mySQL表查询与连接

我有以下四个表格：

1。wmu_kpi_类别：（包含kpi类别的表格）

• 类别识别码
• 类别名称
• 有效

数据：包含5个KPI类别

2。wmu_kpi_子类别：（包含kpi子类别的表格）

• 子类别标识
• 子类别标题
• 类别识别码
• 有效

数据：包含类别id为1、2和3的KPI类别的4个KPI子类别。带有4和5的KPI类别分别有3和6个子类别

3。wmu_名称（公司名称表）

• 标识
• 名称与头衔
• 截面图

数据：包含10个名称

4。wmu指定到KPI（将KPI值应用到每个指定时填写的表格）

• EMPUID
• 标识
• 类别识别码
• 子类别标识
• 目标值

数据：表单在为每个指定分别分配kpi类别和子类别值时填写的表格

如何编写一个查询来显示每个类别和每个名称标题的子类别的名称及其值

每个表的示例数据

“类别id”“类别标题”“类别说明”“有效”“类别年份” “1”“财务”“1”“2013” “2”“增长”“1”“2013” “3”“风险”“1”“2013” “4”“服务质量”“1”“2013” “5”“人”“1”“2013”

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“子类别id”“子类别标题”“子类别描述”“类别id”“有效” 1“上午：预付费（SR）”0“1”1 “2”“上午：预付费用团队目标实现”“0”“1”“1” “3”“经纪业务：佣金净贡献（占RC目标的50%）“0”“1”“1” “4”“经纪业务：净佣金贡献团队目标实现”“0”“1”“1” “5”“IB:管理费贡献（%）”“0”“1”“1” “6”“上午：净销售额比率（SR）=认购/赎回”“0”“2”“1” “上午7点：交易结束（#）=新订阅的数量”“0”“2”“1” “8”“经纪：客户端基数增量：新客户端+重新激活的客户端（#”）“0”“2”“1” “9”“上午+经纪：新高净值客户保留#新高净值客户（余额>200万）/#丢失/转移高净值客户（余额=0）”“0”“2”“1” “上午10点+经纪：RB贡献：成功交易/#与RB的联合访问”“0”“2”“1” “11”“新细分客户（#）1英寸+100米（每半年一次）3英寸20-100米（每半年一次）5英寸2-20米（每半年一次）总计=每个区域18个，总共54个”“0”“2”“1” “12”“违规（#）”“0”“3”“1” “13”“高风险过期审核异常（#）”“0”“3”“1” “14”“关于投资中心的高优先级质量评论（#）”“0”“4”“1” “15”“与西医相关的投诉减少（%）”“0”“4”“1” “16”“高净值客户（余额>=200万）（#）2次拜访客户+100万（每年每IA/IO）2次拜访客户2000-100万（每年每IA/IO）1次拜访客户2-20万（每年每IA/IO）”“0”“4”“1” “17”“对不同客户的访问次数（每个IA/IO每天2次）”“0”“4”“1” “18个高净值客户（余额>=200万）/国际会计准则/国际会计准则”0“5”1” “19”#国际会计准则和国际会计准则工作人员/#投资中心”“0”“5”“0” “20”“中心经理、CSO和经纪人员工/”“投资中心”“0”“5”“1” “21”“按地区/地区划分的员工会议每年访问2次（#”）”“0”“5”“1” “22”“与不同IAs/IOs的联合访问（每周3次）（#”）”“0”“5”“1” “23次不同中心的就诊（每周3次）（#”）“0次”“5次”“1” “24”“针对计划的培训（%）”“0”“5”“1” “25”“领导能力（#）”“0”“5”“1”

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“名称id”“名称标题”“名称描述”“章节id”“有效”“销售” “1”“财富管理主管”“1”“1” “2”“咨询主管”“1”“1” “3”“咨询区域经理”“1”“1” “4”“IA/IO”“1”“1” “5”“中心标头”“1”“1” “6”“中心区域经理”“1”“1” “7”“中心管理器”“1”“1” “8”“CSO”“1”“1” “9”“代理”“1”“1”

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“EMPKI\u id”“类型\u id”“员工\u id”“指定\u id”“类别\u id”“子类别\u id”“目标\u值”“kpi\u年度” "1" "1" "0" "1" "1" "0" "25" "2013" "2" "1" "0" "1" "1" "0" "50" "2013" "3" "1" "0" "1" "1" "0" "0" "2013" "4" "1" "0" "1" "1" "0" "40" "2013" "5" "1" "0" "1" "1" "0" "0" "2013" "6" "1" "0" "1" "1" "0" "10" "2013" "7" "1" "0" "1" "0" "0" "0" "2013" "8" "1" "0" "1" "0" "0" "0" "2013" "9" "1" "0" "1" "2" "0" "25" "2013" "10" "1" "0" "1" "2" "0" "20" "2013" "11" "1" "0" "1" "2" "0" "20" "2013" "12" "1" "0" "1" "2" "0" "20" "2013" "13" "1" "0" "1" "2" "0" "20" "2013" "14" "1" "0" "1" "2" "0" "20" "2013" "15" "1" "0" "1" "2" "0" "0" "2013" "16" "1" "0" "1" "0" "0" "0" "2013" "17" "1" "0" "1" "0" "0" "0" "2013" "18" "1" "0" "1" "3" "0" "15" "2013" "19" "1" "0" "1" "3" "0" "50" "2013" "20" "1" "0" "1" "3" "0" "50" "2013" "21" "1" "0" "1" "0" "0" "0" "2013" "22" "1" "0" "1" "0" "0" "0" "2013" "23" "1" "0" "1" "4" "0" "20" "2013" "24" "1" "0" "1" "4" "0" "50" "2013" "25" "1" "0" "1" "4" "0" "50" "2013" "26" "1" "0" "1" "4" "0" "0" "2013" "27" "1" "0" "1" "4" "0" "0" "2013" "28" "1" "0" "1" "0" "0" "0" "2013" "29" "1" "0" "1" "0" "0" "0" "2013" "30" "1" "0" "1" "5" "0" "15" "2013" "31" "1" "0" "1" "5" "0" "20" "2013" "32" "1" "0" "1" "5" "0" "20" "2013" "33" "1" "0" "1" "5" "0" "20" "2013" "34" "1" "0" "1" "5" "0" "0" "2013" "35" "1" "0" "1" "5" "0" "0" "2013" "36" "1" "0" "1" "5" "0" "0" "2013" "37" "1" "0" "1" "5" "0" "20" "2013" "38" "1" "0" "1" "5" "0" "20" "2013" "39" "1" "0" "1" "0" "0" "0" "2013" "40

SELECT  a.empkpi_id,
        b.designation_title,
        c.category_title,
        d.Subcategory_title,
        a.target_value
FROM    wmu_designation_to_kpis a
        INNER JOIN wmu_designations b
            ON a.designation_id = b.designation_id
        INNER JOIN wmu_kpi_cateogries c
            ON a.category_id = c.category_id
        INNER JOIN wmu_kpi_subcategories d
            ON a.subcategory_id = d.subcategory_id