com.opencredo:concursus-data

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Categories

Categories

Data
GroupId

GroupId

com.opencredo
ArtifactId

ArtifactId

concursus-data
Last Version

Last Version

0.6
Release Date

Release Date

Type

Type

jar
Description

Description

Sonatype helps open source projects to set up Maven repositories on https://oss.sonatype.org/

Download concursus-data

How to add to project

<!-- https://jarcasting.com/artifacts/com.opencredo/concursus-data/ -->
<dependency>
    <groupId>com.opencredo</groupId>
    <artifactId>concursus-data</artifactId>
    <version>0.6</version>
</dependency>
// https://jarcasting.com/artifacts/com.opencredo/concursus-data/
implementation 'com.opencredo:concursus-data:0.6'
// https://jarcasting.com/artifacts/com.opencredo/concursus-data/
implementation ("com.opencredo:concursus-data:0.6")
'com.opencredo:concursus-data:jar:0.6'
<dependency org="com.opencredo" name="concursus-data" rev="0.6">
  <artifact name="concursus-data" type="jar" />
</dependency>
@Grapes(
@Grab(group='com.opencredo', module='concursus-data', version='0.6')
)
libraryDependencies += "com.opencredo" % "concursus-data" % "0.6"
[com.opencredo/concursus-data "0.6"]

Dependencies

compile (1)

Group / Artifact Type Version
com.google.guava : guava jar 18.0

test (2)

Group / Artifact Type Version
junit : junit jar 4.12
org.hamcrest : hamcrest-all jar 1.3

Project Modules

There are no modules declared in this project.

Concursus

Maven Central Build Status

Concursus is a Java 8 framework for building applications that use CQRS and event sourcing patterns, with a Cassandra event log implementation.

See the wiki for further documentation, or browse the javadocs.

Getting Started

Create a project with dependencies on concursus-mapping, concursus-domain-json and jackson-datatype-jsr310:

<dependency>
    <groupId>com.opencredo</groupId>
    <artifactId>concursus-mapping</artifactId>
</dependency>

<dependency>
    <groupId>com.opencredo</groupId>
    <artifactId>concursus-domain-json</artifactId>
</dependency>

<dependency>
    <groupId>com.fasterxml.jackson.datatype</groupId>
    <artifactId>jackson-datatype-jsr310</artifactId>
</dependency>

The first thing we might want to do is generate some events. To begin with, we need an interface class that defines the events we want to create:

@HandlesEventsFor("person")
public interface Events {
    @Initial
    void created(StreamTimestamp ts, String personId, String name, LocalDate dateOfBirth);
    void changedName(StreamTimestamp ts, String personId, String newName);
    void movedToAddress(StreamTimestamp ts, String personId, String addressId);
    @Terminal
    void deleted(StreamTimestamp ts, String personId);
}

Each method in this interface defines an event which can occur to a person. We generate an event by calling one of these methods, which results in an event being sent to an EventOutChannel. Let's create a channel that simply prints the event to the console, and then create a proxy implementation of PersonEvents that sends events to this channel:

// Create an EventOutChannel that simply prints events to the command line
EventOutChannel outChannel = System.out::println;

// Create a proxy that sends events to the outChannel.
PersonEvents proxy = EventEmittingProxy.proxying(outChannel, PersonEvents.class);

// Send an event via the proxy.
proxy.created(StreamTimestamp.now(), "id1", "Arthur Putey", LocalDate.parse("1968-05-28"));

This will output a String like the following:

person:id1 created_0
at 2016-03-31T10:31:17.981Z/
with person/created_0{dateOfBirth=1968-05-28, name=Arthur Putey}

This means that an event of type created_0 occurred to the object person:b2fb2f38-0473-4359-b62b-fad149caf2d5 at 2016-03-31T10:31:17.981Z, and this event had two parameters associated with it, name and dateOfBirth.

We can have the event encoded as JSON if we use an EventOutChannel that performs the encoding:

// Create an EventOutChannel that formats events as JSON and sends them to a command line printer.
EventInChannel<String> print = System.out::println;
ObjectMapper objectMapper = new ObjectMapper()
        .findAndRegisterModules()
        .configure(SerializationFeature.INDENT_OUTPUT, true);
EventOutChannel outChannel = JsonEventOutChannel.using(objectMapper, print);

// Create a proxy that sends events to the outChannel.
PersonEvents proxy = EventEmittingProxy.proxying(outChannel, PersonEvents.class);

// Send an event via the proxy.
proxy.created(StreamTimestamp.now(), "id1, "Arthur Putey", LocalDate.parse("1968-05-28"));

This will output JSON like the following:

{
  "aggregateType" : "person",
  "aggregateId" : "id1",
  "name" : "created",
  "version" : "0",
  "eventTimestamp" : 1459420919667,
  "streamId" : "",
  "processingId" : "",
  "characteristics" : 1,
  "parameters" : {
    "dateOfBirth" : [ 1968, 5, 28 ],
    "name" : "Arthur Putey"
  }
}

Instead of simply printing things to the console, let's start storing events. We can use an InMemoryEventStore to begin with:

// Create an InMemoryEventStore, and a proxy that sends events to it.
InMemoryEventStore eventStore = InMemoryEventStore.empty();
PersonEvents proxy = EventEmittingProxy.proxying(eventStore.toEventOutChannel(), PersonEvents.class);

// Send an event via the proxy.
final String personId = String.randomString();
proxy.created(StreamTimestamp.now(), personId, "Arthur Putey", LocalDate.parse("1968-05-28"));

// Create an EventTypeMatcher based on the Events interface, and use it to map events back out of the store
EventTypeMatcher typeMatcher = EmitterInterfaceInfo.forInterface(PersonEvents.class).getEventTypeMatcher();
// Retrieve the stored events for the aggregate with id=person/personId, and print them to the console.
EventSource.retrievingWith(eventStore)
        .getEvents(typeMatcher, AggregateId.of("person", personId))
        .forEach(System.out::println);

Once we have stored events, we can replay them to event handlers, mapping them back into method calls on the PersonEvents interface:

// Create a mock handler for person events.
PersonEvents handler = mock(PersonEvents.class);

// Create an InMemoryEventStore, and a proxy that sends events to it.
InMemoryEventStore eventStore = InMemoryEventStore.empty();
PersonEvents proxy = EventEmittingProxy.proxying(eventStore.toEventOutChannel(), PersonEvents.class);

// Send an event via the proxy.
String personId = "id1;
proxy.created(StreamTimestamp.now(), personId, "Arthur Putey", LocalDate.parse("1968-05-28"));

// Replay the stored events for the person with id=person/personId to the handler instance.
DispatchingEventSource.dispatching(EventSource.retrievingWith(eventStore), PersonEvents.class)
        .replaying(personId)
        .replayAll(handler);

// Verify that the handler received the event.
verify(handler).created(any(StreamTimestamp.class), any(String.class), eq("Arthur Putey"), eq(LocalDate.parse("1968-05-28")));

Check out the Examples for more detailed examples, including command processing and state-building.

Using Cassandra and Redis

Eventually you will want to store events more permanently. Cassandra and Redis event store implementations are provided in concursus-cassandra and concursus-redis respectively. You will need to create a suitable keyspace and tables in Cassandra before you can use it:

CREATE KEYSPACE IF NOT EXISTS concursus
  WITH REPLICATION = { 'class' : 'SimpleStrategy', 'replication_factor' : 2 };

CREATE TABLE IF NOT EXISTS concursus.Event (
   aggregateType text,
   aggregateId text,
   eventTimestamp timestamp,
   streamId text,
   processingId timeuuid,
   name text,
   version text,
   parameters map<text, text>,
   characteristics int,
   PRIMARY KEY((aggregateType, aggregateId), eventTimestamp, streamId)
) WITH CLUSTERING ORDER BY (eventTimestamp DESC);

CREATE TABLE IF NOT EXISTS concursus.Catalogue (
    aggregateType text,
    bucket int,
    aggregateId text,
    PRIMARY KEY ((aggregateType, bucket), aggregateId)
) WITH CLUSTERING ORDER BY (aggregateId DESC);
com.opencredo

OpenCredo

Versions

Version
0.6
0.5
0.4
0.3
0.2