I know how to use two runner classes to rerun failed scenarios, but I want this feature only for one test.
Let's say that I have 100 scenarios and I only want to rerun scenario 40 when it fails, but if any other scenaria fails, I don't want it to rerun. Is there a way to implement this for one test in particular?
To see how to rerun all failed scenarios, check out this question:
How to rerun the failed scenarios using Cucumber?
You'll have to write custom code for this. Fortunately this is relatively easy with the JUnit Platform API (JUnit 5).
https://github.com/cucumber/cucumber-jvm/tree/main/cucumber-junit-platform-engine#rerunning-failed-scenarios
package com.example;
import org.junit.platform.engine.discovery.DiscoverySelectors;
import org.junit.platform.engine.discovery.UniqueIdSelector;
import org.junit.platform.launcher.Launcher;
import org.junit.platform.launcher.LauncherDiscoveryRequest;
import org.junit.platform.launcher.TestIdentifier;
import org.junit.platform.launcher.core.LauncherFactory;
import org.junit.platform.launcher.listeners.SummaryGeneratingListener;
import org.junit.platform.launcher.listeners.TestExecutionSummary.Failure;
import java.util.List;
import java.util.stream.Collectors;
import static org.junit.platform.engine.discovery.DiscoverySelectors.selectDirectory;
import static org.junit.platform.launcher.core.LauncherDiscoveryRequestBuilder.request;
public class RunCucumber {
public static void main(String[] args) {
LauncherDiscoveryRequest request = request()
.selectors(
selectDirectory("path/to/features")
)
.build();
Launcher launcher = LauncherFactory.create();
SummaryGeneratingListener listener = new SummaryGeneratingListener();
launcher.registerTestExecutionListeners(listener);
launcher.execute(request);
TestExecutionSummary summary = listener.getSummary();
// Do something with summary
List<UniqueIdSelector> failures = summary.getFailures().stream()
.map(Failure::getTestIdentifier)
.filter(TestIdentifier::isTest)
// Filter more to select scenarios to rerun
.map(TestIdentifier::getUniqueId)
.map(DiscoverySelectors::selectUniqueId)
.collect(Collectors.toList());
LauncherDiscoveryRequest rerunRequest = request()
.selectors(failures)
.build();
launcher.execute(rerunRequest);
TestExecutionSummary rerunSummary = listener.getSummary();
// Do something with rerunSummary
}
}
I'm trying to migrate from Vert.x to Quarkus and in Vert.x when I write message consumers like Kafka/AMQP etc. I have to scale the number of verticals to maximize performance across multiple cores i.e. Vertical Scaling - is this possible in Quarkus? I see a similar question here but it wasn't answered.
For example, with Kafka I might create a consumer inside a vertical and then scale that vertical say 10 times (that is specify the number of instances in the deployment to be 10) after doing performance testing to determine that's the optimal number. My understanding is that by default, 1 vertical = 1 event loop and does not scale across multiple cores.
I know that it's possible to use Vert.x verticals in Quarkus but is there another way to scale things like the number of Kafka consumers across multiple core?
I see that this type of scalability is configurable for things like Quarkus HTTP but I can't find anything about message consumers.
Here's the Vert.x Verticle approach that overall I'm very happy with, but I wish there were better documentation on how to do this.
UPDATE - Field injection doesn't work with this example but constructor injection does work.
Lets say I want to inject this
#ApplicationScoped
public class CoffeeRepositoryService {
public CoffeeRepositoryService() {
System.out.println("Injection succeeded!");
}
}
Here's my Verticle
package org.acme;
import io.smallrye.mutiny.Uni;
import io.smallrye.mutiny.vertx.core.AbstractVerticle;
import io.vertx.core.impl.logging.Logger;
import io.vertx.core.impl.logging.LoggerFactory;
import io.vertx.mutiny.core.eventbus.EventBus;
import io.vertx.mutiny.rabbitmq.RabbitMQClient;
import io.vertx.mutiny.rabbitmq.RabbitMQConsumer;
import io.vertx.rabbitmq.QueueOptions;
import io.vertx.rabbitmq.RabbitMQOptions;
public class RQVerticle extends AbstractVerticle {
private final Logger LOGGER = LoggerFactory.getLogger(org.acme.RQVerticle.class);
//This doesn't work - returns null
#Inject
CoffeeRepositoryService coffeeRepositoryService;
RQVerticle() {} // dummy constructor needed
#Inject // constructor injection - this does work
RQVerticle(CoffeeRepositoryService coffeeRepositoryService) {
//Here coffeeRepositoryService is injected properly
}
#Override
public Uni<Void> asyncStart() {
LOGGER.info(
"Creating RabbitMQ Connection after Quarkus successful initialization");
RabbitMQOptions config = new RabbitMQOptions();
config.setUri("amqp://localhost:5672");
RabbitMQClient client = RabbitMQClient.create(vertx, config);
Uni<Void> clientResp = client.start();
clientResp.subscribe()
.with(asyncResult -> {
LOGGER.info("RabbitMQ successfully connected!");
});
return clientResp;
}
}
Main Class - injection doesn't work like this
package org.acme;
import io.quarkus.runtime.Quarkus;
import io.quarkus.runtime.QuarkusApplication;
import io.quarkus.runtime.annotations.QuarkusMain;
import io.vertx.core.DeploymentOptions;
import io.vertx.mutiny.core.Vertx;
#QuarkusMain
public class Main {
public static void main(String... args) {
Quarkus.run(MyApp.class, args);
}
public static class MyApp implements QuarkusApplication {
#Override
public int run(String... args) throws Exception {
var vertx = Vertx.vertx();
System.out.println("Deployment Starting");
DeploymentOptions options = new DeploymentOptions()
.setInstances(2);
vertx.deployVerticleAndAwait(RQVerticle::new, options);
System.out.println("Deployment completed");
Quarkus.waitForExit();
return 0;
}
}
}
Main Class with working injection but cannot deploy more than one instance
package org.acme;
import io.quarkus.runtime.StartupEvent;
import io.vertx.mutiny.core.Vertx;
import javax.enterprise.context.ApplicationScoped;
import javax.enterprise.event.Observes;
import org.jboss.logging.Logger;
#ApplicationScoped
public class MainVerticles {
private static final Logger LOGGER = Logger.getLogger(MainVerticles.class);
public void init(#Observes StartupEvent e, Vertx vertx, RQVerticle verticle) {
public void init(#Observes StartupEvent e, Vertx vertx, RQVerticle verticle) {
DeploymentOptions options = new DeploymentOptions()
.setInstances(2);
vertx.deployVerticle(verticle,options).await().indefinitely();
}
}
Std Out - first main class looks good
2021-09-15 15:48:12,052 INFO [org.acm.RQVerticle] (vert.x-eventloop-thread-2) Creating RabbitMQ Connection after Quarkus successful initialization
2021-09-15 15:48:12,053 INFO [org.acm.RQVerticle] (vert.x-eventloop-thread-3) Creating RabbitMQ Connection after Quarkus successful initialization
Std Out - second main class
2021-09-22 15:48:11,986 ERROR [io.qua.run.Application] (Quarkus Main
Thread) Failed to start application (with profile dev):
java.lang.IllegalArgumentException: Can't specify > 1 instances for
already created verticle
I am trying to create a simple application where the app will consume Kafka message do some cql transform and publish to Kafka and below is the code:
JAVA: 1.8
Flink: 1.13
Scala: 2.11
flink-siddhi: 2.11-0.2.2-SNAPSHOT
I am using library: https://github.com/haoch/flink-siddhi
input json to Kafka:
{
"awsS3":{
"ResourceType":"aws.S3",
"Details":{
"Name":"crossplane-test",
"CreationDate":"2020-08-17T11:28:05+00:00"
},
"AccessBlock":{
"PublicAccessBlockConfiguration":{
"BlockPublicAcls":true,
"IgnorePublicAcls":true,
"BlockPublicPolicy":true,
"RestrictPublicBuckets":true
}
},
"Location":{
"LocationConstraint":"us-west-2"
}
}
}
main class:
public class S3SidhiApp {
public static void main(String[] args) {
internalStreamSiddhiApp.start();
//kafkaStreamApp.start();
}
}
App class:
package flinksidhi.app;
import com.google.gson.JsonObject;
import flinksidhi.event.s3.source.S3EventSource;
import io.siddhi.core.SiddhiManager;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.core.fs.FileSystem;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.siddhi.SiddhiCEP;
import org.json.JSONObject;
import java.nio.ByteBuffer;
import java.nio.charset.StandardCharsets;
import java.util.Map;
import static flinksidhi.app.connector.Consumers.createInputMessageConsumer;
import static flinksidhi.app.connector.Producer.*;
public class internalStreamSiddhiApp {
private static final String inputTopic = "EVENT_STREAM_INPUT";
private static final String outputTopic = "EVENT_STREAM_OUTPUT";
private static final String consumerGroup = "EVENT_STREAM1";
private static final String kafkaAddress = "localhost:9092";
private static final String zkAddress = "localhost:2181";
private static final String S3_CQL1 = "from inputStream select * insert into temp";
private static final String S3_CQL = "from inputStream select json:toObject(awsS3) as obj insert into temp;" +
"from temp select json:getString(obj,'$.awsS3.ResourceType') as affected_resource_type," +
"json:getString(obj,'$.awsS3.Details.Name') as affected_resource_name," +
"json:getString(obj,'$.awsS3.Encryption.ServerSideEncryptionConfiguration') as encryption," +
"json:getString(obj,'$.awsS3.Encryption.ServerSideEncryptionConfiguration.Rules[0].ApplyServerSideEncryptionByDefault.SSEAlgorithm') as algorithm insert into temp2; " +
"from temp2 select affected_resource_name,affected_resource_type, " +
"ifThenElse(encryption == ' ','Fail','Pass') as state," +
"ifThenElse(encryption != ' ' and algorithm == 'aws:kms','None','Critical') as severity insert into outputStream";
public static void start(){
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
//DataStream<String> inputS = env.addSource(new S3EventSource());
//Flink kafka stream consumer
FlinkKafkaConsumer<String> flinkKafkaConsumer =
createInputMessageConsumer(inputTopic, kafkaAddress,zkAddress, consumerGroup);
//Add Data stream source -- flink consumer
DataStream<String> inputS = env.addSource(flinkKafkaConsumer);
SiddhiCEP cep = SiddhiCEP.getSiddhiEnvironment(env);
cep.registerExtension("json:toObject", io.siddhi.extension.execution.json.function.ToJSONObjectFunctionExtension.class);
cep.registerExtension( "json:getString", io.siddhi.extension.execution.json.function.GetStringJSONFunctionExtension.class);
cep.registerStream("inputStream", inputS, "awsS3");
inputS.print();
System.out.println(cep.getDataStreamSchemas());
//json needs extension jars to present during runtime.
DataStream<Map<String,Object>> output = cep
.from("inputStream")
.cql(S3_CQL1)
.returnAsMap("temp");
//Flink kafka stream Producer
FlinkKafkaProducer<Map<String, Object>> flinkKafkaProducer =
createMapProducer(env,outputTopic, kafkaAddress);
//Add Data stream sink -- flink producer
output.addSink(flinkKafkaProducer);
output.print();
try {
env.execute();
} catch (Exception e) {
e.printStackTrace();
}
}
}
Consumer class:
package flinksidhi.app.connector;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.json.JSONObject;
import java.util.Properties;
public class Consumers {
public static FlinkKafkaConsumer<String> createInputMessageConsumer(String topic, String kafkaAddress, String zookeeprAddr, String kafkaGroup ) {
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", kafkaAddress);
properties.setProperty("zookeeper.connect", zookeeprAddr);
properties.setProperty("group.id",kafkaGroup);
FlinkKafkaConsumer<String> consumer = new FlinkKafkaConsumer<String>(
topic,new SimpleStringSchema(),properties);
return consumer;
}
}
Producer class:
package flinksidhi.app.connector;
import flinksidhi.app.util.ConvertJavaMapToJson;
import org.apache.flink.api.common.serialization.SerializationSchema;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.util.serialization.KeyedSerializationSchema;
import org.json.JSONObject;
import java.util.Map;
public class Producer {
public static FlinkKafkaProducer<Tuple2> createStringProducer(StreamExecutionEnvironment env, String topic, String kafkaAddress) {
return new FlinkKafkaProducer<Tuple2>(kafkaAddress, topic, new AverageSerializer());
}
public static FlinkKafkaProducer<Map<String,Object>> createMapProducer(StreamExecutionEnvironment env, String topic, String kafkaAddress) {
return new FlinkKafkaProducer<Map<String,Object>>(kafkaAddress, topic, new SerializationSchema<Map<String, Object>>() {
#Override
public void open(InitializationContext context) throws Exception {
}
#Override
public byte[] serialize(Map<String, Object> stringObjectMap) {
String json = ConvertJavaMapToJson.convert(stringObjectMap);
return json.getBytes();
}
});
}
}
I have tried many things but the code where the CQL is invoked is never called and doesn't even give any error not sure where is it going wrong.
The same thing if I do creating an internal stream source and use the same input json to return as string it works.
Initial guess: if you are using event time, are you sure you have defined watermarks correctly? As stated in the docs:
(...) an incoming element is initially put in a buffer where elements are sorted in ascending order based on their timestamp, and when a watermark arrives, all the elements in this buffer with timestamps smaller than that of the watermark are processed (...)
If this doesn't help, I would suggest to decompose/simplify the job to a bare minimum, for example just a source operator and some naive sink printing/logging elements. And if that works, start adding back operators one by one. You could also start by simplifying your CEP pattern as much as possible.
First of all thanks a lot #Piotr Nowojski , just because of your small pointer which no matter how many times I pondered over about event time , it did not came in my mind. So yes while debugging the two cases:
With internal datasource , where it was processing successfully, while debugging the flow , I identified that it was processing a watermark after it was processing the data, but it did not catch me that it was somehow managing the event time of the data implicitly.
With kafka as a datasource , while I was debugging I could very clearly see that it was not processing any watermark in the flow, but it did not occur to me that , it is happening because of the event time and watermark not handled properly.
Just adding a single line of code in the application code which I understood from below Flink code snippet:
#deprecated In Flink 1.12 the default stream time characteristic has been changed to {#link
* TimeCharacteristic#EventTime}, thus you don't need to call this method for enabling
* event-time support anymore. Explicitly using processing-time windows and timers works in
* event-time mode. If you need to disable watermarks, please use {#link
* ExecutionConfig#setAutoWatermarkInterval(long)}. If you are using {#link
* TimeCharacteristic#IngestionTime}, please manually set an appropriate {#link
* WatermarkStrategy}. If you are using generic "time window" operations (for example {#link
* org.apache.flink.streaming.api.datastream.KeyedStream#timeWindow(org.apache.flink.streaming.api.windowing.time.Time)}
* that change behaviour based on the time characteristic, please use equivalent operations
* that explicitly specify processing time or event time.
*/
I got to know that by default flink considers event time and for that watermark needs to be handled properly which I didn't so I added below link for setting the time characteristics of the flink execution environment:
env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);
and kaboom ... it started working , while this is deprecated and needs some other configuration, but thanks a lot , it was a great pointer and helped me a lot and I solved the issue..
Thanks again #Piotr Nowojski
I have one scenario where i would have only one test method in my testNG test class and i have to form multiple tests from it the reason i'm writting only one test method is that i don't know how many tests i would need, because that number depends on the number of URL's which i'm fetching from a excel sheet.
So basically i will have only one testNG test method which will fetch different URL from excel each time and execute the test and according to test result my listener will mark the test as pass or fail.
Say for example i have 20 URL's in my excel sheet so can one testNG test method execute these 20 URL's one by one and give pass/fail results 20 times. Means at the end i should see 20 tests executed with there pass/fail results.
How can i achieve this ?
Basically You would like to run your test with different data sets,
To do so, you may implement a #Factory annotated constructor and tie this constructor's #Factory annotation to a #DataProvider annotated data provider method
In addition you may use Apache POI to fetch the urls from the given excel file.
import org.apache.poi.ss.usermodel.Row;
import org.apache.poi.ss.usermodel.Workbook;
import org.apache.poi.xssf.usermodel.XSSFWorkbook;
import org.testng.annotations.DataProvider;
import org.testng.annotations.Factory;
import org.testng.annotations.Test;
import java.io.IOException;
import java.io.InputStream;
import java.util.Iterator;
import java.util.stream.Stream;
import java.util.stream.StreamSupport;
import static org.testng.Assert.assertNotNull;
public class SampleTest {
private final String url;
#Factory(dataProvider = "getUrls")
public SampleTest(String url) {
this.url = url;
}
#DataProvider(name = "getUrls")
public static Iterator<Object[]> loadUrls() throws IOException {
InputStream inputStream =
SampleTest.class.getClassLoader().getResourceAsStream("urls-sheet.xlsx");
try (Workbook workbook = new XSSFWorkbook(inputStream)) {
Iterable<Row> iterable = () -> workbook.getSheetAt(0).iterator();
Stream<Row> rows = StreamSupport.stream(iterable.spliterator(), false);
return rows.map(row -> new Object[] {row.getCell(0).getStringCellValue()}).iterator();
}
}
#Test
public void testProvidedUrl() {
assertNotNull(url, "url should have a value");
}
}
Demo source code
See
TestNG #DataProvider – Test parameters example
How to run multiple test cases in testng with different set of test data from excel file?
I am developing an asynchronous mail server in spring boot using kafka.
I have written tests with embedded kafka which starts its own kafka topic in a random port and use it for testing.
When I started this application context is loading and its expecting for kafka cluster in my local. I need to stop application conext from loading.
I replicated the code from https://github.com/code-not-found/spring-kafka/blob/master/spring-kafka-unit-test-classrule/src/test/java/com/codenotfound/kafka/producer/SpringKafkaSenderTest.java which works absolutely fine. When I followed same style in my project, I can see actual apllication starting.
SpringKafkaSenderTest .java
package com.mailer.embeddedkafkatests;
import static org.junit.Assert.assertTrue;
import java.util.Map;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.TimeUnit;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.junit.After;
import org.junit.Before;
import org.junit.ClassRule;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.listener.ContainerProperties;
import org.springframework.kafka.listener.KafkaMessageListenerContainer;
import org.springframework.kafka.listener.MessageListener;
import org.springframework.kafka.test.rule.EmbeddedKafkaRule;
import org.springframework.kafka.test.utils.ContainerTestUtils;
import org.springframework.kafka.test.utils.KafkaTestUtils;
import org.springframework.test.annotation.DirtiesContext;
import org.springframework.test.context.junit4.SpringRunner;
import com.mailer.model.Mail;
import com.mailer.producer.KafkaMessageProducer;
import com.mailer.serializer.MailSerializer;
#RunWith(SpringRunner.class)
#SpringBootTest
#DirtiesContext
public class SpringKafkaSenderTest {
private static final Logger LOGGER =
LoggerFactory.getLogger(SpringKafkaSenderTest.class);
private static String SENDER_TOPIC = "sender.t";
#Autowired
private KafkaMessageProducer sender;
private KafkaMessageListenerContainer<String, Mail> container;
private BlockingQueue<ConsumerRecord<String, Mail>> records;
#ClassRule
public static EmbeddedKafkaRule embeddedKafka =
new EmbeddedKafkaRule(1, true, SENDER_TOPIC);
#Before
public void setUp() throws Exception {
// set up the Kafka consumer properties
Map<String, Object> consumerProperties =
KafkaTestUtils.consumerProps("sender", "false",
embeddedKafka.getEmbeddedKafka());
consumerProperties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
consumerProperties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, MailSerializer.class);
// create a Kafka consumer factory
DefaultKafkaConsumerFactory<String, Mail> consumerFactory =
new DefaultKafkaConsumerFactory<String, Mail>(
consumerProperties);//, new StringDeserializer(), new JsonDeserializer<>(Mail.class));
// set the topic that needs to be consumed
ContainerProperties containerProperties =
new ContainerProperties(SENDER_TOPIC);
// create a Kafka MessageListenerContainer
container = new KafkaMessageListenerContainer<>(consumerFactory,
containerProperties);
// create a thread safe queue to store the received message
records = new LinkedBlockingQueue<>();
// setup a Kafka message listener
container
.setupMessageListener(new MessageListener<String, Mail>() {
#Override
public void onMessage(
ConsumerRecord<String, Mail> record) {
LOGGER.debug("test-listener received message='{}'",
record.toString());
records.add(record);
}
});
// start the container and underlying message listener
container.start();
// wait until the container has the required number of assigned partitions
ContainerTestUtils.waitForAssignment(container,
embeddedKafka.getEmbeddedKafka().getPartitionsPerTopic());
}
#After
public void tearDown() {
// stop the container
container.stop();
}
#Test
public void testSend() throws InterruptedException {
// send the message
Mail mail = new Mail();
mail.setFrom("vinoth#local.com");
sender.sendMessage(mail);
Thread.sleep(4000);
// check that the message was received
ConsumerRecord<String, Mail> received =
records.poll(10, TimeUnit.SECONDS);
// Hamcrest Matchers to check the value
assertTrue(received.value().getFrom().equals(mail.getFrom()));
System.out.println(received.value().getFrom());
// assertThat(received, hasValue(mail));
// AssertJ Condition to check the key
// assertThat(received).has(key(null));
}
}
Why would you like to stop the spring context from loading? Isn't the purpose of this junit to test your spring application?
In any case just remove the #SpringBootTest annotation and the spring context will not load.