Streaming Concepts # Flink’s Table API and SQL support are unified APIs for batch and stream processing. This means that Table API and SQL queries have the same semantics regardless whether their input is bounded batch input or unbounded stream input. The following pages explain concepts, practical limitations, and stream-specific configuration parameters of Flink’s relational APIs on streaming data. State Management # Table programs that run in streaming mode leverage all capabilities of...| nightlies.apache.org
Windowing table-valued functions (Windowing TVFs) # Batch Streaming Windows are at the heart of processing infinite streams. Windows split the stream into “buckets” of finite size, over which we can apply computations. This document focuses on how windowing is performed in Flink SQL and how the programmer can benefit to the maximum from its offered functionality. Apache Flink provides several window table-valued functions (TVF) to divide the elements of your table into windows, including:| nightlies.apache.org
Let’s imagine we’ve got a source of data with a nested array of multiple values.| How to explode nested arrays with Flink SQL