Practical Graph Structures in SQL Server and Azure SQL: Enabling Deeper Insights Using Highly Connected Data

ISBN-13: 9781484294581 / Angielski

Louis Davidson

Opis

Intermediate-Advanced user level

Use the graph table features in Azure SQL that were introduced in SQL Server 2017 and further refined in SQL Server 2019. This book shows you how to create data structures to capture complex connections between items in your data. These connections will help you analyze and draw insights from connections in your data that go beyond classic relationships.

The graph examples in the book are useful for analyzing social media relationships, complex product-to-customer relationships, and any other type of data analysis in which indirect connections that otherwise might be missed using conventional techniques can be mined for their insight and business value. 
Tree structures are covered, with emphasis on a structure commonly used by organizations to aggregate data at different levels of an organization. The book provides code examples of SQL Graph objects as well as an alternate tree implementation technique. Included is sample data (and data generators) for you to test for performance and choose the implementation approach that best suits your needs and that of your application.
If your job involves analyzing or storage of data elements that are connected in a networked topology, then this is the book that will help you bring the power of SQL Server to bear on that data and take advantage of your existing knowledge.  

What You Will Learn

• Understand the graph model and the associated terms used in graph analysis
  
• Store highly connected data in SQL Server and Azure SQL alongside existing relational data
• Make full use of the graph table feature that is refined and enhanced in SQL Server 2019
• Implement high performance tree structures that will make storing and querying tree data possible
• Report on data associated with a tree structure to aggregate results at different levels
  

Who This Book Is For

Spis treści

1. Introduction to Graphs: What a graph is, and ways graphs can be used

2. Data Structures and Algorithms: How graphs are implemented, and the algorithms that are used to process them

3. SQL Graph Tables Basics: The syntax that Microsoft has implemented for use with graph data stored in SQL Server tables

4. SQL Graph Tables: Extended Topics: Methods that can help you load and protect the integrity of the data in your SQL Graph tables

5. Tree Data Structures: A tree structure built using SQL Graph objects, including code to load and manipulate those nodes in ways that you will need when building production systems

6. Tree Structures, Algorithms, and Performance: A new method of implementing a tree, objects that can help you report on your trees faster, and how these methods perform with certain sized data sets

7. Other Directed Acyclic Graphs: A bill of materials directed acyclic graph to demonstrate the techniques you will need when you are working with these structures that are similar to trees

8. A Graph for Testing: A graph structure and data generation tools for you to try on large sets of data to match your expected needs, and a set of performance tips for handling graph objects

O autorze

Louis Davidson has been working with databases for more than 25 years as a corporate database developer and architect, and is now the editor for the Redgate Simple Talk website. He has been a Microsoft MVP for 18 years. In addition to this book on graphs, he has written six editions of his general-purpose SQL Server database design book (Apress).

Louis has been active in speaking about database design and implementation at many conferences over the past 25 years, including SQL PASS, SQL Rally, SQL Saturday events, CA World, Music City Data, and the devLink Technical Conference. He has a bachelor’s degree in computer science from the University of Tennessee at Chattanooga. For more information, please visit his website at drsql.org. 

Blurb

Use the graph table features in Azure SQL that were introduced in SQL Server 2017 and further refined in SQL Server 2019. This book shows you how to create data structures to capture complex connections between items in your data. These connections will help you analyze and draw insights from connections in your data that go beyond classic relationships.

The graph examples in the book are useful for analyzing social media relationships, complex product-to-customer relationships, and any other type of data analysis in which indirect connections that otherwise might be missed using conventional techniques can be mined for their insight and business value. 

Tree structures are covered, with emphasis on a structure commonly used by organizations to aggregate data at different levels of an organization. The book provides code examples of SQL Graph objects as well as an alternate tree implementation technique. Included is sample data (and data generators) for you to test for performance and choose the implementation approach that best suits your needs and that of your application.

If your job involves analyzing or storage of data elements that are connected in a networked topology, then this is the book that will help you bring the power of SQL Server to bear on that data and take advantage of your existing knowledge.  

What You Will Learn

• Understand the graph model and the associated terms used in graph analysis
  
• Store highly connected data in SQL Server and Azure SQL alongside existing relational data
• Make full use of the graph table feature that is refined and enhanced in SQL Server 2019
• Implement high performance tree structures that will make storing and querying tree data possible
• Report on data associated with a tree structure to aggregate results at different levels