A database is a piece of software operating on a computer, which means it is dependent and likely to face the same limitations as other software present on that computer. In other words, it will only be able to process as much data as the hardware can handle.
One of the best ways to speed up queries is to perform SQL performance tuning. In this post, we will answer some of the most frequent questions involving databases and indexes.
What is Indexing in SQL Query Optimization?
Indexing is one of the first things you may have come across while learning the ropes of your database. It is a wonderful tool that enables users to enhance the efficiency of their database. However, bear in mind that not every database requires indexing, and not all indexes are helpful in SQL performance tuning.
Let’s learn more about indexing: what it is and how it helps in enhancing database performance.
How do Indexes Affect SQL Query Performance?
An Index can locate data swiftly without having to go through each row in the table. This saves plenty of time!
Certain data columns are required before you can create an index. These are –
- The Search Key which holds a duplicate of the primary key
- The Data Reference which has a set of pointers
All of these constitute the structure of one index. To understand how an index works, let us take an example. Suppose you need to look for a bit of data in your database. Rather than scour every line yourself, you make the computer search each row till it locates the information. Remember that the search is bound to take much longer if the requisite information is located at the end. Fortunately, you have the option to sort alphabetically to shorten the length of such queries.
What are the Types of Database Indexes?
Database indexes are of two kinds –
Clustered indexes – These arrange data using the primary key. The reason behind using a clustered index is to make sure the primary key is saved in ascending order. This is the same order in which the table stores memory.
A clustered index is automatically created when the primary key is set, which helps in SQL tuning for Oracle in the long run as well.
Non-clustered indexes – A non-clustered index is a data structure that boosts data fetching speed. It is different from clustered indexes, as they are made by data analysts or developers.
When and How Should We Use Indexes?
Since indexes are intended to accelerate database performance, you should apply them whenever you think they can simplify the use of the database. Although smaller databases may not have several opportunities to use indexes, they are likely to see the benefits of indexing as they grow into larger databases.
You can make sure your indexes keep performing well, if you test run a set of queries on your database first. Clock the time those queries take to execute and begin creating your indexes after that. Keep rerunning these ‘tests’ for continuous improvements.
Conclusion
Indexing has its challenges, the biggest one being determining the best ones for every table.
For instance, heaps require clustered indexes because searching for a record in a heap table is comparable to finding a needle in a haystack: it’s inefficient and time-consuming, thanks to the heap’s unordered structure.
On the other hand, locating data is simpler and faster from a table that contains a proper clustered index, just like finding a name in a list that’s alphabetically ordered. DBAs, therefore, recommend that every SQL table contains a proper clustered index. Now that you know how indexes work and how they can optimize database performance, you should be able to use them to reduce query times substantially. If you would like more tips on how to use indexing, or you need a SQL query optimization tool for your database, let our experts know!