This documentation is for an unreleased version of Apache Flink Stateful Functions. We recommend you use the latest stable version.
Application Building Blocks #
Stateful Functions provides a framework for building event driven applications. Here, we explain important aspects of Stateful Function’s architecture.
Event Ingress #
Stateful Function applications sit squarely in the event driven space, so the natural place to start is with getting events into the system.
In Stateful Functions, the component that ingests records into the system is called an event ingress. This can be anything from a Kafka topic, to a message queue, to an http request - anything that can get data into the system and trigger the initial functions to begin computation.
Stateful Functions #
At the core of the diagram are the namesake stateful functions.
Think of these as the building blocks for your service. They can message each other arbitrarily, which is one way in which this framework moves away from the traditional stream processing view of the world. Instead of building up a static dataflow DAG, these functions can communicate with each other in arbitrary, potentially cyclic, even round trip ways.
If you are familiar with actor programming, this does share certain similarities in its ability to dynamically message between components. However, there are a number of significant differences.
Persisted States #
The first is that all functions have locally embedded state, known as persisted states.
One of Apache Flink’s core strengths is its ability to provide fault-tolerant local state. When inside a function, while it is performing some computation, you are always working with local state in local variables.
Fault Tolerance #
For both state and messaging, Stateful Functions is able to provide the exactly-once guarantees users expect from a modern data processing framework.
In the case of failure, the entire state of the world (both persisted states and messages) are rolled back to simulate completely failure free execution.
These guarantees are provided with no database required, instead Stateful Function’s leverages Apache Flink’s proven snapshotting mechanism.
Event Egress #
Finally, applications can output data to external systems via event egresses.
Of course, functions perform arbitrary computation and can do whatever they like, which includes making RPC calls and connecting to other systems. By using an event egress, applications can leverage pre-built integrations built on-top of the Apache Flink connector ecosystem.