最近一个需求如图,为了避免多次查询数据库,就想着尽量写成一个SQL语句

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张三

23

18900000000

24

本人

12

广东省深圳市龙华区某某街道某某小区5栋1608

14

李四

18

18900000001

18

本人

9

湖南省长沙市某某县

13

王五

15

18900000002

15

本人

5

赵六

11

18900000000

13

非本人

钱七

5

观察这个结果,发现数据有4中类型,每种类型都是现实每种类型的value的值,后面跟的是该value的统计数量,最终只显示数量最多的5条。

那么我们就需要对类型、value进行分组统计,但是联系方式处却还有要对关系(本人、非本人)进行分组统计,其他的三种不需要对该关系分组。

SQL如下:

-- 1、该层取指定的条数

select

t.columnDataType as dataType, t.columnDataValue as title, t.counts as count, t.columnDataRelation

from (

-- 2、该层对分的组进行排序

select

t3.columnDataType, t3.columnDataValue, t3.counts, t3.columnDataRelation,

case when @columnDataType=t3.columnDataType then @num:=@num+1 else @num:=1 end rank,

@columnDataType:=t3.columnDataType

from (

-- 3、该层对数据类型、值、关系分组:由于内层已经将不需要区分关系的统计的结果中关系字段统一为一个值了,所以这里再次分组统计后,每种(数据类型、值一致的数据)需要分组的结果行数就是关系的种类数,不需要分组的结果的行数就是一行

select

tmp.columnDataType, tmp.columnDataValue,

sum(tmp.counts) as counts,

tmp.columnDataRelation

from (

-- 4、该层对数据类型、值、关系分组:需要对关系分组的那么关系的值保留,不需要对关系分组的那么关系字段统一输出为一个值

select

t2.column_data_type as columnDataType,t2.column_data_value as columnDataValue,

if(t2.column_data_type in ('0'), t2.column_data_relation, '') as columnDataRelation , count(1) as counts

from 数据主表 t1

inner join 数据明细表 t2 on t1.id_ep_model_analysis = t2.search_index

where t1.search_flow_no='2aff02fccb79471cb34e17723a9d9b1d' and t2.column_data_relation in ('0', '1')

group by t2.column_data_type, t2.column_data_value, t2.column_data_relation

) tmp

group by tmp.columnDataType, tmp.columnDataValue, tmp.columnDataRelation

) t3select

t.columnDataType as dataType, t.columnDataValue as title, t.counts as count,

case when t.columnDataRelation='0' then '非本人' when t.columnDataRelation='1' then '本人' else '' end as flag

from (

select

t3.columnDataType, t3.columnDataValue, t3.counts, t3.columnDataRelation,

case when @columnDataType=t3.columnDataType then @num:=@num+1 else @num:=1 end rank,

@columnDataType:=t3.columnDataType

from (

select

tmp.columnDataType, tmp.columnDataValue, sum(tmp.counts) as counts, tmp.columnDataRelation

from (

select

t2.column_data_type as columnDataType,t2.column_data_value as columnDataValue,

if(t2.column_data_type in ('0'), t2.column_data_relation, '') as columnDataRelation , count(1) as counts

from ep_model_analysis t1

inner join ep_model_analy_dtl t2 on t1.search_index = t2.search_index

where t1.search_flow_no='f8ff8b0764544e4f8c3d79f80c2a2f77'

group by t2.column_data_type, t2.column_data_value, t2.column_data_relation

) tmp

group by tmp.columnDataType, tmp.columnDataValue, tmp.columnDataRelation

order by tmp.columnDataType

) t3, (SELECT @num:=0, @columnDataType:='') t4

order by t3.columnDataType, t3.counts desc, t3.columnDataValue

) t

where t.rank <= 5

order by t3.columnDataType, t3.counts

) t

where t.rank <=5

;

结果示例如下:

-- 上面的SQL结果:

/*

例如:

4查询之后的结果为:

columnDataType  columnDataValue  columnDataRelation  counts

1                             数据1                        0                                  11

1                             数据1                        1                                  3

1                             数据3                        0                                  13

1                             数据3                        1                                  4

1                             数据4                        0                                  31

1                             数据4                        1                                  14

1                             数据5                        0                                  23

1                             数据5                        1                                  8

2                             数据2                                                           12

2                             数据2                                                           5

2                             数据6                                                           121

2                             数据6                                                           51

2                             数据7                                                           124

2                             数据7                                                           54

2                             数据8                                                           23

2                             数据8                                                           5

2                             数据9                                                           34

2                             数据9                                                           5

2                             数据10                                                         15

2                             数据10                                                         6

2                             数据11                                                         18

2                             数据11                                                         5

3查询之后的结果为:

columnDataType  columnDataValue  columnDataRelation  counts

1                               数据1                              0                      11

1                               数据1                              1                      3

1                               数据3                              0                      13

1                               数据3                              1                      4

1                               数据4                              0                      31

1                               数据4                              1                      14

1                               数据5                              0                      23

1                               数据5                              1                      8

2                               数据2                                                     17

2                               数据6                                                     172

2                               数据7                                                     178

2                               数据8                                                     28

2                               数据9                                                     39

2                               数据10                                                   21

2                               数据11                                                   23

2查询之后的结果为:

columnDataType  columnDataValue  columnDataRelation  counts  rank

1                             数据4                            0                          31           1

1                             数据5                            0                          23           2

1                             数据4                            1                          14           3

1                             数据3                            0                          13           4

1                             数据1                            0                          11           5

1                             数据5                            1                          8             6

1                             数据3                            1                          4             7

1                             数据1                            1                          3             8

2                             数据7                                                      178           1

2                             数据6                                                      172           2

2                             数据9                                                      39             3

2                             数据8                                                      28             4

2                             数据11                                                    23             5

2                             数据10                                                    21             6

2                             数据2                                                      17             7

1查询之后的结果为:

columnDataType  columnDataValue  columnDataRelation  counts

1                             数据4                            0                          31

1                             数据5                            0                          23

1                             数据4                            1                          14

1                             数据3                            0                          13

1                             数据1                            0                          11

2                             数据7                                                      178

2                             数据6                                                      172

2                             数据9                                                      39

2                             数据8                                                      28

2                             数据11                                                    23

最终显示的结果就是:

1、columnDataType=1的需要显示关系,取总数最多的五条,

2、columnDataType=2的不显示关系,取总数最多的五条

*/

mysql每组结果分页显示_SQL语句mysql分组统计并对每组分页相关推荐

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