SQL Indexes
- An SQL indexes is a database object that enhances the speed of data retrieval operations on a database table but at the expense of extra space & maintenance time.
- Like an index in a book, which lets you quickly find the required items or topics without having to read the whole book.
- An SQL databases environment needs indexes the most in order to get the best results from the queries formulated, the SELECT ones in particular.
- They can most definitely enhance the query response time by a considerable amount, say from a minute to milliseconds, and so your database queries will be more efficient.
What is an SQL Index?
- An SQL index is a data structure, usually a data tree (or other hash indexes or bitmap indexes), that helps the database management system (DBMS) to identify rows with individual column values quickly.
- Rather than going through the whole table from one end to the other, a proper index allows a database to find the data it needs faster, like the way a shortcut is used to reach a specific page in a book.
- They are the indexes that come into existence on the columns of a database table and one can explicitly make the indexes as a user or implicitly by the system when creating a primary key or unique constraint.
Types of SQL Indexes
1.Single-Column Indexes:
- These indexes are created on a single column of a table.
- When a query involves searching for a single column, the database can utilize this index to find matching rows quickly.
- Example:
CREATE INDEX idx_employee_name
ON employees (name);
In this example, an index named idx_employee_name is created on the name column of the employees table. If you frequently run queries like SELECT * FROM employees WHERE name = ‘John’;, this index would help speed up the search.
2.Composite Indexes (Multi-Column Indexes):
- These morphemes are placed on separate rocks. They are most valuable when there exist conditions on more than one column in the query.
- The following demonstrates how indexes are created on multiple columns:
CREATE INDEX idx_employee_dept_name
ON employees (department_id, name);
- From here, an index is formed on both the department_id and name columns. This composite index is specifically useful for these types of queries:
SELECT * FROM employees
WHERE department_id = 5 AND name = 'Alice';
3.Unique Indexes:
- A unique index guarantees that all values in the indexed column(s) are unique. It is automatically created when the PRIMARY KEY or UNIQUE constraint is enforced on a column.
- Example:
CREATE UNIQUE INDEX idx_unique_employee_id
ON employees (employee_id);
This index is a way to see that every value in the employee_id column is unique, which is a crucial thing for a primary key.
4.Full-Text Indexes:
- These indexes allow for faster search results on text fields containing a huge amount of content; for example, TEXT or VARCHAR fields.
- Essentially, these indexes help in the quick and efficient selection of words or phrases in the large text data.
- Example:
CREATE FULLTEXT INDEX idx_fulltext_description
ON products (description);
The full text indexes play a crucial role in text-based searches and the matching of particular patterns in textual data, instances of which are discussed.
5.Clustered Indexes:
- The clustered index is when the physical arrangement of data rows from the particular table.
- The table can have just one clustered index because the real rows themselves can be arranged in only one way.
- Ultimately, a clustered index is the primary key, which is in most cases as such, but a clustered index can still be created on tables with other columns. However, even so, it is possible to create a clustered index on some tables with elements other than primary keys.
- Example:
CREATE CLUSTERED INDEX idx_clustered_employee_id
ON employees (employee_id);
In the given scenario, the employee_id column will be used to physically order the nuts in the employees table.
6.Non-Clustered Indexes:
- A non-clustered index is a separate data structure that contains references to the table rows.
- Contrary to the clustered indexes, while non-clustered indexes don’t affect the arrangement of the table data in the files.
- The table can hold multiple non-clustered indexes.
- Example:
CREATE NONCLUSTERED INDEX idx_nonclustered_salary
ON employees (salary);
Here, the column salary will be a non-clustered index, meaning that the data in the employees table will stay as it is but the index will allow fast rows access by salary.
How SQL Indexes Work
- When an index is created, the database engine optimally arranges the index data, which makes it possible to have a fast search.
- In most situations, the index module is virtually implemented as B-trees, explicit, and this results in universal download capability.
- The following process explains the way it works:
- Search Operation: When a query is run that includes an index-enabled column, the database engine quickly locates the row(s) that meets the search condition using the index.
- Update Operation: Updated the index after the indexed column values are updated. In this way, the length of insert and update operations gets slightly elongated, as well, the index must be maintained.
- Delete Operation: Updating the index may be also required in case of row deletion since the references in the index need to be deleted as well.
Benefits of SQL Indexes
1.Improved Query Performance:
- Indexes significantly reduce the time to retrieve data.
- Particularly for big tables in the app, an index speeds up the data retrieval process by decreasing the time to locate records.
- If the WHERE clause or join conditions are applied, the index can directly point to the data instead of scanning the entire table.
2.Faster Sorting:
- Indexes can speed up the process by allowing databases to retrieve rows in the required order quickly.
- Indexes also help with speed up the process by allowing the database to retrieve rows in the required order quickly.
3.Lower Disk I/O:
- It is a fact that indexing lets you get hold of data fast and you do not have to read the disk that much.
- Therefore, performance is enhanced when the data that is on the larger datasets is retrieved.
Limitations and Drawbacks
- Storage Overhead: Indexes usually use extra disk space where there may be many indexes or on the large tables besides the indexes.
- Maintenance Overhead: The indexes, along with the tables, are also modified when the data is updated, making the insert, update, and delete processes of an SQL operation also slower.
- Not Always Beneficial: Some of the queries will not have the help of the indexes. For example, queries that return large datasets or those that perform operations across many columns may not experience significant performance improvement.
Example Scenario
Imagine a table students:
CREATE TABLE students (
student_id INT PRIMARY KEY,
name VARCHAR(50),
age INT,
grade VARCHAR(10)
);
Assume you are always looking for records like this:
SELECT * FROM students WHERE grade = 'A';
In order to do this, you can create an index on the grade column:
CREATE INDEX idx_grade
ON students (grade);
This index will speed up the search query as the database is now capable of directly locating rows with grade ‘A’ instead of scanning the complete table.