20 SQL Tips and Tricks for Performance

In this tutorial, we bring you some of the common and useful SQL tips to improve the performance of your database-centric tasks. It doesn’t matter whether you are a DBA, a web developer, or a tester. These tricks can help you complete tasks more efficiently.

SQL Performance Tips to Optimize Queries

The below SQL performance tips will help you keep your database, tables, and queries in check and complete control. Whether it is a database operation or a SQL query you are writing, they will consistently run smoothly.

Make sure you go through these tips and practice them to get the best result from this guide.

Optimize Query Structure

Most of the time, the simple thing proves to be more efficient. So, when writing queries, focus on what’s needed. Choose columns that you need and use filters to fetch the necessary data.

Example:

SELECT * FROM EMPL WHERE DEPT_ID = 5;

-- Optimize by selecting only necessary columns
SELECT EID, F_NAME, L_NAME FROM EMPL WHERE DEPT_ID = 5;

Create SQL Indexes

Indexing is a simple technique for a database to operate efficiently. When we create an index on a column, the database creates a separate data structure for the values in that column. This way, the database only requires to search in a limited space. So, because of indexes, the database finds rows for queries way quicker. The columns frequently used in queries for filtering, joining, or sorting data are the best candidates for indexing. This tip will significantly improve the performance of your SQL queries.

Example:

CREATE INDEX IDX_DEPT_ID ON EMPL(DEPT_ID);

-- Helps speed up queries like
SELECT * FROM EMPL WHERE DEPT_ID = 5;

Use EXISTS Instead of IN

The EXIST clause works faster than the IN operator in a SQL subquery. For example, suppose you’re searching for products within certain categories:

Example:

SELECT * FROM PROD WHERE CAT_ID IN (1, 2, 3);

-- Optimize with EXISTS
SELECT * FROM PROD p WHERE EXISTS (SELECT 1 FROM CATG c WHERE c.CAT_ID = p.CAT_ID);

Use Common Table Expressions (CTE)

CTEs allow temporary result sets stored within your main query that can be referenced later. This helps organize and simplify complex SQL queries by breaking them into smaller parts.

Example:

-- Less efficient (complex subquery)
SELECT * FROM orders o
WHERE order_date IN (
    SELECT order_date FROM orders WHERE status = 'completed'
);

-- More efficient (using CTE)
WITH completed_orders AS (
    SELECT order_date
    FROM orders
    WHERE status = 'completed'
)
SELECT * FROM orders o
WHERE order_date IN (SELECT order_date FROM completed_orders);

Use the Right Data Type

Choosing proper data types in SQL is one of the key performance tips as it directly impacts storage efficiency, data integrity, and query speed. By accurately defining columns with the right data types such as INT for integers or VARCHAR for text, you reduce resource usage, ensuring optimal storage utilization.

Hence, choose the most suitable data types for columns to minimize storage and improve query performance.

Example:

-- Less efficient data type usage
CREATE TABLE PROD (
    PROD_ID INT,
    PROD_NAME VARCHAR(255),
    PRICE FLOAT
);

-- Optimize by using appropriate data types
CREATE TABLE PROD (
    PROD_ID INT,
    PROD_NAME VARCHAR(100),
    PRICE DECIMAL(10, 2)
);

Update Statistics Regularly

Keep statistics up-to-date to help the query optimizer make accurate decisions in query execution plans. By running the below SQL command, you help the database optimizer make informed decisions about how to execute queries. It’s like refreshing your map to ensure it reflects the current road conditions, guiding the system to choose the most efficient routes.

Example:

UPDATE STATISTICS TBL_NAME;

Efficient Joins

One of the best SQL performance tips is optimizing join operations. When using JOIN to combine tables, choose the right join method (INNER, LEFT, etc.) and ensure the columns you’re joining have proper indexes. Efficient join speeds up data retrieval, avoids unnecessary work, and makes your queries run faster. It’s simply about selecting and combining data in a way that makes sense to the database, ensuring smooth and fast operations for getting the information you need.

Example:

-- Less efficient join
SELECT * FROM ORDERS o, CUST c WHERE o.CUST_ID = c.CUST_ID;

-- Optimize with explicit join and suitable indexes
SELECT * FROM ORDERS o
JOIN CUST c ON o.CUST_ID = c.CUST_ID;

Pagination with OFFSET and FETCH

In SQL, handling pagination is like flipping through pages in a book. When fetching a subset of results, use OFFSET and FETCH to navigate to the desired page. For instance:

Example:

SELECT * FROM PROD ORDER BY PROD_ID OFFSET 10 ROWS FETCH NEXT 5 ROWS ONLY;

With this SQL performance tip, you can efficiently retrieve a specific range of records. Also, it is perfect for scenarios like displaying results in chunks on a webpage. It’s akin to turning pages to find the content you want, ensuring swift and efficient data presentation in your SQL queries.

Stored Procedures for Reusability

Stored Procedures in SQL are like pre-packaged solutions for recurring tasks. By creating reusable scripts, you eliminate redundancy, enhance code clarity, and simplify maintenance. It’s like having a set of ready-to-use tools; when a specific task arises, you call the corresponding procedure, ensuring efficiency and consistency in your SQL operations.

Example:

CREATE PROCEDURE GetEmployeeDetails @DEPT_ID INT
   AS
   BEGIN
       SELECT * FROM EMPL WHERE DEPT_ID = @DEPT_ID;
   END;

Minimize Transaction Time

In SQL performance tips, minimizing transaction time is vital. Wrap multiple SQL statements within a transaction to ensure atomicity. For example:

BEGIN TRANSACTION;
-- SQL statements
COMMIT;

By using BEGIN TRANSACTION and COMMIT for a set of SQL statements, we ensure that either all of them succeed or none do. This minimizes the time the database is in a transitional state, reducing potential conflicts and optimizing SQL performance.

Partitioning Tables

Partitioning tables in SQL is like dividing a large book into chapters, making data more manageable. By organizing data into partitions based on certain criteria (e.g., date ranges), you enhance query performance. For instance:

Example:

-- Creating a partitioned sales table
CREATE TABLE SALES (
    SALE_ID INT,
    SALE_DATE DATE
) PARTITION BY RANGE (SALE_DATE);

Partitioning in SQL is like sorting your books by chapters. It helps organize large datasets, making queries faster. By dividing data based on criteria, such as date ranges, you narrow down what the database needs to search, improving performance for handling big sets of information.

Regular Database Maintenance

Schedule routine database maintenance tasks like index reorganization, statistics updates, and integrity checks.

Example:

EXEC sp_updatestats;

Regular database maintenance keeps your database healthy, preventing slowdowns and making SQL run better. It’s like regular check-ups for your car—it keeps everything running smoothly. By updating stats and cleaning up, you ensure your database stays efficient and responsive, essential for its long-term performance.

Use UNION ALL Instead of UNION

When aiming for SQL performance improvement, consider the tip of utilizing UNION ALL instead of UNION for more efficient and faster query processing, particularly with large datasets. While UNION removes duplicates, UNION ALL includes all results, making it more efficient for large datasets. It enhances query speed, a valuable way of optimizing SQL performance.

Example:

-- Less efficient with UNION
SELECT COL1 FROM TBL1
UNION
SELECT COL1 FROM TBL2;

-- More efficient with UNION ALL
SELECT COL1 FROM TBL2
UNION ALL
SELECT COL1 FROM TBL2;

Connection Pooling

In SQL, connection pooling is like carpooling for database access. It efficiently manages and reuses connections, saving time and boosting SQL performance. It’s like sharing a ride—it minimizes the hassle of setting up new connections for each request, making your application run more smoothly, especially when dealing with frequent database interactions.

Example:

from sqlalchemy import create_engine, pool

engine = create_engine('postgresql://user:password@localhost/dbname', poolclass=pool.QueuePool)

# Use the conn pool
with engine.connect() as con:
    # Perform DB ops
    res = con.execute('SELECT * FROM CUST')
    print(res.fetchall())

Caching Strategies

For writing efficient SQL queries, smart caching strategies can be a good performance tip as it ensures faster data retrieval by storing frequently used query results. This practice minimizes redundant database queries, reducing load and optimizing overall SQL performance in real-world database operations.

Example:

-- Create a temporary table for caching
CREATE TEMPORARY TABLE temp_cache AS
SELECT * FROM products;

-- Example query
SELECT * FROM temp_cache;

In this example, a temporary table (temp_cache) is created to store the result of a query temporarily. Subsequent queries can then use this temporary table, mimicking a simple caching mechanism within SQL.

Avoid SELECT * in Views

In SQL, it’s better to be specific in views. Instead of SELECT *, name the columns you need. This helps your views perform faster, using only the necessary data and optimizing SQL efficiency.

Example:

-- Less efficient view with SELECT *
CREATE VIEW inefficient_view AS
SELECT * FROM PROD;

-- More efficient view with explicit columns
CREATE VIEW efficient_view AS
SELECT PROD_ID, PROD_NAME, PRICE FROM PROD;

Plan Cache Monitoring

In SQL, check the plan cache often to make queries faster. Use tools like DMVs to look at execution plans. Monitoring the plan cache helps find problems, tweak queries, and make sure SQL operations work efficiently, improving the overall performance of your database.

Example:

DBCC FREEPROCCACHE;

DBCC FREEPROCCACHE:

In SQL Server, DBCC FREEPROCCACHE is like a refresh button for the plan cache. When used, it clears stored execution plans, prompting the system to create new ones. It’s handy for troubleshooting or ensuring queries get fresh plans but use it carefully to avoid temporary resource spikes.

Use SET NOCOUNT ON

In SQL, make things faster by starting stored procedures with SET NOCOUNT ON. This stops the system from sending row count messages to the client, reducing network load and boosting overall query efficiency.

Example:

SET NOCOUNT ON;

Analyze Query Execution Plans

Analyze and understand query execution plans to identify potential bottlenecks and optimize accordingly.

Example:

SELECT * FROM EMPL WHERE DEPT_ID = 5;
-- View execution plan EXPLAIN
SELECT * FROM EMPL WHERE DEPT_ID = 5;

Evaluate Query Performance Impact

In SQL, regularly check how queries affect performance. Use tools like SQL Server Profiler or equivalents in other databases. This helps find resource-hungry queries, optimize indexes, and keep your database running efficiently for better overall SQL performance.

Example:

-- Start a trace session
-- Capture events, including SQLBatchCompleted and RPC:Completed

-- Example query causing impact
SELECT * FROM ord WHERE cust_id = 1001;

-- Stop the trace session and analyze the captured data

For DBAs and testers, optimizing SQL queries for speed is crucial for smooth database operations. By using short and clear names, monitoring the plan cache, and checking how queries impact performance, you make everything run better. Keep looking at execution plans, use caching wisely, and understand how queries work to keep your SQL system in perfect shape. Following these tips ensures your database runs efficiently and is easy to manage.

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Enjoy Learning,
Team TechBeamers