One of the major difference between stream and batch processing is the need to explicitly handle time in…
Windowing is a key feature in stream processing systems such as Apache Flink. Windowing splits the continuous…
Flink has a powerful functional streaming API which let application developer specify high-level functions for data transformations. Applications developers can choose different transformations.
State management comes out of the box for Flink and it is considered as the first-class citizen. While Flink abstracts the traditional state complexities for application developers, it needs to do a lot more to provide stateful fault-tolerant applications. It needs to checkpoint the state…
Apache Flink abstracts the state management complexities for application developers. It provides fault-tolerance with checkpointing and failure recovery mechanism. The state is required in a certain type of data processing e.g. when we are processing credit card transactions to…
Flink is an open source stream-processing framework. It does provide stateful computation over data…
KeyBy is one of the mostly used transformation operator for data streams. It is used to partition the data…