SQL indexes is a very popular tool for improving query performance and reducing load on server. Suppose you are in a library looking for your favorite book. You can find what that book very fast if the books are neatly arranged by title or author. However, it would take ages to find it if the books were dispersed at random because you will have to scan the entire library.
Databases function similarly. Databases use something called SQL indexes to make data searches quicker and more effective.
Terms like Clustered and Non-Clustered Indexes may seem scary to someone who is unfamiliar with databases. But don’t worry, they’re much simpler to understand once you put them in plain, everyday language. We will help you with this in this articcle.
Let’s dissect it.
What are SQL Indexes in a Database?
For your data, an index functions similarly to a road map. It facilitates quicker information retrieval in the database without requiring a full table scan. Consider an index to be similar to the book’s back index: Rather than having you turn each page, it tells you exactly where to look.
In order to locate what you’re looking for, a database would need to search through every row of a table without indexes, which is extremely slow, particularly if the table contains millions of records!
Clustered vs Non-Clustered SQL Indexes: The Basics
Indexes are of two main types:
Clustered Index | Non-Clustered Index |
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Helps in sorting and storing the actual data rows in the table based on the index key. | Helps in storing a pointer to the actual data, rather than the data itself. |
Only one per table. | Many can exist on a table. |
Visualize it like a phone book organized by last name. | Imagine it like a bookmark pointing to a page in a book. |
Let’s dive a little deeper into each one.
What is a Clustered SQL Index?
Data is physically sorted and stored on the disk in the same order as the index using a clustered index.
To put it simply:
- The clustered index is used to arrange the data in the table.
- Since the data cannot be physically arranged in two different ways simultaneously, there can only be one clustered index.
Example:
An example would be to make a clustered index on the “EmployeeID” column of a table of employees.
EmployeeID will now be used to store and sort the data in the table.
Because the database knows exactly where to go, querying by EmployeeID will always be incredibly quick. It’s like flipping straight to the correct contact in a sorted phone book.
Important Points:
- Data IS the clustered index.
- Typically, the primary key of a table is the clustered index by default.
What is a Non-Clustered SQL Index?
Think of Non-Clustered Index like a separate list that points to the actual data.
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The table’s data remains unchanged and unsorted.
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A pointer to the location of the complete data row is also stored in the non-clustered index, along with a copy of the indexed columns.
Example:
Let’s continue with the employee table and assume that you frequently search by “LastName.” On the “LastName” column, a non-clustered index can be made.
The database now has a shortcut to locate employees by their last names, even though the table itself isn’t sorted by LastName.
Key Points:
- A non-clustered index is a shortcut to the information.
- With SQL Server, a table can have as many as 999 non-clustered indexes.
Clustered vs Non-Clustered SQL Indexes: Visual Example
Imagine a Book:
- Clustered Index → The book’s pages are arranged according to a certain system, such as by chapter numbers.
Because the pages are physically in the correct order, you turn them quickly. - Non-Clustered Index → Topics and page numbers are listed in the book’s index at the back.
When you search for a topic, it directs you to a particular page, which you then access.
When to Use Clustered vs Non-Clustered SQL Indexes
Situation | Best Index Type |
---|---|
When you mostly search data by the primary key or a unique column. | Clustered Index |
You search data by multiple different columns (e.g., name, city, email). | Non-Clustered Index |
When you want faster range queries (like finding records between two dates). | Clustered Index |
You want to fasten up filtering or sorting on non-primary columns. | Non-Clustered Index |
Important Things to Remember
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Only ONE clustered index is possible per table.
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Multiple non-clustered indexes can be allowed per table.
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Indexes do speed up SELECT queries but we should also note that they can slow down INSERT, UPDATE, DELETE because we need to update the index as well.
Common Mistakes to Avoid When Using SQL Indexes
Indexes are very important tools. However, beginners often make a few common mistakes. Here’s what we should watch out for:
1. Over-Indexing
Database will slow down if we create too many indexes. This is because every time we insert, update, or delete data, we must also update the indexes, which is extra work.
✅ Tip:
We should create indexes only on those columns that we use heavily in searches, filters, or joins.
2. Indexing Low-Selectivity Columns
Columns with very few unique values (such as “Country” or “Gender”) are low-selectivity columns.
Since the database still needs to examine a large number of rows, indexes on these columns are not very useful.
✅ Tip:
Look for high-sensitivity columns for indexing, i.e., columns with a lot of unique values, such as “Email,” “EmployeeID,” or “OrderNumber,”.
3. Ignoring Maintenance
SQL Indexes require regular care over time. As data changes (inserts, updates, deletes), indexes can become fragmented.
✅ Tip:
Make a schedule to regularly index maintenance like reorganizing or rebuilding indexes to keep performance high.
Frequently Asked Questions (FAQs)
❓ Is it possible to have both clustered and non-clustered SQL indexes on the same table?
Yes!
A table can have several non-clustered indexes to speed up other kinds of queries, but it usually only has one clustered index (to store and sort the data).
❓ What happens if I don’t create any SQL indexes?
If we don’t build indexes, the database will have to perform a full table scan each time we search for something. This can be extremely slow, particularly on large tables with thousands or millions of rows.
❓ How do I choose which columns to select for SQL indexes?
We can start by analyzing:
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WHERE clauses in your queries
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JOIN conditions
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ORDER BY columns
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Columns used in GROUP BY
These are usually the best candidates for SQL indexes.
Final Pro Tip 🌟
Before creating an index, always ask yourself:
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Do I heavily search or sort this column?
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Will creating this index improve my query performance?
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Is the table large enough to justify an index?
A great indexing plan will make your database fly 🚀, but a bad one can slow it down.
Conclusion
One of the simplest yet most effective methods to improve database performance is to use SQL indexes. We can organize our tables to facilitate quicker, simpler, and more effective data retrieval by being aware of Clustered and Non-Clustered Indexes.
You’ll get a sense of when and where to make indexes for maximum impact as you work with databases more. And never forget to start small. A single strategically placed index can have a profound impact on the performance of our queries. Feel free to drop a comment if you have any queries and we will answer. All the best!
Also check out our other articles –
- Stored Procedures vs Functions in Excel : Understanding the Differences
- SQL -Common Interview Questions and Answers
- How to use Group By and Having in SQL (Beginner Friendly Guide)
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