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Learn to build real-time streaming applications using Apache Flink and Java through hands-on exercises that demonstrate processing data as it flows rather than in batches. Master the fundamentals of distributed stream processing by creating applications that consume Apache Kafka data streams, apply stateful transformations, and output results to new Kafka topics. Explore the complete Flink ecosystem including datastream programming concepts, job lifecycle management, and stream anatomy while working with practical components like data sources, serializers, deserializers, and data sinks. Develop skills in creating branching data streams, implementing windowing and watermarks for time-based processing, and managing keyed state for stateful computations. Gain the essential knowledge needed to build production-grade Apache Flink applications that meet modern real-time data processing requirements in distributed environments.
