Database Index: An Introduction for Beginners

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“Database index” refers to a special type of data structure that speeds up the retrieval of records from a database table. Database indexes ensure that you can efficiently find and access the data in a database table without having to search through every row each time a database query is processed.

A database index can be compared to the index of a book. Indexes in databases refer you to the desired record in the database, just as the index page of a book refers you to the desired topic or chapter.

Although database indexes are essential for fast and efficient data search and access, they consume additional writes and disk space.

What is an index?

Database indexes are special look-up tables that consist of two columns. The first column is the search key and the second is the data pointer. The keys are the values ​​that you want to find and retrieve from your database table, and the pointer or reference stores the disk block address in the database for that particular search key. The key fields are sorted to expedite the data retrieval process for all of your queries.

Why use database indexing?

Here, I’ll show you database indexes in a simplified way. Let’s say you have a database table of the eight employees in a company and you want to search the information for the last entry in the table. To find the previous entry, you now need to search through every row in the database.

For example, suppose you sorted the table alphabetically by the employee’s first name. So here indexing keys are based on the “name column”. If you are looking for the last entry in this case, “Zack“You can jump to the middle of the table and decide whether our entry is before or after the column.

As you know, it comes after the middle row, and you can divide the rows in half again after the middle row and do a similar comparison. That way, you don’t have to go through each line to find the last entry.

Database indexing points to table

If the company had 1,000,000 employees and the last entry was “Zack,” you would have to search 50,000 lines to find his name. With alphabetical indexing, on the other hand, you can do this in just a few steps. You can now imagine how much faster data searching and access can be with database indexing.

Related: The 13 Most Important SQL Commands Every Programmer Should Know

Different file organization methods for database indexes

Indexing depends heavily on the file organization mechanism used. There are typically two types of file organization methods used in database indexing to store data. They are discussed below:

1.Ordered index file: This is the traditional way of storing index data. This method sorts the key values ​​in a specific order. Data in an ordered index file can be stored in two ways.

  • Sparse index: With this type of indexing, an index entry is created for each data record.
  • Density index: Dense indexing creates an index entry for some records. To find a record using this method, you must first determine the most important search key value from index entries that are less than or equal to the search key value you are looking for.

2. Hash file organization: In this file organization method, a hash function determines the location or block of disk where a data set is stored.

Types of database indexing

There are generally three methods of database indexing. You are:

  • Clustered indexing

  • Not clustered indexing

  • Multi-level indexing

1. Clustered indexing

Clustered indexing

With clustered indexing, a single file can hold more than two records. The system keeps the actual data in the clustered indexing instead of the pointers. Searching with clustered indexing is cost effective because all related data is stored in the same location.

A clustering index uses ordered data files to define itself. Merging several database tables is also very common with this type of indexing.

It is also possible to build an index based on non-primary columns that are not unique for each key. In such cases, multiple columns are combined to form the unique key values ​​for clustered indexes.

In short, clustering indexes is where similar types of data are grouped and indexed on them.

Example: Suppose there is a company with over 1,000 employees in 10 different departments. In this case, the company should create a clustering indexing in their DBMS to index the employees who work in the same department.

Each cluster with employees working in the same department is defined as a single cluster, and data pointers in indexes refer to the cluster as a whole.

Related: What Are Foreign Keys in SQL Databases?

2. Ungrouped indexing

Non-clustered database indexing

Ungrouped indexing refers to a type of indexing in which the order of the index rows does not match the physical storage of the original data. Instead, a non-clustered index points to the data store in the database.

Example: Clusterless indexing is like a book with an ordered content page. Here the data pointer or reference is the ordered content page sorted alphabetically and the actual data is the information on the book pages. The content page does not store the information in the order it appears on the book pages.

3. Multi-level indexing

multi-level database indexing

Multi-level indexing is used when the number of indexes is very high and the primary index cannot be stored in main memory. As you may know, database indexes are made up of search keys and data pointers. As the database size increases, so does the number of indexes.

However, to ensure a fast search process, index records must be kept in memory. If a single-level index is used when the index number is high, its size and the multiple accesses make it unlikely that this index will be stored in memory.

This is where multi-level indexing comes into play. This technique breaks the single-level index into several smaller blocks. Once broken up, the outer level block becomes so tiny that it can be easily stored in main memory.

Related: How to Connect to a MySQL Database Using Java Database

What is SQL Index Fragmentation?

If any order of the index pages does not match the physical order in the data file, SQL index fragmentation will result. Initially, all SQL indexes are without fragmentation, but repetitive use of the database (insert / delete / modify data) can result in fragmentation.

Aside from database fragmentation, your database can also face other important issues like database corruption. This can lead to data loss and a damaged website. If you do business with your website, it can be a blow to you.


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