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What are Different Types of Databases?
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SQL Select
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String Functions in SQL
A Quick Guide to Pivoting Data
Advanced
Databricks SQL Functions
Trino Advanced SQL
CoginitiScript Macros
Churn Rate
Index in SQL
Query Date and Time
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Round Timestamps
Get the First Row per Group
CoginitiScript Constants
Analysis
Coalesce in SQL
Calculating Percentiles
How to Do Type Casting
Import a CSV
Compare Values When One Is Null
How to Query a JSON Column
How to Write a Case Statement
How to Have Multiple Counts
Using a Common Table Expression (CTE)
Calculate Cumulative Sum (Running Total)

Index in SQL

In SQL, an index is a data structure used to improve the speed of data retrieval operations on a database table. An index is essentially a copy of a portion of a table that is stored separately and organized in a way that allows the database to find information more quickly.

When you create an index on a table, the database management system (DBMS) creates a separate structure that contains the values of the indexed columns and a pointer to the location of the corresponding data in the table. This makes it faster for the DBMS to search for data based on the indexed column(s) because it does not have to scan the entire table. Instead, it can use the index to locate the relevant rows quickly.

An index can be created on one or more columns of a table. When creating an index, specify whether it should be clustered or non-clustered. A clustered index determines the physical order of the data in the table, while a non-clustered index does not.  You can also specify whether the index key is unique or not.  Unique indexes often increase SELECT performance, and often create implicit unique constraints, which can help with data integrity.

While indexes can improve the performance of data retrieval operations, they can also have some drawbacks. For example, indexes can slow down data modification operations such as INSERT, UPDATE, and DELETE because the DBMS must update the table and the index. Additionally, indexes can take up a significant amount of disk space, especially for large tables with many columns.

Here’s a list of scenarios so you know when it’s a good idea to use SQL index:

  1. Frequent Queries: If a table is queried frequently and has many rows, an index can significantly improve query performance by reducing the number of reads needed to find the desired data.
  2. Large Tables: In large tables, indexes can greatly improve query performance, especially when the queries involve sorting, grouping, or filtering large amounts of data.
  3. Complex Joins: When complex joins are required between multiple tables, indexes can help the database engine optimize the join operation by efficiently locating the required data.
  4. Unique and Primary Keys: Indexes are automatically created on columns defined as unique or primary keys. These indexes can improve performance when querying or modifying data based on these columns.
  5. Where Clause: If the WHERE clause includes a condition that filters a large portion of the data, an index on the columns used in the WHERE clause can improve query performance.

However, it is important to note that creating too many indexes on a table can negatively affect performance, as it can increase the time it takes to insert, update or delete data. Therefore, creating indexes judiciously and only when necessary for improving query performance is important.

While there are many variations on the implementation of indexes across different database platforms, the general syntax specifies the index name, the table to index, and the index keys or column name(s):

CREATE INDEX table_name_idx ON table_name(column_name)