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AuthorDate: Sun Aug 16 03:10:49 2020 -0700
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+<img alt="Stateful Functions" src="docs/fig/stateful_functions_logo.png"
width=350px/>
+
+Stateful Functions is an [Apache Flink](https://flink.apache.org/) library
that **simplifies building distributed stateful applications**. It's based on
functions with persistent state that can interact dynamically with strong
consistency guarantees.
+
+Stateful Functions makes it possible to combine a powerful approach to state
and composition with the elasticity, rapid scaling/scale-to-zero and rolling
upgrade capabilities of FaaS implementations like AWS Lambda and modern
resource orchestration frameworks like Kubernetes. With these features, it
addresses [two of the most cited
shortcomings](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2019/EECS-2019-3.pdf)
of many FaaS setups today: consistent state and efficient messaging between f
[...]
+
+This README is meant as a brief walkthrough on the core concepts and how to
set things up
+to get yourself started with Stateful Functions.
+
+For a fully detailed documentation, please visit the [official
docs](https://ci.apache.org/projects/flink/flink-statefun-docs-master).
+
+For code examples, please take a look at the [examples](statefun-examples/).
+
+[](https://travis-ci.org/apache/flink-statefun)
+
+## Table of Contents
+
+- [Core Concepts](#core-concepts)
+ * [Abstraction](#abstraction)
+ * [Function modules and extensibility](#modules)
+ * [Runtime](#runtime)
+- [Getting Started](#getting-started)
+ * [Running a full example](#greeter)
+ * [Project setup](#project-setup)
+ * [Building the Project](#build)
+ * [Running in the IDE](#ide-harness)
+- [Deploying Applications](#deploying)
+ * [Deploying with a Docker image](#docker)
+ * [Deploying as a Flink job](#flink)
+- [Contributing](#contributing)
+- [License](#license)
+
+## <a name="core-concepts"></a>Core Concepts
+
+### <a name="abstraction"></a>Abstraction
+
+A Stateful Functions application consists of the following primitives:
stateful functions, ingresses,
+routers and egresses.
+
+<p align="center">
+ <img src="docs/fig/stateful_functions_overview.png" width="650px"/>
+</p>
+
+#### Stateful functions
+
+* A _stateful function_ is a small piece of logic/code that is invoked through
a message. Each stateful function
+exists as a uniquely invokable _virtual instance_ of a _function type_. Each
instance is addressed by its ``type``, as well as an unique ``ID`` (a string)
within its type.
+
+* Stateful functions may be invoked from ingresses or any other stateful
function (including itself).
+The caller simply needs to know the address of the target function.
+
+* Function instances are _virtual_, because they are not all active in memory
at the same time.
+At any point in time, only a small set of functions and their state exists as
actual objects. When a
+virtual instance receives a message, one of the objects is configured and
loaded with the state of that virtual
+instance and then processes the message. Similar to virtual memory, the state
of many functions might be “swapped out”
+at any point in time.
+
+* Each virtual instance of a function has its own state, which can be accessed
in local variables.
+That state is private and local to that instance.
+
+If you know Apache Flink’s DataStream API, you can think of stateful functions
a bit like a lightweight
+`KeyedProcessFunction`. The function ``type`` is the process function
transformation, while the ``ID`` is the key. The difference
+is that functions are not assembled in a Directed Acyclic Graph (DAG) that
defines the flow of data (the streaming topology),
+but rather send events arbitrarily to all other functions using addresses.
+
+#### Ingresses and Egresses
+
+* _Ingresses_ are the way that events initially arrive in a Stateful Functions
application.
+Ingresses can be message queues, logs or HTTP servers — anything that produces
an event to be
+handled by the application.
+
+* _Routers_ are attached to ingresses to determine which function instance
should handle an event initially.
+
+* _Egresses_ are a way to send events out from the application in a
standardized way.
+Egresses are optional; it is also possible that no events leave the
application and functions sink events or
+directly make calls to other applications.
+
+### <a name="modules"></a>Modules
+
+A _module_ is the entry point for adding the core building block primitives to
a Stateful Functions
+application, i.e. ingresses, egresses, routers and stateful functions.
+
+A single application may be a combination of multiple modules, each
contributing a part of the whole application.
+This allows different parts of the application to be contributed by different
modules; for example,
+one module may provide ingresses and egresses, while other modules may
individually contribute specific parts of the
+business logic as stateful functions. This facilitates working in independent
teams, but still deploying
+into the same larger application.
+
+## <a name="runtime">Runtime
+
+The Stateful Functions runtime is designed to provide a set of properties
similar to what characterizes [serverless
functions](https://martinfowler.com/articles/serverless.html), but applied to
stateful problems.
+
+<p align="center">
+ <img src="docs/fig/stateful_functions_overview-ops.png" width="600px"/>
+</p>
+
+The runtime is built on Apache Flink<sup>®</sup>, with the following design
principles:
+
+* **Logical Compute/State Co-location:** Messaging, state access/updates and
function invocations are managed tightly together. This ensures a high-level of
consistency out-of-the-box.
+
+* **Physical Compute/State Separation:** Functions can be executed remotely,
with message and state access provided as part of the invocation request. This
way, functions can be managed like stateless processes and support rapid
scaling, rolling upgrades and other common operational patterns.
+
+* **Language Independence:** Function invocations use a simple HTTP/gRPC-based
protocol so that Functions can be easily implemented in various languages.
+
+This makes it possible to execute functions on a Kubernetes deployment, a FaaS
platform or behind a (micro)service, while providing consistent state and
lightweight messaging between functions.
+
+## <a name="getting-started"></a>Getting Started
+
+Follow the steps here to get started right away with Stateful Functions.
+
+This guide will walk you through setting up to
+start developing and testing your own Stateful Functions (Java) application,
and running an existing example. If you prefer to get started with Python, have
a look into the [StateFun Python
SDK](https://github.com/apache/flink-statefun/tree/master/statefun-python-sdk)
and the [Python Greeter
example](https://github.com/apache/flink-statefun/tree/master/statefun-examples/statefun-python-greeter-example).
+
+### <a name="project-setup"></a>Project Setup
+
+Prerequisites:
+
+* Docker
+
+* Maven 3.5.x or above
+
+* Java 8 or above
+
+You can quickly get started building Stateful Functions applications using the
provided quickstart Maven archetype:
+
+```
+mvn archetype:generate \
+ -DarchetypeGroupId=org.apache.flink \
+ -DarchetypeArtifactId=statefun-quickstart \
+ -DarchetypeVersion=2.2-SNAPSHOT
+```
+
+This allows you to name your newly created project. It will interactively ask
you for the `GroupId`,
+`ArtifactId` and package name. There will be a new directory with the same
name as your `ArtifactId`.
+
+We recommend you import this project into your IDE to develop and test it.
+IntelliJ IDEA supports Maven projects out of the box. If you use Eclipse, the
`m2e` plugin allows to import
+Maven projects. Some Eclipse bundles include that plugin by default, others
require you to install it manually.
+
+### <a name="build"></a>Building the Project
+
+If you want to build/package your project, go to your project directory and
run the `mvn clean package` command. You will find a JAR file that contains
your application, plus any libraries that you may have added as dependencies to
the application: `target/<artifact-id>-<version>.jar`.
+
+### <a name="ide-harness"></a>Running from the IDE
+
+To test out your application, you can directly run it in the IDE without any
further packaging or deployments.
+
+Please see the [Harness
example](statefun-examples/statefun-flink-harness-example) on how to do that.
+
+### <a name="greeter"></a>Running a full example
+
+As a simple demonstration, we will be going through the steps to run the
[Greeter example](statefun-examples/statefun-greeter-example).
+
+Before anything else, make sure that you have locally [built the project as
well as the base Stateful Functions Docker image](#build).
+Then, follow the next steps to run the example:
+
+```
+cd statefun-examples/statefun-greeter-example
+docker-compose build
+docker-compose up
+```
+
+This example contains a very basic stateful function with a Kafka ingress and
a Kafka egress.
+
+To see the example in action, send some messages to the topic `names`, and see
what comes out out of the topic `greetings`:
+
+```
+docker-compose exec kafka-broker kafka-console-producer.sh \
+ --broker-list localhost:9092 \
+ --topic names
+```
+
+```
+docker-compose exec kafka-broker kafka-console-consumer.sh \
+ --bootstrap-server localhost:9092 \
+ --isolation-level read_committed \
+ --from-beginning \
+ --topic greetings
+```
+
+## <a name="deploying"></a>Deploying Applications
+
+Stateful Functions applications can be packaged as either [standalone
applications](https://ci.apache.org/projects/flink/flink-statefun-docs-master/deployment-and-operations/packaging.html#images)
or [Flink
jobs](https://ci.apache.org/projects/flink/flink-statefun-docs-master/deployment-and-operations/packaging.html#flink-jar)
that can be
+submitted to a Flink cluster.
+
+### <a name="docker"></a>Deploying with a Docker image
+
+Below is an example Dockerfile for building a Stateful Functions image with an
[embedded](https://ci.apache.org/projects/flink/flink-statefun-docs-master/sdk/modules.html#embedded-module)
module (Java) for an application called `statefun-example`.
+
+```
+FROM flink-statefun[:version-tag]
+
+RUN mkdir -p /opt/statefun/modules/statefun-example
+
+COPY target/statefun-example*jar /opt/statefun/modules/statefun-example/
+```
+
+### <a name="flink"></a>Deploying as a Flink job
+
+If you prefer to package your Stateful Functions application as a Flink job to
submit to an existing Flink cluster,
+simply include `statefun-flink-distribution` as a dependency to your
application.
+
+```
+<dependency>
+ <groupId>org.apache.flink</groupId>
+ <artifactId>statefun-flink-distribution</artifactId>
+ <version>2.2-SNAPSHOT</version>
+</dependency>
+```
+
+It includes all the runtime dependencies and configures the application's main
entry-point.
+You do not need to take any action beyond adding the dependency to your POM
file.
+
+<div class="alert alert-info">
+ <strong>Attention:</strong> The distribution must be bundled in your
application fat JAR so that it is on Flink's <a
href="https://ci.apache.org/projects/flink/flink-docs-stable/monitoring/debugging_classloading.html#inverted-class-loading-and-classloader-resolution-order";>user
code class loader</a>
+</div>
+
+```
+{$FLINK_DIR}/bin/flink run ./statefun-example.jar
+```
+
+## <a name="contributing"></a>Contributing
+
+There are multiple ways to enhance the Stateful Functions API for different
types of applications; the runtime and operations will also evolve with the
developments in Apache Flink.
+
+You can learn more about how to contribute in the [Apache Flink
website](https://flink.apache.org/contributing/how-to-contribute.html). For
code contributions, please read carefully the [Contributing
Code](https://flink.apache.org/contributing/contribute-code.html) section and
check the _Stateful Functions_ component in
[Jira](https://issues.apache.org/jira/browse/FLINK-15969?jql=project%20%3D%20FLINK%20AND%20component%20%3D%20%22Stateful%20Functions%22)
for an overview of ongoing commun [...]
+
+## <a name="license"></a>License
+
+The code in this repository is licensed under the [Apache Software License
2](LICENSE).
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