5 Tips and Tricks for Writing Better SQL Queries

When it comes to writing powerful, data-driven applications, SQL is king. SQL has advanced data retrieval capabilities that make other programming languages pale in comparison. When used consistently and intelligently, SQL can be used to drive almost any application.

However, developers may find SQL challenging when writing efficient and effective queries. In this post, you'll learn how to write better SQL queries that make your application faster and easier to maintain.

1.   Create Small Batches of Data for Deletion and Updation

The more data you have in your database, the more time it takes to run your application. If you keep adding data without removing any old data, your database will become cluttered and inefficient.

You can speed up the deletion process using the delete statement on the database command line or the shell's rm command. Similarly, you can speed up the addition process using the + update statement on the database command line or the shell's sync command.

Depending on what functionality you're adding or deleting data, you may want to create a temporary table to store the deleted or updated data. You can use the create table statement to create a new table or the update statement to change the data in existing tables.

2.   Use a Database Performance Analyzer to See Which Existing Queries Are Taking a Long Time to Run

When finding out how long a particular query will take, you're typically measuring the total time it takes to complete the query and include any order-management operations. However, this number doesn't account for the time it takes to execute the query. You want to know how much time is spent executing the query, but you can't get that information by looking at the query result.

Instead, use SolarWinds DPA for performance troubleshooting the database and getting this data. The performance analyzer reports a lot of helpful information, including the average time it takes to execute queries and the total time it takes to complete a query. It also provides breakdowns by table and column and the averages and maximum rates for each operation.

3.   Use Temp Tables

Temporary tables are optimized for quick modification and deletion and are created automatically when working with large volumes of data. You can think of them as internal help resources for your application. If you need to change the data in one table, you can drop the table without affecting other tables. Similarly, you can use the drop table statement to delete a table.

4.   Avoid Using Another Developer's Code

If you're struggling with a problem specific to your code, it's better to ask other developers to look into it rather than searching for the bug yourself. They're likely to be more familiar with your code and will be able to identify potential problems much faster than you.

While it is rarely a good idea to look at someone else's code, there are situations in which it is necessary. For example, if you've made a mistake that you want to fix, the code you're working with now doesn't support it. In these situations, looking at other developers' code is safer than your own.

5.   Avoid Using Triggers

Triggers are a handy feature of many programming languages. They allow you to create simple, non-interruptive tasks that don't require human interaction. For example, you can create a trigger that runs an automated script each time someone visits your website.

Unfortunately, triggers can be complicated to write correctly. If you make a mistake, your application will fail without any warning. Furthermore, if you need to add new functionality in the future, it will be much harder to write a trigger that can automatically run your code.

While writing queries can seem like an impossible task, there are steps you can take to make it easier. By creating small batches of data for deletion and updation, you can save time deleting old data and start fresh with new data.

This, in turn, reduces your database work and lets you focus on building applications instead of maintaining data. When you avoid negative searches and use triggers sparingly, you can create powerful queries that drive your application forward.