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Index in SQL: Creating, Removing, and Altering

Index in SQL: Creating, Removing, and Altering

In this blog, we will explore topics like index creation, single-column, unique, composite, and implicit indexes. Learn about altering, renaming, and removing indexes, and discover when to avoid using index in SQL. The journey concludes with insights highlighting the essence of efficient database management.

Table of Contents

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What is an Index in SQL?

In SQL, an index is a well-organized list that helps find things quickly in a big database. It is a way to sort and arrange information, making it easier to find what you need. Just as a contents page in a book helps you locate chapters, an index in structured query language(SQL) helps the database find specific data faster by keeping things sorted. It is a tool that speeds up searches in the database, especially when there is a lot of information to look through.

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Why is Indexing in SQL Important?

Indexing in SQL holds immense significance for database performance. Below, we have given a detailed discussion of the significance of the SQL index.

  1. Faster Retrieval: Indexes allow the database engine to easily find specific rows or values within a table. They reduce the need for a full table scan by pointing directly to the relevant data, significantly speeding up search operations, especially when dealing with large datasets.
  2. Improved Query Performance: Queries benefit from indexes by executing more efficiently. When a query includes indexed columns in conditions or joins, the database engine can use these indexes to quickly find the required data, which results in faster query response times.
  3. Optimized Searching: Without indexes, the database often has to examine every row in a table to find specific information. Indexes streamline this process by acting as an organized reference that helps locate data much faster, enhancing search speed, and reducing system resource usage.
  4. Data Integrity Enforcement: Indexes in SQL ensure data consistency by preventing duplicate entries in columns that require uniqueness. This helps maintain the accuracy and integrity of the data stored in the database.
  5. Support for Constraints and Joins: Indexes support various constraints, such as primary keys, unique constraints, and foreign keys. They also enhance the efficiency of join operations between tables by facilitating the matching of related data more rapidly.

When Should You Use Indexing in SQL?

The use of indexing in SQL depends on various aspects, like how much data you have, how often you search, and what you want to achieve with your database. It helps make searches faster and gets the right information quickly. The use of the index in SQL depends on various factors and objectives, such as the following:

  • Large Datasets: Indexing is beneficial when dealing with sizable datasets where searching through entire tables would be time-consuming. If your tables contain a substantial amount of data, indexing can significantly speed up queries.
  • Frequent Searches: When specific columns are frequently used for searching, filtering, or joining data, indexing those columns can notably enhance query performance. Indexes make these operations faster and more efficient.
  • Performance Optimization: If certain queries in your application are slow or take a long time to execute, examining the query execution plan can help identify columns that could benefit from indexing to improve overall performance.
  • Unique Constraints: Columns requiring unique values, such as primary key columns, benefit from indexes. Indexes ensure data integrity and faster retrieval when searching for specific, unique values.

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How to Create an Index in SQL  

To create an index in SQL, you can use the CREATE INDEX statement, followed by specifying the index name, table name, and column(s) you want to index. We will discuss different conditions for creating an index in SQL, such as single-column, unique, composite, and implicit indexes. Before that, let us study the basic syntax to create an index in SQL:

Syntax:

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

Example:

CREATE INDEX idx_name
ON students (first_name, last_name);

Single-Column Indexes

Single-column indexes in SQL are indexes created on a single column within a database table. They significantly improve the speed of data retrieval and query performance when filtering, sorting, or searching based on that specific column.

Syntax:

CREATE INDEX index_name
ON table_name (column_name);

Unique Indexes

Unique indexes in SQL ensure that the values within a column or a set of columns are unique; that is, each value appears only once in the indexed column(s). They prevent duplicate values, which enforces data integrity within a table.

Syntax:

CREATE UNIQUE INDEX idx_unique_column
ON table_name (column_name);

Example: 

CREATE UNIQUE INDEX idx_unique_employee_id
ON employees (employee_id);

Composite Index

A composite index refers to an index that involves multiple columns from a table. It combines two or more columns into a single index structure, allowing for indexing multiple columns together, which helps enhance the performance of queries that involve those columns in the specified order. Composite indexes are useful for optimizing queries that involve multiple columns in filters, sorting, or joining operations.

Syntax:

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

Example:

CREATE INDEX idx_customer_order_date
ON orders (customer_id, order_date);

Implicit Indexes 

In SQL, an implicit index refers to an index automatically created by the database management system (DBMS) without the user explicitly defining it. These indexes are generated based on certain database constraints, operations, or data structures within the system.

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How to Remove an Index in SQL

When considering the removal of an index in SQL, the ‘DROP INDEX’ statement serves as the key command. It is important to be cautious and verify the necessity of deleting an index, as this action is irreversible and can significantly impact the database’s performance. Additionally, enabling proper permissions and confirming the accurate index name are essential steps before executing the ‘DROP INDEX’ statement to eliminate an index from the database schema.

Syntax: 

DROP INDEX index_name;

Altering an Index in SQL

Altering an index in SQL refers to modifying the existing characteristics or properties of an index that has already been created on a table. Altering certain aspects of an index, such as its name or visibility, can be restricted or might not be supported by some database systems due to the following constraints:

  • Renaming an Index: Some databases allow you to rename an existing index. This operation alters the index’s name without changing its underlying structure or properties.
  • Changing Visibility: Depending on the database system, altering the visibility of an index may be supported. This could involve making an index visible or invisible to the query optimizer without actually dropping the index.
  • Adding or Removing Columns: In some cases, you might be able to alter an index by adding or removing columns from its structure. This allows adjusting the index’s composition without dropping and recreating it entirely.
  • Changing Storage Parameters: Certain database systems permit alterations to index storage parameters, such as modifying the tablespace or storage options associated with an index.

Syntax:

ALTER INDEX IndexName
ON TableName TableName;

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When Should the Use of Indexes be Avoided in SQL?

Using indexes in SQL can significantly boost query performance, but there are situations where their use should be approached with caution or avoided:

  1. Small Tables: Adding an index to a table that doesn’t have much data might not help much and could even make things slower.
  2. Frequent Data Modifications: When a table undergoes frequent insertions, updates, or deletions, maintaining indexes can introduce overhead. Each modification might trigger index updates, slowing down these operations.
  3. Picking the Wrong Columns: Making indexes for columns that change a lot or do not have many different values, like a column saying ‘yes’ or ‘no’ or one for gender, might not make searches much faster. It’s important to consider if these could help you find things better when searching.
  4. Loading Lots of Data at Once: When loading a lot of information into the database at once, turning off indexes temporarily can speed things up. Once the data is loaded, the indexes can be turned back on.
  5. Frequent Schema Changes: When the way things are organized in the database keeps changing a lot, handling and updating lots of indexes can get tough. This might not match how people look for things in the database, as the way they search might also change.

Conclusion

Using indexes in SQL significantly enhances query performance by making searches faster and improving data retrieval. They play an important role in optimizing database operations, especially with large datasets and frequently searched columns. However, cautious consideration is necessary to avoid unnecessary indexing, especially with small tables, frequently changing data, or columns that do not significantly help in search improvement. Using index strategies to evolve query patterns and avoiding excessive modifications during schema changes ensures efficient database management and optimized performance.

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FAQs

What is the purpose of an index in SQL?

An index in SQL acts as a roadmap within a database, enabling faster data retrieval by organizing and sorting information. It works like a reference guide, quickly directing queries to specific rows or values, significantly speeding up search operations.

How does indexing improve query performance in SQL?

Indexing in SQL enhances query performance by minimizing the need for scanning entire tables. It allows the database engine to directly pinpoint relevant data, reducing search time and improving response times for queries involving indexed columns.

Can indexes be created on multiple columns in SQL?

Yes, SQL allows the creation of composite indexes involving multiple columns. These composite indexes enable faster retrieval of data when queries involve filtering, sorting, or joining based on those specific columns in the specified order.

Are there situations where using indexes should be avoided in SQL?

Indeed, using indexes may not be advisable for small tables, columns with low selectivity, or frequently changing data. Over-indexing or indexing columns that aren’t frequently used in queries might lead to unnecessary overhead.

How can indexes be altered or removed in SQL?

Indexes in SQL can be altered by modifying visibility, adding or removing columns, or changing storage parameters. Removing an index involves using the ‘DROP INDEX’ statement. However, caution is necessary, as altering or removing indexes should be approached thoughtfully to avoid impacting database performance.

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About the Author

Principal Data Scientist

Meet Akash, a Principal Data Scientist who worked as a Supply Chain professional with expertise in demand planning, inventory management, and network optimization. With a master’s degree from IIT Kanpur, his areas of interest include machine learning and operations research.

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