大数据开发-数仓ads层指标计算
ads层数据往往是最终的结果指标数据,在大屏展示,或者实时流处理时候使用,通过下面两个例子来练习业务大屏展示sql该怎么写。
1.会员分析案例
1.1 数据准备
表结构如下,其中此表是dws层以天为维度的会员表,比如每天的会员信息汇总,
use dws;drop table if exists dws.dws_member_start_day;
create table dws.dws_member_start_day(
`device_id` string, -- 设备id,来区分用户
`uid` string, -- uid
`app_v` string,
`os_type` string,
`language` string,
`channel` string,
`area` string,
`brand` string
) COMMENT '会员日启动汇总'
partitioned by(dt string)
stored as parquet;
1.2 会员指标计算
沉默会员的定义:只在安装当天启动过App,而且安装时间是在7天前
流失会员的定义:最近30天未登录的会员
1.2.1 如何计算沉默会员数
-- 拿到只启动一次的会员,后面再过滤安装时间是再7天前的,使用sum 窗口函数SELECT count(*)
FROM
(SELECT device_id,
sum(device_id) OVER (PARTITION BY device_id) AS sum_num,
dt
FROM dws.dws_member_start_day) tmp
WHERE dt <= date_add(CURRENT_DATE, -7)
AND sum_num=1
1.2.2 如何计算流失会员数
-- 拿到会员最近一次登录时间,并用row_number来过滤SELECT count(*)
FROM
(SELECT device_id,
dt,
row_number() OVER (PARTITION BY device_id
ORDER BY dt DESC) ro
FROM dws.dws_member_start_day) tmp
WHERE ro=1
AND dt >= date_add(CURRENT_DATE, -30)
2. 核心交易案例
2.1 数据准备
给定一个每日订单维度表,表结构如下图:
DROP TABLE IF EXISTS dwd.dwd_trade_orders;create table dwd.dwd_trade_orders(
`orderId` int,
`orderNo` string,
`userId` bigint,
`status` tinyint,
`productMoney` decimal,
`totalMoney` decimal,
`payMethod` tinyint,
`isPay` tinyint,
`areaId` int,
`tradeSrc` tinyint,
`tradeType` int,
`isRefund` tinyint,
`dataFlag` tinyint,
`createTime` string,
`payTime` string,
`modifiedTime` string,
`start_date` string,
`end_date` string
) COMMENT '订单事实拉链表'
partitioned by (dt string)
STORED AS PARQUET;
其中,订单状态 -3 用户拒收 -2未付款的订单 -1用户取消 0 待发货 1配送中 2用户确认收货,订单有效标志 -1 删除 1 有效
数据预处理,在明细事实拉链表处理时不太方便,可以做一张中间表,dws_trade_orders_day
其表结构和加工如下:
DROP TABLE IF EXISTS dws.dws_trade_orders_day;CREATE TABLE IF NOT EXISTS dws.dws_trade_orders_day(day_dt string COMMENT '日期:yyyy-MM-dd',
day_cnt decimal commnet '日订单笔数',
day_sum decimal COMMENT '日订单总额') COMMENT '日订单统计表';
SELECT dt,
count(*) cnt,
sum(totalMoney) sm
FROM
(SELECT DISTINCT orderid,
dt,
totalMoney
FROM dwd.dwd_trade_orders
WHERE status >= 0
AND dataFlag = '1') tmp
GROUP BY dt;
INSERT OVERWRITE TABLE dws.dws_trade_orders_day
SELECT dt,
count(*) cnt,
sum(totalMoney) sm
FROM
(SELECT DISTINCT orderid,
dt,
totalMoney
FROM dwd.dwd_trade_orders
WHERE status >= 0
AND dataFlag = '1') tmp
GROUP BY dt;
SELECT *
FROM dws.dws_trade_orders_day
WHERE day_dt BETWEEN '2020-01-01' AND '2020-12-31';
2.2 指标1,统计2020年每个季度的销售订单笔数、订单总额
先创建ads指标表:dws_trade_orders_quarter
DROP TABLE IF EXISTS dws.dws_trade_orders_quarter;CREATE TABLE IF NOT EXISTS dws.dws_trade_orders_quarter(YEAR string COMMENT '年份',
QUARTER string COMMENT '季度',
cnt decimal COMMENT '订单总笔数',
SUM decimal COMMENT '订单总额') COMMENT '季度订单统计表';
INSERT OVERWRITE TABLE dws.dws_trade_orders_quarter WITH tmp AS
(SELECT substr(day_dt, 0, 4) YEAR,
CASE WHEN substr(dat_dt, 6, 2)="01"
OR substr(dat_dt, 6, 2)="02"
OR substr(day_dt, 6, 2)="03" THEN "1" WHEN substr(dat_dt, 6, 2)="04"
OR substr(dat_dt, 6, 2)="05"
OR substr(day_dt, 6, 2)="06" THEN "2" WHEN substr(dat_dt, 6, 2)="07"
OR substr(dat_dt, 6, 2)="08"
OR substr(day_dt, 6, 2)="09" THEN "3" WHEN substr(dat_dt, 6, 2)="10"
OR substr(dat_dt, 6, 2)="11"
OR substr(day_dt, 6, 2)="12" THEN "4" AS QUARTER day_cnt,
day_sum
FROM dws.dws_trade_orders_day)
SELECT YEAR,
QUARTER,
sum(day_cnt),
sum(day_sum)
FROM tmp
GROUP BY YEAR QUARTER;
2.3 统计2020年每个月的销售订单笔数、订单总额
先创建ads指标表:dws_trade_orders_month
DROP TABLE IF EXISTS dws.dws_trade_orders_month;CREATE TABLE IF NOT EXISTS dws.dws_trade_orders_month(yearstring COMMENT '年份',
MONTH string COMMENT '月份',
month_cnt decimal COMMENT '月订单总笔数',
month_sum decimal COMMENT '月订单总额') COMMENT '月订单统计表';
INSERT OVERWRITE TABLE dws.dws_trade_orders_month WITH tmp AS
(SELECT substr(day_dt, 0, 4) YEAR,
sunstr(day_dt, 6, 2) MONTH,
day_cnt,
day_sum
FROM dws.dws_trade_orders_day)
SELECT YEAR,
MONTH,
sum(day_cnt) month_cnt,
sum(day_sum) month_sum
FROM tmp
GROUP BY YEAR,
MONTH;
2.4 统计2020年每周(周一到周日)的销售订单笔数、订单总额
创建ads层指标表:dws_trade_orders_week
利用到日期函数weekofyear
DROP TABLE IF EXISTS dws.dws_trade_orders_week;CREATE TABLE IF NOT EXISTS dws.dws_trade_orders_week(YEAR string COMMENT '年份',
WEEK string COMMENT '一年中的第几周',
week_cnt decimal COMMENT '周订单总笔数',
week_sum decimal COMMENT '周订单总额') COMMENT '周订单统计表';
INSERT OVERWRITE TABLE dws.dws_trade_orders_week
SELECT substr(day_dt, 0, 4) YEAR,
weekofyear(day_dt) WEEK,
sum(day_cnt),
sum(day_sum)
FROM dws.dws_trade_orders_day
GROUP BY substr(day_dt, 0, 4) YEAR,
weekofyear(day_dt) WEEK;
2.5 统计2020年国家法定节假日、休息日、工作日的订单笔数、订单总额
创建日期信息维表:dim_day_info
并录入节假日信息数据(数据每年都不一样,需要国务院通知的公告,所以定期手动维护)
drop table if exists dim.dim_day_info;create table if not exists dim.dim_day_info(
day_dt string comment '日期',
is_holidays int comment '节假日标识: 0不是 1是',
is_workday int comment '工作日标识 0不是 1是'
) comment '日期信息表';
-- 统计2020节假日的订单笔数,订单总额SELECT nvl(sum(day_cnt), 0) nvl(sum(day_sum), 0)
FROM dws.dws_trade_orders_day A
LEFT JOIN dim.dim_day_info B ON A.day_dt = B.day_dt
WHERE B.is_holiday = 1;
-- 统计2020年休息日的订单笔数,订单总额
SELECT nvl(sum(day_cnt), 0) nvl(sum(day_sum), 0)
FROM dws.dws_trade_orders_day A
LEFT JOIN dim.dim_day_info B ON A.day_dt = B.day_dt
WHERE B.is_workday = 0;
-- 统计2020节工作日的订单笔数,订单总额
SELECT nvl(sum(day_cnt), 0) nvl(sum(day_sum), 0)
FROM dws.dws_trade_orders_day A
LEFT JOIN dim.dim_day_info B ON A.day_dt = B.day_dt
WHERE B.is_workday = 1;
吴邪,小三爷,混迹于后台,大数据,人工智能领域的小菜鸟。
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