Structured streaming is the scalable and fault-tolerant stream processing engine in Apache Spark 2 which can be used to process high-velocity streams.
Stream processing applications work with continuously updated data and react to changes in real-time. In this course, Processing Streaming Data Using Apache Spark Structured Streaming, you'll focus on integrating your streaming application with the Apache Kafka reliable messaging service to work with real-world data such as Twitter streams. First, you’ll explore Spark’s architecture to support distributed processing at scale. Next, you will install and work with the Apache Kafka reliable messaging service. Finally, you'll perform a number of transformation operations on Twitter streams, including windowing and join operations. When you're finished with this course you will have the skills and knowledge to work with high volume and velocity data using Spark and integrate with Apache Kafka to process streaming data.
Stream processing applications work with continuously updated data and react to changes in real-time. In this course, Processing Streaming Data Using Apache Spark Structured Streaming, you'll focus on integrating your streaming application with the Apache Kafka reliable messaging service to work with real-world data such as Twitter streams. First, you’ll explore Spark’s architecture to support distributed processing at scale. Next, you will install and work with the Apache Kafka reliable messaging service. Finally, you'll perform a number of transformation operations on Twitter streams, including windowing and join operations. When you're finished with this course you will have the skills and knowledge to work with high volume and velocity data using Spark and integrate with Apache Kafka to process streaming data.
