文章目录
- 01：其他维度：组织机构
- 02：其他维度：仓库、物流
- 附录一：常见问题
- 1.错误：没有开启Cross Join
- 2.错误：Unable to move source
01：其他维度：组织机构
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目标：实现组织机构维度的设计及构建
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路径
- step1：需求
- step2：设计
- step3：实现
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实施
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需求：实现组织机构维度表的构建，得到每个工程师对应的组织机构信息
- 统计不同服务人员的工单数、核销数等
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设计
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org_employee：员工信息表【员工id、员工编码、员工名称、用户系统id】
select empid,empcode,empname,userid from org_employee; -
org_empposition：员工岗位信息表【员工id、岗位id】
select empid,positionid from org_empposition; -
org_position：岗位信息表【岗位id、岗位编码、岗位名称、部门id】
select positionid,posicode,posiname,orgid from org_position; -
org_organization：部门信息表【部门id、部门编码、部门名称】
select orgid,orgcode,orgname from org_organization;
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实现
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建维度表
-- 创建组织机构维度表，组织机构人员是经常变动的，所以按照日期分区 create external table if not exists one_make_dws.dim_emporg( empid string comment '人员id' , empcode string comment '人员编码(erp对应的账号id)' , empname string comment '人员姓名' , userid string comment '用户系统id（登录用户名）' , posid string comment '岗位id' , posicode string comment '岗位编码' , posiname string comment '岗位名称' , orgid string comment '部门id' , orgcode string comment '部门编码' , orgname string comment '部门名称' ) comment '组织机构维度表' partitioned by (dt string) stored as orc location '/data/dw/dws/one_make/dim_emporg'; -
抽取数据
-- 先根据dwd层的表进行关联，然后分别把数据取出来 insert overwrite table one_make_dws.dim_emporg partition(dt='20210101') select emp.empid as empid , emp.empcode as empcode , emp.empname as empname , emp.userid as userid , pos.positionid as posid , pos.posicode as posicode , pos.posiname as posiname , org.orgid as orgid , org.orgcode as orgcode , org.orgname as orgname from one_make_dwd.org_employee emp left join one_make_dwd.org_empposition emppos on emp.empid = emppos.empid and emp.dt = '20210101' and emppos.dt = '20210101' left join one_make_dwd.org_position pos on emppos.positionid = pos.positionid and pos.dt = '20210101' left join one_make_dwd.org_organization org on pos.orgid = org.orgid and org.dt = '20210101';
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小结**
- 实现组织机构维度的设计及构建
02：其他维度：仓库、物流
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目标：实现仓库维度、物流维度的构建
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路径
- step1：仓库维度
- step2：物流维度
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实施
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仓库维度
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建表
-- 仓库维度表 create external table if not exists one_make_dws.dim_warehouse( code string comment '仓库编码' , name string comment '仓库名称' , company_id string comment '所属公司' , company string comment '公司名称' , srv_station_id string comment '所属服务网点ID' , srv_station_name string comment '所属服务网点名称' )comment '仓库维度表' partitioned by (dt string) stored as orc location '/data/dw/dws/one_make/dim_warehouse'; -
加载
insert overwrite table one_make_dws.dim_warehouse partition(dt='20210101') select warehouse.code as code , warehouse.name as name , warehouse.company as company_id , cmp.compmay as compmay , station.id as srv_station_id , station.name as srv_station_name from one_make_dwd.ciss_base_warehouse warehouse -- 关联公司信息表 left join ( select ygcode as company_id, max(companyname) as compmay from one_make_dwd.ciss_base_baseinfo where dt='20210101' -- 需要对company信息进行分组去重，里面有一些重复数据 group by ygcode) cmp on warehouse.dt = '20210101' and cmp.company_id = warehouse.company -- 关联服务网点和仓库关系表 left join one_make_dwd.ciss_r_serstation_warehouse station_r_warehouse on station_r_warehouse.dt = '20210101' and station_r_warehouse.warehouse_code = warehouse.code -- 关联服务网点表 left join one_make_dwd.ciss_base_servicestation station on station.dt = '20210101' and station.id = station_r_warehouse.service_station_id;
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物流维度
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建表
-- 物流维度表(和服务属性表类似) create external table if not exists one_make_dws.dim_logistics( prop_name string comment '字典名称' , type_id string comment '属性id' , type_name string comment '属性名称' )comment '物流维度表' partitioned by (dt string) stored as orc location '/data/dw/dws/one_make/dim_logistics'; -
加载
insert overwrite table one_make_dws.dim_logistics partition(dt = '20210101') select dict_t.dicttypename as prop_name , dict_e.dictid as type_id , dict_e.dictname as type_name from one_make_dwd.eos_dict_type dict_t inner join one_make_dwd.eos_dict_entry dict_e on dict_t.dt = '20210101' and dict_e.dt = '20210101' and dict_t.dicttypeid = dict_e.dicttypeid and dict_t.dicttypename in ( '物流公司' , '物流类型' ) order by dict_t.dicttypename, dict_e.dictid; -
使用如下写法会好一些
insert overwrite table one_make_dws.dim_logistics partition (dt = '20210101') select dict_t.dicttypename as prop_name , dict_e.dictid as type_id , dict_e.dictname as type_name from one_make_dwd.eos_dict_type dict_t inner join one_make_dwd.eos_dict_entry dict_e on dict_t.dt = '20210101' and dict_e.dt = '20210101' and dict_t.dicttypeid = dict_e.dicttypeid -- 通过状态字符串进行关联 and dict_t.dicttypename in ('物流公司', '物流类型') -- 通过和物流相关的字样进行过滤 order by prop_name, type_id;
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小结**
- 实现仓库维度、物流维度的构建
附录一：常见问题
1.错误：没有开启Cross Join
Exception in thread "main" org.apache.spark.sql.AnalysisException: Detected implicit cartesian product for INNER join between logical plans.Use the CROSS JOIN syntax to allow cartesian products between these relations
- Spark2.x默认不允许执行笛卡尔积，除非显示申明cross join或者开启属性：
spark.sql.crossJoin.enabled true
2.错误：Unable to move source
Error: org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: Unable to move source hdfs://hadoop.bigdata.cn:9000/data/dw/dws/one_make/dim_warehouse/.hive-staging_hive_2020-12-23_04-26-01_363_5663538019799519260-16/-ext-10000/part-00000-63069107-6405-4e31-a55a-6bdeefcd7d9b-c000 to destination hdfs://hadoop.bigdata.cn:9000/data/dw/dws/one_make/dim_warehouse/dt=20210101/part-00000-63069107-6405-4e31-a55a-6bdeefcd7d9b-c000; (state=,code=0)
- 重启SparkSQL的ThriftServer，与MetaStore构建新的会话连接
