Real-Time Data Processing with Apache Spark Structured Streaming

Real-Time Data Processing with Apache Spark Structured Streaming

Real-time data analytics is no longer a luxury—it's a necessity. Understanding and acting on data as it flows can be the difference between staying ahead or falling behind.

In my latest video, I explained real-time analytics using Apache Spark Structured Streaming. This session covers:

  • The fundamentals of real-time analytics and its significance

  • Contrasting batch processing with stream processing

  • An in-depth look at Spark Structured Streaming mechanics

  • Integrating Spark with data sources like Kafka and socket streams

  • Real-world applications including fraud detection, system monitoring, and alerting

Whether you're a data engineer, backend developer, or a cloud enthusiast, this video offers valuable insights into building scalable, real-time data pipelines.

Watch the full video here: Real-Time Analytics with Apache Spark | Stream Processing Explained

Let's explore how to harness the power of real-time data for smarter decision-making.

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