Handling Time in Azure Stream Analytics
When you’re collecting streaming data for analysis, there’s a delay between the time when an event occurs and the time when your analytics system receives the data about that event. Usually, this delay is relatively short, but it can be much longer, such as when a system sending data temporarily loses its connection to the system receiving the data. This delay causes a surprising number of complications.
In this lesson, you’ll learn how Azure Stream Analytics handles late-arriving, early-arriving, and out-of-order events. You’ll also learn how it uses a watermark to determine when to output results.
Learning Objectives
- Describe how Azure Stream Analytics handles late-arriving, early-arriving, and out-of-order events
- Describe the function of watermarks in Azure Stream Analytics
- Describe the metrics that can be used to monitor and troubleshoot Azure Stream Analytics jobs
Intended Audience
- Azure data engineers
Prerequisites
- Basics of Azure Stream Analytics (or take Introduction to Azure Stream Analytics)
- How it ingests data
- How it uses time windows to process data
Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).