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文库吧 > IT > 前沿技术 > 云计算 > 云平台

电商离线数仓(二)

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电商离线数仓(二)

需求一 用户活跃主题(日活、周活、月活)

涉及知识点:concat、concat_ws、collect_set、date_add、next_day、last_day、date_format、hive动态分区、if函数

1、dws层dws_uv_detail_day、dws_uv_detail_wk、dws_uv_detail_mn,ads层的ads_uv_count

--需求一:用户活跃主题
--dws层的日活跃(DAU)
create external table dws_uv_detail_day(
    `mid_id` string COMMENT '设备唯一标识',
    `user_id` string COMMENT '用户标识', 
    `version_code` string COMMENT '程序版本号', 
    `version_name` string COMMENT '程序版本名', 
    `lang` string COMMENT '系统语言', 
    `source` string COMMENT '渠道号', 
    `os` string COMMENT '安卓系统版本', 
    `area` string COMMENT '区域', 
    `model` string COMMENT '手机型号', 
    `brand` string COMMENT '手机品牌', 
    `sdk_version` string COMMENT 'sdkVersion', 
    `gmail` string COMMENT 'gmail', 
    `height_width` string COMMENT '屏幕宽高',
    `app_time` string COMMENT '客户端日志产生时的时间',
    `network` string COMMENT '网络模式',
    `lng` string COMMENT '经度',
    `lat` string COMMENT '纬度'
)partitioned by(dt string)

insert overwrite table dws_uv_detail_day partition(dt='2022-04-12')
select mid_id,
	concat_ws('|', collect_set(user_id)) user_id,
    concat_ws('|', collect_set(version_code)) version_code,
    concat_ws('|', collect_set(version_name)) version_name,
    concat_ws('|', collect_set(lang))lang,
    concat_ws('|', collect_set(source)) source,
    concat_ws('|', collect_set(os)) os,
    concat_ws('|', collect_set(area)) area, 
    concat_ws('|', collect_set(model)) model,
    concat_ws('|', collect_set(brand)) brand,
    concat_ws('|', collect_set(sdk_version)) sdk_version,
    concat_ws('|', collect_set(gmail)) gmail,
    concat_ws('|', collect_set(height_width)) height_width,
    concat_ws('|', collect_set(app_time)) app_time,
    concat_ws('|', collect_set(network)) network,
    concat_ws('|', collect_set(lng)) lng,
    concat_ws('|', collect_set(lat)) lat
from dwd_start_log where dt='2022-04-12' group by mid_id;

-- next_day 获取指定时间的下周几是几号
select next_day('2022-05-03','mo')

-- date_add 对指定时间进行加减操作
select date_add('2022-05-03',+7)

-- 本周一到周日
select date_add(next_day('2022-04-02','MO'),-7)
select date_add(next_day('2022-04-02','MO'),-1)

--dws层的周活跃
create external table dws_uv_detail_wk( 
    `mid_id` string COMMENT '设备唯一标识',
    `user_id` string COMMENT '用户标识', 
    `version_code` string COMMENT '程序版本号', 
    `version_name` string COMMENT '程序版本名', 
    `lang` string COMMENT '系统语言', 
    `source` string COMMENT '渠道号', 
    `os` string COMMENT '安卓系统版本', 
    `area` string COMMENT '区域', 
    `model` string COMMENT '手机型号', 
    `brand` string COMMENT '手机品牌', 
    `sdk_version` string COMMENT 'sdkVersion', 
    `gmail` string COMMENT 'gmail', 
    `height_width` string COMMENT '屏幕宽高',
    `app_time` string COMMENT '客户端日志产生时的时间',
    `network` string COMMENT '网络模式',
    `lng` string COMMENT '经度',
    `lat` string COMMENT '纬度',
    `monday_date` string COMMENT '周一日期',
    `sunday_date` string COMMENT  '周日日期' 
) COMMENT '活跃用户按周明细'
PARTITIONED BY (`wk_dt` string)

--将动态分区设置为非严格模式
set hive.exec.dynamic.partition.mode=nonstrict;

insert overwrite table dws_uv_detail_wk partition(wk_dt)
select mid_id,
	concat_ws('|', collect_set(user_id)) user_id,
    concat_ws('|', collect_set(version_code)) version_code,
    concat_ws('|', collect_set(version_name)) version_name,
    concat_ws('|', collect_set(lang)) lang,
    concat_ws('|', collect_set(source)) source,
    concat_ws('|', collect_set(os)) os,
    concat_ws('|', collect_set(area)) area, 
    concat_ws('|', collect_set(model)) model,
    concat_ws('|', collect_set(brand)) brand,
    concat_ws('|', collect_set(sdk_version)) sdk_version,
    concat_ws('|', collect_set(gmail)) gmail,
    concat_ws('|', collect_set(height_width)) height_width,
    concat_ws('|', collect_set(app_time)) app_time,
    concat_ws('|', collect_set(network)) network,
    concat_ws('|', collect_set(lng)) lng,
    concat_ws('|', collect_set(lat)) lat,
	date_add(next_day('2022-04-12','MO'),-7),
    date_add(next_day('2022-04-12','MO'),-1),
    concat(date_add(next_day('2022-04-12','MO'),-7),
    '_',date_add(next_day('2022-04-12','MO'),-1))
from dws_uv_detail_day 
where dt >= date_add(next_day('2022-04-12','MO'),-7)
and dt<= date_add(next_day('2022-04-12','MO'),-1)
group by mid_id;

select * from dws_uv_detail_wk
select wk_dt,count(*) from dws_uv_detail_wk group by wk_dt

--dws层的月活跃
drop table dws_uv_detail_mn
create external table dws_uv_detail_mn( 
    `mid_id` string COMMENT '设备唯一标识',
    `user_id` string COMMENT '用户标识', 
    `version_code` string COMMENT '程序版本号', 
    `version_name` string COMMENT '程序版本名', 
    `lang` string COMMENT '系统语言', 
    `source` string COMMENT '渠道号', 
    `os` string COMMENT '安卓系统版本', 
    `area` string COMMENT '区域', 
    `model` string COMMENT '手机型号', 
    `brand` string COMMENT '手机品牌', 
    `sdk_version` string COMMENT 'sdkVersion', 
    `gmail` string COMMENT 'gmail', 
    `height_width` string COMMENT '屏幕宽高',
    `app_time` string COMMENT '客户端日志产生时的时间',
    `network` string COMMENT '网络模式',
    `lng` string COMMENT '经度',
    `lat` string COMMENT '纬度'
) COMMENT '活跃用户按月明细'
PARTITIONED BY (`mn` string)

--测试date_format函数
select date_format('2022-05-03','yyyy-MM')

insert overwrite table dws_uv_detail_mn partition(mn)
select mid_id,
    concat_ws('|', collect_set(user_id)) user_id,
    concat_ws('|', collect_set(version_code)) version_code,
    concat_ws('|', collect_set(version_name)) version_name,
    concat_ws('|', collect_set(lang)) lang,
    concat_ws('|', collect_set(source)) source,
    concat_ws('|', collect_set(os)) os,
    concat_ws('|', collect_set(area)) area, 
    concat_ws('|', collect_set(model)) model,
    concat_ws('|', collect_set(brand)) brand,
    concat_ws('|', collect_set(sdk_version)) sdk_version,
    concat_ws('|', collect_set(gmail)) gmail,
    concat_ws('|', collect_set(height_width)) height_width,
    concat_ws('|', collect_set(app_time)) app_time,
    concat_ws('|', collect_set(network)) network,
    concat_ws('|', collect_set(lng)) lng,
    concat_ws('|', collect_set(lat)) lat,
    date_format('2022-04-12','yyyy-MM')
from dws_uv_detail_day where 
date_format(dt,'yyyy-MM')=date_format('2022-04-12','yyyy-MM')
group by mid_id;

select * from dws_uv_detail_mn

--ads层的活跃设备统计结果表
create external table ads_uv_count(
    `dt` string COMMENT '统计日期',
    `day_count` bigint COMMENT '当日用户数量',
    `wk_count`  bigint COMMENT '当周用户数量',
    `mn_count`  bigint COMMENT '当月用户数量',
    `is_weekend` string COMMENT 'Y,N是否是周末,用于得到本周最终结果',
    `is_monthend` string COMMENT 'Y,N是否是月末,用于得到本月最终结果' 
) COMMENT '活跃设备数'
row format delimited fields terminated by 't'

--测试if函数
select if('2022-05-08'=date_add(next_day('2022-05-03','mo'),-1),'Y','N')
--last_day()返回本月最后一天
select last_day('2022-05-08')

insert into table ads_uv_count
select '2022-04-12' dt,t1.c,t2.cc,t3.ccc,
if('2022-04-12'=date_add(next_day('2022-04-12','mo'),-1),'Y','N'),
if('2022-04-12'=last_day('2022-04-12'),'Y','N')
from
(select '2022-04-12' dt,count(*) c 
from dws_uv_detail_day where dt='2022-04-12') t1
left join
(select '2022-04-12' dt,count(*) cc 
from dws_uv_detail_wk where 
wk_dt = concat(date_add(next_day('2022-04-12','mo'),-7),
'_' ,date_add(next_day('2022-04-12','mo'),-1))) t2
on t1.dt = t2.dt left join
(select '2022-04-12' dt,count(*) ccc 
from dws_uv_detail_mn
where mn=date_format('2022-04-12','yyyy-MM')) t3
on t2.dt = t3.dt

 需求二 用户新增主题(每日新增)
--dws层的每日新增
create external table dws_new_mid_day
(
    `mid_id` string COMMENT '设备唯一标识',
    `user_id` string COMMENT '用户标识', 
    `version_code` string COMMENT '程序版本号', 
    `version_name` string COMMENT '程序版本名', 
    `lang` string COMMENT '系统语言', 
    `source` string COMMENT '渠道号', 
    `os` string COMMENT '安卓系统版本', 
    `area` string COMMENT '区域', 
    `model` string COMMENT '手机型号', 
    `brand` string COMMENT '手机品牌', 
    `sdk_version` string COMMENT 'sdkVersion', 
    `gmail` string COMMENT 'gmail', 
    `height_width` string COMMENT '屏幕宽高',
    `app_time` string COMMENT '客户端日志产生时的时间',
    `network` string COMMENT '网络模式',
    `lng` string COMMENT '经度',
    `lat` string COMMENT '纬度',
    `create_date`  string  comment '创建时间' 
)  COMMENT '每日新增设备信息'

select * from dws_new_mid_day 

insert into table dws_new_mid_day
select 
    u.mid_id,
    u.user_id , 
    u.version_code , 
    u.version_name , 
    u.lang , 
    u.source, 
    u.os, 
    u.area, 
    u.model, 
    u.brand, 
    u.sdk_version, 
    u.gmail, 
    u.height_width,
    u.app_time,
    u.network,
    u.lng,
    u.lat,
    '2022-04-12'
from dws_uv_detail_day u left join dws_new_mid_day n
on u.mid_id = n.mid_id 
where u.dt = '2022-04-12' and n.mid_id is null;

--ads层的每日新增统计
create external table ads_new_mid_count(
`create_date`   string comment '创建时间',
`new_mid_count` BIGINT comment '新增设备数量'
) COMMENT '每日新增设备信息数量'
row format delimited
fields terminated by 't'

select * from ads_new_mid_count

insert into table ads_new_mid_count
select create_date,count(*) 
from dws_new_mid_day 
where create_date='2022-04-12'
group by create_date;
需求三 用户留存主题(一日、二日、三日留存)
-- dws层用户每日新增
create external table dws_user_retention_day
(
    `mid_id` string COMMENT '设备唯一标识',
    `user_id` string COMMENT '用户标识', 
    `version_code` string COMMENT '程序版本号', 
    `version_name` string COMMENT '程序版本名', 
    `lang` string COMMENT '系统语言', 
    `source` string COMMENT '渠道号', 
    `os` string COMMENT '安卓系统版本', 
    `area` string COMMENT '区域', 
    `model` string COMMENT '手机型号', 
    `brand` string COMMENT '手机品牌', 
    `sdk_version` string COMMENT 'sdkVersion', 
    `gmail` string COMMENT 'gmail', 
    `height_width` string COMMENT '屏幕宽高',
    `app_time` string COMMENT '客户端日志产生时的时间',
    `network` string COMMENT '网络模式',
    `lng` string COMMENT '经度',
    `lat` string COMMENT '纬度',
   `create_date`    string  comment '设备新增时间',
   `retention_day`  int comment '截止当前日期留存天数'
)  COMMENT '每日用户留存情况'
PARTITIONED BY (`dt` string)

select * from dws_user_retention_day

-- 求出4.1——1日、2日、3日留存情况
insert overwrite table dws_user_retention_day
partition(dt='2022-04-05')
select
    nm.mid_id,
    nm.user_id,
    nm.version_code,
    nm.version_name,
    nm.lang,
    nm.source,
    nm.os,
    nm.area,
    nm.model,
    nm.brand,
    nm.sdk_version,
    nm.gmail,
    nm.height_width,
    nm.app_time,
    nm.network,
    nm.lng,
    nm.lat,
    nm.create_date,
    1 retention_day 
from dws_uv_detail_day ud join dws_new_mid_day nm  on ud.mid_id =nm.mid_id 
where ud.dt='2022-04-05' and nm.create_date=date_add('2022-04-05',-1)
union all
select  
    nm.mid_id,
    nm.user_id , 
    nm.version_code , 
    nm.version_name , 
    nm.lang , 
    nm.source, 
    nm.os, 
    nm.area, 
    nm.model, 
    nm.brand, 
    nm.sdk_version, 
    nm.gmail, 
    nm.height_width,
    nm.app_time,
    nm.network,
    nm.lng,
    nm.lat,
    nm.create_date,
    2 retention_day 
from  dws_uv_detail_day ud join dws_new_mid_day nm   on ud.mid_id =nm.mid_id 
where ud.dt='2022-04-05' and nm.create_date=date_add('2022-04-05',-2)
union all
select  
    nm.mid_id,
    nm.user_id,
    nm.version_code,
    nm.version_name,
    nm.lang, 
    nm.source, 
    nm.os, 
    nm.area, 
    nm.model, 
    nm.brand, 
    nm.sdk_version, 
    nm.gmail, 
    nm.height_width,
    nm.app_time,
    nm.network,
    nm.lng,
    nm.lat,
    nm.create_date,
    3 retention_day 
from  dws_uv_detail_day ud join dws_new_mid_day nm   on ud.mid_id =nm.mid_id 
where ud.dt='2022-04-05' and nm.create_date=date_add('2022-04-05',-3);

--ads用户留存统计表
create external table ads_user_retention_day_count(
`create_date`       string  comment '设备新增日期',
`retention_day`     int comment '截止当前日期留存天数',
`retention_count`    bigint comment  '留存数量'
)  COMMENT '每日用户留存情况'
row format delimited fields terminated by 't'

select * from ads_user_retention_day_count

insert into table ads_user_retention_day_count 
select 
  create_date,
  retention_day,
  count(*) retention_count
from dws_user_retention_day where dt='2022-04-05'
group by create_date,retention_day;

--asd 用户留存率
create external table ads_user_retention_day_rate 
(
`stat_date`          string comment '统计日期',
`create_date`        string  comment '设备新增日期',
`retention_day`      int comment '截止当前日期留存天数',
`retention_count`    bigint comment  '留存数量',
`new_mid_count`      bigint comment '当日设备新增数量',
`retention_ratio`    decimal(10,2) comment '留存率'
)  COMMENT '每日用户留存情况'
row format delimited fields terminated by 't'

insert into table ads_user_retention_day_rate 
select
  '2022-04-05',
  t1.create_date,
  t1.retention_day,
  t1.retention_count,
  t2.new_mid_count,
  t1.retention_count / t2.new_mid_count * 100
from ads_user_retention_day_count t1
join ads_new_mid_count t2
on t1.create_date = t2.create_date
where date_add(t1.create_date,t1.retention_day) = '2022-04-05'

select * from ads_user_retention_day_rate

 需求四 沉默用户主题
--ads层的沉默用户表
create external table ads_silent_count( 
    `dt` string COMMENT '统计日期',
    `silent_count` bigint COMMENT '沉默设备数'
) row format delimited fields terminated by 't'

insert into table ads_silent_count
select '2022-04-12'dt,count(*) from (
select mid_id,count(mid_id) cc
from dws_uv_detail_day where dt<='2022-04-12'
group by mid_id having count(mid_id)=1 and 
max(dt) 
需求五 本周回流用户 
--ads层的本周回流
create external table ads_back_count( 
    `dt` string COMMENT '统计日期',
    `wk_dt` string COMMENT '统计日期所在周',
    `wastage_count` bigint COMMENT '回流设备数'
) row format delimited fields terminated by 't'

insert into table ads_back_count
select '2022-04-05' dt,concat(date_add(next_day('2022-04-05','mo'),-7),
'_',date_add(next_day('2022-04-05','mo'),-1)) wk_dt,count(*) from 
--select t.mid_id from
( select mid_id from dws_uv_detail_wk where wk_dt=
concat(date_add(next_day('2022-04-05','mo'),-7),
'_',date_add(next_day('2022-04-05','mo'),-1)) ) t
left join
( select mid_id from dws_new_mid_day 
where create_date>=date_add(next_day('2022-04-05','mo'),-7)
and create_date<=date_add(next_day('2022-04-05','mo'),-1) ) tt
on t.mid_id=tt.mid_id left join
( select mid_id from dws_uv_detail_wk where wk_dt=
concat(date_add(next_day('2022-04-05','mo'),-14),
'_',date_add(next_day('2022-04-05','mo'),-8)) ) ttt
on t.mid_id=ttt.mid_id 
where tt.mid_id is null and ttt.mid_id is null

select * from ads_back_count
需求六 流失用户数
--ads层的流失用户数
create external table ads_wastage_count(
    `dt` string COMMENT '统计日期',
    `wastage_count` bigint COMMENT '流失设备数'
)row format delimited fields terminated by 't'

select * from ads_wastage_count

insert into table ads_wastage_count
select '2022-04-12',count(*) from
( select mid_id from dws_uv_detail_day group by mid_id 
having max(dt)<=date_add('2022-04-12',-7) ) tt

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