High Performance SQL - jellyfish-tom/TIL GitHub Wiki

[SOURCE]

• https://www.toptal.com/sql-server/sql-database-tuning-for-developers

Indexes

Indexing is an effective way to tune your SQL database that is often neglected during development. In basic terms, an index is a data structure that improves the speed of data retrieval operations on a database table by providing rapid random lookups and efficient access of ordered records. This means that once you’ve created an index, you can select or sort your rows faster than before.

If you’re new to indexes, I recommend using this diagram when structuring your queries: (basically, the goal is to index the major searching and ordering columns)

Avoid Coding Loops

for (int i = 0; i < 1000; i++)
{
    SqlCommand cmd = new SqlCommand("INSERT INTO TBL (A,B,C) VALUES...");
    cmd.ExecuteNonQuery();
}

You should avoid such loops in your code. For example, we could transform the above snippet by using a unique INSERT or UPDATE statement with multiple rows and values:

INSERT INTO TableName (A,B,C) VALUES (1,2,3),(4,5,6),(7,8,9) -- SQL SERVER 2008

INSERT INTO TableName (A,B,C) SELECT 1,2,3 UNION ALL SELECT 4,5,6 -- SQL SERVER 2005

UPDATE TableName SET A = CASE B
        WHEN 1 THEN 'NEW VALUE'
        WHEN 2 THEN 'NEW VALUE 2'
        WHEN 3 THEN 'NEW VALUE 3'
    END
WHERE B in (1,2,3)

Make sure that your WHERE clause avoids updating the stored value if it matches the existing value. Such a trivial optimization can dramatically increase SQL query performance by updating only hundreds of rows instead of thousands. For example:

UPDATE TableName
SET A = @VALUE
WHERE
      B = 'YOUR CONDITION'
            AND A <> @VALUE -- VALIDATION

Avoid Correlated SQL Subqueries

A correlated subquery is one which uses values from the parent query. This kind of SQL query tends to run row-by-row, once for each row returned by the outer query, and thus decreases SQL query performance

Select Sparingly

One of my favorite SQL optimization tips is to avoid SELECT *! Instead, you should individually include the specific columns that you need

For example:

SELECT * FROM Employees

vs.

SELECT FirstName, City, Country FROM Employees

“Does My Record Exist?” Optimization

This SQL optimization technique concerns the use of EXISTS(). If you want to check if a record exists, use EXISTS() instead of COUNT(). While COUNT() scans the entire table, counting up all entries matching your condition, EXISTS() will exit as soon as it sees the result it needs. This will give you better performance and clearer code.

IF (SELECT COUNT(1) FROM EMPLOYEES WHERE FIRSTNAME LIKE '%JOHN%') > 0
    PRINT 'YES' 

vs.

IF EXISTS(SELECT FIRSTNAME FROM EMPLOYEES WHERE FIRSTNAME LIKE '%JOHN%')
    PRINT 'YES'