SQL Server Index Architecture and Design Guide

SQL Server Index Architecture and Design Guide

  • 01/19/2019
  • 64 minutes to read


Applies to: SQL Server (all supported versions) Azure SQL Database Azure SQL Managed Instance Azure Synapse Analytics Parallel Data Warehouse

Poorly designed indexes and a lack of indexes are primary sources of database application bottlenecks. Designing efficient indexes is paramount to achieving good database and application performance. This SQL Server index design guide contains information on index architecture, and best practices to help you design effective indexes to meet the needs of your application.

This guide assumes the reader has a general understanding of the index types available in SQL Server. For a general description of index types, see Index Types.

This guide covers the following types of indexes:

•    Clustered
•    Nonclustered
•    Unique
•    Filtered
•    Columnstore
•    Hash
•    Memory-Optimized Nonclustered
For information about XML indexes, see XML Indexes Overview.
For information about Spatial indexes, see Spatial Indexes Overview.
For information about Full-text indexes, see Populate Full-Text Indexes.

Index Design Basics

Think about a regular book: at the end of the book there is an index which helps to quickly locate information within the book. The index is a sorted list of keywords and next to each keyword is a set of page numbers pointing to the pages where each keyword can be found. A SQL Server index is no different: it is an ordered list of values and for each value there are pointers to the data pages where these values are located. The index itself is stored on pages, making up the Index Pages in SQL Server. In a regular book, if the index spans multiple pages and you have to find pointers to all the pages that contain the word "SQL" for example, you would have to leaf through until you locate the index page that contains the keyword "SQL". From there you follow the pointers to all the book pages. This could be optimized further if at the very beginning of the index, you create a single page that contains an alphabetical list of where each letter can be found. For example: "A through D - page 121", "E through G - page 122" and so on. This additional page would eliminate the step of leafing through the index to find the starting place. Such page does not exist in regular books, but it does exist in a SQL Server index. This single page is referred to as the root page of the index. The root page is the starting page of the tree structure used by a SQL Server index. Following the tree analogy, the end pages which contain pointers to the actual data are referred to as "leaf pages" of the tree.

A SQL Server index is an on-disk or in-memory structure associated with a table or view that speeds retrieval of rows from the table or view. An index contains keys built from one or more columns in the table or view. For on-disk indexes, these keys are stored in a tree structure (B-tree) that enables SQL Server to find the row or rows associated with the key values quickly and efficiently.

An index stores data logically organized as a table with rows and columns, and physically stored in a row-wise data format called rowstore 1, or stored in a column-wise data format called columnstore.

The selection of the right indexes for a database and its workload is a complex balancing act between query speed and update cost. Narrow indexes, or indexes with few columns in the index key, require less disk space and maintenance overhead. Wide indexes, on the other hand, cover more queries. You may have to experiment with several different designs before finding the most efficient index. Indexes can be added, modified, and dropped without affecting the database schema or application design. Therefore, you should not hesitate to experiment with different indexes.

The query optimizer in SQL Server reliably chooses the most effective index in the vast majority of cases. Your overall index design strategy should provide a variety of indexes for the query optimizer to choose from and trust it to make the right decision. This reduces analysis time and produces good performance over a variety of situations. To see which indexes the query optimizer uses for a specific query, in SQL Server Management Studio, on the Query menu, select Include Actual Execution Plan.

Do not always equate index usage with good performance, and good performance with efficient index use. If using an index always helped produce the best performance, the job of the query optimizer would be simple. In reality, an incorrect index choice can cause less than optimal performance. Therefore, the task of the query optimizer is to select an index, or combination of indexes, only when it will improve performance, and to avoid indexed retrieval when it will hinder performance.

1 Rowstore has been the traditional way to store relational table data. In SQL Server, rowstore refers to table where the underlying data storage format is a heap, a B-tree (clustered index), or a memory-optimized table.

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