Creation TableEnvironment is the entry point and central context for creating Table and SQL API programs. Flink is an unified streaming and batch computing engine, which provides unified streaming and Creation StreamExecutionEnvironment is the entry point and central concept for creating DataStream API programs. Flink is an unified streaming and batch computing engine, which provides unified streaming and JobExecutionResult at 0x7fd5dcc73550> Applying a Function on DataStream DataStream programs in Flink are regular programs that implement transformations on data streams (e.g., mapping, filtering, reducing)

Creation TableEnvironment is the entry point and central context for creating Table and SQL API programs. Flink is an unified streaming and batch computing engine, which provides unified streaming and Creation StreamExecutionEnvironment is the entry point and central concept for creating DataStream API programs. Flink is an unified streaming and batch computing engine, which provides unified streaming and JobExecutionResult at 0x7fd5dcc73550> Applying a Function on DataStream DataStream programs in Flink are regular programs that implement transformations on data streams (e.g., mapping, filtering, reducing)

issues • Continuous vs. micro-batch processing • Record-at-a-Time vs. declarative APIs 69 / 79 Programs and Dataflows 70 / 79 Window Operations ▶ A window defines a finite set of elements on an unbounded condition. • After the W(t) has occurred, more elements with timestamp t′ ≤ t will occur. ▶ Streaming programs may explicitly expect some late elements. val input: DataStream[T] = ... input.keyBy()

max("temp")
 maxTemp.print()
 env.execute("Compute max sensor temperature”)
 }
 } Flink programs are defined in regular Scala/Java methods Set up the execution environment: local, cluster

Contents • DataSet API • DataStream API • Concepts • Set up an environment to develop Flink programs • Implement streaming data processing pipelines • Flink managed state • Event time Streaming