Book Image

Guide to NoSQL with Azure Cosmos DB

By : Gaston C. Hillar, Daron Yöndem
Book Image

Guide to NoSQL with Azure Cosmos DB

By: Gaston C. Hillar, Daron Yöndem

Overview of this book

Cosmos DB is a NoSQL database service included in Azure that is continuously adding new features and has quickly become one of the most innovative services found in Azure, targeting mission-critical applications at a global scale. This book starts off by showing you the main features of Cosmos DB, their supported NoSQL data models and the foundations of its scalable and distributed architecture. You will learn to work with the latest available tools that simplify your tasks with Cosmos DB and reduce development costs, such as the Data Explorer in the Azure portal, Microsoft Azure Storage Explorer, and the Cosmos DB Emulator. Next, move on to working with databases and document collections. We will use the tools to run schema agnostic queries against collections with the Cosmos DB SQL dialect and understand their results. Then, we will create a first version of an application that uses the latest .NET Core SDK to interact with Cosmos DB. Next, we will create a second version of the application that will take advantage of important features that the combination of C# and the .NET Core SDK provides, such as POCOs and LINQ queries. By the end of the book, you will be able to build an application that works with a Cosmos DB NoSQL document database with C#, the .NET Core SDK, LINQ, and JSON.
Table of Contents (13 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Chapter 3. Writing and Running Queries on NoSQL Document Databases

In this chapter, we will write and run queries to retrieve data from documents in a collection. We will use the Cosmos DB dialect of SQL to work against a document database with the SQL API. We will understand the different ways of working with the documents, their sub-documents, and their arrays, and we will learn how queries consume resource units. We will do the following in this chapter:

  • Run queries against a collection with different tools
  • Understand query results in JSON arrays
  • Check the request units spent by a query
  • Work with schema-agnostic queries
  • Use built-in array functions
  • Work with joins
  • Use array iteration
  • Work with aggregate functions