调用准备 NVR在线并且有足够的硬盘空间（空间不足会导致无法获取名单库分组），硬盘空间可在NVR设备界面的“存储管理”中确认。 NVR下至少要有一个支持目标识别功能的SDC在线。 导入的目标base64图片数据不要超过40KB，以免图片过大导致导入失败。 接口调用前需确认好环境地址端口、URL、请求方式、请求参数字段与类型等信息。 NVR从8.1.RC1.B015版本开始就支持名单导入，SDC需要包含或能安装目标识别算法包的型号，如C2150、C2120等。

SQL20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 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 ('Sports', 'Shoes', 'Women') and cs_sold_date_sk = d_date_sk and d_date between cast('2001-03-21' as date) and (cast('2001-03-21' as date) + 30) 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;

SQL17 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 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 = '2000Q1' 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 ('2000Q1','2000Q2','2000Q3') 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 ('2000Q1','2000Q2','2000Q3') group by i_item_id ,i_item_desc ,s_state order by i_item_id ,i_item_desc ,s_state limit 100;

SQL18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 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 = 'Primary' and c_current_cdemo_sk = cd2.cd_demo_sk and c_current_addr_sk = ca_address_sk and c_birth_month in (10,1,8,7,3,5) and d_year = 1998 and ca_state in ('NE','OK','NC' ,'CO','ID','AR','MO') 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;

SQL13 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 select avg(ss_quantity) ,avg(ss_ext_sales_price) ,avg(ss_ext_wholesale_cost) ,sum(ss_ext_wholesale_cost) from store_sales ,store ,customer_demographics ,household_demographics ,customer_address ,date_dim where s_store_sk = ss_store_sk and ss_sold_date_sk = d_date_sk and d_year = 2001 and((ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'U' and cd_education_status = '4 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 = 'D' and cd_education_status = '2 yr Degree' and ss_sales_price between 50.00 and 100.00 and hd_dep_count = 1 ) or (ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'S' 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 ('IL', 'WI', 'TN') and ss_net_profit between 100 and 200 ) or (ss_addr_sk = ca_address_sk and ca_country = 'United States' and ca_state in ('MO', 'OK', 'WA') and ss_net_profit between 150 and 300 ) or (ss_addr_sk = ca_address_sk and ca_country = 'United States' and ca_state in ('NE', 'VA', 'GA') and ss_net_profit between 50 and 250 )) ;

SQL12 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 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 ('Music', 'Shoes', 'Children') and ws_sold_date_sk = d_date_sk and d_date between cast('2000-05-14' as date) and (cast('2000-05-14' as date) + 30 ) 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;

SQL7 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 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 = 'M' and cd_marital_status = 'U' and cd_education_status = 'College' and (p_channel_email = 'N' or p_channel_event = 'N') and d_year = 1999 group by i_item_id order by i_item_id limit 100;

SQL10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 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 ('Clark County','Richardson County','Tom Green County','Sullivan County','Cass 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 = 2000 and d_moy between 1 and 1+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 = 2000 and d_moy between 1 ANd 1+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 = 2000 and d_moy between 1 and 1+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;

SQL3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 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 = 125 and dt.d_moy=11 group by dt.d_year ,item.i_brand ,item.i_brand_id order by dt.d_year ,sum_agg desc ,brand_id limit 100;

SQL5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 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('2002-08-05' as date) and (cast('2002-08-05' as date) + 14 ) 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('2002-08-05' as date) and (cast('2002-08-05' as date) + 14 ) 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('2002-08-05' as date) and (cast('2002-08-05' as date) + 14 ) 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;

SQL2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 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)), 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 = 1999) 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 = 1999+1) z where d_week_seq1=d_week_seq2-53 order by d_week_seq1;

命令生成方法 TPC-DS标准99个SQL查询语句可用如下方法生成： 准备工作。生成TPC-DS查询语句前需要修改query_templates目录下的文件： 登录测试过程申请的ECS，进入/data1/script/tpcds-kit/DSGen-software-code-3.2.0rc1/query_templates目录。 1 cd /data1/script/tpcds-kit/DSGen-software-code-3.2.0rc1/query_templates 新建文件hwdws.tpl，内容为： 1 2 3 4 5 define __LIMITA = ""; define __LIMITB = ""; define __LIMITC = "limit %d"; define _BEGIN = "-- begin query " + [_QUERY] + " in stream " + [_STREAM] + " using template " + [_TEMPLATE]; define _END = "-- end query " + [_QUERY] + " in stream " + [_STREAM] + " using template " + [_TEMPLATE]; 因TPC-DS工具中SQL语句生成模板有语法错误，需修改query77.tpl，将135行的‘, coalesce(returns, 0) returns’改为‘, coalesce(returns, 0) as returns’。 执行以下命令生成查询语句。 1 ./dsqgen -input ../query_templates/templates.lst -directory ../query_templates/ -scale 1000 -dialect hwdws 执行后会生成query_0.sql文件，里面放着99个标准SQL语句，需要手动去切分成99个文件。 生成的标准查询中如下日期函数语法在DWS暂不支持，需要手动进行修改： 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 Q5: and (cast('2001-08-19' as date) + 14 days) 修改为 and (cast('2001-08-19' as date) + 14) Q12:and (cast('1999-02-28' as date) + 30 days) 修改为 and (cast('1999-02-28' as date) + 30) Q16:(cast('1999-4-01' as date) + 60 days) 修改为 (cast('1999-4-01' as date) + 60) Q20:and (cast('1998-05-05' as date) + 30 days) 修改为 and (cast('1998-05-05' as date) + 30) Q21:and d_date between (cast ('2000-05-19' as date) - 30 days) 修改为 and d_date between (cast ('2000-05-19' as date) - 30) and (cast ('2000-05-19' as date) + 30 days) 修改为 and (cast ('2000-05-19' as date) + 30) Q32:(cast('1999-02-22' as date) + 90 days) 修改为 (cast('1999-02-22' as date) + 90) Q37:and d_date between cast('1998-04-29' as date) and (cast('1998-04-29' as date) + 60 days) 修改为 and d_date between cast('1998-04-29' as date) and (cast('1998-04-29' as date) + 60) Q40:and d_date between (cast ('2002-05-10' as date) - 30 days) 修改为 and d_date between (cast ('2002-05-10' as date) - 30) and (cast ('2002-05-10' as date) + 30 days) 修改为 and (cast ('2002-05-10' as date) + 30) Q77:and (cast('1999-08-29' as date) + 30 days) 修改为 and (cast('1999-08-29' as date) + 30) Q80:and (cast('2002-08-04' as date) + 30 days) 修改为 and (cast('2002-08-04' as date) + 30) Q82:and d_date between cast('1998-01-18' as date) and (cast('1998-01-18' as date) + 60 days) 修改为 and d_date between cast('1998-01-18' as date) and (cast('1998-01-18' as date) + 60) Q92:(cast('2001-01-26' as date) + 90 days) 修改为 (cast('2001-01-26' as date) + 90) Q94:(cast('1999-5-01' as date) + 60 days) 修改为 (cast('1999-5-01' as date) + 60) Q95:(cast('1999-4-01' as date) + 60 days) 修改为 (cast('1999-4-01' as date) + 60) Q98:and (cast('2002-04-01' as date) + 30 days) 修改为 and (cast('2002-04-01' as date) + 30)

从控制台获取项目ID 在调用接口的时候，部分URL中需要填入项目编号，所以需要获取到项目编号。项目编号获取步骤如下： 登录管理控制台。 单击用户名，在下拉列表中单击“基本信息”。 在基本信息页面单击“管理我的凭证”。 在“API凭证”“我的凭证”页面的项目列表中查看项目ID。 单击用户名，在下拉列表中单击“我的凭证”“My Credential”。 在“我的凭证”“My Credential”页面的项目列表中查看项目ID。 图1 查看项目ID 图2 查看项目ID 图3 查看项目ID 图4 查看项目ID

调用API获取项目ID 项目ID可以通过调用查询指定条件下的项目信息API获取。 项目ID可以通过调用IAM服务的“查询指定条件下的项目信息”API获取。 获取项目ID的接口为“GET https://{Endpoint}/v3/projects”，其中{Endpoint}为IAM的终端节点，可以从管理员处地区和终端节点获取。接口的认证鉴权请参见认证鉴权。 响应示例如下，其中projects下的“id”即为项目ID。 { "projects": [ { "domain_id": "65382450e8f64ac0870cd180d14e684b", "is_domain": false, "parent_id": "65382450e8f64ac0870cd180d14e684b", "name": "xxxxxxxx", "description": "", "links": { "next": null, "previous": null, "self": "https://www.example.com/v3/projects/a4a5d4098fb4474fa22cd05f897d6b99" }, "id": "a4a5d4098fb4474fa22cd05f897d6b99", "enabled": true } ], "links": { "next": null, "previous": null, "self": "https://www.example.com/v3/projects" } }

调用准备 NVR在线并且有足够的硬盘空间（空间不足会导致无法获取名单库分组），硬盘空间可在NVR设备界面的“存储管理”中确认。 NVR下至少要有一个支持目标识别功能的SDC在线。 导入的目标base64图片数据不要超过40KB，以免图片过大导致导入失败。 接口调用前需确认好环境地址端口、URL、请求方式、请求参数字段与类型等信息。 NVR从8.1.RC1.B015版本开始就支持名单导入，SDC需要包含或能安装目标识别算法包的型号，如C2150、C2120等。