What is indexing in SQL- Syntax, Types, Uses, Advantages, Disadvantages, and Scenarios

What is Indexing?

Indexing is a data structure technique that allows the database to quickly locate and access specific data. It’s similar to the index at the back of a book, which helps you find specific pages quickly.

How Indexing Works

1. Index Creation: The database creates an index on a specified column(s).
2. Index Data Structure: The index is stored in a data structure (e.g., B-tree).
3. Query Execution: When a query is executed, the database checks if an index exists for the filtered column(s).
4. Index Scanning: If an index exists, the database scans the index to quickly locate the required data.

Types of Indexes

1. Clustered Index: Reorders the physical records of the table according to the index keys. Each table can have only one clustered index.
2. Non-Clustered Index: Creates a separate data structure that contains the index keys and pointers to the corresponding data rows.
3. Unique Index: Ensures that each value in the indexed column(s) is unique.
4. Composite Index: Indexes multiple columns together.
5. Function-Based Index: Indexes the result of a function or expression.
6. Full-Text Index: Optimizes queries that search for specific words or phrases within a column.
7. Spatial Index: Optimizes spatial queries

Syntax for Creating Indexes

Create Index

CREATE INDEX index_name ON table_name (column_name);

Create Unique Index

CREATE UNIQUE INDEX index_name ON table_name (column_name);

Drop Index

DROP INDEX index_name ON table_name; -- MySQL
DROP INDEX index_name; -- SQL Server, Oracle

Clustered Index

CREATE CLUSTERED INDEX idx_name
ON table_name (column1, column2, ...);

Non-Clustered Index

CREATE NONCLUSTERED INDEX idx_name
ON table_name (column1, column2, ...);

Composite Index

CREATE INDEX idx_name
ON table_name (column1, column2, ...);

Function-Based Index

CREATE INDEX idx_name
ON table_name (FUNCTION(column1));

Full-Text Index

CREATE FULLTEXT INDEX idx_name
ON table_name (column1);

Spatial Index

CREATE SPATIAL INDEX idx_name
ON table_name (column1);

Uses of Indexes

1. Speed up query execution: Indexes can significantly reduce the time it takes to retrieve data.
2. Improve data retrieval: Indexes can help retrieve data more efficiently, especially when filtering or sorting data.
3. Enforce uniqueness: Unique indexes can ensure that duplicate values are not inserted into a column.

Advantages of Indexes

1. Improved query performance: Indexes can significantly speed up query execution.
2. Reduced disk I/O: Indexes can reduce the amount of disk I/O required to retrieve data.
3. Improved data integrity: Unique indexes can help maintain data integrity.

Disadvantages of Indexes

1. Additional storage space: Indexes require additional storage space.
2. Insert, update, and delete overhead: Maintaining indexes can slow down insert, update, and delete operations.
3. Index fragmentation: Indexes can become fragmented over time, leading to decreased performance.

Scenarios for Using Indexes

1. Frequently queried columns: Index columns that are frequently used in WHERE, JOIN, and ORDER BY clauses.
2. Unique or primary key columns: Create unique indexes on columns that require unique values.
3. Large tables: Indexes can significantly improve query performance on large tables.
4. Columns with low cardinality: Indexes can be beneficial for columns with low cardinality (e.g., boolean or enum columns).

Example Use Case

Suppose we have a table employees with columns id, name, email, and department. We frequently query employees by email and department. We can create a composite index on email and department to improve query performance.

CREATE TABLE employees (
  id INT PRIMARY KEY,
  name VARCHAR(255),
  email VARCHAR(255),
  department VARCHAR(255)
);

CREATE INDEX idx_email_department ON employees (email, department);

By creating an index on email and department, we can significantly speed up queries that filter employees by these columns.

Example:–

CREATE INDEX idx_column_name ON table_name (column_name);
SELECT
column_name,
COUNT() AS occurrence FROM table_name WHERE some_filter = 'value' GROUP BY column_name HAVING COUNT() > 1;

EXPLAIN PLAN FOR
SELECT
    column_name,
    COUNT(*)
FROM
    table_name
GROUP BY
    column_name
HAVING
    COUNT(*) > 1;

SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY);