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旅游集市数仓建设

news 2025/8/10 9:14:25

旅游集市数仓建设

小白如何从0到1成为大数据工程师

目录

旅游集市数仓建设

1.上传数据

2.可能用到的UDF函数

3.创建所需数据库及表

1）ODS层

①ods_oidd

②ods_wcdr

③ods_ddr

④ods_dpi

2）DWD层

①dwd_res_regn_mergelocation_msk_d

②dwm_staypoint_msk_d

③dws_province_tourist_msk_d

④dws_city_tourist_msk_d

⑤dws_county_tourist_msk_d

3）DIM层

①dim_usertag_msk_m

4）ADS层

1）需求矩阵

2）根据区县游客表计算如下指标

1.上传数据

cd /usr/local/soft/mkdir ctyun/cd ctyun/pwd

2.可能用到的UDF函数

cd /usr/local/soft/mkdir jars/cd jars/pwd

添加资源并注册函数

add jars /usr/local/soft/jars/jtxy_hdfs-1.0-SNAPSHOT.jar;create temporary function get_points as 'ctyun.udf.getPointsUDF';create temporary function dateBetweenUDF as 'ctyun.udf.dateBetweenUDF';create temporary function calLength as 'ctyun.udf.calLength';create temporary function get_city_or_prov_id as 'ctyun.udf.getCityIdOrProvID';

3.创建所需数据库及表

create database ods;use ods;

1）ODS层
①ods_oidd

OIDD是采集A接口的信令数据，包括手机在发生业务时的位置信息。OIDD信令类型数据分为三大 类，呼叫记录、短信记录和用户位置更新记录。

CREATE EXTERNAL TABLE IF NOT EXISTS ods.ods_oidd(mdn string comment '手机号码'  
,start_time string comment '业务开始时间'  
,county_id string comment '区县编码'  
,longi string comment '经度'  
,lati string comment '纬度'  
,bsid string comment '基站标识'  
,grid_id string comment '网格号'  
,biz_type string comment '业务类型'  
,event_type string comment '事件类型'  
,data_source string comment '数据源'  
) 
comment  'oidd位置数据表'PARTITIONED BY (day_id string comment '天分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat' 
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'  
location '/data/tour/ods/ods_oidd'; // 添加分区
alter table ods.ods_oidd add partition(day_id=20180503);// 加载数据
load data local inpath '/usr/local/soft/ctyun/ods_oidd/day_id=20180503/*' into table ods_oidd partition(day_id=20180503);

//查看数据select * from  ods.ods_oidd limit 10;

dfs -mkdir -p /data/tour/ods/ods_oidd;dfs -ls /data/tour/ods/ods_oidd;dfs -ls /data/tour/ods/;dfs -rmr /data/tour/ods/ods_oidd;

②ods_wcdr

WCDR采集网络中ABIS接口的数据，基于业务发生过程中三个扇区的测量信息，通过三角定位法 确定用户的位置信息。

CREATE EXTERNAL TABLE IF NOT EXISTS ods.ods_wcdr (mdn string comment '手机号码'  
,start_time string comment '业务开始时间'  
,county_id string comment '区县编码'  
,longi string comment '经度'  
,lati string comment '纬度'  
,bsid string comment '基站标识'  
,grid_id string comment '网格号'  
,biz_type string comment '业务类型'  
,event_type string comment '事件类型'  
,data_source string comment '数据源'  
) 
comment  'wcdr位置数据表'PARTITIONED BY (day_id string comment '天分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat' 
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'  
location '/data/tour/ods/ods_wcdr'; // 添加分区
alter table ods.ods_wcdr add partition(day_id=20180503);// 加载数据
load data local inpath '/usr/local/soft/ctyun/ods_wcdr/day_id=20180503/*' into 
table ods_wcdr partition(day_id=20180503);

//查看数据select * from ods.ods_wcdr limit 10;

③ods_ddr

当前DDR中只有移动数据详单可以提取基站标识，其他语音，短信，增值等业务没有位置信息， 不做为数据融合的基础数据。

CREATE EXTERNAL TABLE IF NOT EXISTS ods.ods_ddr(mdn string comment '手机号码'  
,start_time string comment '业务开始时间'  
,county_id string comment '区县编码'  
,longi string comment '经度'  
,lati string comment '纬度'  
,bsid string comment '基站标识'  
,grid_id string comment '网格号'  
,biz_type string comment '业务类型'  
,event_type string comment '事件类型'  
,data_source string comment '数据源'  
) 
comment  'ddr位置数据表'PARTITIONED BY (day_id string comment '天分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat' 
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'  
location '/data/tour/ods/ods_ddr'; // 添加分区
alter table ods.ods_ddr add partition(day_id=20180503);// 加载数据
load data local inpath '/usr/local/soft/ctyun/ods_ddr/day_id=20180503/*' into 
table ods_ddr partition(day_id=20180503);

// 查询数据select * from ods.ods_ddr limit 10;

④ods_dpi

移动DPI数据采集用户移动用户数据上网时移动核心网和PDSN之间接口的数据。

CREATE EXTERNAL TABLE IF NOT EXISTS ods.ods_dpi(mdn string comment '手机号码'  
,start_time string comment '业务开始时间'  
,county_id string comment '区县编码'  
,longi string comment '经度'  
,lati string comment '纬度'  
,bsid string comment '基站标识'  
,grid_id string comment '网格号'  
,biz_type string comment '业务类型'  
,event_type string comment '事件类型'  
,data_source string comment '数据源'  
) 
comment  'dpi位置数据表'PARTITIONED BY (day_id string comment '天分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat' 
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'  
location '/data/tour/ods/ods_dpi'; // 添加分区
alter table ods.ods_dpi add partition(day_id=20180503);// 加载数据
load data local inpath '/usr/local/soft/ctyun/ods_dpi/day_id=20180503/*' into 
table ods_dpi partition(day_id=20180503);

// 查询数据select * from ods.ods_dpi limit 10;

2）DWD层
create database dwd;use dwd;

①dwd_res_regn_mergelocation_msk_d

在ODS层中，由于数据来源不同，原始位置数据被分成了好几张表加载到了我们的ODS层。 为了方便大家的使用，我们在DWD层做了一张位置数据融合表，在这里，我们将oidd、wcdr、 ddr、dpi位置数据汇聚到一张表里面，统一字段名，提升数据质量，这样就有了一张可供大家方 便使用的明细表了。

CREATE EXTERNAL TABLE IF NOT EXISTS dwd.dwd_res_regn_mergelocation_msk_d (mdn string comment '手机号码'  
,start_time string comment '业务开始时间'  
,county_id string comment '区县编码'  
,longi string comment '经度'  
,lati string comment '纬度'  
,bsid string comment '基站标识'  
,grid_id string comment '网格号'  
,biz_type string comment '业务类型'  
,event_type string comment '事件类型'  
,data_source string comment '数据源'  
) 
comment  '位置数据融合表'PARTITIONED BY (day_id string comment '天分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS ORCFilelocation '/data/tour/dwd/dwd_res_regn_mergelocation_msk_d'; // 添加分区
alter table dwd.dwd_res_regn_mergelocation_msk_d add partition(day_id=20180503);

手动下载数据

// hive 直接运行速度太慢，可用手动load/put文件方式
// 手动load
// 注意 上面的建表语句文件存储格式修改为了ORCFile 所以不能直接使用下面的load方法load data local inpath '/usr/local/soft/ctyun/dwd_merge/part-00000*' into 
table dwd.dwd_res_regn_mergelocation_msk_d partition(day_id=20180503);// union allinsert into table dwd.dwd_res_regn_mergelocation_msk_d 
partition(day_id="20180503")select  mdn  ,start_time  ,county_id  ,longi  ,lati  ,bsid  ,grid_id  ,biz_type  ,event_type  ,data_source 
from ods.ods_oiddwhere day_id = "20180503"union allselect  mdn  ,start_time  ,county_id  ,longi  ,lati  ,bsid  ,grid_id  ,biz_type  ,event_type  ,data_source 
from ods.ods_wcdrwhere day_id = "20180503"union allselect  mdn  ,start_time  ,county_id  ,longi  ,lati  ,bsid  ,grid_id  ,biz_type  ,event_type  ,data_source 
from ods.ods_dpiwhere day_id = "20180503"union allselect  mdn  ,start_time  ,county_id  ,longi  ,lati  ,bsid  ,grid_id  
,biz_type  
,event_type  
,data_source 
from ods.ods_ddrwhere day_id = "20180503";

②dwm_staypoint_msk_d

计算一个人在一个网格内的停留时间，按手机号，网格id，区县id分组

1、对所有时间进行排序

2、取第一个点的开始时间和最后一个点的结束时间

create database dwm;use dwm;

CREATE EXTERNAL TABLE IF NOT EXISTS dwm.dwm_staypoint_msk_d (mdn string comment '用户手机号码'  
,longi string comment '网格中心点经度'  
,lati string comment '网格中心点纬度'  
,grid_id string comment '停留点所在电信内部网格号'  
,county_id string comment '停留点区县'  
,duration string comment '机主在停留点停留的时间长度（分钟）,lTime-eTime'  
,grid_first_time string comment '网格第一个记录位置点时间（秒级）'  
,grid_last_time string comment '网格最后一个记录位置点时间（秒级）'  
) 
comment  '停留点表'PARTITIONED BY (day_id string comment '天分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS TEXTFILElocation '/data/tour/dwm/dwm_staypoint_msk_d';

通过grid_id 网格id 获取 网格中心点经纬度 longi、lati

该SQL执行会出现问题： 执行流程一直处于 0% Map  0% reduce
/**
insert into table dwm.dwm_staypoint_msk_d partition(day_id=20180503)
select  t1.mdn,get_points(grid_id)[0] as longi,get_points(grid_id)[1] as lati,t1.grid_id,t1.county_id,dateBetweenUDF(t1.grid_first_time,t1.grid_last_time) as duration,t1.grid_first_time,t1.grid_last_time
from (select  mdn,grid_id,county_id,min(split(start_time,',')[0]) as grid_first_time,max(split(start_time,',')[1]) as grid_last_timefrom dwd.dwd_res_regn_mergelocation_msk_dwhere day_id="20180503"group by mdn, grid_id, county_id
)t1;
*/优化后的SQL：WITH split_table as (
SELECT
mdn
,grid_id
,county_id
,split(start_time,',')[1] as grid_first_time
,split(start_time,',')[0] as grid_last_time
FROM dwd.dwd_res_regn_mergelocation_msk_d
where day_id="20180503"
)
, max_min_table as (
SELECT
mdn
,grid_id
,county_id
,Max(grid_first_time) OVER(PARTITION BY mdn,grid_id,county_id) as grid_first_time
,MIN(grid_last_time) OVER(PARTITION BY mdn,grid_id,county_id) as grid_last_time
FROM split_table 
)insert into table dwm.dwm_staypoint_msk_d partition(day_id=20180503)
SELECT 
t1.mdn
,get_points(t1.grid_id)[0] as longi
,get_points(t1.grid_id)[1] as lati
,t1.grid_id
,t1.county_id
,dateBetweenUDF(t1.grid_first_time,t1.grid_last_time) as duration
,t1.grid_first_time
,t1.grid_last_time
FROM (
SELECT
mdn
,grid_id
,county_id
,grid_first_time
,grid_last_time
FROM max_min_table
group by 
mdn
,grid_id
,county_id
,grid_first_time
,grid_last_time
) t1

③dws_province_tourist_msk_d

游客定义 出行距离大于300km 常住地在用户画像表中 在省内停留时间大于3个小时

create database dws;use dws;

CREATE EXTERNAL TABLE IF NOT EXISTS dws.dws_province_tourist_msk_d (mdn string comment '手机号大写MD5加密'  
,source_county_id string comment '游客来源区县'  
,d_province_id string comment '旅游目的地省代码'  
,d_stay_time double comment '游客在该省停留的时间长度（小时）'  
,d_max_distance double comment '游客本次出游距离'  
) 
comment  '旅游应用专题数据省级别-天'PARTITIONED BY (day_id string comment '日分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS PARQUETlocation '/data/tour/dws/dws_province_tourist_msk_d';

停留点表dwm_staypoint_msk_d与用户画像维表dim_usertag_msk_m 通过mdn关联，使用 get_city_or_prov_id(county_id,"province")方法，传入county_id，返回province_id，然后按 mdn、province_id、resi_county_id分组，使用calLength(grid_id, resi_grid_id) 传入网格id、居 住地网格id，算出出行距离，并计算每个用户到每个省的累计出行时间，然后取出 累计时间最大 值超过3小时（180分钟），出行距离大于300km的用户

④dws_city_tourist_msk_d

出行距离大于100km 在市内停留时间大于3个小时

CREATE EXTERNAL TABLE IF NOT EXISTS dws.dws_city_tourist_msk_d (mdn string comment '手机号大写MD5加密'  
,source_county_id string comment '游客来源区县'  
,d_city_id string comment '旅游目的地市代码'  
,d_stay_time double comment '游客在该省市停留的时间长度（小时）'  
,d_max_distance double comment '游客本次出游距离'  
) 
comment  '旅游应用专题数据城市级别-天'PARTITIONED BY (day_id string comment '日分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS PARQUETlocation '/data/tour/dws/dws_city_tourist_msk_d';

停留点表dwm_staypoint_msk_d与用户画像维表dim_usertag_msk_m 通过mdn关联，使用 get_city_or_prov_id(county_id,"city")方法，传入county_id，返回city_id，然后按mdn、city_id、 resi_county_id分组，使用calLength(grid_id, resi_grid_id) 传入网格id、居住地网格id，算出出行 距离，并计算每个用户到每个市的累计出行时间，然后取出 累计时间最大值超过3小时（180分 钟），出行距离大于100km的用户

⑤dws_county_tourist_msk_d

出行距离大于10km 在县内停留时间大于3个小时

CREATE EXTERNAL TABLE IF NOT EXISTS dws.dws_county_tourist_msk_d (mdn string comment '手机号大写MD5加密'  ,source_county_id string comment '游客来源区县'  ,d_county_id string comment '旅游目的地县代码'  ,d_stay_time double comment '游客在该县停留的时间长度（小时）'  ,d_max_distance double comment '游客本次出游距离'  
) 
comment  '旅游应用专题数据县级别-天'PARTITIONED BY (day_id string comment '日分区'  
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' 
STORED AS PARQUETlocation '/data/tour/dws/dws_county_tourist_msk_d';

停留点表dwm_staypoint_msk_d与用户画像维表dim_usertag_msk_m 通过mdn关联，按mdn、 county_id、resi_county_id分组，使用calLength(grid_id, resi_grid_id) 传入网格id、居住地id， 算出出行距离，并计算每个用户到每个县的累计出行时间，然后取出 累计时间最大值超过3小时 （180分钟），出行距离大于10km的用户

运行SQL时报错 我们要创建一下UDF函数

add jars /usr/local/soft/jars/jtxy_hdfs-1.0-SNAPSHOT.jar;create temporary function get_points as 'ctyun.udf.getPointsUDF';create temporary function dateBetweenUDF as 'ctyun.udf.dateBetweenUDF';create temporary function calLength as 'ctyun.udf.calLength';create temporary function get_city_or_prov_id as 'ctyun.udf.getCityIdOrProvID';

insert into table dws.dws_county_tourist_msk_d partition(day_id="20180503")select  ttt1.mdn,ttt1.source_county_id,ttt1.d_county_id,ttt1.d_stay_time,ttt1.d_max_distancefrom(select  mdn,resi_county_id as source_county_id,county_id as d_county_id,sum(duration) as d_stay_time,max(calLength(tt1.grid_id,tt1.resi_grid_id)) as d_max_distancefrom(select  t1.mdn,t1.grid_id,t1.county_id,t1.duration,t2.resi_county_id,t2.resi_grid_idfrom (select  *from dwm.dwm_staypoint_msk_d
where day_id='20180503') t1 join(select *from dim.dim_usertag_msk_mwhere month_id='201805') t2 on t1.mdn = t2.mdn) tt1 group by tt1.mdn,tt1.county_id,tt1.resi_county_id)ttt1 where d_stay_time > 180 and d_max_distance > 10000;

3）DIM层
create database dim;use dim;

①dim_usertag_msk_m
CREATE EXTERNAL TABLE IF NOT EXISTS dim.dim_usertag_msk_m (mdn string comment '手机号大写MD5加密'  
,name string comment '姓名'  
,gender string comment '性别，1男2女'  
,age string comment '年龄'  
,id_number string comment '证件号码'  
,number_attr string comment '号码归属地'  
,trmnl_brand string comment '终端品牌'    
,trmnl_price string comment '终端价格',packg string comment '套餐'  
,conpot string comment '消费潜力'  
,resi_grid_id string comment '常住地网格'  
,resi_county_id string comment '常住地区县'  
) 
comment  '用户画像表'PARTITIONED BY (month_id string comment '月分区'  
) 
ROW FORMAT DELIMITED 
FIELDS TERMINATED BY '\t' 
STORED AS PARQUETlocation '/data/tour/dim/dim_usertag_msk_m'; // 添加分区
alter table dim.dim_usertag_msk_m add partition(month_id=201805);// 加载数据
load data local inpath 
'/usr/local/soft/ctyun/dim_usertag_msk_m/month_id=201805/*' into table 
dim.dim_usertag_msk_m partition(month_id=201805);

// 查询数据select * from dim_usertag_msk_m limit 10;

4）ADS层

根据需求建设

1）需求矩阵

2）根据区县游客表计算如下指标

客流量按天 [区县id,客流量]

select  t1.d_county_id,count(*) as d_county_cnt
from (select  d_county_idfrom dws.dws_county_tourist_msk_dwhere t1.day_id="20180503"
) t1 group by t1.d_county_id;

性别按天 [区县id,性别,客流量]

select  t1.d_county_id,t2.gender,count(*) as d_county_gender_cnt
from(select  mdn,d_county_idfrom dws.dws_county_tourist_msk_dwhere day_id="20180503"
) t1 left join (select  mdn,genderfrom dim.dim_usertag_msk_mwhere month_id=20180503
) t2 on t1.mdn = t2.mdn
group by t1.d_county_id,t2.gender;

年龄按天 [区县id,年龄,客流量]
常住地按天 [区县id,常住地市,客流量]
归属地按天 [区县id,归属地市,客流量]

select  t1.d_county_id,t2.number_attr,count(*) as d_county_number_attr_cnt
from(select  mdn,d_county_idfrom dws.dws_county_tourist_msk_dwhere day_id="20180503"
) t1 left join (select  mdn,number_attrfrom dim.dim_usertag_msk_mwhere month_id=20180503
) t2 on t1.mdn = t2.mdn
group by t1.d_county_id,t2.number_attr;

终端型号按天 [区县id,终端型号,客流量]
消费等级按天 [区县id,消费等级,客流量]
停留时长按天 [区县id,停留时长,客流量]

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