Dataflow Programming: Building a Java Pipeline With Flink and Kafka

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This post details building a Java pipeline with Flink and Kafka for clickstream data analysis. It covers setting up a Maven project with Flink dependencies (flink-streaming-java, flink-json, flink-connector-kafka), building an uber JAR using the maven-shade-plugin, defining POJO data structures for input (ClickStreamRecord) and output (ClickStreamAnalytics), creating a Flink entry point (ClickStreamJob), and initializing the StreamExecutionEnvironment. It also demonstrates loading Kafka configuration properties from a file and outlines the process of consuming from Kafka, performing keyBy and windowing operations, and producing results.