How to Create and Manage Indexes in SQL Server

May 27, 2014 , , , 0 Comments

Database developer is often required to improve the performance of queries. SQL Server allows implementing indexes to reduce the execution time of queries. In addition they can restrict the view of data to different users by implementing views.

The SQL Server also provides an in-built full-text search capability that allows fast searching of data. This article discusses how to create and manage indexes and views.

Creating and Managing Indexes

When a user queries data from a table based on conditions, the server scans all the data stored in the database table. With an increasing volume of data, the execution time for queries also increases. As a database developer, you need to ensure that the users are able to access data in the least possible time. SQL Server allows you to create indexes on tables to enable quick access to data. In addition, SQL Server allows you to create XML indexes for columns that store XML data.

At times, the table that you need to search contains voluminous data. In such cases, it is advisable to create partitioned indexes. A partitioned index makes the index more manageable and scale able as they store only data of a particular partition.

As a database developer, you need to create and manage indexes. Before creating an index, it is important to identify the different types of indexes.

Identifying the Types of Indexes

Before identifying the types of indexes, it is important to understand the need to implement an index.
The data in the database tables is stored in the form of data pages. Each data page is 8 KB in size. Therefore, data of the complete table is stored in multiple data pages. When a user queries a data value from the table, the query processor searches for the data value in all the data pages. When it finds the value, it returns the result set. With an increasing volume of data, this process of querying data takes time.

To reduce the data query time, the SQL Server allows you to important indexes on tables. An index is a data structure associated with a table that helps in fast search of data in the table. Indexes in the SQL Server are like the indexes at the back of a book that you can use to locate text in the book.

Benefits provided by using Indexes:

  • Accelerate queries that join tables, and perform sorting and grouping
  • Enforce uniqueness of rows, (if configured for that)

An index contains a collection of keys and pointers. Keys are values built from one or more columns in the table with which the key is associated. The column on which the key is built is the one on which the data is frequently searched. Pointers store the address of the storage location where a data page is stored in the memory, as depicted in the following figure.

How to Create and Manage Indexes in SQL Server

When the users query data with conditions based on the key columns, the query processor scans the indexes, retrieves the address of the data page where the required data is stored in the memory, and accesses the information. The query processor does not need to search for data in all the data pages. Therefore, the query execution time is reduced.

The keys in the indexes are stored in a B-Tree in the memory. A B-Tree is a data-indexing method that organizes the index into a multi-level set of nodes. Each page in an index B-Tree is called an index node. Each index contains a single root page at the top of the tree. This root page, or root node, branches out into n number of pages at each intermediate level until it reaches the bottom, or leaf level, of the index. The index tree is traversed by following pointers from the upper-level pages down through the lower-level pages.

The key values in the root page and the intermediate pages are sorted in the ascending order. Therefore, in the B-Tree structure, the set of nodes on which the server will search for data values is reduced. This enables the SQL Server to find the records associated with the key values quickly and efficiently. When you modify the data of an indexed column, the associated indexes are updated automatically.

Rhett Butler

Some say he’s half man half fish, others say he’s more of a seventy/thirty split. Either way he’s a fishy bastard. Google