Optimizing SQL query that have multiple joins

Question

I have the following tables in my database which I cannot change or modify. I kept the Log table simple but LogDetail is the same as in my database.

Log Table

 Id  User Department Service     Method

 21  John Sales      UserService GetUser

LogDetail Table

Id LogRef ParamName  ParamValue

30 21     FirstName  Adam
31 21     LastName   Smith     
32 21     Age        35
33 21     Gender     M

Now, I am using following query to get who searched (Adam, Smith, 35, M)

SELECT 
L.*, D1.ParamName, D2.ParamName, D3.ParamName, D4.ParamName
FROM Log as L
INNER JOIN LogDetail as D1 on L.Id = D1.LogRef
INNER JOIN LogDetail as D2 on L.Id = D2.LogRef
INNER JOIN LogDetail as D3 on L.Id = D3.LogRef
INNER JOIN LogDetail as D4 on L.Id = D4.LogRef
WHERE
D1.ParamName='FirstName' and D1.ParamValue='Adam' and
D2.ParamName='LastName' and D2.ParamValue='Smith' and
D3.ParamName='Age' and D3.ParamValue=35 and
D4.ParamName='Gender' and D4.ParamValue='M'

Is there a better way to do this?

Answer 1

This is what happens when you use an EAV schema (key-value pairs basically)

There isn't much you can except add an index on (ParamName, ParamValue) for LogDetail. This assumes the clustered index stays as LogRef

Answer 2

One things you can do just use Index on fields used in joining clause.