Book Image

Stream Analytics with Microsoft Azure

By : Krishnaswamy Venkataraman, Anindita Basak, Ryan Murphy, Manpreet Singh
Book Image

Stream Analytics with Microsoft Azure

By: Krishnaswamy Venkataraman, Anindita Basak, Ryan Murphy, Manpreet Singh

Overview of this book

Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time. This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data.
Table of Contents (18 chapters)
Title Page
About the Authors
About the Reviewers
Customer Feedback

Chapter 5. Building Using Stream Analytics Query Language

In this chapter, we will explore the SQL-like query language used in Azure Stream Analytics to run transformations and computations on streaming data. We'll discuss how common and complex stream processing requirements can be met with straightforward queries, demonstrating with samples along the way.

Specifically, the topics we will cover in the chapter are:

  • Using built-in functions within queries to parse, aggregate, and transform streaming data
  • Working with simple and complex data types typical of streaming data
  • Exploring the building block elements of the Stream Analytics query language
  • Windowing to perform computation on events grouped by configurable periods of time
  • Handling the temporal nature of streaming data with job configuration settings and time management query patterns
  • Understanding event delivery guarantees offered by Stream Analytics


Most examples in this chapter use data and resources generated by the Cortana Intelligence...