In database management systems (DBMS), indexing is a technique used to optimize data retrieval from tables. Indexing is a way of sorting data based on specific columns, and this sorting is used to speed up queries that search for specific values or ranges of values. Indexing in DBMS improves the performance of database queries by reducing the number of disk accesses required to retrieve data.
📘 What is Indexing in DBMS?
In a database, an index is a data structure that provides a quick look-up of specific data based on the values in one or more columns. Indexes are used to speed up data retrieval and improve the performance of queries. Indexing works by creating a separate table that contains the indexed column values and a pointer to the original table's location. This makes it possible to retrieve data quickly, without having to search through the entire table.
📘 Types of Indexes in DBMS
There are several types of indexes in DBMS, each with its own advantages and disadvantages. The most common types of indexes are:
♦ Primary Index in DBMS
A primary index is an index that is created on a primary key column in a database table. Primary keys are unique identifiers that are used to identify each row in a table. A primary index is created automatically when a primary key is defined for a table. It is a type of clustered index that is used to physically order the table based on the primary key.
Example: Consider a table called "Employees" with columns "EmpID", "EmpName", "EmpDept", and "EmpSalary". The primary key for this table is the "EmpID" column. A primary index will be created automatically on the "EmpID" column to allow for fast retrieval of rows based on the primary key.
♦ Secondary Index in DBMS
A secondary index is an index that is created on a non-primary key column in a database table. Secondary indexes are used to speed up data retrieval for columns that are frequently searched but are not part of the primary key. Unlike primary indexes, secondary indexes do not order the physical data in the table.
Example: Consider the same "Employees" table with a secondary index on the "EmpDept" column. This index allows for faster retrieval of rows based on the department that the employee works in.
♦ Clustering Index in DBMS
A clustering index is a type of index that is used to physically order the data in a table based on the values in one or more columns. Clustering indexes are often used in conjunction with primary keys to order the table based on the primary key. They can also be used to order the table based on a non-primary key column.
Example: Suppose we have a table called "Sales" with columns "ProductID", "ProductDescription", "SalesDate", and "SalesAmount". We create a clustering index on the "SalesDate" column to physically order the data in the table based on the date of the sale.
♦ Multilevel Index in DBMS
A multilevel index is a type of index that is used to improve the performance of queries on very large tables. A multilevel index is created by creating a primary index on a subset of the table, and then creating secondary indexes on the remaining subsets. This creates a hierarchical structure of indexes that allows for faster data retrieval.
Example: Suppose we have a table called "Customers" with millions of rows. We create a primary index on the "CustomerID" column, and then create secondary indexes on subsets of the table based on geographic location, age, and other factors. This creates a hierarchical structure of indexes that allows for fast data retrieval.
♦ B-Tree Index in DBMS
A B-tree index is a type of index that is commonly used in DBMS. A B-tree index is a balanced tree structure that is used to organize data for quick access. B-tree indexes are used for range queries and exact match queries.
Example: Suppose we have a table called "Inventory" with columns "ProductID", "ProductName", "ProductDescription", "ProductPrice", and "ProductQuantity". We create a B-tree index on the "ProductPrice" column to allow for fast retrieval of products based on price. The B-tree index creates a balanced tree structure with pointers to the data in the table, allowing for fast data retrieval.
In the example above, the B-tree index is created on the "ProductPrice" column. Each node in the tree contains a range of values and pointers to the next level of the tree. The leaf nodes of the tree contain pointers to the actual data in the table. When a query is made to retrieve data based on the "ProductPrice" column, the B -tree index is used to quickly find the relevant leaf nodes, which contain pointers to the data in the table.
In conclusion, indexing is a crucial aspect of database management systems that plays a key role in improving the performance of data retrieval operations. Primary indexes, secondary indexes, clustering indexes, multilevel indexes, and B-tree indexes are some of the different types of indexes that are commonly used in DBMS. Understanding the advantages and disadvantages of each type of index is essential for selecting the appropriate indexing strategy for a given application.
📘 Clustered Index vs Non - clustered Index
Clustered Index and Non-Clustered Index are two types of indexing techniques used in database management systems. Here is a comparison between clustered and non-clustered indexes in tabular form:
A clustered index determines the physical order of data in a table and is ideal for columns that are frequently searched and sorted, while a non-clustered index is created separately from the table and is ideal for columns that are infrequently searched and sorted. The choice between clustered and non-clustered indexes depends on the specific requirements of the application and the characteristics of the data being indexed.
📘 Advantages of Indexing
📘 Disadvantages of Indexing
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