MCSA Certification Tutorial: The Core Indexing Concepts in SQL Server

Perhaps the most essential part of being able to develop and optimize SQL to its full potential is the usage of indexes. That’s why you need to learn the core indexing concepts in SQL Server as you prepare for your MCSA Certification.

This article looks into how indexes works and can help you develop a clear understanding of how indexes can benefit the data retrieval process.

Indexes in SQL

Indexes help quickly retrieving data from tables, thus saving time and promoting efficiency.

To help you understand this better, consider the following example:

Say you’ve been reading a book on coding using C++. If one day you feel the need to pull up a certain section from the book, you can do this simply by locating the section using the index. This will save you time and is a far more efficient method instead of you having to go through the entire book in search of a certain piece of information.

Applying this principle in the world of SQL, a database without indexes would have trouble locating specific pieces of information without crawling the entire database every single time the request is made. With the presence of indexes, this process is sped up and made much more effective.

Creating Indexes in SQL

Indexes in SQL are a method of fine-tuning the performance of a database and allowing faster retrieval of information. Indexes work by creating a separate entry for each element present in the indexed columns. This makes it easy for the system to quickly run searches and locate specific information.

Syntax for Creating an Index in SQL

Index with One Field

CREATE [UNIQUE] INDEX name_index

ON the_name (col1, col2, ... col n);

Break-down of terms used in the syntax are as follows:

the_name

This represents the name that has been assigned to the index.

UNIQUE

This represents a modifier that highlights that the values contained in the columns to be indexed are to be unique.

name_index

This represents the name of the index that is being created.

col1, col2, ... col n

These represent the names of columns that will be used for creating the index.

Here’s an example that shows how to create an index:

CREATE INDEX tokens_new

 ON websites (token_names);

The example shows the creation of an index representing a column for token called tokens_new. The index feature a single field; token_names.

Index with More Than One Field

Indexes can be designed to cover more than one field.

CREATE INDEX tokens_new

ON websites (token_names, token_id);

Being very similar to how you would create an index for a single field, this example would create an index token_names based off two columns: token_names and token_id

Removing an Index

Removing/dropping an index can be very easily accomplished using the DROP INDEX statement.

The following is the syntax for removing an index:

DROP INDEX table_name.index_name;

Break-down of terms used in the syntax are as follows:

  • index_name

This represents the name of the index that is to be removed.

  • table_name

This represents the name of the index it relates to.

Example:

DROP INDEX tokens.token_names;

While most SQL developers understand the applications of indexes and their use in enabling processes to run faster and more smoothly, they often miss out on the measures that can be taken to compliment the creation of indexes.

Things to Remember When Creating Indexes in SQL

Questions such as: How can I use indexes to speed up queries or update them, how can I develop indexes that save up space and enhance the processing speed, are important to consider.

The following are some tips on creating indexes in SQL:

Declare Columns for Indexing As “NOT NULL”

For columns that you are looking to build indexes for, we recommend that you declare them as “NOT NULL.” This technique saves space and speeds up the time it takes to process queries.

Use Columns with Integer Types When Creating Indexes

Save space and accelerate the process of data retrieval by creating indexes on columns with integer types. Integers generally take less storage space and can speed up the process of finding information contained within a dataspace.

Furthermore, when using columns that are not of type integer, we recommend that you develop a substitute integer key or a substitute column of type integer and map it on to the column that you are looking to design the index for.

Use Columns With Lowest Cardinality First

The sequence of columns when building indexes is very important. We recommend that you use columns with the lowest number of elements first and move your way to the column with the highest number of elements.

Use Narrow Indexes

The less storage space that you use, the faster the system can process. Narrower indexes that take up a limited amount of space can help queries run at a faster speed and promote greater efficiency.

The advantages of using indexes in SQL are also associated with the costs of sacrificing disk space and slower INSERT, UPDATE, and DELETE operations. To be willing to comprise on the speed of these operations to speed up the process of entertaining queries is worth looking into.

Having said that, being able to deal with databases consisting of tens and hundreds of records under one table, and being able to retrieve information can take a very long time. Indexes representing these columns can make the retrieval of information efficient and help tackle queries in the shortest time possible.

Reflecting upon the teaching contained in MCSA Certification courses, we recommend that businesses and users can identify the particular needs that they are looking to satisfy with the use of a SQL server. They can then highlight the columns that they access frequently and decide on a number of indexes they require to carry out their routine tasks.