Status

Current state: [ UNDER DISCUSSION  ACCEPTED ]

Discussion thread: <link to mailing list DISCUSS thread>

JIRA: 

Released: 

Problem:

Samza today provides various api's like high level (fluent/application) for chaining complex jobs, low level (task) with configuration like Samza-Yarn, Samza as a library (Samza standalone) and in coming future Samza will support In-memory system for in memory streams that a user can produce/conusme from. Still Samza users have to get their hands dirty with too much configuration details and dependency on external system(like kafka) to write integration tests. In order to alleviate this we intend to provide a fluent test api to users. This will help in setting-up quick tests against their system without depending on underlying incoming stream from another system e.g Kafka Topic.

The goal of the proposed SEP we will provide a standardized framework to set-up continuous integration test for High Level Api, Low Level Api with Single Container configuration & Multi Container Configuration (Samza standalone using Zookeeper) with ease. Users won’t have to worry about the underlying Samza config details or even understand implementation details. This abstraction will increase developer productivity and help client's make their Samza system robust.

...

• Samza Job Owners: To make their Samza jobs robust
• Samza Dev Teams: To enable dev teams make their samza infra robust

Motivation

Addition of this Continuous Integration Test Framework will alleviate:

This SEP targets two phase development of the Framework:

• PHASE I: Testing Samza's public apis targeting Samza job Owners
• PHASE II: Testing various component of Samza targeting testing  Samza Dev team

Terminologies

• p1: refers to apis targeted for development for Phase I
• p2: refers to apis targeted for development for Phase II

Motivation

Addition of this Integration Test Framework will alleviate:

1. Lack of a standardized way to set up integration tests for users

2. Lack of brevity in code and

3. Lack of a standardized way to set up integration tests for users

4. Lack of brevity in code and much detailed understanding of low level configs to set up samza systems

5. Lack of a pluggable Test System with any Samza configuration (single & multi-container)

6. Comprehensive set of tests for Samza api

Assumptions 

Design

We propose a three step process for configuration of integration test for your samza job. Three facets are data injection, transformation and validation.

...

Data Injection:

In the context of this Test framework an input stream means a stream that Samza job may consume from and an output stream means a stream that Samza job can produce to. The initial source of data stream is always supposed to be bounded since this is a test, and that may originate as one of the following sources listed below.

• In Memory Data Stream
  Users have ability to produce to & consume from in memory system partitions after SEP-8. In Memory Data system alleviates the need of serialization/deserialization of data since it does not persist data. We take advantage of this and provide very succinct Stream classes to serve as input data sources, which are the following:
  • Collection Stream (p1)
    Users can plug a collection (either List or Map) to create an in-memory input stream
    e.g:  CollectionStream.of(...,{1,2,3,4})
  • Event Builder Stream (p2)
    Event builder helps a user to mimic runtime samza processing environment in its tests, for example adding an exception in the steam, advancing time for window functions.
• File Stream
  Users can create an input stream reading and writing from local file
  e.g:  FileStream.of("/path/to/file")
• Local Kafka Stream
  Users can also consume bounded streams from a kafka topic which serves as initial input. Samza already provide api's to consume from and produce to kafka. For kafka streams we will need serde configurations, however implementation of bounded streams in kafka (using Latche Message or EndOfStreamMessage) is beyond scope of this SEP

For in memory streams the api actually initializes the stream by spinning up a Samza producer using an InMemorySystemProducer to write the stream, this is how a collection of data or events gets initialized as a steam. It also configures any output stream if the user has added any.

Data Transformation:

This is the Samza job you write, this can be either done using Low Level Api or the fluent High Level Api. Test frameworks provides api to set up test for both the cases. Test framework supports both the apis with Single container and Multi-container mode. Users implement StreamTask/Async Stream/Stream Application in the same way, as they do for their Samza job (or pass an instance of Samza job).

Data Validation: 

Data Types & Partitions:

The framework will provide complete flexibility for usage of primitive and derived data types. Serdes are required for local kafka stream and file stream but in memory streams dont require any Serde configuration. Serdes will be also required if users want to maintain State. Test framework will provide api's for initialization of input streams (both single and multi-partition), and also data validation on single partition and multi-partition of the bounded streams 

...

Test framework will support stateful and stateless testing, satateful testing can be either done using RocksDB or maintaining state in memory

Future Changes with Stream Descriptors:

The test framework is designed in a way which asks users to do none or minimal Samza configs, in future we intend to use StreamDescriptors in the test framework to do Samza configs. With StreamDescriptor and High Level api, another wrapper can be provided over the job to run the configuration in a test environment

Test Matrix (Plan)

Shown below is a targeted test matrix plan to test various components of Samza in p2.

n = number of threads

x = number of partitions 

m = number of containers

...

Public Interfaces

/**
* TestRunner provides static factory for quick setup of Samza environment for testing Low level api and High level api , users can configure input streams 
* they consume from and output streams they produce to, users pass in their Samza job api logic via StreamTask/AsyncStreamTask/StreamApplication
*/ 

public class TestRunner {
  
  // Static Factory to config & create runner for low level api 
  public static TestRunner of(StreamTaskClass tasktaskClass) {...}
  // Static  public static TestRunner of(AsyncStreamTask task) {...}Factory to config & create runner for high level api
  public static TestRunner of(StreamApplication app) {...}
  
  // Add/Ovveride any custom configs
  public TestRunner addOverrideConfigsaddConfigs(Map<String,String> configs) {...}
  public TestRunner addOverrideConfigs(String configUriConfig configs) {...}
  public TestRunner addOverrideConfig(String key, String val){...}
 
  // SetConfigure containerstate mode either single container or multi containerfor application
  public TestRunner setContainerModeaddState(ModeString modestoreName) {...}  
  
  // Multithreading configsConfigure an input stream for users
samza system, publicthat TestRunnerjob setTaskMaxConcurrency(Integer value) {...}can consume from
  public TestRunner setTaskCallBackTimeoutMSaddInputStream(IntegerCollectionStream valuestream) {...}
  public// TestRunner setJobContainerThreadPoolSize(Integer valueConfigures an output stream for samza system, that job can producer to
  public TestRunner addOutputStream(CollectionStream stream) {...}
 
  // Consume Configuremessages statefrom fora applicationStream
  public TestRunner addState(String storeName static <T> Map<Integer, List<T>> consumeStream(CollectionStream stream, Integer timeout) {...}  
  
  // ConfigureRun an input stream for samza system, that job can consume fromthe TestRunner
  public TestRunnervoid addInputStreamrun(CollectionStream stream) {...}
}

 

Types of Input Streams

CollectionStream:

/**
* CollectionStream //acts Configuresa andescriptor outputthat streamcan forbe samzaused system,to thatbuild joban canin producermemory to
input stream public TestRunner addOutputStream(CollectionStream stream) {...}
  (single/multiple partition) of java collections
*/
 
public class CollectionStream<T> { 
  // RunCreate thean app
  public void run(empty stream with single partition that a Samza job can produce to
  public static <T> CollectionStream<T> empty(String systemName, String streamName) {...}
}

 

Types of Input Streams

/**
* CollectionStream provides utilities to build an in memory input stream of collections(list, map). It also supports initialization of 
* multiple partitions for an input stream 
*/
 
public class CollectionStream<T> {   
  // Create an empty stream with multiple partitions that a Samza job can produce to
  public static <T> CollectionStream<T> empty(String systemName, String streamName, Integer partitionCount) {...}
  
  // Create ana emptystream streamof thatmessages afrom Samzainput joblist canwith producesingle topartition
  public static <T> CollectionStream<T> emptyof(String systemName, String steamId) streamName, Iterable<T> collection){...}
  
  // Create a stream of messages from input list with singlemultiple partition
, key public of partitions map is partitionId
  public static <T> CollectionStream<T> of(String systemName, String steamIdstreamName, Iterable<T> collectionMap<Integer,? extends Iterable<T>> partitions){...}
  
  // Create a stream of messages from input list with multiple partition, key of partitions map is partitionId
  public static <T> CollectionStream<T> of(String steamId, Map<Integer,Iterable<T>> partitions){...}
  
}

/**
* EventStream provides utilities to build an in memory input stream of events. It helps mimic run time environment of your job, 
* advancing time for windowing functions  
*/
 
public class EventStream<T> {
  public static abstract class Builder<T> {
    public abstract Builder addElement();
    public abstract Builder addException();
    public abstract Builder advanceTimeTo(long time);
    public abstract EventStream<T> build(); 
 }

 public static <T> Builder<T> builder() {...}
}

/**
* FileStream provides utilities to build a stream of messages from a file on disk
*/
 
public class FileStream<T> {
  public static <T> FileStream<T> of(String fileUri) {...}
}

...

}

/**
* CollectionStreamSystem provides utilities to create and initialize an in memory input stream.
*/
 
public class CollectionStreamSystem { 

 // Create a CollectionStreamSystem 
 public static CollectionStreamSystem create(String name) {...}  
 
}

FileStream:

...

...

/**
* SimpleFileStream Testprovides caseutilities using a collection as an input forto build a low level application. It demonstrates set up and comparison ofstream of messages from a testfile withon disk
*/
 
public class FileStream<T> {
  public static <T> FileStream<T> of(String fileUri) {...}
}
 
public class FileStreamSystem {
  public static FileStreamSystem create(String name) {...}
}

Examples Usages of Test Api:

/**
* Simple Test case using a collection as an input for a low level application. It demonstrates set up and comparison of a test with 
* minimal(eg. here none) configs and it reads an input stream of integers and multiplies each integer with 10
*/
 
// Create a StreamTask
MyStreamTestTask myTask = new StreamTask() {
  @Override
  public void process(IncomingMessageEnvelope envelope, MessageCollector collector, TaskCoordinator coordinator) throws Exception {
    Integer obj = (Integer) envelope.getMessage();
    collector.send(new OutgoingMessageEnvelope(new SystemStream("test","output"), obj*10));
  }
};
 

CollectionStream<Integer> input = CollectionStream
	.of("test", "input" minimal(eg. here none) configs and it reads an input stream of integers and multiplies each integer with 10
*/
 
class MyStreamTaskFactory implements StreamTaskFactory {
    @Override
    public StreamTask createInstance() {
      return (envelope, collector, coordinator) -> {
        return;
      };
    }
  }
}

StreamDescriptor.Input input = StreamDescriptor.<String, String>input("input")
    .withKeySerde(new StringSerde("UTF-8"))
    .withMsgSerde(new StringSerde("UTF-8"));

StreamDescriptor.Output output = StreamDescriptor.<String, String>output("output")
    .withKeySerde(new StringSerde("UTF-8"))
    .withMsgSerde(new StringSerde("UTF-8"));

InMemoryTestSystem testingSystem = InMemoryTestSystem.create("samza-test")
    .addInput(input, {1,2,3,4,5})

CollectionStream output =  CollectionStream
	.addOutput(output);

StreamTaskApplication app = StreamApplications.createStreamTaskApp(config, new MyStreamTaskFactory());


app
  .addInputsempty("test", "output")

TestRunner
    .of(MyStreamTestTask.class)
    .addInputStream(input)
    .addOutputsaddOutputStream(output)
    .runAsTestrun();
 
 
// Assertions on the outputs
Assert.assertThat(testingSystemTestRunner.getStreamStateconsumeStream(output), IsIterableContainingInOrder.contains({10,20,30,40,50})));

/**
* Simple Test case using a collection as an input for a low level application in the async mode
*/

// 
public class AsyncRestTaskMyAsyncStreamTask implements AsyncStreamTask, InitableTask, ClosableTask {
  private Client client;
  private WebTarget target; 

  @Override
  public void init(Config config, TaskContext taskContext) throws Exception {
    // Your initialization of web client code goes here
    client = ClientBuilder.newClient();
    target = client.target("http://example.com/resource/").path("hello");
  }

  @Override
  public void processAsync(IncomingMessageEnvelope envelope, MessageCollector collector,
      TaskCoordinator coordinator, final TaskCallback callback) {
    target.request().async().get(new InvocationCallback<Response>() {
      @Override
      public void completed(Response response) {
        Integer obj = (Integer) envelope.getMessage();
        collector.send(new OutgoingMessageEnvelope(new SystemStream("test-samza","output"), obj*10));
        callback.complete();
      }

      @Override
      public void failed(Throwable throwable) {
        System.out.println("Invocation failed.");
        callback.failure(throwable);
      }
    });
  }

  @Override
  public void close() throws Exception {
    client.close();
  }
}
 

// Initialize and run the test framework
TestRunner
 {
    client.of(new AsyncRestTask())
	.setTaskCallBackTimeoutMS(200)close();
  }
}

CollectionStream<Integer> input = CollectionStream
	.setTaskMaxConcurrency(4)
	.addInputStream(CollectionStream.of("test-samza.Input", {1,2,3,4}))
	.addOutputStream(CollectionStream.empty("test-samza.output"))
	of("test", "input", {1,2,3,4});
CollectionStream output = CollectionStream
	.empty("test", "output");

TestRunner
    .of(MyAsyncStreamTask.class)
    .addInputStream(input)
    .addOutputStream(output)
    .run();
 
// Assertions on the outputs
StreamAssert.that("test-samza.output").containsInAnyOrder({10,20,30,40});

...

/**
* Simple Test case using a collection as an input for a High level application
*/
 
public class MyStreamApplication implements StreamApplication {
  @Override
  public void init(StreamGraph graph, Config config) {
    MessageStream<Integer> pageViews = graph.getInputStream(“test-samza.page-views”);

    pageViews.map(s -> "processed " + s)
             .sendTo(graph.getOutputStream(“test-samza.output”));
 }
}


.output”));
 }
}
 
CollectionStream<Integer> input = CollectionStream
	.of("test", "input", {1,2,3,4});

CollectionStream output = CollectionStream
	.empty("test", "output");
 
// Initialize and run the test framework
TestRunner
	.of(new MyStreamApplication());
    .addInputStream(CollectionStream.of("test-samza.input", {1,2,3}))
    .addOutputStream(CollectionStream.empty("test-samza.output"))output)
    .addOverrideConfig("job.default.system", "test") 
    .run();
 
// Assertions on the outputs
StreamAssert.that("test-samza.Output"output).contains({"processed 1", "processed 2", "processed 4"});

Implementation and Test Plan

• Introduce the new interface and api for test framework
• Use the same api to write comprehensive integration test for: 
  • Samza Low level Async Api (Single and Multi-Container Mode)
  • Samza Low level Synchronous Api (Single and Multi-Container Mode)
  • Samza High Level Api (Single and Multi-Container Mode)

Compatibility, Deprecation, and Migration Plan

As this is a new feature, no plans are required for compatibility, deprecation and migration.

Rejected Alternatives