Efficient streaming data processing is critical for real-time analytics and decision-making. In this course, Window and Join Operations in Apache Spark, you'll learn how to apply windowing techniques like tumbling, sliding, and session windows to process streaming data, handle late-arriving data with watermarks, and implement stream-static and stream-stream joins for enriching and combining datasets in real time. When you’re finished with this course, you’ll have a better understanding of how to manage streaming data workflows for efficient, real-time analytics using Spark.
Overview
Efficient streaming data processing is critical for real-time analytics and decision-making. In this course, Window and Join Operations in Apache Spark, you'll learn how to apply windowing techniques like tumbling, sliding, and session windows to process streaming data, handle late-arriving data with watermarks, and implement stream-static and stream-stream joins for enriching and combining datasets in real time. When you’re finished with this course, you’ll have a better understanding of how to manage streaming data workflows for efficient, real-time analytics using Spark.
Taught by
Pinal Dave
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