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

Integration of JavaScript user-defined functions using Azure Stream Analytics

JavaScript user-defined functions with the enhanced support of String, Math, Array, Date, regular expressions, Integer to Float conversion, and hex to decimal/binary/integer functions are supported with Azure Stream Analytics to apply query transformation, on streaming data. These functions provide generic stateless computation values applied to input data streams or reference data streams of Stream Analytics without plugging into any data source.

The JavaScript UDF for Stream Analytics jobs are advantageous in the following domains:

  • Data Streams with string manipulation with JavaScript regular expression functions like Regexp, along with String methods like extract (Regexp_extract), replace (Regexp_replace), match (Regexp_match), and split (Regexp_split)
  • Data events conversion, for example, Hex to Integer, decimal to binary, and data encoding/decoding
  • Mathematical and statistical function computations on complex events...