SparkSQL电商用户画像(七)之用户画像开发(客户消费订单表)
2021/5/18 19:27:43
本文主要是介绍SparkSQL电商用户画像(七)之用户画像开发(客户消费订单表),对大家解决编程问题具有一定的参考价值,需要的程序猿们随着小编来一起学习吧!
--用户画像 客户消费订单表 create database if not exists gdm; create table if not exists gdm.itcast_gdm_user_consume_order( user_id string, --客户ID first_order_time timestamp, --第一次消费时间 last_order_time timestamp, --最近一次消费时间 first_order_ago bigint, --首单距今时间 last_order_ago bigint, --尾单距今时间 month1_hg_order_cnt bigint, --近30天购买次数(不含退拒) month1_hg_order_amt double, --近30天购买金额(不含退拒) month2_hg_order_cnt bigint, --近60天购买次数(不含退拒) month2_hg_order_amt double, --近60天购买金额(不含退拒) month3_hg_order_cnt bigint, --近90天购买次数(不含退拒) month3_hg_order_amt double, --近90天购买金额(不含退拒) month1_order_cnt bigint, --近30天购买次数(含退拒) month1_order_amt double, --近30天购买金额(含退拒) month2_order_cnt bigint, --近60天购买次数(含退拒) month2_order_amt double, --近60天购买金额(含退拒) month3_order_cnt bigint, --近90天购买次数(含退拒) month3_order_amt double, --近90天购买金额(含退拒) max_order_amt double, --最大消费金额 min_order_amt double, --最小消费金额 total_order_cnt bigint, --累计消费次数(不含退拒) total_order_amt double, --累计消费金额(不含退拒) user_avg_amt double, --客单价(含退拒) month3_user_avg_amt double, --近90天的客单价 common_address string, --常用收货地址 common_paytype string, --常用支付方式 month1_cart_cnt bigint, --近30天购物车的次数 month1_cart_goods_cnt bigint, --近30天购物车商品件数 month1_cart_submit_cnt bigint, --近30天购物车提交商品件数 month1_cart_rate double, --近30天购物车成功率 month1_cart_cancle_cnt double, --近30天购物车放弃件数 return_cnt bigint, --退货商品数量 return_amt double, --退货商品金额 reject_cnt bigint, --拒收商品数量 reject_amt double, --拒收商品金额 last_return_time timestamp, --最近一次退货时间 school_order_cnt bigint, --学校下单总数 company_order_cnt bigint, --单位下单总数 home_order_cnt bigint, --家里下单总数 forenoon_order_cnt bigint, --上午下单总数 afternoon_order_cnt bigint, --下午下单总数 night_order_cnt bigint, --晚上下单总数 morning_order_cnt bigint, --凌晨下单总数 dw_date timestamp ) partitioned by (dt string);
---客户消费订单模型表-临时表01 drop table if exists gdm.itcast_gdm_user_consume_order_temp_01; CREATE TABLE gdm.itcast_gdm_user_consume_order_temp_01 AS SELECT t.user_id, MIN(order_date) first_order_time,--第一次消费时间 MAX(order_date) last_order_time,--最近一次消费时间 DATEDIFF(MIN(order_date), '2017-01-01') first_order_ago,--首单距今时间 DATEDIFF(MAX(order_date), '2017-01-01') last_order_ago,--尾单距今时间 SUM( CASE WHEN t.dat_30 = 1 AND t.order_flag = 0 THEN 1 END ) month1_hg_order_cnt,--近30天购买次数(不含退拒) SUM( CASE WHEN t.dat_30 = 1 AND t.order_flag = 0 THEN t.order_money END ) month1_hg_order_amt,--近30天购买金额(不含退拒) SUM( CASE WHEN t.dat_60 = 1 AND t.order_flag = 0 THEN 1 END ) month2_hg_order_cnt,--近60天购买次数(不含退拒) SUM( CASE WHEN t.dat_60 = 1 AND t.order_flag = 0 THEN t.order_money END ) month2_hg_order_amt,--近60天购买金额(不含退拒) SUM( CASE WHEN t.dat_90 = 1 AND t.order_flag = 0 THEN 1 END ) month3_hg_order_cnt,--近90天购买次数(不含退拒) SUM( CASE WHEN t.dat_90 = 1 AND t.order_flag = 0 THEN t.order_money END ) month3_hg_order_amt,--近90天购买金额(不含退拒) SUM(dat_30) month1_order_cnt,--近30天购买次数(含退拒) SUM( CASE WHEN t.dat_30 = 1 THEN t.order_money END ) month1_order_amt,--近30天购买金额(含退拒) SUM(dat_60) month2_order_cnt,--近60天购买次数(含退拒) SUM( CASE WHEN t.dat_60 = 1 THEN t.order_money END ) month2_order_amt,--近60天购买金额(含退拒) SUM(dat_90) month3_order_cnt,--近90天购买次数(含退拒) SUM( CASE WHEN t.dat_90 = 1 THEN t.order_money END ) month3_order_amt,--近90天购买金额(含退拒) MAX(t.order_money) max_order_amt,--最大消费金额 MIN(t.order_money) min_order_amt,--最小消费金额 SUM( CASE WHEN t.order_flag = 0 THEN 1 END ) total_order_cnt,--累计消费次数(不含退拒) SUM( CASE WHEN t.order_flag = 0 THEN t.order_money END ) total_order_amt,--累计消费金额(不含退拒) SUM(coupon_money) total_coupon_amt,--累计使用代金券金额 SUM(t.order_money) / COUNT(1) user_avg_amt,--客单价(含退拒) 0 month3_user_avg_amt,--近90天的客单价(含退拒) 0 common_address,--常用收获地址 0 common_paytype,--常用支付方式 0 month1_cart_cnt,--最近30天购物车次数 0 month1_cart_goods_cnt,--最近30天购物车商品件数 0 month1_cart_submit_cnt,--最近30天购物车提交商品件数 0 month1_order_rate,--最近30天购物车成功率 0 month1_cart_cancle_cnt,--最近30天购物车放弃件数 SUM( CASE WHEN t.order_status = 3 THEN t1.goods_amount END ) return_cnt,--退货商品数量 SUM( CASE WHEN t.order_status = 3 THEN t.order_money END ) return_amt,--退货商品金额 SUM( CASE WHEN t.order_status = 4 THEN t1.goods_amount END ) reject_cnt,--拒收商品数量 SUM( CASE WHEN t.order_status = 4 THEN t.order_money END ) reject_amt,--拒收商品金额 MAX( CASE WHEN t.order_status = 3 THEN t.order_date END ) last_return_time,--最近一次退货时间 SUM( CASE WHEN t2.order_addr = 1 THEN 1 END ) school_order_cnt,--学校下单总数 SUM( CASE WHEN t2.order_addr = 2 THEN 1 END ) company_order_cnt,--单位下单总数 SUM( CASE WHEN t2.order_addr = 3 THEN 1 END ) home_order_cnt,--家里下单总数 SUM( CASE WHEN t.order_hour >= 8 AND t.order_hour <= 11 THEN 1 END ) forenoon_order_cnt,--上午下单总数 SUM( CASE WHEN t.order_hour >= 12 AND t.order_hour <= 18 THEN 1 END ) afternoon_order_cnt,--下午下单总数 SUM( CASE WHEN t.order_hour >= 19 AND t.order_hour <= 22 THEN 1 END ) night_order_cnt,--晚上下单总数 SUM( CASE WHEN t.order_hour >= 23 AND t.order_hour <= 7 THEN 1 END ) morning_order_cnt --凌晨下单总数 FROM (SELECT a.*, ( CASE WHEN order_date >= DATE_SUB('2017-01-01', 29) AND order_date <= '2017-01-01' THEN 1 END ) dat_30, ( CASE WHEN order_date >= DATE_SUB('2017-01-01', 59) AND order_date <= '2017-01-01' THEN 1 END ) dat_60, ( CASE WHEN order_date >= DATE_SUB('2017-01-01', 89) AND order_date <= '2017-01-01' THEN 1 END ) dat_90, ( CASE WHEN a.order_status IN (3, 4) THEN 1 ELSE 0 END ) order_flag,--退货与拒收标示 HOUR(order_date) order_hour FROM gdm.itcast_gdm_order a WHERE dt = '2017-01-01') t LEFT JOIN (SELECT order_id, goods_amount FROM fdm.itcast_fdm_order_goods) t1 ON (t.order_id = t1.order_id) LEFT JOIN (SELECT user_id, order_addr FROM gdm.itcast_user_order_addr_model) t2 ON (t.user_id = t2.user_id) GROUP BY t.user_id ;
---购物车临时模型表--临时表02 DROP TABLE IF EXISTS gdm.itcast_gdm_user_consume_order_temp_02; CREATE TABLE gdm.itcast_gdm_user_consume_order_temp_02 AS SELECT user_id, COUNT(1) month1_cart_cnt,--最近30天购物车次数 SUM(goods_num) month1_cart_goods_cnt,--最近30天购物车商品件数 SUM( CASE WHEN sumbit_time <> '' THEN goods_num ELSE 0 END ) month1_cart_submit_cnt,--最近30天购物车提交商品件数 '' month1_cart_rate,--最近30天购物车成功率 SUM( CASE WHEN cancle_time <> '' THEN goods_num ELSE 0 END ) month1_cart_cancle_cnt --最近30天购物车放弃件数 FROM fdm.itcast_fdm_order_cart WHERE dt = '2017-01-01' AND to_date (add_time) >= DATE_SUB('2017-01-01', 29) AND to_date (add_time) <= '2017-01-01' GROUP BY user_id ;
---购物车临时模型表---常用地址和常用支付方式-临时表03 drop table if exists gdm.itcast_gdm_user_consume_order_temp_03; create table gdm.gdm_user_consume_order_temp_03 as select t.user_id, t.con, t.type, t.cnt from (select b.user_id, b.con, b.type, b.cnt, row_number() over(distribute by b.user_id, b.type sort by b.cnt, b.type desc) rn from (select a.user_id,concat( coalesce(area_name, ''), coalesce(address, '')) con, 'address' type, count(1) cnt from gdm.itcast_gdm_order a where dt = '2017-01-01' group by a.user_id, concat( coalesce(area_name, ''), coalesce(address, '') ) union all select a.user_id, a.pay_type con, 'pay_type' type, count(1) cnt from gdm.itcast_gdm_order a where dt = '2017-01-01' group by a.user_id, a.pay_type) b) t where t.rn = 1 ;
--购物车表和订单表整合 drop table if exists gdm.itcast_gdm_user_consume_order_temp_100; create table gdm.gdm_user_consume_order_temp_100 as select a.user_id from (select user_id from gdm.itcast_gdm_user_consume_order_temp_01 union all select user_id from gdm.itcast_gdm_user_consume_order_temp_02) a group by a.user_id ;
--生成最终的客户消费订单表 INSERT overwrite TABLE gdm.itcast_gdm_user_consume_order PARTITION (dt = '2017-01-01') SELECT t.user_id, --客户ID t1.first_order_time, --常用地址和常用支付方式次消费时间 t1.last_order_time, --最近一次消费时间 t1.first_order_ago, --首单距今时间 t1.last_order_ago, --尾单距今时间 t1.month1_hg_order_cnt,--近30天购买次数(不含退拒) t1.month1_hg_order_amt,--近30天购买金额(不含退拒) t1.month2_hg_order_cnt,--近60天购买次数(不含退拒) t1.month2_hg_order_amt,--近60天购买金额(不含退拒) t1.month3_hg_order_cnt,--近90天购买次数(不含退拒) t1.month3_hg_order_amt,--近90天购买金额(不含退拒) t1.month1_order_cnt, --近30天购买次数(含退拒) t1.month1_order_amt, --近30天购买金额(含退拒) t1.month2_order_cnt, --近60天购买次数(含退拒) t1.month2_order_amt, --近60天购买金额(含退拒) t1.month3_order_cnt, --近90天购买次数(含退拒) t1.month3_order_amt, --近90天购买金额(含退拒) t1.max_order_amt, --最大消费金额 t1.min_order_amt, --最小消费金额 t1.total_order_cnt, --累计消费次数(不含退拒) t1.total_order_amt, --累计消费金额(不含退拒) t1.user_avg_amt, --客单价(含退拒) ( CASE WHEN t1.month3_order_cnt <> 0 THEN t1.month3_order_amt / t1.month3_order_cnt ELSE 0 END ) month3_user_avg_amt, --近90天的客单价(含退拒) t3.common_address, --常用收货地址 t3.common_paytype, --常用支付方式 t2.month1_cart_cnt, --近30天购物车的次数 t2.month1_cart_goods_cnt, --近30天购物车商品件数 t2.month1_cart_submit_cnt, --近30天购物车提交商品件数 ( CASE WHEN t1.month1_order_cnt <> 0 THEN t2.month1_cart_submit_cnt / t2.month1_cart_goods_cnt ELSE 0 END ) month1_cart_rate, --近30天购物车成功率 t2.month1_cart_cancle_cnt, --近30天购物车放弃件数 t1.return_cnt, --退货商品数量 t1.return_amt, --退货商品金额 t1.reject_cnt, --拒收商品数量 t1.reject_amt, --拒收商品金额 t1.last_return_time, --最近一次退货时间 t1.school_order_cnt, --学校下单总数 t1.company_order_cnt, --单位下单总数 t1.home_order_cnt, --家里下单总数 t1.forenoon_order_cnt, --上午下单总数 t1.afternoon_order_cnt, --下午下单总数 t1.night_order_cnt, --晚上下单总数 t1.morning_order_cnt, --凌晨下单总数 FROM_UNIXTIME(UNIX_TIMESTAMP()) dw_date FROM gdm.itcast_gdm_user_consume_order_temp_100 t LEFT JOIN gdm.itcast_gdm_user_consume_order_temp_01 t1 ON (t.user_id = t1.user_id) LEFT JOIN gdm.itcast_gdm_user_consume_order_temp_02 t2 ON (t.user_id = t2.user_id) LEFT JOIN (SELECT user_id, MAX( CASE WHEN type = 'address' THEN con END ) common_address, MAX( CASE WHEN type = 'pay_type' THEN con END ) common_paytype FROM gdm.itcast_gdm_user_consume_order_temp_03 GROUP BY user_id) t3 ON (t.user_id = t3.user_id);
这篇关于SparkSQL电商用户画像(七)之用户画像开发(客户消费订单表)的文章就介绍到这儿,希望我们推荐的文章对大家有所帮助,也希望大家多多支持为之网!
- 2024-11-27消息中间件底层原理资料详解
- 2024-11-27RocketMQ底层原理资料详解:新手入门教程
- 2024-11-27MQ底层原理资料详解:新手入门教程
- 2024-11-27MQ项目开发资料入门教程
- 2024-11-27RocketMQ源码资料详解:新手入门教程
- 2024-11-27本地多文件上传简易教程
- 2024-11-26消息中间件源码剖析教程
- 2024-11-26JAVA语音识别项目资料的收集与应用
- 2024-11-26Java语音识别项目资料:入门级教程与实战指南
- 2024-11-26SpringAI:Java 开发的智能新利器