Question

我有这个查询生成大约40,000条记录，这个查询的执行时间大约是1分30秒。

SELECT DISTINCT
a.ID,
a.NAME,
a.DIV,
a.UID,
(select NAME from EMPLOYEE where UID= a.UID and UID<>'') as boss_id, 
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 1 and id = a.ID) as TERM1,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 2 and id = a.ID) as TERM2,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 3 and id = a.ID) as TERM3,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 4 and id = a.ID) as TERM4,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 5 and id = a.ID) as TERM5,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 6 and id = a.ID) as TERM6,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 7 and id = a.ID) as TERM7,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 8 and id = a.ID) as TERM8
FROM EMPLOYEE a
WHERE ID LIKE 'D%'

我尝试使用group by，不同类型的连接来改善执行时间，但无法成功。表ABC和XYZ都被编入索引。此外，我认为此问题的根本原因是DISTINCT关键字或MAX功能。如何优化上述查询以将执行时间降至至少不到一分钟？

感谢任何帮助。

Answer 1

查询未经过测试，这只是一个关于如何以两种不同方式完成此任务的想法。

（SQL Server solutions here）

对每个ID使用LEFT JOIN应如下所示：

 SELECT a.ID,
        a.NAME,
        a.DIV,
        a.UID,
        b.Name as boss_id, 
        MAX(xyz1.create_time) as TERM1,
        MAX(xyz2.create_time) as TERM2,
        MAX(xyz3.create_time) as TERM3,
        MAX(xyz4.create_time) as TERM4,
        MAX(xyz5.create_time) as TERM5,
        MAX(xyz6.create_time) as TERM6,
        MAX(xyz7.create_time) as TERM7,
        MAX(xyz8.create_time) as TERM8
FROM EMPLOYEE a
    JOIN EMPLOYEE b on a.UID = b.UID and b.UID <> ''
    LEFT JOIN XYZ xyz1 on a.ID = xyz1.ID and xyz1.XYZ_ID = 1
    LEFT JOIN XYZ xyz2 on a.ID = xyz2.ID and xyz1.XYZ_ID = 2
    LEFT JOIN XYZ xyz3 on a.ID = xyz3.ID and xyz1.XYZ_ID = 3
    LEFT JOIN XYZ xyz4 on a.ID = xyz4.ID and xyz1.XYZ_ID = 4
    LEFT JOIN XYZ xyz5 on a.ID = xyz5.ID and xyz1.XYZ_ID = 5
    LEFT JOIN XYZ xyz6 on a.ID = xyz6.ID and xyz1.XYZ_ID = 6
    LEFT JOIN XYZ xyz7 on a.ID = xyz7.ID and xyz1.XYZ_ID = 7
    LEFT JOIN XYZ xyz8 on a.ID = xyz8.ID and xyz1.XYZ_ID = 8
WHERE a.ID LIKE 'D%'
GROUP BY a.ID, a.NAME, a.DIV, a.UID, b.Name

使用PIVOT看起来像这样：

select * from (
    SELECT DISTINCT
                a.ID,
                a.NAME,
                a.DIV,
                a.UID,
                b.NAME as boss_id,
                xyz.xyz_id,
                xyz.create_time
    FROM EMPLOYEE a
        JOIN EMPLOYEE b on a.UID = b.UID and b.UID <> ''
        LEFT JOIN (SELECT DATE(MAX(create_time)) create_time, XYZ_ID, ID 
                   from XYZ 
                   where XYZ_ID between 1 and 8 
                   group by XYZ_ID, ID) xyz on a.ID = xyz1.ID
    WHERE a.ID LIKE 'D%') src
PIVOT (
    max(create_time) for xyz_id IN (['1'], ['2'], ['3'], ['4'], 
                                    ['5'], ['6'], ['7'], ['8'])
) PIV

试一试

Answer 2

我建议group by和条件聚合：

SELECT e.ID, e.NAME, e.DIV, e.UID,
       DATE(MAX(CASE WHEN XYZ_ID = 1 THEN create_time END)) as term1,
       DATE(MAX(CASE WHEN XYZ_ID = 2 THEN create_time END)) as term2,
       DATE(MAX(CASE WHEN XYZ_ID = 3 THEN create_time END)) as term3,
       DATE(MAX(CASE WHEN XYZ_ID = 4 THEN create_time END)) as term4,
       DATE(MAX(CASE WHEN XYZ_ID = 5 THEN create_time END)) as term5,
       DATE(MAX(CASE WHEN XYZ_ID = 6 THEN create_time END)) as term6,
       DATE(MAX(CASE WHEN XYZ_ID = 7 THEN create_time END)) as term7,
       DATE(MAX(CASE WHEN XYZ_ID = 8 THEN create_time END)) as term8
FROM EMPLOYEE e LEFT JOIN
     XYZ
     ON xyz.ID = e.id
WHERE e.ID LIKE 'D%'
GROUP BY e.ID, e.NAME, e.DIV, e.UID;

我不理解boss_id的逻辑，所以我把它排除在外。这应该会显着提高性能。

优化具有DISTINCT关键字和函数的SQL查询

2 个答案: