What is indexing in databases and why is it important?

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Indexing in databases is a technique used to enhance the speed and efficiency of data retrieval operations. An index in a database is similar to an index in a book — it helps locate data without scanning every row in a table. Technically, an index is a data structure (usually a B-tree or a hash table) that stores the values of one or more columns in a way that allows for fast searching, filtering, and sorting.

When a query is executed, the database can use the index to quickly find the location of the requested data, rather than performing a full table scan. For example, if a table contains millions of records, searching for a specific value without an index would require checking each row individually. With an index, the database can jump directly to the relevant data, greatly improving performance.

Importance of indexing:

• Speeds up queries: Especially SELECT queries with WHERE, ORDER BY, JOIN, and GROUP BY clauses.

• Improves performance: Essential for large databases with frequent read operations.

• Supports constraints: Indexes are automatically used to enforce primary key and unique constraints.

However, indexes also have drawbacks:

• They require additional storage.

• They slow down write operations (INSERT, UPDATE, DELETE), since indexes need to be updated when data changes.

In summary, indexing is crucial for optimizing query performance in relational databases, especially when dealing with large datasets. Proper indexing strategies balance speed and resource usage.

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