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Chapter 1: Using SAS Event Stream Processing to Process Real World Events
By Michael Harvey, Robert Ligtenberg, and Jerry Baulier
Introduction
How Does SAS Event Stream Processing Work?
What is a SAS Event Stream Processing Model?
Processing Events in Derived Windows
Examples of Event Transformations
Example: Using a Join Window
Example: Using a Pattern Window and a Notification Window
Streaming Analytics
Using SAS Micro Analytic Service Modules with Streaming Analytics
Addressing Big Data and the Internet of Things
Edge Model to Process Measurements from a Power Substation
On-Premises Model for Further Processing
Conclusion
About the Contributors
Introduction
As Andrew G. Psaltis, the regional CTO for Cloudera, observes, “Data is flowing everywhere around us, through phones, credit cards, sensor-equipped buildings, vending machines, thermostats, trains, buses, planes, posts to social media, digital pictures and video – and the list goes on.” Being able to harness that data presents abundant business opportunities. How can a business best capitalize on those opportunities?
The answer: SAS Event Stream Processing. It enables you to process and analyze continuously flowing real-world events in real time. Events arrive through high-throughput, low-latency data flows called event streams. These data flows are generated by occurrences such as sensor readings or market data. Each event within an event stream can be represented as a data record that consists of any number of fields. For example, an event generated by a pressure sensor could include two fields: a pressure reading and a timestamp. A more complex financial trade event could include multiple fields for transaction type, shares traded, price, broker, seller, stock symbol, timestamp, and so on. SAS Event Stream Processing can process the pressure data or the trades at any given moment. It can alert you to events of interest the instant that they occur.
Innovations in technology have enabled the reduction of the cost and size of sensors. Now sensors can be readily deployed within industrial equipment and consumer products. The number of sensors available has exploded, and a large portion of these sensors are now connected through the internet. The deluge of resulting data streams is often called Big Data. The Internet of Things (IoT) attaches a plethora of devices, sensors, and objects in our world to the internet. Big Data is collected and processed in real time from these “things.”
SAS Event Stream Processing processes real-world data as it is generated. This instantly processed data is called streaming data. Processing streaming data introduces a paradigm shift from the traditional approach, where data is captured and stored in a database. After an event from an event stream is processed, it can be stored or discard...
