点 * 16节点 | 4c32G SSD节点 * 32节点 |
|---|---|---|
| 总体运行时间(单位:s) | 7256.95 | 4480.91 |
| Q1 | 10.84 | 6.46 |
| Q2 | 186.51 | 90.99 |
| Q3 | 15.07 | 7.73 |
| Q4 | 248.03 | 151.00 |
| Q5 | 36.74 | 19.04 |
| Q6 | 3.51 | 3.43 |
| Q7 | 21.57 | 11.62 |
| Q8 | 5.19 | 4.56 |
| Q9 | 190.55 | 107.06 |
| Q10 | 11.75 | 7.82 |
| Q11 | 163.67 | 108.16 |
| Q12 | 2.20 | 1.92 |
| Q13 | 38.58 | 21.14 |
| Q14 | 147.32 | 80.37 |
| Q15 | 4.96 | 3.85 |
| Q16 | 106.88 | 56.92 |
| Q17 | 17.62 | 19.46 |
| Q18 | 16.94 | 10.95 |
| Q19 | 5.98 | 4.02 |
| Q20 | 2.60 | 1.86 |
| Q21 | 3.33 | 2.16 |
| Q22 | 28.96 | 22.50 |
| Q23 | 520.05 | 301.01 |
| Q24 | 97.89 | 52.23 |
| Q25 | 14.69 | 13.42 |
| Q26 | 12.23 | 6.75 |
| Q27 | 22.13 | 11.91 |
| Q28 | 113.72 | 62.42 |
| Q29 | 34.24 | 21.01 |
| Q30 | 5.87 | 4.32 |
| Q31 | 23.84 | 18.55 |
| Q32 | 5.36 | 3.63 |
| Q33 | 6.53 | 6.80 |
| Q34 | 26.44 | 14.35 |
| Q35 | 25.74 | 17.87 |
| Q36 | 50.54 | 31.10 |
| Q37 | 24.28 | 13.84 |
| Q38 | 65.68 | 46.06 |
| Q39 | 13.75 | 7.11 |
| Q40 | 7.85 | 4.81 |
| Q41 | 0.33 | 0.48 |
| Q42 | 3.50 | 2.50 |
| Q43 | 30.71 | 15.16 |
| Q44 | 40.59 | 26.89 |
| Q45 | 4.90 | 3.92 |
| Q46 | 54.95 | 28.25 |
| Q47 | 102.36 | 54.14 |
| Q48 | 30.92 | 17.09 |
| Q49 | 10.01 | 7.17 |
| Q50 | 91.14 | 45.38 |
| Q51 | 94.95 | 59.32 |
| Q52 | 3.63 | 2.15 |
| Q53 | 14.51 | 8.48 |
| Q54 | 7.58 | 5.96 |
| Q55 | 3.11 | 2.18 |
| Q56 | 7.77 | 6.92 |
| Q57 | 54.48 | 29.51 |
| Q58 | 6.01 | 7.67 |
| Q59 | 261.91 | 129.07 |
| Q60 | 9.47 | 8.03 |
| Q61 | 8.40 | 6.40 |
| Q62 | 35.19 | 17.73 |
| Q63 | 14.39 | 8.48 |
| Q64 | 158.01 | 84.22 |
| Q65 | 99.88 | 55.36 |
| Q66 | 15.39 | 8.96 |
| Q67 | 1505.68 | 1242.13 |
| Q68 | 25.29 | 13.63 |
| Q69 | 11.12 | 7.75 |
| Q70 | 73.55 | 41.16 |
| Q71 | 12.65 | 8.66 |
| Q72 | 69.10 | 37.50 |
| Q73 | 16.61 | 9.18 |
| Q74 | 110.13 | 73.99 |
| Q75 | 115.83 | 56.23 |
| Q76 | 62.31 | 28.80 |
| Q77 | 7.53 | 4.86 |
| Q78 | 377.60 | 185.02 |
| Q79 | 63.53 | 33.06 |
| Q80 | 21.17 | 11.52 |
| Q81 | 5.58 | 3.23 |
| Q82 | 44.67 | 25.08 |
| Q83 | 6.38 | 7.07 |
| Q84 | 6.49 | 4.16 |
| Q85 | 17.91 | 12.90 |
| Q86 | 17.98 | 16.75 |
| Q87 | 66.96 | 46.37 |
| Q88 | 141.73 | 99.38 |
| Q89 | 18.47 | 10.42 |
| Q90 | 14.46 | 7.94 |
| Q91 | 2.34 | 2.33, |
| Q92 | 4.07 | 2.97 |
| Q93 | 97.05 | 48.21 |
| Q94 | 49.88 | 32.99 |
| Q95 | 506.75 | 266.26 |
| Q96 | 55.22 | 30.00 |
| Q97 | 151.87 | 53.30 |
| Q98 | 4.28 | 3.20 |
| Q99 | 69.02 | 33.23 |
附：99条TPC-DS SQL语句：
Query1:
with customer_total_return as
(select sr_customer_sk as ctr_customer_sk
,sr_store_sk as ctr_store_sk
,sum(SR_FEE) as ctr_total_return
from store_returns
,date_dim
where sr_returned_date_sk = d_date_sk
and d_year =2000
group by sr_customer_sk
,sr_store_sk)
select c_customer_id
from customer_total_return ctr1
,store
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_store_sk = ctr2.ctr_store_sk)
and s_store_sk = ctr1.ctr_store_sk
and s_state = 'SD'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id
limit 100;
Query2:
with wscs as
(select sold_date_sk
,sales_price
from (select ws_sold_date_sk sold_date_sk
,ws_ext_sales_price sales_price
from web_sales
union all
select cs_sold_date_sk sold_date_sk
,cs_ext_sales_price sales_price
from catalog_sales) as alias1),
wswscs as
(select d_week_seq,
sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales,
sum(case when (d_day_name='Tuesday') then sales_price else null end) tue_sales,
sum(case when (d_day_name='Wednesday') then sales_price else null end) wed_sales,
sum(case when (d_day_name='Thursday') then sales_price else null end) thu_sales,
sum(case when (d_day_name='Friday') then sales_price else null end) fri_sales,
sum(case when (d_day_name='Saturday') then sales_price else null end) sat_sales
from wscs
,date_dim
where d_date_sk = sold_date_sk
group by d_week_seq)
select d_week_seq1
,round(sun_sales1/sun_sales2,2)
,round(mon_sales1/mon_sales2,2)
,round(tue_sales1/tue_sales2,2)
,round(wed_sales1/wed_sales2,2)
,round(thu_sales1/thu_sales2,2)
,round(fri_sales1/fri_sales2,2)
,round(sat_sales1/sat_sales2,2)
from
(select wswscs.d_week_seq d_week_seq1
,sun_sales sun_sales1
,mon_sales mon_sales1
,tue_sales tue_sales1
,wed_sales wed_sales1
,thu_sales thu_sales1
,fri_sales fri_sales1
,sat_sales sat_sales1
from wswscs,date_dim
where date_dim.d_week_seq = wswscs.d_week_seq and
d_year = 2001) y,
(select wswscs.d_week_seq d_week_seq2
,sun_sales sun_sales2
,mon_sales mon_sales2
,tue_sales tue_sales2
,wed_sales wed_sales2
,thu_sales thu_sales2
,fri_sales fri_sales2
,sat_sales sat_sales2
from wswscs
,date_dim
where date_dim.d_week_seq = wswscs.d_week_seq and
d_year = 2001+1) z
where d_week_seq1=d_week_seq2-53
order by d_week_seq1;
Query3:
select dt.d_year
,item.i_brand_id brand_id
,item.i_brand brand
,sum(ss_ext_sales_price) sum_agg
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_manufact_id = 436
and dt.d_moy=12
group by dt.d_year
,item.i_brand
,item.i_brand_id
order by dt.d_year
,sum_agg desc
,brand_id
limit 100;
Query4:
with year_total as (
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum(((ss_ext_list_price-ss_ext_wholesale_cost-ss_ext_discount_amt)+ss_ext_sales_price)/2) year_total
,'s' sale_type
from customer
,store_sales
,date_dim
where c_customer_sk = ss_customer_sk
and ss_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum((((cs_ext_list_price-cs_ext_wholesale_cost-cs_ext_discount_amt)+cs_ext_sales_price)/2) ) year_total
,'c' sale_type
from customer
,catalog_sales
,date_dim
where c_customer_sk = cs_bill_customer_sk
and cs_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum((((ws_ext_list_price-ws_ext_wholesale_cost-ws_ext_discount_amt)+ws_ext_sales_price)/2) ) year_total
,'w' sale_type
from customer
,web_sales
,date_dim
where c_customer_sk = ws_bill_customer_sk
and ws_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
)
select
t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_email_address
from year_total t_s_firstyear
,year_total t_s_secyear
,year_total t_c_firstyear
,year_total t_c_secyear
,year_total t_w_firstyear
,year_total t_w_secyear
where t_s_secyear.customer_id = t_s_firstyear.customer_id
and t_s_firstyear.customer_id = t_c_secyear.customer_id
and t_s_firstyear.customer_id = t_c_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_secyear.customer_id
and t_s_firstyear.sale_type = 's'
and t_c_firstyear.sale_type = 'c'
and t_w_firstyear.sale_type = 'w'
and t_s_secyear.sale_type = 's'
and t_c_secyear.sale_type = 'c'
and t_w_secyear.sale_type = 'w'
and t_s_firstyear.dyear = 2001
and t_s_secyear.dyear = 2001+1
and t_c_firstyear.dyear = 2001
and t_c_secyear.dyear = 2001+1
and t_w_firstyear.dyear = 2001
and t_w_secyear.dyear = 2001+1
and t_s_firstyear.year_total > 0
and t_c_firstyear.year_total > 0
and t_w_firstyear.year_total > 0
and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
> case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
> case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
order by t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_email_address
limit 100;
Query5:
with ssr as
(select s_store_id,
sum(sales_price) as sales,
sum(profit) as profit,
sum(return_amt) as returns,
sum(net_loss) as profit_loss
from
( select ss_store_sk as store_sk,
ss_sold_date_sk as date_sk,
ss_ext_sales_price as sales_price,
ss_net_profit as profit,
cast(0 as decimal(7,2)) as return_amt,
cast(0 as decimal(7,2)) as net_loss
from store_sales
union all
select sr_store_sk as store_sk,
sr_returned_date_sk as date_sk,
cast(0 as decimal(7,2)) as sales_price,
cast(0 as decimal(7,2)) as profit,
sr_return_amt as return_amt,
sr_net_loss as net_loss
from store_returns
) salesreturns,
date_dim,
store
where date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '14 days')
and store_sk = s_store_sk
group by s_store_id)
,
csr as
(select cp_catalog_page_id,
sum(sales_price) as sales,
sum(profit) as profit,
sum(return_amt) as returns,
sum(net_loss) as profit_loss
from
( select cs_catalog_page_sk as page_sk,
cs_sold_date_sk as date_sk,
cs_ext_sales_price as sales_price,
cs_net_profit as profit,
cast(0 as decimal(7,2)) as return_amt,
cast(0 as decimal(7,2)) as net_loss
from catalog_sales
union all
select cr_catalog_page_sk as page_sk,
cr_returned_date_sk as date_sk,
cast(0 as decimal(7,2)) as sales_price,
cast(0 as decimal(7,2)) as profit,
cr_return_amount as return_amt,
cr_net_loss as net_loss
from catalog_returns
) salesreturns,
date_dim,
catalog_page
where date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '14 days')
and page_sk = cp_catalog_page_sk
group by cp_catalog_page_id)
,
wsr as
(select web_site_id,
sum(sales_price) as sales,
sum(profit) as profit,
sum(return_amt) as returns,
sum(net_loss) as profit_loss
from
( select ws_web_site_sk as wsr_web_site_sk,
ws_sold_date_sk as date_sk,
ws_ext_sales_price as sales_price,
ws_net_profit as profit,
cast(0 as decimal(7,2)) as return_amt,
cast(0 as decimal(7,2)) as net_loss
from web_sales
union all
select ws_web_site_sk as wsr_web_site_sk,
wr_returned_date_sk as date_sk,
cast(0 as decimal(7,2)) as sales_price,
cast(0 as decimal(7,2)) as profit,
wr_return_amt as return_amt,
wr_net_loss as net_loss
from web_returns left outer join web_sales on
( wr_item_sk = ws_item_sk
and wr_order_number = ws_order_number)
) salesreturns,
date_dim,
web_site
where date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '14 days')
and wsr_web_site_sk = web_site_sk
group by web_site_id)
select channel
, id
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
from
(select 'store channel' as channel
, 'store' || s_store_id as id
, sales
, returns
, (profit - profit_loss) as profit
from ssr
union all
select 'catalog channel' as channel
, 'catalog_page' || cp_catalog_page_id as id
, sales
, returns
, (profit - profit_loss) as profit
from csr
union all
select 'web channel' as channel
, 'web_site' || web_site_id as id
, sales
, returns
, (profit - profit_loss) as profit
from wsr
) x
group by rollup (channel, id)
order by channel
,id
limit 100;
Query6:
select a.ca_state state, count(*) cnt
from customer_address a
,customer c
,store_sales s
,date_dim d
,item i
where a.ca_address_sk = c.c_current_addr_sk
and c.c_customer_sk = s.ss_customer_sk
and s.ss_sold_date_sk = d.d_date_sk
and s.ss_item_sk = i.i_item_sk
and d.d_month_seq =
(select distinct (d_month_seq)
from date_dim
where d_year = 2000
and d_moy = 2 )
and i.i_current_price > 1.2 *
(select avg(j.i_current_price)
from item j
where j.i_category = i.i_category)
group by a.ca_state
having count(*) >= 10
order by cnt, a.ca_state
limit 100;
Query7:
select i_item_id,
avg(ss_quantity) agg1,
avg(ss_list_price) agg2,
avg(ss_coupon_amt) agg3,
avg(ss_sales_price) agg4
from store_sales, customer_demographics, date_dim, item, promotion
where ss_sold_date_sk = d_date_sk and
ss_item_sk = i_item_sk and
ss_cdemo_sk = cd_demo_sk and
ss_promo_sk = p_promo_sk and
cd_gender = 'F' and
cd_marital_status = 'W' and
cd_education_status = 'Primary' 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 100;
Query8:
select s_store_name
,sum(ss_net_profit)
from store_sales
,date_dim
,store,
(select ca_zip
from (
SELECT substr(ca_zip,1,5) ca_zip
FROM customer_address
WHERE substr(ca_zip,1,5) IN (
'89436','30868','65085','22977','83927','77557',
'58429','40697','80614','10502','32779',
'91137','61265','98294','17921','18427',
'21203','59362','87291','84093','21505',
'17184','10866','67898','25797','28055',
'18377','80332','74535','21757','29742',
'90885','29898','17819','40811','25990',
'47513','89531','91068','10391','18846',
'99223','82637','41368','83658','86199',
'81625','26696','89338','88425','32200',
'81427','19053','77471','36610','99823',
'43276','41249','48584','83550','82276',
'18842','78890','14090','38123','40936',
'34425','19850','43286','80072','79188',
'54191','11395','50497','84861','90733',
'21068','57666','37119','25004','57835',
'70067','62878','95806','19303','18840',
'19124','29785','16737','16022','49613',
'89977','68310','60069','98360','48649',
'39050','41793','25002','27413','39736',
'47208','16515','94808','57648','15009',
'80015','42961','63982','21744','71853',
'81087','67468','34175','64008','20261',
'11201','51799','48043','45645','61163',
'48375','36447','57042','21218','41100',
'89951','22745','35851','83326','61125',
'78298','80752','49858','52940','96976',
'63792','11376','53582','18717','90226',
'50530','94203','99447','27670','96577',
'57856','56372','16165','23427','54561',
'28806','44439','22926','30123','61451',
'92397','56979','92309','70873','13355',
'21801','46346','37562','56458','28286',
'47306','99555','69399','26234','47546',
'49661','88601','35943','39936','25632',
'24611','44166','56648','30379','59785',
'11110','14329','93815','52226','71381',
'13842','25612','63294','14664','21077',
'82626','18799','60915','81020','56447',
'76619','11433','13414','42548','92713',
'70467','30884','47484','16072','38936',
'13036','88376','45539','35901','19506',
'65690','73957','71850','49231','14276',
'20005','18384','76615','11635','38177',
'55607','41369','95447','58581','58149',
'91946','33790','76232','75692','95464',
'22246','51061','56692','53121','77209',
'15482','10688','14868','45907','73520',
'72666','25734','17959','24677','66446',
'94627','53535','15560','41967','69297',
'11929','59403','33283','52232','57350',
'43933','40921','36635','10827','71286',
'19736','80619','25251','95042','15526',
'36496','55854','49124','81980','35375',
'49157','63512','28944','14946','36503',
'54010','18767','23969','43905','66979',
'33113','21286','58471','59080','13395',
'79144','70373','67031','38360','26705',
'50906','52406','26066','73146','15884',
'31897','30045','61068','45550','92454',
'13376','14354','19770','22928','97790',
'50723','46081','30202','14410','20223',
'88500','67298','13261','14172','81410',
'93578','83583','46047','94167','82564',
'21156','15799','86709','37931','74703',
'83103','23054','70470','72008','49247',
'91911','69998','20961','70070','63197',
'54853','88191','91830','49521','19454',
'81450','89091','62378','25683','61869',
'51744','36580','85778','36871','48121',
'28810','83712','45486','67393','26935',
'42393','20132','55349','86057','21309',
'80218','10094','11357','48819','39734',
'40758','30432','21204','29467','30214',
'61024','55307','74621','11622','68908',
'33032','52868','99194','99900','84936',
'69036','99149','45013','32895','59004',
'32322','14933','32936','33562','72550',
'27385','58049','58200','16808','21360',
'32961','18586','79307','15492')
intersect
select ca_zip
from (SELECT substr(ca_zip,1,5) ca_zip,count(*) cnt
FROM customer_address, customer
WHERE ca_address_sk = c_current_addr_sk and
c_preferred_cust_flag='Y'
group by ca_zip
having count(*) > 10)A1)A2) V1
where ss_store_sk = s_store_sk
and ss_sold_date_sk = d_date_sk
and d_qoy = 1 and d_year = 2002
and (substr(s_zip,1,2) = substr(V1.ca_zip,1,2))
group by s_store_name
order by s_store_name
limit 100;
Query9:
select case when (select count(*)
from store_sales
where ss_quantity between 1 and 20) > 409437
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 1 and 20)
else (select avg(ss_net_paid)
from store_sales
where ss_quantity between 1 and 20) end bucket1 ,
case when (select count(*)
from store_sales
where ss_quantity between 21 and 40) > 4595804
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 21 and 40)
else (select avg(ss_net_paid)
from store_sales
where ss_quantity between 21 and 40) end bucket2,
case when (select count(*)
from store_sales
where ss_quantity between 41 and 60) > 1333710
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 41 and 60)
else (select avg(ss_net_paid)
from store_sales
where ss_quantity between 41 and 60) end bucket3,
case when (select count(*)
from store_sales
where ss_quantity between 61 and 80) > 2361102
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 61 and 80)
else (select avg(ss_net_paid)
from store_sales
where ss_quantity between 61 and 80) end bucket4,
case when (select count(*)
from store_sales
where ss_quantity between 81 and 100) > 1517817
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 81 and 100)
else (select avg(ss_net_paid)
from store_sales
where ss_quantity between 81 and 100) end bucket5
from reason
where r_reason_sk = 1
;
Query10:
select
cd_gender,
cd_marital_status,
cd_education_status,
count(*) cnt1,
cd_purchase_estimate,
count(*) cnt2,
cd_credit_rating,
count(*) cnt3,
cd_dep_count,
count(*) cnt4,
cd_dep_employed_count,
count(*) cnt5,
cd_dep_college_count,
count(*) cnt6
from
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
ca_county in ('Walker County','Richland County','Gaines County','Douglas County','Dona Ana County') and
cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
ss_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 4 and 4+3) and
(exists (select *
from web_sales,date_dim
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 4 ANd 4+3) or
exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 4 and 4+3))
group by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
order by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
limit 100;
Query11:
with year_total as (
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum(ss_ext_list_price-ss_ext_discount_amt) year_total
,'s' sale_type
from customer
,store_sales
,date_dim
where c_customer_sk = ss_customer_sk
and ss_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum(ws_ext_list_price-ws_ext_discount_amt) year_total
,'w' sale_type
from customer
,web_sales
,date_dim
where c_customer_sk = ws_bill_customer_sk
and ws_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
)
select
t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_email_address
from year_total t_s_firstyear
,year_total t_s_secyear
,year_total t_w_firstyear
,year_total t_w_secyear
where t_s_secyear.customer_id = t_s_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_secyear.customer_id
and t_s_firstyear.customer_id = t_w_firstyear.customer_id
and t_s_firstyear.sale_type = 's'
and t_w_firstyear.sale_type = 'w'
and t_s_secyear.sale_type = 's'
and t_w_secyear.sale_type = 'w'
and t_s_firstyear.dyear = 2001
and t_s_secyear.dyear = 2001+1
and t_w_firstyear.dyear = 2001
and t_w_secyear.dyear = 2001+1
and t_s_firstyear.year_total > 0
and t_w_firstyear.year_total > 0
and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else 0.0 end
> case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else 0.0 end
order by t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_email_address
limit 100;
Query12:
select i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
,sum(ws_ext_sales_price) as itemrevenue
,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
(partition by i_class) as revenueratio
from
web_sales
,item
,date_dim
where
ws_item_sk = i_item_sk
and i_category in ('Jewelry', 'Sports', 'Books')
and ws_sold_date_sk = d_date_sk
and d_date between cast('2001-01-12' as date)
and (cast('2001-01-12' as date) + interval '30 days')
group by
i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
order by
i_category
,i_class
,i_item_id
,i_item_desc
,revenueratio
limit 100;
Query13:
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 = 'D'
and cd_education_status = '2 yr Degree'
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 = 'Secondary'
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 = 'W'
and cd_education_status = 'Advanced Degree'
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 ('CO', 'IL', 'MN')
and ss_net_profit between 100 and 200
) or
(ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('OH', 'MT', 'NM')
and ss_net_profit between 150 and 300
) or
(ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('TX', 'MO', 'MI')
and ss_net_profit between 50 and 250
))
;
Query14:
with cross_items as
(select i_item_sk ss_item_sk
from item,
(select iss.i_brand_id brand_id
,iss.i_class_id class_id
,iss.i_category_id category_id
from store_sales
,item iss
,date_dim d1
where ss_item_sk = iss.i_item_sk
and ss_sold_date_sk = d1.d_date_sk
and d1.d_year between 1998 AND 1998 + 2
intersect
select ics.i_brand_id
,ics.i_class_id
,ics.i_category_id
from catalog_sales
,item ics
,date_dim d2
where cs_item_sk = ics.i_item_sk
and cs_sold_date_sk = d2.d_date_sk
and d2.d_year between 1998 AND 1998 + 2
intersect
select iws.i_brand_id
,iws.i_class_id
,iws.i_category_id
from web_sales
,item iws
,date_dim d3
where ws_item_sk = iws.i_item_sk
and ws_sold_date_sk = d3.d_date_sk
and d3.d_year between 1998 AND 1998 + 2) as alias1
where i_brand_id = brand_id
and i_class_id = class_id
and i_category_id = category_id
),
avg_sales as
(select avg(quantity*list_price) average_sales
from (select ss_quantity quantity
,ss_list_price list_price
from store_sales
,date_dim
where ss_sold_date_sk = d_date_sk
and d_year between 1998 and 1998 + 2
union all
select cs_quantity quantity
,cs_list_price list_price
from catalog_sales
,date_dim
where cs_sold_date_sk = d_date_sk
and d_year between 1998 and 1998 + 2
union all
select ws_quantity quantity
,ws_list_price list_price
from web_sales
,date_dim
where ws_sold_date_sk = d_date_sk
and d_year between 1998 and 1998 + 2) x)
select channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales)
from(
select 'store' channel, i_brand_id,i_class_id
,i_category_id,sum(ss_quantity*ss_list_price) sales
, count(*) number_sales
from store_sales
,item
,date_dim
where ss_item_sk in (select ss_item_sk from cross_items)
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 1998+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)
union all
select 'catalog' channel, i_brand_id,i_class_id,i_category_id, sum(cs_quantity*cs_list_price) sales, count(*) number_sales
from catalog_sales
,item
,date_dim
where cs_item_sk in (select ss_item_sk from cross_items)
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 1998+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales)
union all
select 'web' channel, i_brand_id,i_class_id,i_category_id, sum(ws_quantity*ws_list_price) sales , count(*) number_sales
from web_sales
,item
,date_dim
where ws_item_sk in (select ss_item_sk from cross_items)
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 1998+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(ws_quantity*ws_list_price) > (select average_sales from avg_sales)
) y
group by rollup (channel, i_brand_id,i_class_id,i_category_id)
order by channel,i_brand_id,i_class_id,i_category_id
limit 100;
Query15:
select ca_zip
,sum(cs_sales_price)
from catalog_sales
,customer
,customer_address
,date_dim
where cs_bill_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475',
'85392', '85460', '80348', '81792')
or ca_state in ('CA','WA','GA')
or cs_sales_price > 500)
and cs_sold_date_sk = d_date_sk
and d_qoy = 2 and d_year = 2000
group by ca_zip
order by ca_zip
limit 100;
Query16:
select
count(distinct cs_order_number) as "order count"
,sum(cs_ext_ship_cost) as "total shipping cost"
,sum(cs_net_profit) as "total net profit"
from
catalog_sales cs1
,date_dim
,customer_address
,call_center
where
d_date between '1999-4-01' and
(cast('1999-4-01' as date) + interval '60 days')
and cs1.cs_ship_date_sk = d_date_sk
and cs1.cs_ship_addr_sk = ca_address_sk
and ca_state = 'GA'
and cs1.cs_call_center_sk = cc_call_center_sk
and cc_county in ('Daviess County','Franklin Parish','Barrow County','Luce County',
'Fairfield County'
)
and exists (select *
from catalog_sales cs2
where cs1.cs_order_number = cs2.cs_order_number
and cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk)
and not exists(select *
from catalog_returns cr1
where cs1.cs_order_number = cr1.cr_order_number)
order by count(distinct cs_order_number)
limit 100;
Query17:
select i_item_id
,i_item_desc
,s_state
,count(ss_quantity) as store_sales_quantitycount
,avg(ss_quantity) as store_sales_quantityave
,stddev_samp(ss_quantity) as store_sales_quantitystdev
,stddev_samp(ss_quantity)/avg(ss_quantity) as store_sales_quantitycov
,count(sr_return_quantity) as store_returns_quantitycount
,avg(sr_return_quantity) as store_returns_quantityave
,stddev_samp(sr_return_quantity) as store_returns_quantitystdev
,stddev_samp(sr_return_quantity)/avg(sr_return_quantity) as store_returns_quantitycov
,count(cs_quantity) as catalog_sales_quantitycount ,avg(cs_quantity) as catalog_sales_quantityave
,stddev_samp(cs_quantity) as catalog_sales_quantitystdev
,stddev_samp(cs_quantity)/avg(cs_quantity) as catalog_sales_quantitycov
from store_sales
,store_returns
,catalog_sales
,date_dim d1
,date_dim d2
,date_dim d3
,store
,item
where d1.d_quarter_name = '1998Q1'
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and ss_customer_sk = sr_customer_sk
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
and d2.d_quarter_name in ('1998Q1','1998Q2','1998Q3')
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
and d3.d_quarter_name in ('1998Q1','1998Q2','1998Q3')
group by i_item_id
,i_item_desc
,s_state
order by i_item_id
,i_item_desc
,s_state
limit 100;
Query18:
select i_item_id,
ca_country,
ca_state,
ca_county,
avg( cast(cs_quantity as decimal(12,2))) agg1,
avg( cast(cs_list_price as decimal(12,2))) agg2,
avg( cast(cs_coupon_amt as decimal(12,2))) agg3,
avg( cast(cs_sales_price as decimal(12,2))) agg4,
avg( cast(cs_net_profit as decimal(12,2))) agg5,
avg( cast(c_birth_year as decimal(12,2))) agg6,
avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7
from catalog_sales, customer_demographics cd1,
customer_demographics cd2, customer, customer_address, date_dim, item
where cs_sold_date_sk = d_date_sk and
cs_item_sk = i_item_sk and
cs_bill_cdemo_sk = cd1.cd_demo_sk and
cs_bill_customer_sk = c_customer_sk and
cd1.cd_gender = 'M' and
cd1.cd_education_status = 'College' and
c_current_cdemo_sk = cd2.cd_demo_sk and
c_current_addr_sk = ca_address_sk and
c_birth_month in (9,5,12,4,1,10) and
d_year = 2001 and
ca_state in ('ND','WI','AL'
,'NC','OK','MS','TN')
group by rollup (i_item_id, ca_country, ca_state, ca_county)
order by ca_country,
ca_state,
ca_county,
i_item_id
limit 100;
Query19:
select i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact,
sum(ss_ext_sales_price) ext_price
from date_dim, store_sales, item,customer,customer_address,store
where d_date_sk = ss_sold_date_sk
and ss_item_sk = i_item_sk
and i_manager_id=7
and d_moy=11
and d_year=1999
and ss_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
and substr(ca_zip,1,5) <> substr(s_zip,1,5)
and ss_store_sk = s_store_sk
group by i_brand
,i_brand_id
,i_manufact_id
,i_manufact
order by ext_price desc
,i_brand
,i_brand_id
,i_manufact_id
,i_manufact
limit 100 ;
Query20:
select i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
,sum(cs_ext_sales_price) as itemrevenue
,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over
(partition by i_class) as revenueratio
from catalog_sales
,item
,date_dim
where cs_item_sk = i_item_sk
and i_category in ('Jewelry', 'Sports', 'Books')
and cs_sold_date_sk = d_date_sk
and d_date between cast('2001-01-12' as date)
and (cast('2001-01-12' as date) + interval '30 days')
group by i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
order by i_category
,i_class
,i_item_id
,i_item_desc
,revenueratio
limit 100;
Query21:
select *
from(select w_warehouse_name
,i_item_id
,sum(case when (cast(d_date as date) < cast ('1998-04-08' as date))
then inv_quantity_on_hand
else 0 end) as inv_before
,sum(case when (cast(d_date as date) >= cast ('1998-04-08' as date))
then inv_quantity_on_hand
else 0 end) as inv_after
from inventory
,warehouse
,item
,date_dim
where i_current_price between 0.99 and 1.49
and i_item_sk = inv_item_sk
and inv_warehouse_sk = w_warehouse_sk
and inv_date_sk = d_date_sk
and d_date between (cast ('1998-04-08' as date) - interval '30 days')
and (cast ('1998-04-08' as date) + interval '30 days')
group by w_warehouse_name, i_item_id) x
where (case when inv_before > 0
then inv_after / inv_before
else null
end) between 2.0/3.0 and 3.0/2.0
order by w_warehouse_name
,i_item_id
limit 100;
Query22:
select i_product_name
,i_brand
,i_class
,i_category
,avg(inv_quantity_on_hand) qoh
from inventory
,date_dim
,item
where inv_date_sk=d_date_sk
and inv_item_sk=i_item_sk
and d_month_seq between 1212 and 1212 + 11
group by rollup(i_product_name
,i_brand
,i_class
,i_category)
order by qoh, i_product_name, i_brand, i_class, i_category
limit 100;
Query23:
with frequent_ss_items as
(select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
from store_sales
,date_dim
,item
where ss_sold_date_sk = d_date_sk
and ss_item_sk = i_item_sk
and d_year in (1999,1999+1,1999+2,1999+3)
group by substr(i_item_desc,1,30),i_item_sk,d_date
having count(*) >4),
max_store_sales as
(select max(csales) tpcds_cmax
from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
from store_sales
,customer
,date_dim
where ss_customer_sk = c_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (1999,1999+1,1999+2,1999+3)
group by c_customer_sk) as alias1),
best_ss_customer as
(select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
from store_sales
,customer
where ss_customer_sk = c_customer_sk
group by c_customer_sk
having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select
*
from
max_store_sales))
select sum(sales)
from (select cs_quantity*cs_list_price sales
from catalog_sales
,date_dim
where d_year = 1999
and d_moy = 1
and cs_sold_date_sk = d_date_sk
and cs_item_sk in (select item_sk from frequent_ss_items)
and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
union all
select ws_quantity*ws_list_price sales
from web_sales
,date_dim
where d_year = 1999
and d_moy = 1
and ws_sold_date_sk = d_date_sk
and ws_item_sk in (select item_sk from frequent_ss_items)
and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as alias2
limit 100;
Query24:
with ssales as
(select c_last_name
,c_first_name
,s_store_name
,ca_state
,s_state
,i_color
,i_current_price
,i_manager_id
,i_units
,i_size
,sum(ss_sales_price) netpaid
from store_sales
,store_returns
,store
,item
,customer
,customer_address
where ss_ticket_number = sr_ticket_number
and ss_item_sk = sr_item_sk
and ss_customer_sk = c_customer_sk
and ss_item_sk = i_item_sk
and ss_store_sk = s_store_sk
and c_current_addr_sk = ca_address_sk
and c_birth_country <> upper(ca_country)
and s_zip = ca_zip
and s_market_id=7
group by c_last_name
,c_first_name
,s_store_name
,ca_state
,s_state
,i_color
,i_current_price
,i_manager_id
,i_units
,i_size)
select c_last_name
,c_first_name
,s_store_name
,sum(netpaid) paid
from ssales
where i_color = 'orchid'
group by c_last_name
,c_first_name
,s_store_name
having sum(netpaid) > (select 0.05*avg(netpaid)
from ssales)
order by c_last_name
,c_first_name
,s_store_name
;
Query25:
select
i_item_id
,i_item_desc
,s_store_id
,s_store_name
,sum(ss_net_profit) as store_sales_profit
,sum(sr_net_loss) as store_returns_loss
,sum(cs_net_profit) as catalog_sales_profit
from
store_sales
,store_returns
,catalog_sales
,date_dim d1
,date_dim d2
,date_dim d3
,store
,item
where
d1.d_moy = 4
and d1.d_year = 2000
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and ss_customer_sk = sr_customer_sk
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
and d2.d_moy between 4 and 10
and d2.d_year = 2000
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
and d3.d_moy between 4 and 10
and d3.d_year = 2000
group by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
order by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
limit 100;
Query26:
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 = 'F' and
cd_marital_status = 'W' and
cd_education_status = 'Primary' 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 100;
Query27:
select i_item_id,
s_state, grouping(s_state) g_state,
avg(ss_quantity) agg1,
avg(ss_list_price) agg2,
avg(ss_coupon_amt) agg3,
avg(ss_sales_price) agg4
from store_sales, customer_demographics, date_dim, store, item
where ss_sold_date_sk = d_date_sk and
ss_item_sk = i_item_sk and
ss_store_sk = s_store_sk and
ss_cdemo_sk = cd_demo_sk and
cd_gender = 'M' and
cd_marital_status = 'W' and
cd_education_status = 'College' and
d_year = 2002 and
s_state in ('MO','LA', 'GA', 'MI', 'SC', 'OH')
group by rollup (i_item_id, s_state)
order by i_item_id
,s_state
limit 100;
Query28:
select *
from (select avg(ss_list_price) B1_LP
,count(ss_list_price) B1_CNT
,count(distinct ss_list_price) B1_CNTD
from store_sales
where ss_quantity between 0 and 5
and (ss_list_price between 11 and 11+10
or ss_coupon_amt between 460 and 460+1000
or ss_wholesale_cost between 14 and 14+20)) B1,
(select avg(ss_list_price) B2_LP
,count(ss_list_price) B2_CNT
,count(distinct ss_list_price) B2_CNTD
from store_sales
where ss_quantity between 6 and 10
and (ss_list_price between 91 and 91+10
or ss_coupon_amt between 1430 and 1430+1000
or ss_wholesale_cost between 32 and 32+20)) B2,
(select avg(ss_list_price) B3_LP
,count(ss_list_price) B3_CNT
,count(distinct ss_list_price) B3_CNTD
from store_sales
where ss_quantity between 11 and 15
and (ss_list_price between 66 and 66+10
or ss_coupon_amt between 920 and 920+1000
or ss_wholesale_cost between 4 and 4+20)) B3,
(select avg(ss_list_price) B4_LP
,count(ss_list_price) B4_CNT
,count(distinct ss_list_price) B4_CNTD
from store_sales
where ss_quantity between 16 and 20
and (ss_list_price between 142 and 142+10
or ss_coupon_amt between 3054 and 3054+1000
or ss_wholesale_cost between 80 and 80+20)) B4,
(select avg(ss_list_price) B5_LP
,count(ss_list_price) B5_CNT
,count(distinct ss_list_price) B5_CNTD
from store_sales
where ss_quantity between 21 and 25
and (ss_list_price between 135 and 135+10
or ss_coupon_amt between 14180 and 14180+1000
or ss_wholesale_cost between 38 and 38+20)) B5,
(select avg(ss_list_price) B6_LP
,count(ss_list_price) B6_CNT
,count(distinct ss_list_price) B6_CNTD
from store_sales
where ss_quantity between 26 and 30
and (ss_list_price between 28 and 28+10
or ss_coupon_amt between 2513 and 2513+1000
or ss_wholesale_cost between 42 and 42+20)) B6
limit 100;
Query29:
select
i_item_id
,i_item_desc
,s_store_id
,s_store_name
,sum(ss_quantity) as store_sales_quantity
,sum(sr_return_quantity) as store_returns_quantity
,sum(cs_quantity) as catalog_sales_quantity
from
store_sales
,store_returns
,catalog_sales
,date_dim d1
,date_dim d2
,date_dim d3
,store
,item
where
d1.d_moy = 4
and d1.d_year = 1999
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and ss_customer_sk = sr_customer_sk
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
and d2.d_moy between 4 and 4 + 3
and d2.d_year = 1999
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
and d3.d_year in (1999,1999+1,1999+2)
group by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
order by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
limit 100;
Query30:
with customer_total_return as
(select wr_returning_customer_sk as ctr_customer_sk
,ca_state as ctr_state,
sum(wr_return_amt) as ctr_total_return
from web_returns
,date_dim
,customer_address
where wr_returned_date_sk = d_date_sk
and d_year =2002
and wr_returning_addr_sk = ca_address_sk
group by wr_returning_customer_sk
,ca_state)
select c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
,c_last_review_date,ctr_total_return
from customer_total_return ctr1
,customer_address
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_state = ctr2.ctr_state)
and ca_address_sk = c_current_addr_sk
and ca_state = 'IL'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
,c_last_review_date,ctr_total_return
limit 100;
Query31:
with ss as
(select ca_county,d_qoy, d_year,sum(ss_ext_sales_price) as store_sales
from store_sales,date_dim,customer_address
where ss_sold_date_sk = d_date_sk
and ss_addr_sk=ca_address_sk
group by ca_county,d_qoy, d_year),
ws as
(select ca_county,d_qoy, d_year,sum(ws_ext_sales_price) as web_sales
from web_sales,date_dim,customer_address
where ws_sold_date_sk = d_date_sk
and ws_bill_addr_sk=ca_address_sk
group by ca_county,d_qoy, d_year)
select
ss1.ca_county
,ss1.d_year
,ws2.web_sales/ws1.web_sales web_q1_q2_increase
,ss2.store_sales/ss1.store_sales store_q1_q2_increase
,ws3.web_sales/ws2.web_sales web_q2_q3_increase
,ss3.store_sales/ss2.store_sales store_q2_q3_increase
from
ss ss1
,ss ss2
,ss ss3
,ws ws1
,ws ws2
,ws ws3
where
ss1.d_qoy = 1
and ss1.d_year = 2000
and ss1.ca_county = ss2.ca_county
and ss2.d_qoy = 2
and ss2.d_year = 2000
and ss2.ca_county = ss3.ca_county
and ss3.d_qoy = 3
and ss3.d_year = 2000
and ss1.ca_county = ws1.ca_county
and ws1.d_qoy = 1
and ws1.d_year = 2000
and ws1.ca_county = ws2.ca_county
and ws2.d_qoy = 2
and ws2.d_year = 2000
and ws1.ca_county = ws3.ca_county
and ws3.d_qoy = 3
and ws3.d_year =2000
and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end
> case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end
and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end
> case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end
order by ss1.d_year;
Query32:
select sum(cs_ext_discount_amt) as "excess discount amount"
from
catalog_sales
,item
,date_dim
where
i_manufact_id = 269
and i_item_sk = cs_item_sk
and d_date between '1998-03-18' and
(cast('1998-03-18' as date) + interval '90 days')
and d_date_sk = cs_sold_date_sk
and cs_ext_discount_amt
> (
select
1.3 * avg(cs_ext_discount_amt)
from
catalog_sales
,date_dim
where
cs_item_sk = i_item_sk
and d_date between '1998-03-18' and
(cast('1998-03-18' as date) + interval '90 days')
and d_date_sk = cs_sold_date_sk
)
limit 100;
Query33:
with ss as (
select
i_manufact_id,sum(ss_ext_sales_price) total_sales
from
store_sales,
date_dim,
customer_address,
item
where
i_manufact_id in (select
i_manufact_id
from
item
where i_category in ('Books'))
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 1999
and d_moy = 3
and ss_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_manufact_id),
cs as (
select
i_manufact_id,sum(cs_ext_sales_price) total_sales
from
catalog_sales,
date_dim,
customer_address,
item
where
i_manufact_id in (select
i_manufact_id
from
item
where i_category in ('Books'))
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 1999
and d_moy = 3
and cs_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_manufact_id),
ws as (
select
i_manufact_id,sum(ws_ext_sales_price) total_sales
from
web_sales,
date_dim,
customer_address,
item
where
i_manufact_id in (select
i_manufact_id
from
item
where i_category in ('Books'))
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 1999
and d_moy = 3
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_manufact_id)
select i_manufact_id ,sum(total_sales) total_sales
from (select * from ss
union all
select * from cs
union all
select * from ws) tmp1
group by i_manufact_id
order by total_sales
limit 100;
Query34:
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 3 or date_dim.d_dom between 25 and 28)
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) > 1.2
and date_dim.d_year in (1999,1999+1,1999+2)
and store.s_county in ('Daviess County','Franklin Parish','Barrow County','Luce County',
'Fairfield County','Richland County','Ziebach County','Walker County')
group by ss_ticket_number,ss_customer_sk) dn,customer
where ss_customer_sk = c_customer_sk
and cnt between 15 and 20
order by c_last_name,c_first_name,c_salutation,c_preferred_cust_flag desc, ss_ticket_number;
Query35:
select
ca_state,
cd_gender,
cd_marital_status,
cd_dep_count,
count(*) cnt1,
avg(cd_dep_count),
max(cd_dep_count),
sum(cd_dep_count),
cd_dep_employed_count,
count(*) cnt2,
avg(cd_dep_employed_count),
max(cd_dep_employed_count),
sum(cd_dep_employed_count),
cd_dep_college_count,
count(*) cnt3,
avg(cd_dep_college_count),
max(cd_dep_college_count),
sum(cd_dep_college_count)
from
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
ss_sold_date_sk = d_date_sk and
d_year = 1999 and
d_qoy < 4) and
(exists (select *
from web_sales,date_dim
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 1999 and
d_qoy < 4) or
exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
d_year = 1999 and
d_qoy < 4))
group by ca_state,
cd_gender,
cd_marital_status,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
order by ca_state,
cd_gender,
cd_marital_status,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
limit 100;
Query36:
select
sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin
,i_category
,i_class
,grouping(i_category)+grouping(i_class) as lochierarchy
,rank() over (
partition by grouping(i_category)+grouping(i_class),
case when grouping(i_class) = 0 then i_category end
order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent
from
store_sales
,date_dim d1
,item
,store
where
d1.d_year = 2000
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and s_state in ('MO','LA','GA','MI',
'SC','OH','SD','AL')
group by rollup(i_category,i_class)
order by
lochierarchy desc
,case when grouping(i_category)+grouping(i_class) = 0 then i_category end
,rank_within_parent
limit 100;
Query37:
select i_item_id
,i_item_desc
,i_current_price
from item, inventory, date_dim, catalog_sales
where i_current_price between 22 and 22 + 30
and inv_item_sk = i_item_sk
and d_date_sk=inv_date_sk
and d_date between cast('2001-06-02' as date) and (cast('2001-06-02' as date) + interval '60 days')
and i_manufact_id in (678,964,918,849)
and inv_quantity_on_hand between 100 and 500
and cs_item_sk = i_item_sk
group by i_item_id,i_item_desc,i_current_price
order by i_item_id
limit 100;
Query38:
select count(*) from (
select distinct c_last_name, c_first_name, d_date
from store_sales, date_dim, customer
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_customer_sk = customer.c_customer_sk
and d_month_seq between 1212 and 1212 + 11
intersect
select distinct c_last_name, c_first_name, d_date
from catalog_sales, date_dim, customer
where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1212 and 1212 + 11
intersect
select distinct c_last_name, c_first_name, d_date
from web_sales, date_dim, customer
where web_sales.ws_sold_date_sk = date_dim.d_date_sk
and web_sales.ws_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1212 and 1212 + 11
) hot_cust
limit 100;
Query39:
with inv as
(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
,stdev,mean, case mean when 0 then null else stdev/mean end cov
from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean
from inventory
,item
,warehouse
,date_dim
where inv_item_sk = i_item_sk
and inv_warehouse_sk = w_warehouse_sk
and inv_date_sk = d_date_sk
and d_year =1998
group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo
where case mean when 0 then 0 else stdev/mean end > 1)
select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov
,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov
from inv inv1,inv inv2
where inv1.i_item_sk = inv2.i_item_sk
and inv1.w_warehouse_sk = inv2.w_warehouse_sk
and inv1.d_moy=4
and inv2.d_moy=4+1
order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
,inv2.d_moy,inv2.mean, inv2.cov
;
Query40:
select
w_state
,i_item_id
,sum(case when (cast(d_date as date) < cast ('1998-04-08' as date))
then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before
,sum(case when (cast(d_date as date) >= cast ('1998-04-08' as date))
then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after
from
catalog_sales left outer join catalog_returns on
(cs_order_number = cr_order_number
and cs_item_sk = cr_item_sk)
,warehouse
,item
,date_dim
where
i_current_price between 0.99 and 1.49
and i_item_sk = cs_item_sk
and cs_warehouse_sk = w_warehouse_sk
and cs_sold_date_sk = d_date_sk
and d_date between (cast ('1998-04-08' as date) - interval '30 days')
and (cast ('1998-04-08' as date) + interval '30 days')
group by
w_state,i_item_id
order by w_state,i_item_id
limit 100;
Query41:
select distinct(i_product_name)
from item i1
where i_manufact_id between 742 and 742+40
and (select count(*) as item_cnt
from item
where (i_manufact = i1.i_manufact and
((i_category = 'Women' and
(i_color = 'orchid' or i_color = 'papaya') and
(i_units = 'Pound' or i_units = 'Lb') and
(i_size = 'petite' or i_size = 'medium')
) or
(i_category = 'Women' and
(i_color = 'burlywood' or i_color = 'navy') and
(i_units = 'Bundle' or i_units = 'Each') and
(i_size = 'N/A' or i_size = 'extra large')
) or
(i_category = 'Men' and
(i_color = 'bisque' or i_color = 'azure') and
(i_units = 'N/A' or i_units = 'Tsp') and
(i_size = 'small' or i_size = 'large')
) or
(i_category = 'Men' and
(i_color = 'chocolate' or i_color = 'cornflower') and
(i_units = 'Bunch' or i_units = 'Gross') and
(i_size = 'petite' or i_size = 'medium')
))) or
(i_manufact = i1.i_manufact and
((i_category = 'Women' and
(i_color = 'salmon' or i_color = 'midnight') and
(i_units = 'Oz' or i_units = 'Box') and
(i_size = 'petite' or i_size = 'medium')
) or
(i_category = 'Women' and
(i_color = 'snow' or i_color = 'steel') and
(i_units = 'Carton' or i_units = 'Tbl') and
(i_size = 'N/A' or i_size = 'extra large')
) or
(i_category = 'Men' and
(i_color = 'purple' or i_color = 'gainsboro') and
(i_units = 'Dram' or i_units = 'Unknown') and
(i_size = 'small' or i_size = 'large')
) or
(i_category = 'Men' and
(i_color = 'metallic' or i_color = 'forest') and
(i_units = 'Gram' or i_units = 'Ounce') and
(i_size = 'petite' or i_size = 'medium')
)))) > 0
order by i_product_name
limit 100;
Query42:
select dt.d_year
,item.i_category_id
,item.i_category
,sum(ss_ext_sales_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=12
and dt.d_year=1998
group by dt.d_year
,item.i_category_id
,item.i_category
order by sum(ss_ext_sales_price) desc,dt.d_year
,item.i_category_id
,item.i_category
limit 100 ;
Query43:
select s_store_name, s_store_id,
sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
from date_dim, store_sales, store
where d_date_sk = ss_sold_date_sk and
s_store_sk = ss_store_sk and
s_gmt_offset = -6 and
d_year = 1998
group by s_store_name, s_store_id
order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales
limit 100;
Query44:
select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing
from(select *
from (select item_sk,rank() over (order by rank_col asc) rnk
from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
from store_sales ss1
where ss_store_sk = 50
group by ss_item_sk
having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
from store_sales
where ss_store_sk = 50
and ss_hdemo_sk is null
group by ss_store_sk))V1)V11
where rnk < 11) asceding,
(select *
from (select item_sk,rank() over (order by rank_col desc) rnk
from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
from store_sales ss1
where ss_store_sk = 50
group by ss_item_sk
having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
from store_sales
where ss_store_sk = 50
and ss_hdemo_sk is null
group by ss_store_sk))V2)V21
where rnk < 11) descending,
item i1,
item i2
where asceding.rnk = descending.rnk
and i1.i_item_sk=asceding.item_sk
and i2.i_item_sk=descending.item_sk
order by asceding.rnk
limit 100;
Query45:
select ca_zip, ca_county, sum(ws_sales_price)
from web_sales, customer, customer_address, date_dim, item
where ws_bill_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
and ws_item_sk = i_item_sk
and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792')
or
i_item_id in (select i_item_id
from item
where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)
)
)
and ws_sold_date_sk = d_date_sk
and d_qoy = 2 and d_year = 2000
group by ca_zip, ca_county
order by ca_zip, ca_county
limit 100;
Query46:
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 = 6 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 ('Oakland','Riverside','Union','Salem','Greenwood')
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;
Query47:
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 = 2000 or
( d_year = 2000-1 and d_moy =12) or
( d_year = 2000+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.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 = 2000 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, nsum
limit 100;
Query48:
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 = 1998
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 = 'Primary'
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 = 'Advanced Degree'
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 ('KY', 'GA', 'NM')
and ss_net_profit between 0 and 2000
)
or
(ss_addr_sk = ca_address_sk
and
ca_country = 'United States'
and
ca_state in ('MT', 'OR', 'IN')
and ss_net_profit between 150 and 3000
)
or
(ss_addr_sk = ca_address_sk
and
ca_country = 'United States'
and
ca_state in ('WI', 'MO', 'WV')
and ss_net_profit between 50 and 25000
)
)
;
Query49:
select channel, item, return_ratio, return_rank, currency_rank from
(select
'web' as channel
,web.item
,web.return_ratio
,web.return_rank
,web.currency_rank
from (
select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
( select ws.ws_item_sk as item
,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/
cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/
cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio
from
web_sales ws left outer join web_returns wr
on (ws.ws_order_number = wr.wr_order_number and
ws.ws_item_sk = wr.wr_item_sk)
,date_dim
where
wr.wr_return_amt > 10000
and ws.ws_net_profit > 1
and ws.ws_net_paid > 0
and ws.ws_quantity > 0
and ws_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 12
group by ws.ws_item_sk
) in_web
) web
where
(
web.return_rank <= 10
or
web.currency_rank <= 10
)
union
select
'catalog' as channel
,catalog.item
,catalog.return_ratio
,catalog.return_rank
,catalog.currency_rank
from (
select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
( select
cs.cs_item_sk as item
,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/
cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/
cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio
from
catalog_sales cs left outer join catalog_returns cr
on (cs.cs_order_number = cr.cr_order_number and
cs.cs_item_sk = cr.cr_item_sk)
,date_dim
where
cr.cr_return_amount > 10000
and cs.cs_net_profit > 1
and cs.cs_net_paid > 0
and cs.cs_quantity > 0
and cs_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 12
group by cs.cs_item_sk
) in_cat
) catalog
where
(
catalog.return_rank <= 10
or
catalog.currency_rank <=10
)
union
select
'store' as channel
,store.item
,store.return_ratio
,store.return_rank
,store.currency_rank
from (
select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
( select sts.ss_item_sk as item
,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio
from
store_sales sts left outer join store_returns sr
on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk)
,date_dim
where
sr.sr_return_amt > 10000
and sts.ss_net_profit > 1
and sts.ss_net_paid > 0
and sts.ss_quantity > 0
and ss_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 12
group by sts.ss_item_sk
) in_store
) store
where (
store.return_rank <= 10
or
store.currency_rank <= 10
)
) as alias1
order by 1,4,5,2
limit 100;
Query50:
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 = 2000
and d2.d_moy = 9
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;
Query51:
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 1212 and 1212+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 1212 and 1212+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;
Query52:
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=12
and dt.d_year=1998
group by dt.d_year
,item.i_brand
,item.i_brand_id
order by dt.d_year
,ext_price desc
,brand_id
limit 100 ;
Query53:
select * from
(select i_manufact_id,
sum(ss_sales_price) sum_sales,
avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_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_month_seq in (1212,1212+1,1212+2,1212+3,1212+4,1212+5,1212+6,1212+7,1212+8,1212+9,1212+10,1212+11) and
((i_category in ('Books','Children','Electronics') and
i_class in ('personal','portable','reference','self-help') and
i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
'exportiunivamalg #9','scholaramalgamalg #9'))
or(i_category in ('Women','Music','Men') and
i_class in ('accessories','classical','fragrances','pants') and
i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
'importoamalg #1')))
group by i_manufact_id, d_qoy ) tmp1
where case when avg_quarterly_sales > 0
then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales
else null end > 0.1
order by avg_quarterly_sales,
sum_sales,
i_manufact_id
limit 100;
Query54:
with my_customers as (
select distinct c_customer_sk
, c_current_addr_sk
from
( select cs_sold_date_sk sold_date_sk,
cs_bill_customer_sk customer_sk,
cs_item_sk item_sk
from catalog_sales
union all
select ws_sold_date_sk sold_date_sk,
ws_bill_customer_sk customer_sk,
ws_item_sk item_sk
from web_sales
) cs_or_ws_sales,
item,
date_dim,
customer
where sold_date_sk = d_date_sk
and item_sk = i_item_sk
and i_category = 'Jewelry'
and i_class = 'consignment'
and c_customer_sk = cs_or_ws_sales.customer_sk
and d_moy = 3
and d_year = 1999
)
, my_revenue as (
select c_customer_sk,
sum(ss_ext_sales_price) as revenue
from my_customers,
store_sales,
customer_address,
store,
date_dim
where c_current_addr_sk = ca_address_sk
and ca_county = s_county
and ca_state = s_state
and ss_sold_date_sk = d_date_sk
and c_customer_sk = ss_customer_sk
and d_month_seq between (select distinct d_month_seq+1
from date_dim where d_year = 1999 and d_moy = 3)
and (select distinct d_month_seq+3
from date_dim where d_year = 1999 and d_moy = 3)
group by c_customer_sk
)
, segments as
(select cast((revenue/50) as int) as segment
from my_revenue
)
select segment, count(*) as num_customers, segment*50 as segment_base
from segments
group by segment
order by segment, num_customers
limit 100;
Query55:
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=36
and d_moy=12
and d_year=2001
group by i_brand, i_brand_id
order by ext_price desc, i_brand_id
limit 100 ;
Query56:
with ss as (
select i_item_id,sum(ss_ext_sales_price) total_sales
from
store_sales,
date_dim,
customer_address,
item
where i_item_id in (select
i_item_id
from item
where i_color in ('orchid','chiffon','lace'))
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 1
and ss_addr_sk = ca_address_sk
and ca_gmt_offset = -8
group by i_item_id),
cs as (
select i_item_id,sum(cs_ext_sales_price) total_sales
from
catalog_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from item
where i_color in ('orchid','chiffon','lace'))
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 1
and cs_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -8
group by i_item_id),
ws as (
select i_item_id,sum(ws_ext_sales_price) total_sales
from
web_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from item
where i_color in ('orchid','chiffon','lace'))
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 1
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -8
group by i_item_id)
select i_item_id ,sum(total_sales) total_sales
from (select * from ss
union all
select * from cs
union all
select * from ws) tmp1
group by i_item_id
order by total_sales,
i_item_id
limit 100;
Query57:
with v1 as(
select i_category, i_brand,
cc_name,
d_year, d_moy,
sum(cs_sales_price) sum_sales,
avg(sum(cs_sales_price)) over
(partition by i_category, i_brand,
cc_name, d_year)
avg_monthly_sales,
rank() over
(partition by i_category, i_brand,
cc_name
order by d_year, d_moy) rn
from item, catalog_sales, date_dim, call_center
where cs_item_sk = i_item_sk and
cs_sold_date_sk = d_date_sk and
cc_call_center_sk= cs_call_center_sk and
(
d_year = 2000 or
( d_year = 2000-1 and d_moy =12) or
( d_year = 2000+1 and d_moy =1)
)
group by i_category, i_brand,
cc_name , d_year, d_moy),
v2 as(
select v1.cc_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. cc_name = v1_lag. cc_name and
v1. cc_name = v1_lead. cc_name and
v1.rn = v1_lag.rn + 1 and
v1.rn = v1_lead.rn - 1)
select *
from v2
where d_year = 2000 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, nsum
limit 100;
Query58:
with ss_items as
(select i_item_id item_id
,sum(ss_ext_sales_price) ss_item_rev
from store_sales
,item
,date_dim
where ss_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
where d_week_seq = (select d_week_seq
from date_dim
where d_date = '1998-02-19'))
and ss_sold_date_sk = d_date_sk
group by i_item_id),
cs_items as
(select i_item_id item_id
,sum(cs_ext_sales_price) cs_item_rev
from catalog_sales
,item
,date_dim
where cs_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
where d_week_seq = (select d_week_seq
from date_dim
where d_date = '1998-02-19'))
and cs_sold_date_sk = d_date_sk
group by i_item_id),
ws_items as
(select i_item_id item_id
,sum(ws_ext_sales_price) ws_item_rev
from web_sales
,item
,date_dim
where ws_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
where d_week_seq =(select d_week_seq
from date_dim
where d_date = '1998-02-19'))
and ws_sold_date_sk = d_date_sk
group by i_item_id)
select ss_items.item_id
,ss_item_rev
,ss_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ss_dev
,cs_item_rev
,cs_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 cs_dev
,ws_item_rev
,ws_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ws_dev
,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
from ss_items,cs_items,ws_items
where ss_items.item_id=cs_items.item_id
and ss_items.item_id=ws_items.item_id
and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
order by item_id
,ss_item_rev
limit 100;
Query59:
with wss as
(select d_week_seq,
ss_store_sk,
sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
from store_sales,date_dim
where d_date_sk = ss_sold_date_sk
group by d_week_seq,ss_store_sk
)
select s_store_name1,s_store_id1,d_week_seq1
,sun_sales1/sun_sales2,mon_sales1/mon_sales2
,tue_sales1/tue_sales2,wed_sales1/wed_sales2,thu_sales1/thu_sales2
,fri_sales1/fri_sales2,sat_sales1/sat_sales2
from
(select s_store_name s_store_name1,wss.d_week_seq d_week_seq1
,s_store_id s_store_id1,sun_sales sun_sales1
,mon_sales mon_sales1,tue_sales tue_sales1
,wed_sales wed_sales1,thu_sales thu_sales1
,fri_sales fri_sales1,sat_sales sat_sales1
from wss,store,date_dim d
where d.d_week_seq = wss.d_week_seq and
ss_store_sk = s_store_sk and
d_month_seq between 1185 and 1185 + 11) y,
(select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
,s_store_id s_store_id2,sun_sales sun_sales2
,mon_sales mon_sales2,tue_sales tue_sales2
,wed_sales wed_sales2,thu_sales thu_sales2
,fri_sales fri_sales2,sat_sales sat_sales2
from wss,store,date_dim d
where d.d_week_seq = wss.d_week_seq and
ss_store_sk = s_store_sk and
d_month_seq between 1185+ 12 and 1185 + 23) x
where s_store_id1=s_store_id2
and d_week_seq1=d_week_seq2-52
order by s_store_name1,s_store_id1,d_week_seq1
limit 100;
Query60:
with ss as (
select
i_item_id,sum(ss_ext_sales_price) total_sales
from
store_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from
item
where i_category in ('Children'))
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 1999
and d_moy = 9
and ss_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_item_id),
cs as (
select
i_item_id,sum(cs_ext_sales_price) total_sales
from
catalog_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from
item
where i_category in ('Children'))
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 1999
and d_moy = 9
and cs_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_item_id),
ws as (
select
i_item_id,sum(ws_ext_sales_price) total_sales
from
web_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from
item
where i_category in ('Children'))
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 1999
and d_moy = 9
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_item_id)
select
i_item_id
,sum(total_sales) total_sales
from (select * from ss
union all
select * from cs
union all
select * from ws) tmp1
group by i_item_id
order by i_item_id
,total_sales
limit 100;
Query61:
select promotions,total,cast(promotions as decimal(15,4))/cast(total as decimal(15,4))*100
from
(select sum(ss_ext_sales_price) promotions
from store_sales
,store
,promotion
,date_dim
,customer
,customer_address
,item
where ss_sold_date_sk = d_date_sk
and ss_store_sk = s_store_sk
and ss_promo_sk = p_promo_sk
and ss_customer_sk= c_customer_sk
and ca_address_sk = c_current_addr_sk
and ss_item_sk = i_item_sk
and ca_gmt_offset = -7
and i_category = 'Books'
and (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y')
and s_gmt_offset = -7
and d_year = 1999
and d_moy = 11) promotional_sales,
(select sum(ss_ext_sales_price) total
from store_sales
,store
,date_dim
,customer
,customer_address
,item
where ss_sold_date_sk = d_date_sk
and ss_store_sk = s_store_sk
and ss_customer_sk= c_customer_sk
and ca_address_sk = c_current_addr_sk
and ss_item_sk = i_item_sk
and ca_gmt_offset = -7
and i_category = 'Books'
and s_gmt_offset = -7
and d_year = 1999
and d_moy = 11) all_sales
order by promotions, total
limit 100;
Query62:
select
substr(w_warehouse_name,1,20)
,sm_type
,web_name
,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and
(ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and
(ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and
(ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
web_sales
,warehouse
,ship_mode
,web_site
,date_dim
where
d_month_seq between 1212 and 1212 + 11
and ws_ship_date_sk = d_date_sk
and ws_warehouse_sk = w_warehouse_sk
and ws_ship_mode_sk = sm_ship_mode_sk
and ws_web_site_sk = web_site_sk
group by
substr(w_warehouse_name,1,20)
,sm_type
,web_name
order by substr(w_warehouse_name,1,20)
,sm_type
,web_name
limit 100;
Query63:
select *
from (select i_manager_id
,sum(ss_sales_price) sum_sales
,avg(sum(ss_sales_price)) over (partition by i_manager_id) 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_month_seq in (1212,1212+1,1212+2,1212+3,1212+4,1212+5,1212+6,1212+7,1212+8,1212+9,1212+10,1212+11)
and (( i_category in ('Books','Children','Electronics')
and i_class in ('personal','portable','reference','self-help')
and i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
'exportiunivamalg #9','scholaramalgamalg #9'))
or( i_category in ('Women','Music','Men')
and i_class in ('accessories','classical','fragrances','pants')
and i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
'importoamalg #1')))
group by i_manager_id, 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 i_manager_id
,avg_monthly_sales
,sum_sales
limit 100;
Query64:
with cs_ui as
(select cs_item_sk
,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund
from catalog_sales
,catalog_returns
where cs_item_sk = cr_item_sk
and cs_order_number = cr_order_number
group by cs_item_sk
having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)),
cross_sales as
(select i_product_name product_name
,i_item_sk item_sk
,s_store_name store_name
,s_zip store_zip
,ad1.ca_street_number b_street_number
,ad1.ca_street_name b_street_name
,ad1.ca_city b_city
,ad1.ca_zip b_zip
,ad2.ca_street_number c_street_number
,ad2.ca_street_name c_street_name
,ad2.ca_city c_city
,ad2.ca_zip c_zip
,d1.d_year as syear
,d2.d_year as fsyear
,d3.d_year s2year
,count(*) cnt
,sum(ss_wholesale_cost) s1
,sum(ss_list_price) s2
,sum(ss_coupon_amt) s3
FROM store_sales
,store_returns
,cs_ui
,date_dim d1
,date_dim d2
,date_dim d3
,store
,customer
,customer_demographics cd1
,customer_demographics cd2
,promotion
,household_demographics hd1
,household_demographics hd2
,customer_address ad1
,customer_address ad2
,income_band ib1
,income_band ib2
,item
WHERE ss_store_sk = s_store_sk AND
ss_sold_date_sk = d1.d_date_sk AND
ss_customer_sk = c_customer_sk AND
ss_cdemo_sk= cd1.cd_demo_sk AND
ss_hdemo_sk = hd1.hd_demo_sk AND
ss_addr_sk = ad1.ca_address_sk and
ss_item_sk = i_item_sk and
ss_item_sk = sr_item_sk and
ss_ticket_number = sr_ticket_number and
ss_item_sk = cs_ui.cs_item_sk and
c_current_cdemo_sk = cd2.cd_demo_sk AND
c_current_hdemo_sk = hd2.hd_demo_sk AND
c_current_addr_sk = ad2.ca_address_sk and
c_first_sales_date_sk = d2.d_date_sk and
c_first_shipto_date_sk = d3.d_date_sk and
ss_promo_sk = p_promo_sk and
hd1.hd_income_band_sk = ib1.ib_income_band_sk and
hd2.hd_income_band_sk = ib2.ib_income_band_sk and
cd1.cd_marital_status <> cd2.cd_marital_status and
i_color in ('maroon','burnished','dim','steel','navajo','chocolate') and
i_current_price between 35 and 35 + 10 and
i_current_price between 35 + 1 and 35 + 15
group by i_product_name
,i_item_sk
,s_store_name
,s_zip
,ad1.ca_street_number
,ad1.ca_street_name
,ad1.ca_city
,ad1.ca_zip
,ad2.ca_street_number
,ad2.ca_street_name
,ad2.ca_city
,ad2.ca_zip
,d1.d_year
,d2.d_year
,d3.d_year
)
select cs1.product_name
,cs1.store_name
,cs1.store_zip
,cs1.b_street_number
,cs1.b_street_name
,cs1.b_city
,cs1.b_zip
,cs1.c_street_number
,cs1.c_street_name
,cs1.c_city
,cs1.c_zip
,cs1.syear
,cs1.cnt
,cs1.s1 as s11
,cs1.s2 as s21
,cs1.s3 as s31
,cs2.s1 as s12
,cs2.s2 as s22
,cs2.s3 as s32
,cs2.syear
,cs2.cnt
from cross_sales cs1,cross_sales cs2
where cs1.item_sk=cs2.item_sk and
cs1.syear = 2000 and
cs2.syear = 2000 + 1 and
cs2.cnt <= cs1.cnt and
cs1.store_name = cs2.store_name and
cs1.store_zip = cs2.store_zip
order by cs1.product_name
,cs1.store_name
,cs2.cnt
,cs1.s1
,cs2.s1;
Query65:
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 1212 and 1212+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 1212 and 1212+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 100;
Query66:
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
,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
,d_year as year
,sum(case when d_moy = 1
then ws_sales_price* ws_quantity else 0 end) as jan_sales
,sum(case when d_moy = 2
then ws_sales_price* ws_quantity else 0 end) as feb_sales
,sum(case when d_moy = 3
then ws_sales_price* ws_quantity else 0 end) as mar_sales
,sum(case when d_moy = 4
then ws_sales_price* ws_quantity else 0 end) as apr_sales
,sum(case when d_moy = 5
then ws_sales_price* ws_quantity else 0 end) as may_sales
,sum(case when d_moy = 6
then ws_sales_price* ws_quantity else 0 end) as jun_sales
,sum(case when d_moy = 7
then ws_sales_price* ws_quantity else 0 end) as jul_sales
,sum(case when d_moy = 8
then ws_sales_price* ws_quantity else 0 end) as aug_sales
,sum(case when d_moy = 9
then ws_sales_price* ws_quantity else 0 end) as sep_sales
,sum(case when d_moy = 10
then ws_sales_price* ws_quantity else 0 end) as oct_sales
,sum(case when d_moy = 11
then ws_sales_price* ws_quantity else 0 end) as nov_sales
,sum(case when d_moy = 12
then ws_sales_price* ws_quantity else 0 end) as dec_sales
,sum(case when d_moy = 1
then ws_net_paid_inc_tax * ws_quantity else 0 end) as jan_net
,sum(case when d_moy = 2
then ws_net_paid_inc_tax * ws_quantity else 0 end) as feb_net
,sum(case when d_moy = 3
then ws_net_paid_inc_tax * ws_quantity else 0 end) as mar_net
,sum(case when d_moy = 4
then ws_net_paid_inc_tax * ws_quantity else 0 end) as apr_net
,sum(case when d_moy = 5
then ws_net_paid_inc_tax * ws_quantity else 0 end) as may_net
,sum(case when d_moy = 6
then ws_net_paid_inc_tax * ws_quantity else 0 end) as jun_net
,sum(case when d_moy = 7
then ws_net_paid_inc_tax * ws_quantity else 0 end) as jul_net
,sum(case when d_moy = 8
then ws_net_paid_inc_tax * ws_quantity else 0 end) as aug_net
,sum(case when d_moy = 9
then ws_net_paid_inc_tax * ws_quantity else 0 end) as sep_net
,sum(case when d_moy = 10
then ws_net_paid_inc_tax * ws_quantity else 0 end) as oct_net
,sum(case when d_moy = 11
then ws_net_paid_inc_tax * ws_quantity else 0 end) as nov_net
,sum(case when d_moy = 12
then ws_net_paid_inc_tax * 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 = 2002
and t_time between 49530 and 49530+28800
and sm_carrier in ('DIAMOND','AIRBORNE')
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
,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
,d_year as year
,sum(case when d_moy = 1
then cs_ext_sales_price* cs_quantity else 0 end) as jan_sales
,sum(case when d_moy = 2
then cs_ext_sales_price* cs_quantity else 0 end) as feb_sales
,sum(case when d_moy = 3
then cs_ext_sales_price* cs_quantity else 0 end) as mar_sales
,sum(case when d_moy = 4
then cs_ext_sales_price* cs_quantity else 0 end) as apr_sales
,sum(case when d_moy = 5
then cs_ext_sales_price* cs_quantity else 0 end) as may_sales
,sum(case when d_moy = 6
then cs_ext_sales_price* cs_quantity else 0 end) as jun_sales
,sum(case when d_moy = 7
then cs_ext_sales_price* cs_quantity else 0 end) as jul_sales
,sum(case when d_moy = 8
then cs_ext_sales_price* cs_quantity else 0 end) as aug_sales
,sum(case when d_moy = 9
then cs_ext_sales_price* cs_quantity else 0 end) as sep_sales
,sum(case when d_moy = 10
then cs_ext_sales_price* cs_quantity else 0 end) as oct_sales
,sum(case when d_moy = 11
then cs_ext_sales_price* cs_quantity else 0 end) as nov_sales
,sum(case when d_moy = 12
then cs_ext_sales_price* cs_quantity else 0 end) as dec_sales
,sum(case when d_moy = 1
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jan_net
,sum(case when d_moy = 2
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as feb_net
,sum(case when d_moy = 3
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as mar_net
,sum(case when d_moy = 4
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as apr_net
,sum(case when d_moy = 5
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as may_net
,sum(case when d_moy = 6
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jun_net
,sum(case when d_moy = 7
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jul_net
,sum(case when d_moy = 8
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as aug_net
,sum(case when d_moy = 9
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as sep_net
,sum(case when d_moy = 10
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as oct_net
,sum(case when d_moy = 11
then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as nov_net
,sum(case when d_moy = 12
then cs_net_paid_inc_ship_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 = 2002
and t_time between 49530 AND 49530+28800
and sm_carrier in ('DIAMOND','AIRBORNE')
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;
Query67:
select *
from (select i_category
,i_class
,i_brand
,i_product_name
,d_year
,d_qoy
,d_moy
,s_store_id
,sumsales
,rank() over (partition by i_category order by sumsales desc) rk
from (select i_category
,i_class
,i_brand
,i_product_name
,d_year
,d_qoy
,d_moy
,s_store_id
,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
from store_sales
,date_dim
,store
,item
where ss_sold_date_sk=d_date_sk
and ss_item_sk=i_item_sk
and ss_store_sk = s_store_sk
and d_month_seq between 1212 and 1212+11
group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
where rk <= 100
order by i_category
,i_class
,i_brand
,i_product_name
,d_year
,d_qoy
,d_moy
,s_store_id
,sumsales
,rk
limit 100;
Query68:
select c_last_name
,c_first_name
,ca_city
,bought_city
,ss_ticket_number
,extended_price
,extended_tax
,list_price
from (select ss_ticket_number
,ss_customer_sk
,ca_city bought_city
,sum(ss_ext_sales_price) extended_price
,sum(ss_ext_list_price) list_price
,sum(ss_ext_tax) extended_tax
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 date_dim.d_dom between 1 and 2
and (household_demographics.hd_dep_count = 6 or
household_demographics.hd_vehicle_count= 3)
and date_dim.d_year in (1999,1999+1,1999+2)
and store.s_city in ('Oakland','Riverside')
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
,ss_ticket_number
limit 100;
Query69:
select
cd_gender,
cd_marital_status,
cd_education_status,
count(*) cnt1,
cd_purchase_estimate,
count(*) cnt2,
cd_credit_rating,
count(*) cnt3
from
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
ca_state in ('CO','IL','MN') and
cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
ss_sold_date_sk = d_date_sk and
d_year = 1999 and
d_moy between 1 and 1+2) and
(not exists (select *
from web_sales,date_dim
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 1999 and
d_moy between 1 and 1+2) and
not exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
d_year = 1999 and
d_moy between 1 and 1+2))
group by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating
order by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating
limit 100;
Query70:
select
sum(ss_net_profit) as total_sum
,s_state
,s_county
,grouping(s_state)+grouping(s_county) as lochierarchy
,rank() over (
partition by grouping(s_state)+grouping(s_county),
case when grouping(s_county) = 0 then s_state end
order by sum(ss_net_profit) desc) as rank_within_parent
from
store_sales
,date_dim d1
,store
where
d1.d_month_seq between 1212 and 1212+11
and d1.d_date_sk = ss_sold_date_sk
and s_store_sk = ss_store_sk
and s_state in
( select s_state
from (select s_state as s_state,
rank() over ( partition by s_state order by sum(ss_net_profit) desc) as ranking
from store_sales, store, date_dim
where d_month_seq between 1212 and 1212+11
and d_date_sk = ss_sold_date_sk
and s_store_sk = ss_store_sk
group by s_state
) tmp1
where ranking <= 5
)
group by rollup(s_state,s_county)
order by
lochierarchy desc
,case when grouping(s_state)+grouping(s_county) = 0 then s_state end
,rank_within_parent
limit 100;
Query71:
select i_brand_id brand_id, i_brand brand,t_hour,t_minute,
sum(ext_price) ext_price
from item, (select ws_ext_sales_price as ext_price,
ws_sold_date_sk as sold_date_sk,
ws_item_sk as sold_item_sk,
ws_sold_time_sk as time_sk
from web_sales,date_dim
where d_date_sk = ws_sold_date_sk
and d_moy=12
and d_year=2000
union all
select cs_ext_sales_price as ext_price,
cs_sold_date_sk as sold_date_sk,
cs_item_sk as sold_item_sk,
cs_sold_time_sk as time_sk
from catalog_sales,date_dim
where d_date_sk = cs_sold_date_sk
and d_moy=12
and d_year=2000
union all
select ss_ext_sales_price as ext_price,
ss_sold_date_sk as sold_date_sk,
ss_item_sk as sold_item_sk,
ss_sold_time_sk as time_sk
from store_sales,date_dim
where d_date_sk = ss_sold_date_sk
and d_moy=12
and d_year=2000
) tmp,time_dim
where
sold_item_sk = i_item_sk
and i_manager_id=1
and time_sk = t_time_sk
and (t_meal_time = 'breakfast' or t_meal_time = 'dinner')
group by i_brand, i_brand_id,t_hour,t_minute
order by ext_price desc, i_brand_id
;
Query72:
select i_item_desc
,w_warehouse_name
,d1.d_week_seq
,sum(case when p_promo_sk is null then 1 else 0 end) no_promo
,sum(case when p_promo_sk is not null then 1 else 0 end) promo
,count(*) total_cnt
from catalog_sales
join inventory on (cs_item_sk = inv_item_sk)
join warehouse on (w_warehouse_sk=inv_warehouse_sk)
join item on (i_item_sk = cs_item_sk)
join customer_demographics on (cs_bill_cdemo_sk = cd_demo_sk)
join household_demographics on (cs_bill_hdemo_sk = hd_demo_sk)
join date_dim d1 on (cs_sold_date_sk = d1.d_date_sk)
join date_dim d2 on (inv_date_sk = d2.d_date_sk)
join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk)
left outer join promotion on (cs_promo_sk=p_promo_sk)
left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number)
where d1.d_week_seq = d2.d_week_seq
and inv_quantity_on_hand < cs_quantity
and d3.d_date > d1.d_date + 5
and hd_buy_potential = '1001-5000'
and d1.d_year = 2001
and cd_marital_status = 'M'
group by i_item_desc,w_warehouse_name,d1.d_week_seq
order by total_cnt desc, i_item_desc, w_warehouse_name, d_week_seq
limit 100;
Query73:
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 ('Daviess County','Franklin Parish','Barrow County','Luce 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;
Query74:
with year_total as (
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,d_year as year
,max(ss_net_paid) year_total
,'s' sale_type
from customer
,store_sales
,date_dim
where c_customer_sk = ss_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (2001,2001+1)
group by c_customer_id
,c_first_name
,c_last_name
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,d_year as year
,max(ws_net_paid) year_total
,'w' sale_type
from customer
,web_sales
,date_dim
where c_customer_sk = ws_bill_customer_sk
and ws_sold_date_sk = d_date_sk
and d_year in (2001,2001+1)
group by c_customer_id
,c_first_name
,c_last_name
,d_year
)
select
t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name
from year_total t_s_firstyear
,year_total t_s_secyear
,year_total t_w_firstyear
,year_total t_w_secyear
where t_s_secyear.customer_id = t_s_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_secyear.customer_id
and t_s_firstyear.customer_id = t_w_firstyear.customer_id
and t_s_firstyear.sale_type = 's'
and t_w_firstyear.sale_type = 'w'
and t_s_secyear.sale_type = 's'
and t_w_secyear.sale_type = 'w'
and t_s_firstyear.year = 2001
and t_s_secyear.year = 2001+1
and t_w_firstyear.year = 2001
and t_w_secyear.year = 2001+1
and t_s_firstyear.year_total > 0
and t_w_firstyear.year_total > 0
and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
> case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
order by 2,1,3
limit 100;
Query75:
WITH all_sales AS (
SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,SUM(sales_cnt) AS sales_cnt
,SUM(sales_amt) AS sales_amt
FROM (SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,cs_quantity - COALESCE(cr_return_quantity,0) AS sales_cnt
,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt
FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk
JOIN date_dim ON d_date_sk=cs_sold_date_sk
LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number
AND cs_item_sk=cr_item_sk)
WHERE i_category='Sports'
UNION
SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,ss_quantity - COALESCE(sr_return_quantity,0) AS sales_cnt
,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt
FROM store_sales JOIN item ON i_item_sk=ss_item_sk
JOIN date_dim ON d_date_sk=ss_sold_date_sk
LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number
AND ss_item_sk=sr_item_sk)
WHERE i_category='Sports'
UNION
SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,ws_quantity - COALESCE(wr_return_quantity,0) AS sales_cnt
,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt
FROM web_sales JOIN item ON i_item_sk=ws_item_sk
JOIN date_dim ON d_date_sk=ws_sold_date_sk
LEFT JOIN web_returns ON (ws_order_number=wr_order_number
AND ws_item_sk=wr_item_sk)
WHERE i_category='Sports') sales_detail
GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id)
SELECT prev_yr.d_year AS prev_year
,curr_yr.d_year AS year
,curr_yr.i_brand_id
,curr_yr.i_class_id
,curr_yr.i_category_id
,curr_yr.i_manufact_id
,prev_yr.sales_cnt AS prev_yr_cnt
,curr_yr.sales_cnt AS curr_yr_cnt
,curr_yr.sales_cnt-prev_yr.sales_cnt AS sales_cnt_diff
,curr_yr.sales_amt-prev_yr.sales_amt AS sales_amt_diff
FROM all_sales curr_yr, all_sales prev_yr
WHERE curr_yr.i_brand_id=prev_yr.i_brand_id
AND curr_yr.i_class_id=prev_yr.i_class_id
AND curr_yr.i_category_id=prev_yr.i_category_id
AND curr_yr.i_manufact_id=prev_yr.i_manufact_id
AND curr_yr.d_year=2002
AND prev_yr.d_year=2002-1
AND CAST(curr_yr.sales_cnt AS DECIMAL(17,2))/CAST(prev_yr.sales_cnt AS DECIMAL(17,2))<0.9
ORDER BY sales_cnt_diff,sales_amt_diff
limit 100;
Query76:
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_addr_sk' col_name, d_year, d_qoy, i_category, ss_ext_sales_price ext_sales_price
FROM store_sales, item, date_dim
WHERE ss_addr_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_web_page_sk' col_name, d_year, d_qoy, i_category, ws_ext_sales_price ext_sales_price
FROM web_sales, item, date_dim
WHERE ws_web_page_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_warehouse_sk' col_name, d_year, d_qoy, i_category, cs_ext_sales_price ext_sales_price
FROM catalog_sales, item, date_dim
WHERE cs_warehouse_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 100;
Query77:
with ss as
(select s_store_sk,
sum(ss_ext_sales_price) as sales,
sum(ss_net_profit) as profit
from store_sales,
date_dim,
store
where ss_sold_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and ss_store_sk = s_store_sk
group by s_store_sk)
,
sr as
(select s_store_sk,
sum(sr_return_amt) as returns,
sum(sr_net_loss) as profit_loss
from store_returns,
date_dim,
store
where sr_returned_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and sr_store_sk = s_store_sk
group by s_store_sk),
cs as
(select cs_call_center_sk,
sum(cs_ext_sales_price) as sales,
sum(cs_net_profit) as profit
from catalog_sales,
date_dim
where cs_sold_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
group by cs_call_center_sk
),
cr as
(select cr_call_center_sk,
sum(cr_return_amount) as returns,
sum(cr_net_loss) as profit_loss
from catalog_returns,
date_dim
where cr_returned_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
group by cr_call_center_sk
),
ws as
( select wp_web_page_sk,
sum(ws_ext_sales_price) as sales,
sum(ws_net_profit) as profit
from web_sales,
date_dim,
web_page
where ws_sold_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and ws_web_page_sk = wp_web_page_sk
group by wp_web_page_sk),
wr as
(select wp_web_page_sk,
sum(wr_return_amt) as returns,
sum(wr_net_loss) as profit_loss
from web_returns,
date_dim,
web_page
where wr_returned_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and wr_web_page_sk = wp_web_page_sk
group by wp_web_page_sk)
select channel
, id
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
from
(select 'store channel' as channel
, ss.s_store_sk as id
, sales
, coalesce(returns, 0) as returns
, (profit - coalesce(profit_loss,0)) as profit
from ss left join sr
on ss.s_store_sk = sr.s_store_sk
union all
select 'catalog channel' as channel
, cs_call_center_sk as id
, sales
, returns
, (profit - profit_loss) as profit
from cs
, cr
union all
select 'web channel' as channel
, ws.wp_web_page_sk as id
, sales
, coalesce(returns, 0) returns
, (profit - coalesce(profit_loss,0)) as profit
from ws left join wr
on ws.wp_web_page_sk = wr.wp_web_page_sk
) x
group by rollup (channel, id)
order by channel
,id
limit 100;
Query78:
with ws as
(select d_year AS ws_sold_year, ws_item_sk,
ws_bill_customer_sk ws_customer_sk,
sum(ws_quantity) ws_qty,
sum(ws_wholesale_cost) ws_wc,
sum(ws_sales_price) ws_sp
from web_sales
left join web_returns on wr_order_number=ws_order_number and ws_item_sk=wr_item_sk
join date_dim on ws_sold_date_sk = d_date_sk
where wr_order_number is null
group by d_year, ws_item_sk, ws_bill_customer_sk
),
cs as
(select d_year AS cs_sold_year, cs_item_sk,
cs_bill_customer_sk cs_customer_sk,
sum(cs_quantity) cs_qty,
sum(cs_wholesale_cost) cs_wc,
sum(cs_sales_price) cs_sp
from catalog_sales
left join catalog_returns on cr_order_number=cs_order_number and cs_item_sk=cr_item_sk
join date_dim on cs_sold_date_sk = d_date_sk
where cr_order_number is null
group by d_year, cs_item_sk, cs_bill_customer_sk
),
ss as
(select d_year AS ss_sold_year, ss_item_sk,
ss_customer_sk,
sum(ss_quantity) ss_qty,
sum(ss_wholesale_cost) ss_wc,
sum(ss_sales_price) ss_sp
from store_sales
left join store_returns on sr_ticket_number=ss_ticket_number and ss_item_sk=sr_item_sk
join date_dim on ss_sold_date_sk = d_date_sk
where sr_ticket_number is null
group by d_year, ss_item_sk, ss_customer_sk
)
select
ss_sold_year, ss_item_sk, ss_customer_sk,
round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio,
ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price,
coalesce(ws_qty,0)+coalesce(cs_qty,0) other_chan_qty,
coalesce(ws_wc,0)+coalesce(cs_wc,0) other_chan_wholesale_cost,
coalesce(ws_sp,0)+coalesce(cs_sp,0) other_chan_sales_price
from ss
left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk)
left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk)
where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=2000
order by
ss_sold_year, ss_item_sk, ss_customer_sk,
ss_qty desc, ss_wc desc, ss_sp desc,
other_chan_qty,
other_chan_wholesale_cost,
other_chan_sales_price,
ratio
limit 100;
Query79:
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 = 8 or household_demographics.hd_vehicle_count > 0)
and date_dim.d_dow = 1
and date_dim.d_year in (1998,1998+1,1998+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 100;
Query80:
with ssr as
(select s_store_id as store_id,
sum(ss_ext_sales_price) as sales,
sum(coalesce(sr_return_amt, 0)) as returns,
sum(ss_net_profit - coalesce(sr_net_loss, 0)) as profit
from store_sales left outer join store_returns on
(ss_item_sk = sr_item_sk and ss_ticket_number = sr_ticket_number),
date_dim,
store,
item,
promotion
where ss_sold_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and ss_store_sk = s_store_sk
and ss_item_sk = i_item_sk
and i_current_price > 50
and ss_promo_sk = p_promo_sk
and p_channel_tv = 'N'
group by s_store_id)
,
csr as
(select cp_catalog_page_id as catalog_page_id,
sum(cs_ext_sales_price) as sales,
sum(coalesce(cr_return_amount, 0)) as returns,
sum(cs_net_profit - coalesce(cr_net_loss, 0)) as profit
from catalog_sales left outer join catalog_returns on
(cs_item_sk = cr_item_sk and cs_order_number = cr_order_number),
date_dim,
catalog_page,
item,
promotion
where cs_sold_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and cs_catalog_page_sk = cp_catalog_page_sk
and cs_item_sk = i_item_sk
and i_current_price > 50
and cs_promo_sk = p_promo_sk
and p_channel_tv = 'N'
group by cp_catalog_page_id)
,
wsr as
(select web_site_id,
sum(ws_ext_sales_price) as sales,
sum(coalesce(wr_return_amt, 0)) as returns,
sum(ws_net_profit - coalesce(wr_net_loss, 0)) as profit
from web_sales left outer join web_returns on
(ws_item_sk = wr_item_sk and ws_order_number = wr_order_number),
date_dim,
web_site,
item,
promotion
where ws_sold_date_sk = d_date_sk
and d_date between cast('1998-08-04' as date)
and (cast('1998-08-04' as date) + interval '30 days')
and ws_web_site_sk = web_site_sk
and ws_item_sk = i_item_sk
and i_current_price > 50
and ws_promo_sk = p_promo_sk
and p_channel_tv = 'N'
group by web_site_id)
select channel
, id
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
from
(select 'store channel' as channel
, 'store' || store_id as id
, sales
, returns
, profit
from ssr
union all
select 'catalog channel' as channel
, 'catalog_page' || catalog_page_id as id
, sales
, returns
, profit
from csr
union all
select 'web channel' as channel
, 'web_site' || web_site_id as id
, sales
, returns
, profit
from wsr
) x
group by rollup (channel, id)
order by channel
,id
limit 100;
Query81:
with customer_total_return as
(select cr_returning_customer_sk as ctr_customer_sk
,ca_state as ctr_state,
sum(cr_return_amt_inc_tax) as ctr_total_return
from catalog_returns
,date_dim
,customer_address
where cr_returned_date_sk = d_date_sk
and d_year =1998
and cr_returning_addr_sk = ca_address_sk
group by cr_returning_customer_sk
,ca_state )
select c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
,ca_location_type,ctr_total_return
from customer_total_return ctr1
,customer_address
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_state = ctr2.ctr_state)
and ca_address_sk = c_current_addr_sk
and ca_state = 'IL'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
,ca_location_type,ctr_total_return
limit 100;
Query82:
select i_item_id
,i_item_desc
,i_current_price
from item, inventory, date_dim, store_sales
where i_current_price between 30 and 30+30
and inv_item_sk = i_item_sk
and d_date_sk=inv_date_sk
and d_date between cast('2002-05-30' as date) and (cast('2002-05-30' as date) + interval '60 days')
and i_manufact_id in (437,129,727,663)
and inv_quantity_on_hand between 100 and 500
and ss_item_sk = i_item_sk
group by i_item_id,i_item_desc,i_current_price
order by i_item_id
limit 100;
Query83:
with sr_items as
(select i_item_id item_id,
sum(sr_return_quantity) sr_item_qty
from store_returns,
item,
date_dim
where sr_item_sk = i_item_sk
and d_date in
(select d_date
from date_dim
where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
and sr_returned_date_sk = d_date_sk
group by i_item_id),
cr_items as
(select i_item_id item_id,
sum(cr_return_quantity) cr_item_qty
from catalog_returns,
item,
date_dim
where cr_item_sk = i_item_sk
and d_date in
(select d_date
from date_dim
where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
and cr_returned_date_sk = d_date_sk
group by i_item_id),
wr_items as
(select i_item_id item_id,
sum(wr_return_quantity) wr_item_qty
from web_returns,
item,
date_dim
where wr_item_sk = i_item_sk
and d_date in
(select d_date
from date_dim
where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
and wr_returned_date_sk = d_date_sk
group by i_item_id)
select sr_items.item_id
,sr_item_qty
,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev
,cr_item_qty
,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev
,wr_item_qty
,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev
,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average
from sr_items
,cr_items
,wr_items
where sr_items.item_id=cr_items.item_id
and sr_items.item_id=wr_items.item_id
order by sr_items.item_id
,sr_item_qty
limit 100;
Query84:
select c_customer_id as customer_id
, coalesce(c_last_name,'') || ', ' || coalesce(c_first_name,'') as customername
from customer
,customer_address
,customer_demographics
,household_demographics
,income_band
,store_returns
where ca_city = 'Hopewell'
and c_current_addr_sk = ca_address_sk
and ib_lower_bound >= 32287
and ib_upper_bound <= 32287 + 50000
and ib_income_band_sk = hd_income_band_sk
and cd_demo_sk = c_current_cdemo_sk
and hd_demo_sk = c_current_hdemo_sk
and sr_cdemo_sk = cd_demo_sk
order by c_customer_id
limit 100;
Query85:
select substr(r_reason_desc,1,20)
,avg(ws_quantity)
,avg(wr_refunded_cash)
,avg(wr_fee)
from web_sales, web_returns, web_page, customer_demographics cd1,
customer_demographics cd2, customer_address, date_dim, reason
where ws_web_page_sk = wp_web_page_sk
and ws_item_sk = wr_item_sk
and ws_order_number = wr_order_number
and ws_sold_date_sk = d_date_sk and d_year = 1998
and cd1.cd_demo_sk = wr_refunded_cdemo_sk
and cd2.cd_demo_sk = wr_returning_cdemo_sk
and ca_address_sk = wr_refunded_addr_sk
and r_reason_sk = wr_reason_sk
and
(
(
cd1.cd_marital_status = 'M'
and
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = '4 yr Degree'
and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 100.00 and 150.00
)
or
(
cd1.cd_marital_status = 'D'
and
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = 'Primary'
and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 50.00 and 100.00
)
or
(
cd1.cd_marital_status = 'U'
and
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = 'Advanced Degree'
and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 150.00 and 200.00
)
)
and
(
(
ca_country = 'United States'
and
ca_state in ('KY', 'GA', 'NM')
and ws_net_profit between 100 and 200
)
or
(
ca_country = 'United States'
and
ca_state in ('MT', 'OR', 'IN')
and ws_net_profit between 150 and 300
)
or
(
ca_country = 'United States'
and
ca_state in ('WI', 'MO', 'WV')
and ws_net_profit between 50 and 250
)
)
group by r_reason_desc
order by substr(r_reason_desc,1,20)
,avg(ws_quantity)
,avg(wr_refunded_cash)
,avg(wr_fee)
limit 100;
Query86:
select
sum(ws_net_paid) as total_sum
,i_category
,i_class
,grouping(i_category)+grouping(i_class) as lochierarchy
,rank() over (
partition by grouping(i_category)+grouping(i_class),
case when grouping(i_class) = 0 then i_category end
order by sum(ws_net_paid) desc) as rank_within_parent
from
web_sales
,date_dim d1
,item
where
d1.d_month_seq between 1212 and 1212+11
and d1.d_date_sk = ws_sold_date_sk
and i_item_sk = ws_item_sk
group by rollup(i_category,i_class)
order by
lochierarchy desc,
case when grouping(i_category)+grouping(i_class) = 0 then i_category end,
rank_within_parent
limit 100;
Query87:
select count(*)
from ((select distinct c_last_name, c_first_name, d_date
from store_sales, date_dim, customer
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_customer_sk = customer.c_customer_sk
and d_month_seq between 1212 and 1212+11)
except
(select distinct c_last_name, c_first_name, d_date
from catalog_sales, date_dim, customer
where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1212 and 1212+11)
except
(select distinct c_last_name, c_first_name, d_date
from web_sales, date_dim, customer
where web_sales.ws_sold_date_sk = date_dim.d_date_sk
and web_sales.ws_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1212 and 1212+11)
) cool_cust
;
Query88:
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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+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 = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
and store.s_store_name = 'ese') s8
;
Query89:
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 (2000) and
((i_category in ('Home','Books','Electronics') and
i_class in ('wallpaper','parenting','musical')
)
or (i_category in ('Shoes','Jewelry','Men') and
i_class in ('womens','birdal','pants')
))
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 100;
Query90:
select cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio
from ( select count(*) amc
from web_sales, household_demographics , time_dim, web_page
where ws_sold_time_sk = time_dim.t_time_sk
and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
and ws_web_page_sk = web_page.wp_web_page_sk
and time_dim.t_hour between 6 and 6+1
and household_demographics.hd_dep_count = 8
and web_page.wp_char_count between 5000 and 5200) at,
( select count(*) pmc
from web_sales, household_demographics , time_dim, web_page
where ws_sold_time_sk = time_dim.t_time_sk
and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
and ws_web_page_sk = web_page.wp_web_page_sk
and time_dim.t_hour between 14 and 14+1
and household_demographics.hd_dep_count = 8
and web_page.wp_char_count between 5000 and 5200) pt
order by am_pm_ratio
limit 100;
Query91:
select
cc_call_center_id Call_Center,
cc_name Call_Center_Name,
cc_manager Manager,
sum(cr_net_loss) Returns_Loss
from
call_center,
catalog_returns,
date_dim,
customer,
customer_address,
customer_demographics,
household_demographics
where
cr_call_center_sk = cc_call_center_sk
and cr_returned_date_sk = d_date_sk
and cr_returning_customer_sk= c_customer_sk
and cd_demo_sk = c_current_cdemo_sk
and hd_demo_sk = c_current_hdemo_sk
and ca_address_sk = c_current_addr_sk
and d_year = 1999
and d_moy = 11
and ( (cd_marital_status = 'M' and cd_education_status = 'Unknown')
or(cd_marital_status = 'W' and cd_education_status = 'Advanced Degree'))
and hd_buy_potential like '0-500%'
and ca_gmt_offset = -7
group by cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status
order by sum(cr_net_loss) desc;
Query92:
select
sum(ws_ext_discount_amt) as "Excess Discount Amount"
from
web_sales
,item
,date_dim
where
i_manufact_id = 269
and i_item_sk = ws_item_sk
and d_date between '1998-03-18' and
(cast('1998-03-18' as date) + interval '90 days')
and d_date_sk = ws_sold_date_sk
and ws_ext_discount_amt
> (
SELECT
1.3 * avg(ws_ext_discount_amt)
FROM
web_sales
,date_dim
WHERE
ws_item_sk = i_item_sk
and d_date between '1998-03-18' and
(cast('1998-03-18' as date) + interval '90 days')
and d_date_sk = ws_sold_date_sk
)
order by sum(ws_ext_discount_amt)
limit 100;
Query93:
select ss_customer_sk
,sum(act_sales) sumsales
from (select ss_item_sk
,ss_ticket_number
,ss_customer_sk
,case when sr_return_quantity is not null then (ss_quantity-sr_return_quantity)*ss_sales_price
else (ss_quantity*ss_sales_price) end act_sales
from store_sales left outer join store_returns on (sr_item_sk = ss_item_sk
and sr_ticket_number = ss_ticket_number)
,reason
where sr_reason_sk = r_reason_sk
and r_reason_desc = 'Did not like the warranty') t
group by ss_customer_sk
order by sumsales, ss_customer_sk
limit 100;
Query94:
select
count(distinct ws_order_number) as "order count"
,sum(ws_ext_ship_cost) as "total shipping cost"
,sum(ws_net_profit) as "total net profit"
from
web_sales ws1
,date_dim
,customer_address
,web_site
where
d_date between '1999-5-01' and
(cast('1999-5-01' as date) + interval '60 days')
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
and ca_state = 'TX'
and ws1.ws_web_site_sk = web_site_sk
and web_company_name = 'pri'
and exists (select *
from web_sales ws2
where ws1.ws_order_number = ws2.ws_order_number
and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
and not exists(select *
from web_returns wr1
where ws1.ws_order_number = wr1.wr_order_number)
order by count(distinct ws_order_number)
limit 100;
Query95:
with ws_wh as
(select ws1.ws_order_number,ws1.ws_warehouse_sk wh1,ws2.ws_warehouse_sk wh2
from web_sales ws1,web_sales ws2
where ws1.ws_order_number = ws2.ws_order_number
and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
select
count(distinct ws_order_number) as "order count"
,sum(ws_ext_ship_cost) as "total shipping cost"
,sum(ws_net_profit) as "total net profit"
from
web_sales ws1
,date_dim
,customer_address
,web_site
where
d_date between '1999-5-01' and
(cast('1999-5-01' as date) + interval '60 days')
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
and ca_state = 'TX'
and ws1.ws_web_site_sk = web_site_sk
and web_company_name = 'pri'
and ws1.ws_order_number in (select ws_order_number
from ws_wh)
and ws1.ws_order_number in (select wr_order_number
from web_returns,ws_wh
where wr_order_number = ws_wh.ws_order_number)
order by count(distinct ws_order_number)
limit 100;
Query96:
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(*)
limit 100;
Query97:
with ssci as (
select ss_customer_sk customer_sk
,ss_item_sk item_sk
from store_sales,date_dim
where ss_sold_date_sk = d_date_sk
and d_month_seq between 1212 and 1212 + 11
group by ss_customer_sk
,ss_item_sk),
csci as(
select cs_bill_customer_sk customer_sk
,cs_item_sk item_sk
from catalog_sales,date_dim
where cs_sold_date_sk = d_date_sk
and d_month_seq between 1212 and 1212 + 11
group by cs_bill_customer_sk
,cs_item_sk)
select sum(case when ssci.customer_sk is not null and csci.customer_sk is null then 1 else 0 end) store_only
,sum(case when ssci.customer_sk is null and csci.customer_sk is not null then 1 else 0 end) catalog_only
,sum(case when ssci.customer_sk is not null and csci.customer_sk is not null then 1 else 0 end) store_and_catalog
from ssci full outer join csci on (ssci.customer_sk=csci.customer_sk
and ssci.item_sk = csci.item_sk)
limit 100;
Query98:
select i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
,sum(ss_ext_sales_price) as itemrevenue
,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over
(partition by i_class) as revenueratio
from
store_sales
,item
,date_dim
where
ss_item_sk = i_item_sk
and i_category in ('Jewelry', 'Sports', 'Books')
and ss_sold_date_sk = d_date_sk
and d_date between cast('2001-01-12' as date)
and (cast('2001-01-12' as date) + interval '30 days')
group by
i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
order by
i_category
,i_class
,i_item_id
,i_item_desc
,revenueratio;
Query99:
select
substr(w_warehouse_name,1,20)
,sm_type
,cc_name
,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and
(cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and
(cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and
(cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
catalog_sales
,warehouse
,ship_mode
,call_center
,date_dim
where
d_month_seq between 1212 and 1212 + 11
and cs_ship_date_sk = d_date_sk
and cs_warehouse_sk = w_warehouse_sk
and cs_ship_mode_sk = sm_ship_mode_sk
and cs_call_center_sk = cc_call_center_sk
group by
substr(w_warehouse_name,1,20)
,sm_type
,cc_name
order by substr(w_warehouse_name,1,20)
,sm_type
,cc_name
