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

Built-in functions

Stream Analytics query language (SAQL) comes with many built-in functions to assist with aggregating and transforming data. These functions can help us with simple operations on a single value, as in data type conversions and string concatenations, as well as with more complex operations, like identifying the first event in a period of time or geospatial intersections of event locations. Types of built-in functions include scalar, record, mathematical, input metadata, date and time, aggregate, analytic, geospatial, and array functions.

Scalar functions

Simple functions that operate on a single value and return a single value are known as scalar functions. SAQL provides many scalar functions for string manipulation. For example, UPPER capitalizes all characters in a string expression, as in the following query example:

select ehinput.timestamp,, ehinput.speed, ehinput.outsidetemperature,
    UPPER( as city
from ehinput

Note the uppercase values in column...