Indexing in SQL- Explain with examples

by | Apr 8, 2024 | SQL | 0 comments

Indexing in SQL is a technique used to improve the performance of queries by creating special data structures (indexes) that allow for faster data retrieval. Indexes are created on one or more columns of a table, and they store the values of those columns in a sorted order, along with pointers to the corresponding rows in the table.

Here’s an overview of indexing in SQL:

  1. Types of Indexes:
    • Single-Column Index: An index created on a single column of a table.
    • Composite Index: An index created on multiple columns of a table.
    • Unique Index: An index that enforces uniqueness on the indexed columns, preventing duplicate values.
    • Clustered Index: An index that orders the physical rows of the table based on the indexed columns. In most database systems, a table can have only one clustered index.
    • Non-clustered Index: An index that contains a sorted list of references to the physical rows of the table. A table can have multiple non-clustered indexes.
  2. Advantages of Indexing:
    • Faster Data Retrieval: Indexes allow the database engine to quickly locate rows based on the indexed columns, resulting in faster query execution times.
    • Improved Performance for WHERE Clauses: Indexes can significantly improve the performance of queries with WHERE clauses that filter rows based on the indexed columns.
    • Efficient Sorting and Join Operations: Indexes can speed up sorting and joining operations by providing pre-sorted lists of values.
  3. Considerations for Indexing:
    • Selectivity: Choose columns with high selectivity for indexing, i.e., columns with a wide range of values and relatively few duplicates.
    • Query Patterns: Analyze the query patterns of your application to identify frequently executed queries that can benefit from indexing.
    • Write Operations: Keep in mind that indexes incur overhead during data modification operations (INSERT, UPDATE, DELETE), as the indexes must be maintained along with the underlying data.
    • Disk Space: Indexes consume additional disk space, so consider the trade-off between improved query performance and increased storage requirements.
  4. Creating Indexes:
    • In SQL, you can create indexes using the CREATE INDEX statement.
    • Example: CREATE INDEX idx_lastname ON employees(last_name);
  5. Dropping Indexes:
    • If an index is no longer needed or if it negatively impacts performance, you can drop it using the DROP INDEX statement.
    • Example: DROP INDEX idx_lastname;

Indexing is a critical aspect of database performance tuning, and understanding when and how to use indexes effectively can significantly improve the overall performance of your SQL queries and database operations.

Written by HintsToday Team

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