Optimizing SQL query having DISTINCT keyword and functions - sql

Question

I have this query that generates about 40,000 records and the execution time of this query is about 1 minute 30 seconds.
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%'
I tried using group by, different kinds of join to improve the execution time but couldn't succeed.Both the tables ABC and XYZ are indexed.
Also, I think that the root cause of this problem is either the DISTINCT keyword or the MAX function.
How can I optimize the above query to bring down the execution time to at least less than a minute?
Any help is appreciated.

Answer 1

Query is not tested, this is just an idea on how you could get this done in two different ways.
(SQL Server solutions here)
Using LEFT JOIN for each ID should look something like this:
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
Using PIVOT would look something like this:
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
Give it a shot

Answer 2

I would recommend group by and conditional aggregation:
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;
I don't understand the logic for boss_id, so I left that out. This should improve the performance significantly.