Flink integration test(s) with Testcontainers - apache-flink

Question

I have a simple Apache Flink job that looks very much like this:
public final class Application {
public static void main(final String... args) throws Exception {
final var env = StreamExecutionEnvironment.getExecutionEnvironment();
final var executionConfig = env.getConfig();
final var params = ParameterTool.fromArgs(args);
executionConfig.setGlobalJobParameters(params);
executionConfig.setParallelism(params.getInt("application.parallelism"));
final var source = KafkaSource.<CustomKafkaMessage>builder()
.setBootstrapServers(params.get("application.kafka.bootstrap-servers"))
.setGroupId(config.get("application.kafka.consumer.group-id"))
// .setStartingOffsets(OffsetsInitializer.committedOffsets(OffsetResetStrategy.EARLIEST))
.setStartingOffsets(OffsetsInitializer.earliest())
.setTopics(config.getString("application.kafka.listener.topics"))
.setValueOnlyDeserializer(new MessageDeserializationSchema())
.build();
env.fromSource(source, WatermarkStrategy.noWatermarks(), "custom.kafka-source")
.uid("custom.kafka-source")
.rebalance()
.flatMap(new CustomFlatMapFunction())
.uid("custom.flatmap-function")
.filter(new CustomFilterFunction())
.uid("custom.filter-function")
.addSink(new CustomDiscardSink()) // Will be a Kafka sink in the future
.uid("custom.discard-sink");
env.execute(config.get("application.job-name"));
}
}
Problem is that I would like to provide an integration test for the entire application — sort of like an end-to-end (set of) test(s) for the entire job. I'm using Testcontainers, but I'm not really sure how to move forward with this. For instance, this is how the test looks like (for now):
#Testcontainers
final class ApplicationTest {
private static final DockerImageName DOCKER_IMAGE = DockerImageName.parse("confluentinc/cp-kafka:7.0.1");
#Container
private static final KafkaContainer KAFKA_CONTAINER = new KafkaContainer(DOCKER_IMAGE);
#ClassRule // How come this work in JUnit Jupiter? :/
public static MiniClusterResource cluster;
#BeforeAll
static void init() {
KAFKA_CONTAINER.start();
// ...probably need to wait and create the topic(s) as well
final var config = new MiniClusterResourceConfiguration.Builder().setNumberSlotsPerTaskManager(2)
.setNumberTaskManagers(1)
.build();
cluster = new MiniClusterResource(config);
}
#Test
void main() throws Exception {
// new Application(); // ...what's next?
}
}
I'm not sure how to implement what's required to trigger the job as-is from that point on. Basically, I would like to execute what was defined before, without (almost) any modifications — I've seen plenty of examples that practically build the entire job again, so that's not an option.
Can somebody provide any pointers here?
MessageDeserializationSchema is unbounded, so isEndOfStream returns false. Not sure if that's an impediment.

Answer 1

In order to make the pipeline more testable, I suggest you create a method on your Application class that takes a source and a sink as parameters, and creates and executes the pipeline, using those connectors.
In your tests you can call that method with special sources and sinks that you use for testing. In particular, you will want to use a KafkaSource that uses .setBounded(...) in the tests so that it cleanly handles just the range of data intended for the test(s).
The solutions and tests for the Apache Flink training exercises are organized along these lines; for example, see RideCleansingSolution.java and RideCleansingIntegrationTest.java. These examples don't use kafka or test containers, but hopefully they'll still be helpful.

Answer 2

I would suggest you instrument your application as an opaque-box test by interacting with it through its public API. This can be done either as an out-process test (e.g. by running your application in a container as well, using Testcontainers) are as an in-process test (by creating your Application and calling its main() method).
Now in your comments you explained, that you want to check for the side-effects of interacting with your application (Kafka messages being published). To check this, connect to the KafkaContainer with your own KafkaConsumer from within the test and use a library such as Awaitiliy to wait until the messages have been received.