Overview/Description
Learn the fundamentals of streaming data with Apache Spark. During this course, you will discover the differences between batch and streaming data. Observe the types of streaming data sources. Learn about how to process streaming data, transform the stream, and materialize the results. Decouple a streaming application from the data sources with a message transport. Next, learn about techniques used in Spark 1.x to work with streaming data and how it contrasts with processing batch data; how structured streaming in Spark 2.x is able to ease the task of stream processing for the app developer; and how streaming processing works in both Spark 1.x and 2.x. Finally, learn how triggers can be set up to periodically process streaming data; and the key aspects of working with structured streaming in Spark
Streaming Data Architectures: An Introduction to Streaming Data
Course Overview
recognize the differences between batch and streaming data and the types of streaming data sources
list the steps in involved in processing streaming data, the transformation of streams, and the materialization of the results of the transformation
describe how the use of a message transport decouples a streaming application from the sources of streaming data
describe the techniques used in Spark 1.x to work with streaming data and how it contrasts with processing batch data
recall how structured streaming in Spark 2.x is able to ease the task of stream processing for the app developer
compare how streaming processing works in both Spark 1.x and 2.x
recognize how triggers can be set up to periodically process streaming data and describe the various output modes available to publish the results of stream processing
recognize the key aspects of working with structured streaming in Spark