Hi All,
I have Message
SQL Server parse and compile time:
CPU time = 0 ms, elapsed time = 0 ms.
(100 rows affected)
Table 'Category'. Scan count 0, logical reads 200, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table Organization. Scan count 0, logical reads 200, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'Department'. Scan count 1, logical reads 3878, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'Status'. Scan count 0, logical reads 200, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
Table 'Request'. Scan count 1, logical reads 26, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
(1 row affected)
SQL Server Execution Times:
CPU time = 16 ms, elapsed time = 30 ms.
SQL Server Execution Times:
CPU time = 16 ms, elapsed time = 31 ms.
SQL Server Execution Times:
CPU time = 0 ms, elapsed time = 0 ms.
Is that Mean Department with logical reads 3878 root that giving issue on performance? How can I get a very optimize speed of query execution, any idea?
Execution Plan
Query Cost (relative to batch) : 100%
Select Cost 0% <- Compute Scalar Cost 0% <- Top Cost 0% <- Nested Loops (Left Outer Join) Cost 0 % <- 1. Nested Loops (Left Outer Join) Cost 0%
<- 2. Clustered Index Seek (Clustered) [Category].[PK_Category] [Category] Cost 11%
Expanded from <- 1. Nested Loops (Left Outer Join) Cost 0%
a. <- Nested Loops (Left Outer Join) Cost 14% <- Nested Loop (Left Outer Join) Cost 0%
i. <- Filter Cost 1% <- Clustered Index Scan (Clustered) [Request].[PK_Request] [Request] Cost 10%
ii. <- Clustered Index Seek (Clustered) [Status].[PK_Status] [Status] Cost 11%
b. <- Clustered Index Seek (Clustered) [Department].[PK_Department] [Department] Cost 29%
Thanks.
Regards,
Micheale
