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Posted to commits@flink.apache.org by fh...@apache.org on 2016/12/02 13:34:55 UTC
[05/51] [abbrv] [partial] flink git commit: [FLINK-4676] [connectors]
Merge batch and streaming connectors into common Maven module.
http://git-wip-us.apache.org/repos/asf/flink/blob/de4fe3b7/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaConsumerTestBase.java
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diff --git a/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaConsumerTestBase.java b/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaConsumerTestBase.java
deleted file mode 100644
index aa7ea49..0000000
--- a/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaConsumerTestBase.java
+++ /dev/null
@@ -1,2006 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.flink.streaming.connectors.kafka;
-
-import kafka.consumer.Consumer;
-import kafka.consumer.ConsumerConfig;
-import kafka.consumer.ConsumerIterator;
-import kafka.consumer.KafkaStream;
-import kafka.javaapi.consumer.ConsumerConnector;
-import kafka.message.MessageAndMetadata;
-import kafka.server.KafkaServer;
-import org.apache.commons.io.output.ByteArrayOutputStream;
-import org.apache.flink.api.common.ExecutionConfig;
-import org.apache.flink.api.common.JobExecutionResult;
-import org.apache.flink.api.common.functions.FlatMapFunction;
-import org.apache.flink.api.common.functions.MapFunction;
-import org.apache.flink.api.common.functions.RichFlatMapFunction;
-import org.apache.flink.api.common.functions.RichMapFunction;
-import org.apache.flink.api.common.restartstrategy.RestartStrategies;
-import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
-import org.apache.flink.api.common.typeinfo.TypeHint;
-import org.apache.flink.api.common.typeinfo.TypeInformation;
-import org.apache.flink.api.common.typeutils.TypeSerializer;
-import org.apache.flink.api.java.tuple.Tuple1;
-import org.apache.flink.api.java.tuple.Tuple2;
-import org.apache.flink.api.java.tuple.Tuple3;
-import org.apache.flink.api.java.typeutils.TypeInfoParser;
-import org.apache.flink.client.program.ProgramInvocationException;
-import org.apache.flink.configuration.Configuration;
-import org.apache.flink.core.memory.DataInputView;
-import org.apache.flink.core.memory.DataInputViewStreamWrapper;
-import org.apache.flink.core.memory.DataOutputView;
-import org.apache.flink.core.memory.DataOutputViewStreamWrapper;
-import org.apache.flink.runtime.client.JobCancellationException;
-import org.apache.flink.runtime.client.JobExecutionException;
-import org.apache.flink.runtime.jobmanager.scheduler.NoResourceAvailableException;
-import org.apache.flink.runtime.state.CheckpointListener;
-import org.apache.flink.streaming.api.checkpoint.Checkpointed;
-import org.apache.flink.streaming.api.datastream.DataStream;
-import org.apache.flink.streaming.api.datastream.DataStreamSink;
-import org.apache.flink.streaming.api.datastream.DataStreamSource;
-import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
-import org.apache.flink.streaming.api.functions.AssignerWithPunctuatedWatermarks;
-import org.apache.flink.streaming.api.functions.sink.DiscardingSink;
-import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
-import org.apache.flink.streaming.api.functions.sink.SinkFunction;
-import org.apache.flink.streaming.api.functions.source.RichParallelSourceFunction;
-import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
-import org.apache.flink.streaming.api.functions.source.SourceFunction;
-import org.apache.flink.streaming.api.operators.AbstractStreamOperator;
-import org.apache.flink.streaming.api.operators.OneInputStreamOperator;
-import org.apache.flink.streaming.api.watermark.Watermark;
-import org.apache.flink.streaming.connectors.kafka.testutils.DataGenerators;
-import org.apache.flink.streaming.connectors.kafka.testutils.FailingIdentityMapper;
-import org.apache.flink.streaming.connectors.kafka.testutils.JobManagerCommunicationUtils;
-import org.apache.flink.streaming.connectors.kafka.testutils.PartitionValidatingMapper;
-import org.apache.flink.streaming.connectors.kafka.testutils.ThrottledMapper;
-import org.apache.flink.streaming.connectors.kafka.testutils.Tuple2Partitioner;
-import org.apache.flink.streaming.connectors.kafka.testutils.ValidatingExactlyOnceSink;
-import org.apache.flink.streaming.runtime.streamrecord.StreamRecord;
-import org.apache.flink.streaming.util.serialization.DeserializationSchema;
-import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchema;
-import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchemaWrapper;
-import org.apache.flink.streaming.util.serialization.KeyedSerializationSchema;
-import org.apache.flink.streaming.util.serialization.KeyedSerializationSchemaWrapper;
-import org.apache.flink.streaming.util.serialization.SimpleStringSchema;
-import org.apache.flink.streaming.util.serialization.TypeInformationKeyValueSerializationSchema;
-import org.apache.flink.streaming.util.serialization.TypeInformationSerializationSchema;
-import org.apache.flink.test.util.SuccessException;
-import org.apache.flink.testutils.junit.RetryOnException;
-import org.apache.flink.testutils.junit.RetryRule;
-import org.apache.flink.util.Collector;
-import org.apache.kafka.clients.producer.ProducerConfig;
-import org.apache.kafka.common.errors.TimeoutException;
-import org.junit.Assert;
-import org.junit.Before;
-import org.junit.Rule;
-
-import javax.management.MBeanServer;
-import javax.management.ObjectName;
-import java.io.ByteArrayInputStream;
-import java.io.IOException;
-import java.lang.management.ManagementFactory;
-import java.util.ArrayList;
-import java.util.BitSet;
-import java.util.Collections;
-import java.util.Date;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Properties;
-import java.util.Random;
-import java.util.Set;
-import java.util.UUID;
-import java.util.concurrent.atomic.AtomicReference;
-
-import static org.apache.flink.test.util.TestUtils.tryExecute;
-import static org.junit.Assert.assertEquals;
-import static org.junit.Assert.assertFalse;
-import static org.junit.Assert.assertNotNull;
-import static org.junit.Assert.assertNull;
-import static org.junit.Assert.assertTrue;
-import static org.junit.Assert.fail;
-
-
-@SuppressWarnings("serial")
-public abstract class KafkaConsumerTestBase extends KafkaTestBase {
-
- @Rule
- public RetryRule retryRule = new RetryRule();
-
-
- // ------------------------------------------------------------------------
- // Common Test Preparation
- // ------------------------------------------------------------------------
-
- /**
- * Makes sure that no job is on the JobManager any more from any previous tests that use
- * the same mini cluster. Otherwise, missing slots may happen.
- */
- @Before
- public void ensureNoJobIsLingering() throws Exception {
- JobManagerCommunicationUtils.waitUntilNoJobIsRunning(flink.getLeaderGateway(timeout));
- }
-
-
- // ------------------------------------------------------------------------
- // Suite of Tests
- //
- // The tests here are all not activated (by an @Test tag), but need
- // to be invoked from the extending classes. That way, the classes can
- // select which tests to run.
- // ------------------------------------------------------------------------
-
- /**
- * Test that ensures the KafkaConsumer is properly failing if the topic doesnt exist
- * and a wrong broker was specified
- *
- * @throws Exception
- */
- public void runFailOnNoBrokerTest() throws Exception {
- try {
- Properties properties = new Properties();
-
- StreamExecutionEnvironment see = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- see.getConfig().disableSysoutLogging();
- see.setRestartStrategy(RestartStrategies.noRestart());
- see.setParallelism(1);
-
- // use wrong ports for the consumers
- properties.setProperty("bootstrap.servers", "localhost:80");
- properties.setProperty("zookeeper.connect", "localhost:80");
- properties.setProperty("group.id", "test");
- properties.setProperty("request.timeout.ms", "3000"); // let the test fail fast
- properties.setProperty("socket.timeout.ms", "3000");
- properties.setProperty("session.timeout.ms", "2000");
- properties.setProperty("fetch.max.wait.ms", "2000");
- properties.setProperty("heartbeat.interval.ms", "1000");
- properties.putAll(secureProps);
- FlinkKafkaConsumerBase<String> source = kafkaServer.getConsumer("doesntexist", new SimpleStringSchema(), properties);
- DataStream<String> stream = see.addSource(source);
- stream.print();
- see.execute("No broker test");
- } catch(ProgramInvocationException pie) {
- if(kafkaServer.getVersion().equals("0.9") || kafkaServer.getVersion().equals("0.10")) {
- assertTrue(pie.getCause() instanceof JobExecutionException);
-
- JobExecutionException jee = (JobExecutionException) pie.getCause();
-
- assertTrue(jee.getCause() instanceof TimeoutException);
-
- TimeoutException te = (TimeoutException) jee.getCause();
-
- assertEquals("Timeout expired while fetching topic metadata", te.getMessage());
- } else {
- assertTrue(pie.getCause() instanceof JobExecutionException);
-
- JobExecutionException jee = (JobExecutionException) pie.getCause();
-
- assertTrue(jee.getCause() instanceof RuntimeException);
-
- RuntimeException re = (RuntimeException) jee.getCause();
-
- assertTrue(re.getMessage().contains("Unable to retrieve any partitions for the requested topics [doesntexist]"));
- }
- }
- }
-
- /**
- * Ensures that the committed offsets to Kafka are the offsets of "the next record to process"
- */
- public void runCommitOffsetsToKafka() throws Exception {
- // 3 partitions with 50 records each (0-49, so the expected commit offset of each partition should be 50)
- final int parallelism = 3;
- final int recordsInEachPartition = 50;
-
- final String topicName = writeSequence("testCommitOffsetsToKafkaTopic", recordsInEachPartition, parallelism, 1);
-
- final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.getConfig().disableSysoutLogging();
- env.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env.setParallelism(parallelism);
- env.enableCheckpointing(200);
-
- DataStream<String> stream = env.addSource(kafkaServer.getConsumer(topicName, new SimpleStringSchema(), standardProps));
- stream.addSink(new DiscardingSink<String>());
-
- final AtomicReference<Throwable> errorRef = new AtomicReference<>();
- final Thread runner = new Thread("runner") {
- @Override
- public void run() {
- try {
- env.execute();
- }
- catch (Throwable t) {
- if (!(t.getCause() instanceof JobCancellationException)) {
- errorRef.set(t);
- }
- }
- }
- };
- runner.start();
-
- final Long l50 = 50L; // the final committed offset in Kafka should be 50
- final long deadline = 30000 + System.currentTimeMillis();
-
- KafkaTestEnvironment.KafkaOffsetHandler kafkaOffsetHandler = kafkaServer.createOffsetHandler(standardProps);
-
- do {
- Long o1 = kafkaOffsetHandler.getCommittedOffset(topicName, 0);
- Long o2 = kafkaOffsetHandler.getCommittedOffset(topicName, 1);
- Long o3 = kafkaOffsetHandler.getCommittedOffset(topicName, 2);
-
- if (l50.equals(o1) && l50.equals(o2) && l50.equals(o3)) {
- break;
- }
-
- Thread.sleep(100);
- }
- while (System.currentTimeMillis() < deadline);
-
- // cancel the job
- JobManagerCommunicationUtils.cancelCurrentJob(flink.getLeaderGateway(timeout));
-
- final Throwable t = errorRef.get();
- if (t != null) {
- throw new RuntimeException("Job failed with an exception", t);
- }
-
- // final check to see if offsets are correctly in Kafka
- Long o1 = kafkaOffsetHandler.getCommittedOffset(topicName, 0);
- Long o2 = kafkaOffsetHandler.getCommittedOffset(topicName, 1);
- Long o3 = kafkaOffsetHandler.getCommittedOffset(topicName, 2);
- Assert.assertEquals(Long.valueOf(50L), o1);
- Assert.assertEquals(Long.valueOf(50L), o2);
- Assert.assertEquals(Long.valueOf(50L), o3);
-
- kafkaOffsetHandler.close();
- deleteTestTopic(topicName);
- }
-
- /**
- * This test first writes a total of 300 records to a test topic, reads the first 150 so that some offsets are
- * committed to Kafka, and then startup the consumer again to read the remaining records starting from the committed offsets.
- * The test ensures that whatever offsets were committed to Kafka, the consumer correctly picks them up
- * and starts at the correct position.
- */
- public void runStartFromKafkaCommitOffsets() throws Exception {
- final int parallelism = 3;
- final int recordsInEachPartition = 300;
-
- final String topicName = writeSequence("testStartFromKafkaCommitOffsetsTopic", recordsInEachPartition, parallelism, 1);
-
- KafkaTestEnvironment.KafkaOffsetHandler kafkaOffsetHandler = kafkaServer.createOffsetHandler(standardProps);
-
- Long o1;
- Long o2;
- Long o3;
- int attempt = 0;
- // make sure that o1, o2, o3 are not all null before proceeding
- do {
- attempt++;
- LOG.info("Attempt " + attempt + " to read records and commit some offsets to Kafka");
-
- final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.getConfig().disableSysoutLogging();
- env.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env.setParallelism(parallelism);
- env.enableCheckpointing(20); // fast checkpoints to make sure we commit some offsets
-
- env
- .addSource(kafkaServer.getConsumer(topicName, new SimpleStringSchema(), standardProps))
- .map(new ThrottledMapper<String>(50))
- .map(new MapFunction<String, Object>() {
- int count = 0;
- @Override
- public Object map(String value) throws Exception {
- count++;
- if (count == 150) {
- throw new SuccessException();
- }
- return null;
- }
- })
- .addSink(new DiscardingSink<>());
-
- tryExecute(env, "Read some records to commit offsets to Kafka");
-
- o1 = kafkaOffsetHandler.getCommittedOffset(topicName, 0);
- o2 = kafkaOffsetHandler.getCommittedOffset(topicName, 1);
- o3 = kafkaOffsetHandler.getCommittedOffset(topicName, 2);
- } while (o1 == null && o2 == null && o3 == null && attempt < 3);
-
- if (o1 == null && o2 == null && o3 == null) {
- throw new RuntimeException("No offsets have been committed after 3 attempts");
- }
-
- LOG.info("Got final committed offsets from Kafka o1={}, o2={}, o3={}", o1, o2, o3);
-
- final StreamExecutionEnvironment env2 = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env2.getConfig().disableSysoutLogging();
- env2.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env2.setParallelism(parallelism);
-
- // whatever offsets were committed for each partition, the consumer should pick
- // them up and start from the correct position so that the remaining records are all read
- HashMap<Integer, Tuple2<Integer, Integer>> partitionsToValuesCountAndStartOffset = new HashMap<>();
- partitionsToValuesCountAndStartOffset.put(0, new Tuple2<>(
- (o1 != null) ? (int) (recordsInEachPartition - o1) : recordsInEachPartition,
- (o1 != null) ? o1.intValue() : 0
- ));
- partitionsToValuesCountAndStartOffset.put(1, new Tuple2<>(
- (o2 != null) ? (int) (recordsInEachPartition - o2) : recordsInEachPartition,
- (o2 != null) ? o2.intValue() : 0
- ));
- partitionsToValuesCountAndStartOffset.put(2, new Tuple2<>(
- (o3 != null) ? (int) (recordsInEachPartition - o3) : recordsInEachPartition,
- (o3 != null) ? o3.intValue() : 0
- ));
-
- readSequence(env2, standardProps, topicName, partitionsToValuesCountAndStartOffset);
-
- kafkaOffsetHandler.close();
- deleteTestTopic(topicName);
- }
-
- /**
- * This test ensures that when the consumers retrieve some start offset from kafka (earliest, latest), that this offset
- * is committed to Kafka, even if some partitions are not read.
- *
- * Test:
- * - Create 3 partitions
- * - write 50 messages into each.
- * - Start three consumers with auto.offset.reset='latest' and wait until they committed into Kafka.
- * - Check if the offsets in Kafka are set to 50 for the three partitions
- *
- * See FLINK-3440 as well
- */
- public void runAutoOffsetRetrievalAndCommitToKafka() throws Exception {
- // 3 partitions with 50 records each (0-49, so the expected commit offset of each partition should be 50)
- final int parallelism = 3;
- final int recordsInEachPartition = 50;
-
- final String topicName = writeSequence("testAutoOffsetRetrievalAndCommitToKafkaTopic", recordsInEachPartition, parallelism, 1);
-
- final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.getConfig().disableSysoutLogging();
- env.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env.setParallelism(parallelism);
- env.enableCheckpointing(200);
-
- Properties readProps = new Properties();
- readProps.putAll(standardProps);
- readProps.setProperty("auto.offset.reset", "latest"); // set to reset to latest, so that partitions are initially not read
-
- DataStream<String> stream = env.addSource(kafkaServer.getConsumer(topicName, new SimpleStringSchema(), readProps));
- stream.addSink(new DiscardingSink<String>());
-
- final AtomicReference<Throwable> errorRef = new AtomicReference<>();
- final Thread runner = new Thread("runner") {
- @Override
- public void run() {
- try {
- env.execute();
- }
- catch (Throwable t) {
- if (!(t.getCause() instanceof JobCancellationException)) {
- errorRef.set(t);
- }
- }
- }
- };
- runner.start();
-
- KafkaTestEnvironment.KafkaOffsetHandler kafkaOffsetHandler = kafkaServer.createOffsetHandler(standardProps);
-
- final Long l50 = 50L; // the final committed offset in Kafka should be 50
- final long deadline = 30000 + System.currentTimeMillis();
- do {
- Long o1 = kafkaOffsetHandler.getCommittedOffset(topicName, 0);
- Long o2 = kafkaOffsetHandler.getCommittedOffset(topicName, 1);
- Long o3 = kafkaOffsetHandler.getCommittedOffset(topicName, 2);
-
- if (l50.equals(o1) && l50.equals(o2) && l50.equals(o3)) {
- break;
- }
-
- Thread.sleep(100);
- }
- while (System.currentTimeMillis() < deadline);
-
- // cancel the job
- JobManagerCommunicationUtils.cancelCurrentJob(flink.getLeaderGateway(timeout));
-
- final Throwable t = errorRef.get();
- if (t != null) {
- throw new RuntimeException("Job failed with an exception", t);
- }
-
- // final check to see if offsets are correctly in Kafka
- Long o1 = kafkaOffsetHandler.getCommittedOffset(topicName, 0);
- Long o2 = kafkaOffsetHandler.getCommittedOffset(topicName, 1);
- Long o3 = kafkaOffsetHandler.getCommittedOffset(topicName, 2);
- Assert.assertEquals(Long.valueOf(50L), o1);
- Assert.assertEquals(Long.valueOf(50L), o2);
- Assert.assertEquals(Long.valueOf(50L), o3);
-
- kafkaOffsetHandler.close();
- deleteTestTopic(topicName);
- }
-
- /**
- * Ensure Kafka is working on both producer and consumer side.
- * This executes a job that contains two Flink pipelines.
- *
- * <pre>
- * (generator source) --> (kafka sink)-[KAFKA-TOPIC]-(kafka source) --> (validating sink)
- * </pre>
- *
- * We need to externally retry this test. We cannot let Flink's retry mechanism do it, because the Kafka producer
- * does not guarantee exactly-once output. Hence a recovery would introduce duplicates that
- * cause the test to fail.
- *
- * This test also ensures that FLINK-3156 doesn't happen again:
- *
- * The following situation caused a NPE in the FlinkKafkaConsumer
- *
- * topic-1 <-- elements are only produced into topic1.
- * topic-2
- *
- * Therefore, this test is consuming as well from an empty topic.
- *
- */
- @RetryOnException(times=2, exception=kafka.common.NotLeaderForPartitionException.class)
- public void runSimpleConcurrentProducerConsumerTopology() throws Exception {
- final String topic = "concurrentProducerConsumerTopic_" + UUID.randomUUID().toString();
- final String additionalEmptyTopic = "additionalEmptyTopic_" + UUID.randomUUID().toString();
-
- final int parallelism = 3;
- final int elementsPerPartition = 100;
- final int totalElements = parallelism * elementsPerPartition;
-
- createTestTopic(topic, parallelism, 2);
- createTestTopic(additionalEmptyTopic, parallelism, 1); // create an empty topic which will remain empty all the time
-
- final StreamExecutionEnvironment env =
- StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(parallelism);
- env.enableCheckpointing(500);
- env.setRestartStrategy(RestartStrategies.noRestart()); // fail immediately
- env.getConfig().disableSysoutLogging();
-
- TypeInformation<Tuple2<Long, String>> longStringType = TypeInfoParser.parse("Tuple2<Long, String>");
-
- TypeInformationSerializationSchema<Tuple2<Long, String>> sourceSchema =
- new TypeInformationSerializationSchema<>(longStringType, env.getConfig());
-
- TypeInformationSerializationSchema<Tuple2<Long, String>> sinkSchema =
- new TypeInformationSerializationSchema<>(longStringType, env.getConfig());
-
- // ----------- add producer dataflow ----------
-
- DataStream<Tuple2<Long, String>> stream = env.addSource(new RichParallelSourceFunction<Tuple2<Long,String>>() {
-
- private boolean running = true;
-
- @Override
- public void run(SourceContext<Tuple2<Long, String>> ctx) throws InterruptedException {
- int cnt = getRuntimeContext().getIndexOfThisSubtask() * elementsPerPartition;
- int limit = cnt + elementsPerPartition;
-
-
- while (running && cnt < limit) {
- ctx.collect(new Tuple2<>(1000L + cnt, "kafka-" + cnt));
- cnt++;
- // we delay data generation a bit so that we are sure that some checkpoints are
- // triggered (for FLINK-3156)
- Thread.sleep(50);
- }
- }
-
- @Override
- public void cancel() {
- running = false;
- }
- });
- Properties producerProperties = FlinkKafkaProducerBase.getPropertiesFromBrokerList(brokerConnectionStrings);
- producerProperties.setProperty("retries", "3");
- producerProperties.putAll(secureProps);
- kafkaServer.produceIntoKafka(stream, topic, new KeyedSerializationSchemaWrapper<>(sinkSchema), producerProperties, null);
-
- // ----------- add consumer dataflow ----------
-
- List<String> topics = new ArrayList<>();
- topics.add(topic);
- topics.add(additionalEmptyTopic);
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<Tuple2<Long, String>> source = kafkaServer.getConsumer(topics, sourceSchema, props);
-
- DataStreamSource<Tuple2<Long, String>> consuming = env.addSource(source).setParallelism(parallelism);
-
- consuming.addSink(new RichSinkFunction<Tuple2<Long, String>>() {
-
- private int elCnt = 0;
- private BitSet validator = new BitSet(totalElements);
-
- @Override
- public void invoke(Tuple2<Long, String> value) throws Exception {
- String[] sp = value.f1.split("-");
- int v = Integer.parseInt(sp[1]);
-
- assertEquals(value.f0 - 1000, (long) v);
-
- assertFalse("Received tuple twice", validator.get(v));
- validator.set(v);
- elCnt++;
-
- if (elCnt == totalElements) {
- // check if everything in the bitset is set to true
- int nc;
- if ((nc = validator.nextClearBit(0)) != totalElements) {
- fail("The bitset was not set to 1 on all elements. Next clear:"
- + nc + " Set: " + validator);
- }
- throw new SuccessException();
- }
- }
-
- @Override
- public void close() throws Exception {
- super.close();
- }
- }).setParallelism(1);
-
- try {
- tryExecutePropagateExceptions(env, "runSimpleConcurrentProducerConsumerTopology");
- }
- catch (ProgramInvocationException | JobExecutionException e) {
- // look for NotLeaderForPartitionException
- Throwable cause = e.getCause();
-
- // search for nested SuccessExceptions
- int depth = 0;
- while (cause != null && depth++ < 20) {
- if (cause instanceof kafka.common.NotLeaderForPartitionException) {
- throw (Exception) cause;
- }
- cause = cause.getCause();
- }
- throw e;
- }
-
- deleteTestTopic(topic);
- }
-
- /**
- * Tests the proper consumption when having a 1:1 correspondence between kafka partitions and
- * Flink sources.
- */
- public void runOneToOneExactlyOnceTest() throws Exception {
-
- final String topic = "oneToOneTopic";
- final int parallelism = 5;
- final int numElementsPerPartition = 1000;
- final int totalElements = parallelism * numElementsPerPartition;
- final int failAfterElements = numElementsPerPartition / 3;
-
- createTestTopic(topic, parallelism, 1);
-
- DataGenerators.generateRandomizedIntegerSequence(
- StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort),
- kafkaServer,
- topic, parallelism, numElementsPerPartition, true);
-
- // run the topology that fails and recovers
-
- DeserializationSchema<Integer> schema =
- new TypeInformationSerializationSchema<>(BasicTypeInfo.INT_TYPE_INFO, new ExecutionConfig());
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.enableCheckpointing(500);
- env.setParallelism(parallelism);
- env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0));
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
-
- FlinkKafkaConsumerBase<Integer> kafkaSource = kafkaServer.getConsumer(topic, schema, props);
-
- env
- .addSource(kafkaSource)
- .map(new PartitionValidatingMapper(parallelism, 1))
- .map(new FailingIdentityMapper<Integer>(failAfterElements))
- .addSink(new ValidatingExactlyOnceSink(totalElements)).setParallelism(1);
-
- FailingIdentityMapper.failedBefore = false;
- tryExecute(env, "One-to-one exactly once test");
-
- deleteTestTopic(topic);
- }
-
- /**
- * Tests the proper consumption when having fewer Flink sources than Kafka partitions, so
- * one Flink source will read multiple Kafka partitions.
- */
- public void runOneSourceMultiplePartitionsExactlyOnceTest() throws Exception {
- final String topic = "oneToManyTopic";
- final int numPartitions = 5;
- final int numElementsPerPartition = 1000;
- final int totalElements = numPartitions * numElementsPerPartition;
- final int failAfterElements = numElementsPerPartition / 3;
-
- final int parallelism = 2;
-
- createTestTopic(topic, numPartitions, 1);
-
- DataGenerators.generateRandomizedIntegerSequence(
- StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort),
- kafkaServer,
- topic, numPartitions, numElementsPerPartition, false);
-
- // run the topology that fails and recovers
-
- DeserializationSchema<Integer> schema =
- new TypeInformationSerializationSchema<>(BasicTypeInfo.INT_TYPE_INFO, new ExecutionConfig());
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.enableCheckpointing(500);
- env.setParallelism(parallelism);
- env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0));
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<Integer> kafkaSource = kafkaServer.getConsumer(topic, schema, props);
-
- env
- .addSource(kafkaSource)
- .map(new PartitionValidatingMapper(numPartitions, 3))
- .map(new FailingIdentityMapper<Integer>(failAfterElements))
- .addSink(new ValidatingExactlyOnceSink(totalElements)).setParallelism(1);
-
- FailingIdentityMapper.failedBefore = false;
- tryExecute(env, "One-source-multi-partitions exactly once test");
-
- deleteTestTopic(topic);
- }
-
- /**
- * Tests the proper consumption when having more Flink sources than Kafka partitions, which means
- * that some Flink sources will read no partitions.
- */
- public void runMultipleSourcesOnePartitionExactlyOnceTest() throws Exception {
- final String topic = "manyToOneTopic";
- final int numPartitions = 5;
- final int numElementsPerPartition = 1000;
- final int totalElements = numPartitions * numElementsPerPartition;
- final int failAfterElements = numElementsPerPartition / 3;
-
- final int parallelism = 8;
-
- createTestTopic(topic, numPartitions, 1);
-
- DataGenerators.generateRandomizedIntegerSequence(
- StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort),
- kafkaServer,
- topic, numPartitions, numElementsPerPartition, true);
-
- // run the topology that fails and recovers
-
- DeserializationSchema<Integer> schema =
- new TypeInformationSerializationSchema<>(BasicTypeInfo.INT_TYPE_INFO, new ExecutionConfig());
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.enableCheckpointing(500);
- env.setParallelism(parallelism);
- // set the number of restarts to one. The failing mapper will fail once, then it's only success exceptions.
- env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0));
- env.getConfig().disableSysoutLogging();
- env.setBufferTimeout(0);
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<Integer> kafkaSource = kafkaServer.getConsumer(topic, schema, props);
-
- env
- .addSource(kafkaSource)
- .map(new PartitionValidatingMapper(numPartitions, 1))
- .map(new FailingIdentityMapper<Integer>(failAfterElements))
- .addSink(new ValidatingExactlyOnceSink(totalElements)).setParallelism(1);
-
- FailingIdentityMapper.failedBefore = false;
- tryExecute(env, "multi-source-one-partitions exactly once test");
-
-
- deleteTestTopic(topic);
- }
-
-
- /**
- * Tests that the source can be properly canceled when reading full partitions.
- */
- public void runCancelingOnFullInputTest() throws Exception {
- final String topic = "cancelingOnFullTopic";
-
- final int parallelism = 3;
- createTestTopic(topic, parallelism, 1);
-
- // launch a producer thread
- DataGenerators.InfiniteStringsGenerator generator =
- new DataGenerators.InfiniteStringsGenerator(kafkaServer, topic);
- generator.start();
-
- // launch a consumer asynchronously
-
- final AtomicReference<Throwable> jobError = new AtomicReference<>();
-
- final Runnable jobRunner = new Runnable() {
- @Override
- public void run() {
- try {
- final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(parallelism);
- env.enableCheckpointing(100);
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<String> source = kafkaServer.getConsumer(topic, new SimpleStringSchema(), props);
-
- env.addSource(source).addSink(new DiscardingSink<String>());
-
- env.execute("Runner for CancelingOnFullInputTest");
- }
- catch (Throwable t) {
- jobError.set(t);
- }
- }
- };
-
- Thread runnerThread = new Thread(jobRunner, "program runner thread");
- runnerThread.start();
-
- // wait a bit before canceling
- Thread.sleep(2000);
-
- Throwable failueCause = jobError.get();
- if(failueCause != null) {
- failueCause.printStackTrace();
- Assert.fail("Test failed prematurely with: " + failueCause.getMessage());
- }
-
- // cancel
- JobManagerCommunicationUtils.cancelCurrentJob(flink.getLeaderGateway(timeout), "Runner for CancelingOnFullInputTest");
-
- // wait for the program to be done and validate that we failed with the right exception
- runnerThread.join();
-
- failueCause = jobError.get();
- assertNotNull("program did not fail properly due to canceling", failueCause);
- assertTrue(failueCause.getMessage().contains("Job was cancelled"));
-
- if (generator.isAlive()) {
- generator.shutdown();
- generator.join();
- }
- else {
- Throwable t = generator.getError();
- if (t != null) {
- t.printStackTrace();
- fail("Generator failed: " + t.getMessage());
- } else {
- fail("Generator failed with no exception");
- }
- }
-
- deleteTestTopic(topic);
- }
-
- /**
- * Tests that the source can be properly canceled when reading empty partitions.
- */
- public void runCancelingOnEmptyInputTest() throws Exception {
- final String topic = "cancelingOnEmptyInputTopic";
-
- final int parallelism = 3;
- createTestTopic(topic, parallelism, 1);
-
- final AtomicReference<Throwable> error = new AtomicReference<>();
-
- final Runnable jobRunner = new Runnable() {
- @Override
- public void run() {
- try {
- final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(parallelism);
- env.enableCheckpointing(100);
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<String> source = kafkaServer.getConsumer(topic, new SimpleStringSchema(), props);
-
- env.addSource(source).addSink(new DiscardingSink<String>());
-
- env.execute("CancelingOnEmptyInputTest");
- }
- catch (Throwable t) {
- LOG.error("Job Runner failed with exception", t);
- error.set(t);
- }
- }
- };
-
- Thread runnerThread = new Thread(jobRunner, "program runner thread");
- runnerThread.start();
-
- // wait a bit before canceling
- Thread.sleep(2000);
-
- Throwable failueCause = error.get();
- if (failueCause != null) {
- failueCause.printStackTrace();
- Assert.fail("Test failed prematurely with: " + failueCause.getMessage());
- }
- // cancel
- JobManagerCommunicationUtils.cancelCurrentJob(flink.getLeaderGateway(timeout));
-
- // wait for the program to be done and validate that we failed with the right exception
- runnerThread.join();
-
- failueCause = error.get();
- assertNotNull("program did not fail properly due to canceling", failueCause);
- assertTrue(failueCause.getMessage().contains("Job was cancelled"));
-
- deleteTestTopic(topic);
- }
-
- /**
- * Tests that the source can be properly canceled when reading full partitions.
- */
- public void runFailOnDeployTest() throws Exception {
- final String topic = "failOnDeployTopic";
-
- createTestTopic(topic, 2, 1);
-
- DeserializationSchema<Integer> schema =
- new TypeInformationSerializationSchema<>(BasicTypeInfo.INT_TYPE_INFO, new ExecutionConfig());
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(12); // needs to be more that the mini cluster has slots
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<Integer> kafkaSource = kafkaServer.getConsumer(topic, schema, props);
-
- env
- .addSource(kafkaSource)
- .addSink(new DiscardingSink<Integer>());
-
- try {
- env.execute("test fail on deploy");
- fail("this test should fail with an exception");
- }
- catch (ProgramInvocationException e) {
-
- // validate that we failed due to a NoResourceAvailableException
- Throwable cause = e.getCause();
- int depth = 0;
- boolean foundResourceException = false;
-
- while (cause != null && depth++ < 20) {
- if (cause instanceof NoResourceAvailableException) {
- foundResourceException = true;
- break;
- }
- cause = cause.getCause();
- }
-
- assertTrue("Wrong exception", foundResourceException);
- }
-
- deleteTestTopic(topic);
- }
-
- /**
- * Test producing and consuming into multiple topics
- * @throws java.lang.Exception
- */
- public void runProduceConsumeMultipleTopics() throws java.lang.Exception {
- final int NUM_TOPICS = 5;
- final int NUM_ELEMENTS = 20;
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.getConfig().disableSysoutLogging();
-
- // create topics with content
- final List<String> topics = new ArrayList<>();
- for (int i = 0; i < NUM_TOPICS; i++) {
- final String topic = "topic-" + i;
- topics.add(topic);
- // create topic
- createTestTopic(topic, i + 1 /*partitions*/, 1);
- }
- // run first job, producing into all topics
- DataStream<Tuple3<Integer, Integer, String>> stream = env.addSource(new RichParallelSourceFunction<Tuple3<Integer, Integer, String>>() {
-
- @Override
- public void run(SourceContext<Tuple3<Integer, Integer, String>> ctx) throws Exception {
- int partition = getRuntimeContext().getIndexOfThisSubtask();
-
- for (int topicId = 0; topicId < NUM_TOPICS; topicId++) {
- for (int i = 0; i < NUM_ELEMENTS; i++) {
- ctx.collect(new Tuple3<>(partition, i, "topic-" + topicId));
- }
- }
- }
-
- @Override
- public void cancel() {
- }
- });
-
- Tuple2WithTopicSchema schema = new Tuple2WithTopicSchema(env.getConfig());
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- kafkaServer.produceIntoKafka(stream, "dummy", schema, props, null);
-
- env.execute("Write to topics");
-
- // run second job consuming from multiple topics
- env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.getConfig().disableSysoutLogging();
-
- stream = env.addSource(kafkaServer.getConsumer(topics, schema, props));
-
- stream.flatMap(new FlatMapFunction<Tuple3<Integer, Integer, String>, Integer>() {
- Map<String, Integer> countPerTopic = new HashMap<>(NUM_TOPICS);
- @Override
- public void flatMap(Tuple3<Integer, Integer, String> value, Collector<Integer> out) throws Exception {
- Integer count = countPerTopic.get(value.f2);
- if (count == null) {
- count = 1;
- } else {
- count++;
- }
- countPerTopic.put(value.f2, count);
-
- // check map:
- for (Map.Entry<String, Integer> el: countPerTopic.entrySet()) {
- if (el.getValue() < NUM_ELEMENTS) {
- break; // not enough yet
- }
- if (el.getValue() > NUM_ELEMENTS) {
- throw new RuntimeException("There is a failure in the test. I've read " +
- el.getValue() + " from topic " + el.getKey());
- }
- }
- // we've seen messages from all topics
- throw new SuccessException();
- }
- }).setParallelism(1);
-
- tryExecute(env, "Count elements from the topics");
-
-
- // delete all topics again
- for (int i = 0; i < NUM_TOPICS; i++) {
- final String topic = "topic-" + i;
- deleteTestTopic(topic);
- }
- }
-
- /**
- * Serialization scheme forwarding byte[] records.
- */
- private static class ByteArraySerializationSchema implements KeyedSerializationSchema<byte[]> {
-
- @Override
- public byte[] serializeKey(byte[] element) {
- return null;
- }
-
- @Override
- public byte[] serializeValue(byte[] element) {
- return element;
- }
-
- @Override
- public String getTargetTopic(byte[] element) {
- return null;
- }
- }
-
- private static class Tuple2WithTopicSchema implements KeyedDeserializationSchema<Tuple3<Integer, Integer, String>>,
- KeyedSerializationSchema<Tuple3<Integer, Integer, String>> {
-
- private final TypeSerializer<Tuple2<Integer, Integer>> ts;
-
- public Tuple2WithTopicSchema(ExecutionConfig ec) {
- ts = TypeInfoParser.<Tuple2<Integer, Integer>>parse("Tuple2<Integer, Integer>").createSerializer(ec);
- }
-
- @Override
- public Tuple3<Integer, Integer, String> deserialize(byte[] messageKey, byte[] message, String topic, int partition, long offset) throws IOException {
- DataInputView in = new DataInputViewStreamWrapper(new ByteArrayInputStream(message));
- Tuple2<Integer, Integer> t2 = ts.deserialize(in);
- return new Tuple3<>(t2.f0, t2.f1, topic);
- }
-
- @Override
- public boolean isEndOfStream(Tuple3<Integer, Integer, String> nextElement) {
- return false;
- }
-
- @Override
- public TypeInformation<Tuple3<Integer, Integer, String>> getProducedType() {
- return TypeInfoParser.parse("Tuple3<Integer, Integer, String>");
- }
-
- @Override
- public byte[] serializeKey(Tuple3<Integer, Integer, String> element) {
- return null;
- }
-
- @Override
- public byte[] serializeValue(Tuple3<Integer, Integer, String> element) {
- ByteArrayOutputStream by = new ByteArrayOutputStream();
- DataOutputView out = new DataOutputViewStreamWrapper(by);
- try {
- ts.serialize(new Tuple2<>(element.f0, element.f1), out);
- } catch (IOException e) {
- throw new RuntimeException("Error" ,e);
- }
- return by.toByteArray();
- }
-
- @Override
- public String getTargetTopic(Tuple3<Integer, Integer, String> element) {
- return element.f2;
- }
- }
-
- /**
- * Test Flink's Kafka integration also with very big records (30MB)
- * see http://stackoverflow.com/questions/21020347/kafka-sending-a-15mb-message
- *
- */
- public void runBigRecordTestTopology() throws Exception {
-
- final String topic = "bigRecordTestTopic";
- final int parallelism = 1; // otherwise, the kafka mini clusters may run out of heap space
-
- createTestTopic(topic, parallelism, 1);
-
- final TypeInformation<Tuple2<Long, byte[]>> longBytesInfo = TypeInfoParser.parse("Tuple2<Long, byte[]>");
-
- final TypeInformationSerializationSchema<Tuple2<Long, byte[]>> serSchema =
- new TypeInformationSerializationSchema<>(longBytesInfo, new ExecutionConfig());
-
- final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
- env.enableCheckpointing(100);
- env.setParallelism(parallelism);
-
- // add consuming topology:
- Properties consumerProps = new Properties();
- consumerProps.putAll(standardProps);
- consumerProps.setProperty("fetch.message.max.bytes", Integer.toString(1024 * 1024 * 14));
- consumerProps.setProperty("max.partition.fetch.bytes", Integer.toString(1024 * 1024 * 14)); // for the new fetcher
- consumerProps.setProperty("queued.max.message.chunks", "1");
- consumerProps.putAll(secureProps);
-
- FlinkKafkaConsumerBase<Tuple2<Long, byte[]>> source = kafkaServer.getConsumer(topic, serSchema, consumerProps);
- DataStreamSource<Tuple2<Long, byte[]>> consuming = env.addSource(source);
-
- consuming.addSink(new SinkFunction<Tuple2<Long, byte[]>>() {
-
- private int elCnt = 0;
-
- @Override
- public void invoke(Tuple2<Long, byte[]> value) throws Exception {
- elCnt++;
- if (value.f0 == -1) {
- // we should have seen 11 elements now.
- if (elCnt == 11) {
- throw new SuccessException();
- } else {
- throw new RuntimeException("There have been "+elCnt+" elements");
- }
- }
- if (elCnt > 10) {
- throw new RuntimeException("More than 10 elements seen: "+elCnt);
- }
- }
- });
-
- // add producing topology
- Properties producerProps = new Properties();
- producerProps.setProperty("max.request.size", Integer.toString(1024 * 1024 * 15));
- producerProps.setProperty("retries", "3");
- producerProps.putAll(secureProps);
- producerProps.setProperty(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, brokerConnectionStrings);
-
- DataStream<Tuple2<Long, byte[]>> stream = env.addSource(new RichSourceFunction<Tuple2<Long, byte[]>>() {
-
- private boolean running;
-
- @Override
- public void open(Configuration parameters) throws Exception {
- super.open(parameters);
- running = true;
- }
-
- @Override
- public void run(SourceContext<Tuple2<Long, byte[]>> ctx) throws Exception {
- Random rnd = new Random();
- long cnt = 0;
- int sevenMb = 1024 * 1024 * 7;
-
- while (running) {
- byte[] wl = new byte[sevenMb + rnd.nextInt(sevenMb)];
- ctx.collect(new Tuple2<>(cnt++, wl));
-
- Thread.sleep(100);
-
- if (cnt == 10) {
- // signal end
- ctx.collect(new Tuple2<>(-1L, new byte[]{1}));
- break;
- }
- }
- }
-
- @Override
- public void cancel() {
- running = false;
- }
- });
-
- kafkaServer.produceIntoKafka(stream, topic, new KeyedSerializationSchemaWrapper<>(serSchema), producerProps, null);
-
- tryExecute(env, "big topology test");
- deleteTestTopic(topic);
- }
-
-
- public void runBrokerFailureTest() throws Exception {
- final String topic = "brokerFailureTestTopic";
-
- final int parallelism = 2;
- final int numElementsPerPartition = 1000;
- final int totalElements = parallelism * numElementsPerPartition;
- final int failAfterElements = numElementsPerPartition / 3;
-
-
- createTestTopic(topic, parallelism, 2);
-
- DataGenerators.generateRandomizedIntegerSequence(
- StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort),
- kafkaServer,
- topic, parallelism, numElementsPerPartition, true);
-
- // find leader to shut down
- int leaderId = kafkaServer.getLeaderToShutDown(topic);
-
- LOG.info("Leader to shutdown {}", leaderId);
-
-
- // run the topology (the consumers must handle the failures)
-
- DeserializationSchema<Integer> schema =
- new TypeInformationSerializationSchema<>(BasicTypeInfo.INT_TYPE_INFO, new ExecutionConfig());
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(parallelism);
- env.enableCheckpointing(500);
- env.setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- FlinkKafkaConsumerBase<Integer> kafkaSource = kafkaServer.getConsumer(topic, schema, props);
-
- env
- .addSource(kafkaSource)
- .map(new PartitionValidatingMapper(parallelism, 1))
- .map(new BrokerKillingMapper<Integer>(leaderId, failAfterElements))
- .addSink(new ValidatingExactlyOnceSink(totalElements)).setParallelism(1);
-
- BrokerKillingMapper.killedLeaderBefore = false;
- tryExecute(env, "Broker failure once test");
-
- // start a new broker:
- kafkaServer.restartBroker(leaderId);
- }
-
- public void runKeyValueTest() throws Exception {
- final String topic = "keyvaluetest";
- createTestTopic(topic, 1, 1);
- final int ELEMENT_COUNT = 5000;
-
- // ----------- Write some data into Kafka -------------------
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(1);
- env.setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
-
- DataStream<Tuple2<Long, PojoValue>> kvStream = env.addSource(new SourceFunction<Tuple2<Long, PojoValue>>() {
- @Override
- public void run(SourceContext<Tuple2<Long, PojoValue>> ctx) throws Exception {
- Random rnd = new Random(1337);
- for (long i = 0; i < ELEMENT_COUNT; i++) {
- PojoValue pojo = new PojoValue();
- pojo.when = new Date(rnd.nextLong());
- pojo.lon = rnd.nextLong();
- pojo.lat = i;
- // make every second key null to ensure proper "null" serialization
- Long key = (i % 2 == 0) ? null : i;
- ctx.collect(new Tuple2<>(key, pojo));
- }
- }
- @Override
- public void cancel() {
- }
- });
-
- KeyedSerializationSchema<Tuple2<Long, PojoValue>> schema = new TypeInformationKeyValueSerializationSchema<>(Long.class, PojoValue.class, env.getConfig());
- Properties producerProperties = FlinkKafkaProducerBase.getPropertiesFromBrokerList(brokerConnectionStrings);
- producerProperties.setProperty("retries", "3");
- kafkaServer.produceIntoKafka(kvStream, topic, schema, producerProperties, null);
- env.execute("Write KV to Kafka");
-
- // ----------- Read the data again -------------------
-
- env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(1);
- env.setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
-
-
- KeyedDeserializationSchema<Tuple2<Long, PojoValue>> readSchema = new TypeInformationKeyValueSerializationSchema<>(Long.class, PojoValue.class, env.getConfig());
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- DataStream<Tuple2<Long, PojoValue>> fromKafka = env.addSource(kafkaServer.getConsumer(topic, readSchema, props));
- fromKafka.flatMap(new RichFlatMapFunction<Tuple2<Long,PojoValue>, Object>() {
- long counter = 0;
- @Override
- public void flatMap(Tuple2<Long, PojoValue> value, Collector<Object> out) throws Exception {
- // the elements should be in order.
- Assert.assertTrue("Wrong value " + value.f1.lat, value.f1.lat == counter );
- if (value.f1.lat % 2 == 0) {
- assertNull("key was not null", value.f0);
- } else {
- Assert.assertTrue("Wrong value " + value.f0, value.f0 == counter);
- }
- counter++;
- if (counter == ELEMENT_COUNT) {
- // we got the right number of elements
- throw new SuccessException();
- }
- }
- });
-
- tryExecute(env, "Read KV from Kafka");
-
- deleteTestTopic(topic);
- }
-
- public static class PojoValue {
- public Date when;
- public long lon;
- public long lat;
- public PojoValue() {}
- }
-
-
- /**
- * Test delete behavior and metrics for producer
- * @throws Exception
- */
- public void runAllDeletesTest() throws Exception {
- final String topic = "alldeletestest";
- createTestTopic(topic, 1, 1);
- final int ELEMENT_COUNT = 300;
-
- // ----------- Write some data into Kafka -------------------
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(1);
- env.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
-
- DataStream<Tuple2<byte[], PojoValue>> kvStream = env.addSource(new SourceFunction<Tuple2<byte[], PojoValue>>() {
- @Override
- public void run(SourceContext<Tuple2<byte[], PojoValue>> ctx) throws Exception {
- Random rnd = new Random(1337);
- for (long i = 0; i < ELEMENT_COUNT; i++) {
- final byte[] key = new byte[200];
- rnd.nextBytes(key);
- ctx.collect(new Tuple2<>(key, (PojoValue) null));
- }
- }
- @Override
- public void cancel() {
- }
- });
-
- TypeInformationKeyValueSerializationSchema<byte[], PojoValue> schema = new TypeInformationKeyValueSerializationSchema<>(byte[].class, PojoValue.class, env.getConfig());
-
- Properties producerProperties = FlinkKafkaProducerBase.getPropertiesFromBrokerList(brokerConnectionStrings);
- producerProperties.setProperty("retries", "3");
- producerProperties.putAll(secureProps);
- kafkaServer.produceIntoKafka(kvStream, topic, schema, producerProperties, null);
-
- env.execute("Write deletes to Kafka");
-
- // ----------- Read the data again -------------------
-
- env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setParallelism(1);
- env.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
- DataStream<Tuple2<byte[], PojoValue>> fromKafka = env.addSource(kafkaServer.getConsumer(topic, schema, props));
-
- fromKafka.flatMap(new RichFlatMapFunction<Tuple2<byte[], PojoValue>, Object>() {
- long counter = 0;
- @Override
- public void flatMap(Tuple2<byte[], PojoValue> value, Collector<Object> out) throws Exception {
- // ensure that deleted messages are passed as nulls
- assertNull(value.f1);
- counter++;
- if (counter == ELEMENT_COUNT) {
- // we got the right number of elements
- throw new SuccessException();
- }
- }
- });
-
- tryExecute(env, "Read deletes from Kafka");
-
- deleteTestTopic(topic);
- }
-
- /**
- * Test that ensures that DeserializationSchema.isEndOfStream() is properly evaluated.
- *
- * @throws Exception
- */
- public void runEndOfStreamTest() throws Exception {
-
- final int ELEMENT_COUNT = 300;
- final String topic = writeSequence("testEndOfStream", ELEMENT_COUNT, 1, 1);
-
- // read using custom schema
- final StreamExecutionEnvironment env1 = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env1.setParallelism(1);
- env1.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env1.getConfig().disableSysoutLogging();
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
-
- DataStream<Tuple2<Integer, Integer>> fromKafka = env1.addSource(kafkaServer.getConsumer(topic, new FixedNumberDeserializationSchema(ELEMENT_COUNT), props));
- fromKafka.flatMap(new FlatMapFunction<Tuple2<Integer,Integer>, Void>() {
- @Override
- public void flatMap(Tuple2<Integer, Integer> value, Collector<Void> out) throws Exception {
- // noop ;)
- }
- });
-
- JobExecutionResult result = tryExecute(env1, "Consume " + ELEMENT_COUNT + " elements from Kafka");
-
- deleteTestTopic(topic);
- }
-
- /**
- * Test metrics reporting for consumer
- *
- * @throws Exception
- */
- public void runMetricsTest() throws Throwable {
-
- // create a stream with 5 topics
- final String topic = "metricsStream";
- createTestTopic(topic, 5, 1);
-
- final Tuple1<Throwable> error = new Tuple1<>(null);
- Runnable job = new Runnable() {
- @Override
- public void run() {
- try {
- // start job writing & reading data.
- final StreamExecutionEnvironment env1 = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env1.setParallelism(1);
- env1.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- env1.getConfig().disableSysoutLogging();
- env1.disableOperatorChaining(); // let the source read everything into the network buffers
-
- Properties props = new Properties();
- props.putAll(standardProps);
- props.putAll(secureProps);
-
- TypeInformationSerializationSchema<Tuple2<Integer, Integer>> schema = new TypeInformationSerializationSchema<>(TypeInfoParser.<Tuple2<Integer, Integer>>parse("Tuple2<Integer, Integer>"), env1.getConfig());
- DataStream<Tuple2<Integer, Integer>> fromKafka = env1.addSource(kafkaServer.getConsumer(topic, schema, standardProps));
- fromKafka.flatMap(new FlatMapFunction<Tuple2<Integer, Integer>, Void>() {
- @Override
- public void flatMap(Tuple2<Integer, Integer> value, Collector<Void> out) throws Exception {// no op
- }
- });
-
- DataStream<Tuple2<Integer, Integer>> fromGen = env1.addSource(new RichSourceFunction<Tuple2<Integer, Integer>>() {
- boolean running = true;
-
- @Override
- public void run(SourceContext<Tuple2<Integer, Integer>> ctx) throws Exception {
- int i = 0;
- while (running) {
- ctx.collect(Tuple2.of(i++, getRuntimeContext().getIndexOfThisSubtask()));
- Thread.sleep(1);
- }
- }
-
- @Override
- public void cancel() {
- running = false;
- }
- });
-
- kafkaServer.produceIntoKafka(fromGen, topic, new KeyedSerializationSchemaWrapper<>(schema), standardProps, null);
-
- env1.execute("Metrics test job");
- } catch(Throwable t) {
- LOG.warn("Got exception during execution", t);
- if(!(t.getCause() instanceof JobCancellationException)) { // we'll cancel the job
- error.f0 = t;
- }
- }
- }
- };
- Thread jobThread = new Thread(job);
- jobThread.start();
-
- try {
- // connect to JMX
- MBeanServer mBeanServer = ManagementFactory.getPlatformMBeanServer();
- // wait until we've found all 5 offset metrics
- Set<ObjectName> offsetMetrics = mBeanServer.queryNames(new ObjectName("*current-offsets*:*"), null);
- while (offsetMetrics.size() < 5) { // test will time out if metrics are not properly working
- if (error.f0 != null) {
- // fail test early
- throw error.f0;
- }
- offsetMetrics = mBeanServer.queryNames(new ObjectName("*current-offsets*:*"), null);
- Thread.sleep(50);
- }
- Assert.assertEquals(5, offsetMetrics.size());
- // we can't rely on the consumer to have touched all the partitions already
- // that's why we'll wait until all five partitions have a positive offset.
- // The test will fail if we never meet the condition
- while (true) {
- int numPosOffsets = 0;
- // check that offsets are correctly reported
- for (ObjectName object : offsetMetrics) {
- Object offset = mBeanServer.getAttribute(object, "Value");
- if((long) offset >= 0) {
- numPosOffsets++;
- }
- }
- if (numPosOffsets == 5) {
- break;
- }
- // wait for the consumer to consume on all partitions
- Thread.sleep(50);
- }
-
- // check if producer metrics are also available.
- Set<ObjectName> producerMetrics = mBeanServer.queryNames(new ObjectName("*KafkaProducer*:*"), null);
- Assert.assertTrue("No producer metrics found", producerMetrics.size() > 30);
-
-
- LOG.info("Found all JMX metrics. Cancelling job.");
- } finally {
- // cancel
- JobManagerCommunicationUtils.cancelCurrentJob(flink.getLeaderGateway(timeout));
- }
-
- while (jobThread.isAlive()) {
- Thread.sleep(50);
- }
- if (error.f0 != null) {
- throw error.f0;
- }
-
- deleteTestTopic(topic);
- }
-
-
- public static class FixedNumberDeserializationSchema implements DeserializationSchema<Tuple2<Integer, Integer>> {
-
- final int finalCount;
- int count = 0;
-
- TypeInformation<Tuple2<Integer, Integer>> ti = TypeInfoParser.parse("Tuple2<Integer, Integer>");
- TypeSerializer<Tuple2<Integer, Integer>> ser = ti.createSerializer(new ExecutionConfig());
-
- public FixedNumberDeserializationSchema(int finalCount) {
- this.finalCount = finalCount;
- }
-
- @Override
- public Tuple2<Integer, Integer> deserialize(byte[] message) throws IOException {
- DataInputView in = new DataInputViewStreamWrapper(new ByteArrayInputStream(message));
- return ser.deserialize(in);
- }
-
- @Override
- public boolean isEndOfStream(Tuple2<Integer, Integer> nextElement) {
- return ++count >= finalCount;
- }
-
- @Override
- public TypeInformation<Tuple2<Integer, Integer>> getProducedType() {
- return ti;
- }
- }
-
-
- // ------------------------------------------------------------------------
- // Reading writing test data sets
- // ------------------------------------------------------------------------
-
- /**
- * Runs a job using the provided environment to read a sequence of records from a single Kafka topic.
- * The method allows to individually specify the expected starting offset and total read value count of each partition.
- * The job will be considered successful only if all partition read results match the start offset and value count criteria.
- */
- protected void readSequence(StreamExecutionEnvironment env, Properties cc,
- final String topicName,
- final Map<Integer, Tuple2<Integer, Integer>> partitionsToValuesCountAndStartOffset) throws Exception {
- final int sourceParallelism = partitionsToValuesCountAndStartOffset.keySet().size();
-
- int finalCountTmp = 0;
- for (Map.Entry<Integer, Tuple2<Integer, Integer>> valuesCountAndStartOffset : partitionsToValuesCountAndStartOffset.entrySet()) {
- finalCountTmp += valuesCountAndStartOffset.getValue().f0;
- }
- final int finalCount = finalCountTmp;
-
- final TypeInformation<Tuple2<Integer, Integer>> intIntTupleType = TypeInfoParser.parse("Tuple2<Integer, Integer>");
-
- final TypeInformationSerializationSchema<Tuple2<Integer, Integer>> deser =
- new TypeInformationSerializationSchema<>(intIntTupleType, env.getConfig());
-
- // create the consumer
- cc.putAll(secureProps);
- FlinkKafkaConsumerBase<Tuple2<Integer, Integer>> consumer = kafkaServer.getConsumer(topicName, deser, cc);
-
- DataStream<Tuple2<Integer, Integer>> source = env
- .addSource(consumer).setParallelism(sourceParallelism)
- .map(new ThrottledMapper<Tuple2<Integer, Integer>>(20)).setParallelism(sourceParallelism);
-
- // verify data
- source.flatMap(new RichFlatMapFunction<Tuple2<Integer, Integer>, Integer>() {
-
- private HashMap<Integer, BitSet> partitionsToValueCheck;
- private int count = 0;
-
- @Override
- public void open(Configuration parameters) throws Exception {
- partitionsToValueCheck = new HashMap<>();
- for (Integer partition : partitionsToValuesCountAndStartOffset.keySet()) {
- partitionsToValueCheck.put(partition, new BitSet());
- }
- }
-
- @Override
- public void flatMap(Tuple2<Integer, Integer> value, Collector<Integer> out) throws Exception {
- int partition = value.f0;
- int val = value.f1;
-
- BitSet bitSet = partitionsToValueCheck.get(partition);
- if (bitSet == null) {
- throw new RuntimeException("Got a record from an unknown partition");
- } else {
- bitSet.set(val - partitionsToValuesCountAndStartOffset.get(partition).f1);
- }
-
- count++;
-
- LOG.info("Received message {}, total {} messages", value, count);
-
- // verify if we've seen everything
- if (count == finalCount) {
- for (Map.Entry<Integer, BitSet> partitionsToValueCheck : this.partitionsToValueCheck.entrySet()) {
- BitSet check = partitionsToValueCheck.getValue();
- int expectedValueCount = partitionsToValuesCountAndStartOffset.get(partitionsToValueCheck.getKey()).f0;
-
- if (check.cardinality() != expectedValueCount) {
- throw new RuntimeException("Expected cardinality to be " + expectedValueCount +
- ", but was " + check.cardinality());
- } else if (check.nextClearBit(0) != expectedValueCount) {
- throw new RuntimeException("Expected next clear bit to be " + expectedValueCount +
- ", but was " + check.cardinality());
- }
- }
-
- // test has passed
- throw new SuccessException();
- }
- }
-
- }).setParallelism(1);
-
- tryExecute(env, "Read data from Kafka");
-
- LOG.info("Successfully read sequence for verification");
- }
-
- /**
- * Variant of {@link KafkaConsumerTestBase#readSequence(StreamExecutionEnvironment, Properties, String, Map)} to
- * expect reading from the same start offset and the same value count for all partitions of a single Kafka topic.
- */
- protected void readSequence(StreamExecutionEnvironment env, Properties cc,
- final int sourceParallelism,
- final String topicName,
- final int valuesCount, final int startFrom) throws Exception {
- HashMap<Integer, Tuple2<Integer, Integer>> partitionsToValuesCountAndStartOffset = new HashMap<>();
- for (int i = 0; i < sourceParallelism; i++) {
- partitionsToValuesCountAndStartOffset.put(i, new Tuple2<>(valuesCount, startFrom));
- }
- readSequence(env, cc, topicName, partitionsToValuesCountAndStartOffset);
- }
-
- protected String writeSequence(
- String baseTopicName,
- final int numElements,
- final int parallelism,
- final int replicationFactor) throws Exception
- {
- LOG.info("\n===================================\n" +
- "== Writing sequence of " + numElements + " into " + baseTopicName + " with p=" + parallelism + "\n" +
- "===================================");
-
- final TypeInformation<Tuple2<Integer, Integer>> resultType =
- TypeInformation.of(new TypeHint<Tuple2<Integer, Integer>>() {});
-
- final KeyedSerializationSchema<Tuple2<Integer, Integer>> serSchema =
- new KeyedSerializationSchemaWrapper<>(
- new TypeInformationSerializationSchema<>(resultType, new ExecutionConfig()));
-
- final KeyedDeserializationSchema<Tuple2<Integer, Integer>> deserSchema =
- new KeyedDeserializationSchemaWrapper<>(
- new TypeInformationSerializationSchema<>(resultType, new ExecutionConfig()));
-
- final int maxNumAttempts = 10;
-
- for (int attempt = 1; attempt <= maxNumAttempts; attempt++) {
-
- final String topicName = baseTopicName + '-' + attempt;
-
- LOG.info("Writing attempt #1");
-
- // -------- Write the Sequence --------
-
- createTestTopic(topicName, parallelism, replicationFactor);
-
- StreamExecutionEnvironment writeEnv = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- writeEnv.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- writeEnv.getConfig().disableSysoutLogging();
-
- DataStream<Tuple2<Integer, Integer>> stream = writeEnv.addSource(new RichParallelSourceFunction<Tuple2<Integer, Integer>>() {
-
- private boolean running = true;
-
- @Override
- public void run(SourceContext<Tuple2<Integer, Integer>> ctx) throws Exception {
- int cnt = 0;
- int partition = getRuntimeContext().getIndexOfThisSubtask();
-
- while (running && cnt < numElements) {
- ctx.collect(new Tuple2<>(partition, cnt));
- cnt++;
- }
- }
-
- @Override
- public void cancel() {
- running = false;
- }
- }).setParallelism(parallelism);
-
- // the producer must not produce duplicates
- Properties producerProperties = FlinkKafkaProducerBase.getPropertiesFromBrokerList(brokerConnectionStrings);
- producerProperties.setProperty("retries", "0");
- producerProperties.putAll(secureProps);
-
- kafkaServer.produceIntoKafka(stream, topicName, serSchema, producerProperties, new Tuple2Partitioner(parallelism))
- .setParallelism(parallelism);
-
- try {
- writeEnv.execute("Write sequence");
- }
- catch (Exception e) {
- LOG.error("Write attempt failed, trying again", e);
- deleteTestTopic(topicName);
- JobManagerCommunicationUtils.waitUntilNoJobIsRunning(flink.getLeaderGateway(timeout));
- continue;
- }
-
- LOG.info("Finished writing sequence");
-
- // -------- Validate the Sequence --------
-
- // we need to validate the sequence, because kafka's producers are not exactly once
- LOG.info("Validating sequence");
-
- JobManagerCommunicationUtils.waitUntilNoJobIsRunning(flink.getLeaderGateway(timeout));
-
- final StreamExecutionEnvironment readEnv = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- readEnv.getConfig().setRestartStrategy(RestartStrategies.noRestart());
- readEnv.getConfig().disableSysoutLogging();
- readEnv.setParallelism(parallelism);
-
- Properties readProps = (Properties) standardProps.clone();
- readProps.setProperty("group.id", "flink-tests-validator");
- readProps.putAll(secureProps);
- FlinkKafkaConsumerBase<Tuple2<Integer, Integer>> consumer = kafkaServer.getConsumer(topicName, deserSchema, readProps);
-
- readEnv
- .addSource(consumer)
- .map(new RichMapFunction<Tuple2<Integer, Integer>, Tuple2<Integer, Integer>>() {
-
- private final int totalCount = parallelism * numElements;
- private int count = 0;
-
- @Override
- public Tuple2<Integer, Integer> map(Tuple2<Integer, Integer> value) throws Exception {
- if (++count == totalCount) {
- throw new SuccessException();
- } else {
- return value;
- }
- }
- }).setParallelism(1)
- .addSink(new DiscardingSink<Tuple2<Integer, Integer>>()).setParallelism(1);
-
- final AtomicReference<Throwable> errorRef = new AtomicReference<>();
-
- Thread runner = new Thread() {
- @Override
- public void run() {
- try {
- tryExecute(readEnv, "sequence validation");
- } catch (Throwable t) {
- errorRef.set(t);
- }
- }
- };
- runner.start();
-
- final long deadline = System.currentTimeMillis() + 10000;
- long delay;
- while (runner.isAlive() && (delay = deadline - System.currentTimeMillis()) > 0) {
- runner.join(delay);
- }
-
- boolean success;
-
- if (runner.isAlive()) {
- // did not finish in time, maybe the producer dropped one or more records and
- // the validation did not reach the exit point
- success = false;
- JobManagerCommunicationUtils.cancelCurrentJob(flink.getLeaderGateway(timeout));
- }
- else {
- Throwable error = errorRef.get();
- if (error != null) {
- success = false;
- LOG.info("Attempt " + attempt + " failed with exception", error);
- }
- else {
- success = true;
- }
- }
-
- JobManagerCommunicationUtils.waitUntilNoJobIsRunning(flink.getLeaderGateway(timeout));
-
- if (success) {
- // everything is good!
- return topicName;
- }
- else {
- deleteTestTopic(topicName);
- // fall through the loop
- }
- }
-
- throw new Exception("Could not write a valid sequence to Kafka after " + maxNumAttempts + " attempts");
- }
-
- // ------------------------------------------------------------------------
- // Debugging utilities
- // ------------------------------------------------------------------------
-
- /**
- * Read topic to list, only using Kafka code.
- */
- private static List<MessageAndMetadata<byte[], byte[]>> readTopicToList(String topicName, ConsumerConfig config, final int stopAfter) {
- ConsumerConnector consumerConnector = Consumer.createJavaConsumerConnector(config);
- // we request only one stream per consumer instance. Kafka will make sure that each consumer group
- // will see each message only once.
- Map<String,Integer> topicCountMap = Collections.singletonMap(topicName, 1);
- Map<String, List<KafkaStream<byte[], byte[]>>> streams = consumerConnector.createMessageStreams(topicCountMap);
- if (streams.size() != 1) {
- throw new RuntimeException("Expected only one message stream but got "+streams.size());
- }
- List<KafkaStream<byte[], byte[]>> kafkaStreams = streams.get(topicName);
- if (kafkaStreams == null) {
- throw new RuntimeException("Requested stream not available. Available streams: "+streams.toString());
- }
- if (kafkaStreams.size() != 1) {
- throw new RuntimeException("Requested 1 stream from Kafka, bot got "+kafkaStreams.size()+" streams");
- }
- LOG.info("Opening Consumer instance for topic '{}' on group '{}'", topicName, config.groupId());
- ConsumerIterator<byte[], byte[]> iteratorToRead = kafkaStreams.get(0).iterator();
-
- List<MessageAndMetadata<byte[], byte[]>> result = new ArrayList<>();
- int read = 0;
- while(iteratorToRead.hasNext()) {
- read++;
- result.add(iteratorToRead.next());
- if (read == stopAfter) {
- LOG.info("Read "+read+" elements");
- return result;
- }
- }
- return result;
- }
-
- private static void printTopic(String topicName, ConsumerConfig config,
- DeserializationSchema<?> deserializationSchema,
- int stopAfter) throws IOException {
-
- List<MessageAndMetadata<byte[], byte[]>> contents = readTopicToList(topicName, config, stopAfter);
- LOG.info("Printing contents of topic {} in consumer grouo {}", topicName, config.groupId());
-
- for (MessageAndMetadata<byte[], byte[]> message: contents) {
- Object out = deserializationSchema.deserialize(message.message());
- LOG.info("Message: partition: {} offset: {} msg: {}", message.partition(), message.offset(), out.toString());
- }
- }
-
- private static void printTopic(String topicName, int elements,DeserializationSchema<?> deserializer)
- throws IOException
- {
- // write the sequence to log for debugging purposes
- Properties newProps = new Properties(standardProps);
- newProps.setProperty("group.id", "topic-printer"+ UUID.randomUUID().toString());
- newProps.setProperty("auto.offset.reset", "smallest");
- newProps.setProperty("zookeeper.connect", standardProps.getProperty("zookeeper.connect"));
- newProps.putAll(secureProps);
-
- ConsumerConfig printerConfig = new ConsumerConfig(newProps);
- printTopic(topicName, printerConfig, deserializer, elements);
- }
-
-
- public static class BrokerKillingMapper<T> extends RichMapFunction<T,T>
- implements Checkpointed<Integer>, CheckpointListener {
-
- private static final long serialVersionUID = 6334389850158707313L;
-
- public static volatile boolean killedLeaderBefore;
- public static volatile boolean hasBeenCheckpointedBeforeFailure;
-
- private final int shutdownBrokerId;
- private final int failCount;
- private int numElementsTotal;
-
- private boolean failer;
- private boolean hasBeenCheckpointed;
-
-
- public BrokerKillingMapper(int shutdownBrokerId, int failCount) {
- this.shutdownBrokerId = shutdownBrokerId;
- this.failCount = failCount;
- }
-
- @Override
- public void open(Configuration parameters) {
- failer = getRuntimeContext().getIndexOfThisSubtask() == 0;
- }
-
- @Override
- public T map(T value) throws Exception {
- numElementsTotal++;
-
- if (!killedLeaderBefore) {
- Thread.sleep(10);
-
- if (failer && numElementsTotal >= failCount) {
- // shut down a Kafka broker
- KafkaServer toShutDown = null;
- for (KafkaServer server : kafkaServer.getBrokers()) {
-
- if (kafkaServer.getBrokerId(server) == shutdownBrokerId) {
- toShutDown = server;
- break;
- }
- }
-
- if (toShutDown == null) {
- StringBuilder listOfBrokers = new StringBuilder();
- for (KafkaServer server : kafkaServer.getBrokers()) {
- listOfBrokers.append(kafkaServer.getBrokerId(server));
- listOfBrokers.append(" ; ");
- }
-
- throw new Exception("Cannot find broker to shut down: " + shutdownBrokerId
- + " ; available brokers: " + listOfBrokers.toString());
- }
- else {
- hasBeenCheckpointedBeforeFailure = hasBeenCheckpointed;
- killedLeaderBefore = true;
- toShutDown.shutdown();
- }
- }
- }
- return value;
- }
-
- @Override
- public void notifyCheckpointComplete(long checkpointId) {
- hasBeenCheckpointed = true;
- }
-
- @Override
- public Integer snapshotState(long checkpointId, long checkpointTimestamp) {
- return numElementsTotal;
- }
-
- @Override
- public void restoreState(Integer state) {
- this.numElementsTotal = state;
- }
- }
-}
http://git-wip-us.apache.org/repos/asf/flink/blob/de4fe3b7/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaProducerTestBase.java
----------------------------------------------------------------------
diff --git a/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaProducerTestBase.java b/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaProducerTestBase.java
deleted file mode 100644
index c925c8f..0000000
--- a/flink-streaming-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaProducerTestBase.java
+++ /dev/null
@@ -1,193 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.flink.streaming.connectors.kafka;
-
-import org.apache.flink.api.common.functions.RichMapFunction;
-import org.apache.flink.api.common.restartstrategy.RestartStrategies;
-import org.apache.flink.api.common.typeinfo.TypeInformation;
-import org.apache.flink.api.java.tuple.Tuple2;
-import org.apache.flink.api.java.typeutils.TypeInfoParser;
-import org.apache.flink.streaming.api.datastream.DataStream;
-import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
-import org.apache.flink.streaming.api.functions.sink.SinkFunction;
-import org.apache.flink.streaming.api.functions.source.SourceFunction;
-import org.apache.flink.streaming.connectors.kafka.partitioner.KafkaPartitioner;
-import org.apache.flink.streaming.util.serialization.KeyedSerializationSchemaWrapper;
-import org.apache.flink.streaming.util.serialization.TypeInformationSerializationSchema;
-import org.apache.flink.test.util.SuccessException;
-
-
-import java.io.Serializable;
-import java.util.Properties;
-
-import static org.apache.flink.test.util.TestUtils.tryExecute;
-import static org.junit.Assert.assertEquals;
-import static org.junit.Assert.fail;
-
-@SuppressWarnings("serial")
-public abstract class KafkaProducerTestBase extends KafkaTestBase {
-
-
- /**
- *
- * <pre>
- * +------> (sink) --+--> [KAFKA-1] --> (source) -> (map) --+
- * / | \
- * / | \
- * (source) ----------> (sink) --+--> [KAFKA-2] --> (source) -> (map) -----+-> (sink)
- * \ | /
- * \ | /
- * +------> (sink) --+--> [KAFKA-3] --> (source) -> (map) --+
- * </pre>
- *
- * The mapper validates that the values come consistently from the correct Kafka partition.
- *
- * The final sink validates that there are no duplicates and that all partitions are present.
- */
- public void runCustomPartitioningTest() {
- try {
- LOG.info("Starting KafkaProducerITCase.testCustomPartitioning()");
-
- final String topic = "customPartitioningTestTopic";
- final int parallelism = 3;
-
- createTestTopic(topic, parallelism, 1);
-
- TypeInformation<Tuple2<Long, String>> longStringInfo = TypeInfoParser.parse("Tuple2<Long, String>");
-
- StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("localhost", flinkPort);
- env.setRestartStrategy(RestartStrategies.noRestart());
- env.getConfig().disableSysoutLogging();
-
- TypeInformationSerializationSchema<Tuple2<Long, String>> serSchema =
- new TypeInformationSerializationSchema<>(longStringInfo, env.getConfig());
-
- TypeInformationSerializationSchema<Tuple2<Long, String>> deserSchema =
- new TypeInformationSerializationSchema<>(longStringInfo, env.getConfig());
-
- // ------ producing topology ---------
-
- // source has DOP 1 to make sure it generates no duplicates
- DataStream<Tuple2<Long, String>> stream = env.addSource(new SourceFunction<Tuple2<Long, String>>() {
-
- private boolean running = true;
-
- @Override
- public void run(SourceContext<Tuple2<Long, String>> ctx) throws Exception {
- long cnt = 0;
- while (running) {
- ctx.collect(new Tuple2<Long, String>(cnt, "kafka-" + cnt));
- cnt++;
- }
- }
-
- @Override
- public void cancel() {
- running = false;
- }
- })
- .setParallelism(1);
-
- Properties props = new Properties();
- props.putAll(FlinkKafkaProducerBase.getPropertiesFromBrokerList(brokerConnectionStrings));
- props.putAll(secureProps);
-
- // sink partitions into
- kafkaServer.produceIntoKafka(stream, topic,
- new KeyedSerializationSchemaWrapper<>(serSchema),
- props,
- new CustomPartitioner(parallelism)).setParallelism(parallelism);
-
- // ------ consuming topology ---------
-
- Properties consumerProps = new Properties();
- consumerProps.putAll(standardProps);
- consumerProps.putAll(secureProps);
- FlinkKafkaConsumerBase<Tuple2<Long, String>> source = kafkaServer.getConsumer(topic, deserSchema, consumerProps);
-
- env.addSource(source).setParallelism(parallelism)
-
- // mapper that validates partitioning and maps to partition
- .map(new RichMapFunction<Tuple2<Long, String>, Integer>() {
-
- private int ourPartition = -1;
- @Override
- public Integer map(Tuple2<Long, String> value) {
- int partition = value.f0.intValue() % parallelism;
- if (ourPartition != -1) {
- assertEquals("inconsistent partitioning", ourPartition, partition);
- } else {
- ourPartition = partition;
- }
- return partition;
- }
- }).setParallelism(parallelism)
-
- .addSink(new SinkFunction<Integer>() {
-
- private int[] valuesPerPartition = new int[parallelism];
-
- @Override
- public void invoke(Integer value) throws Exception {
- valuesPerPartition[value]++;
-
- boolean missing = false;
- for (int i : valuesPerPartition) {
- if (i < 100) {
- missing = true;
- break;
- }
- }
- if (!missing) {
- throw new SuccessException();
- }
- }
- }).setParallelism(1);
-
- tryExecute(env, "custom partitioning test");
-
- deleteTestTopic(topic);
-
- LOG.info("Finished KafkaProducerITCase.testCustomPartitioning()");
- }
- catch (Exception e) {
- e.printStackTrace();
- fail(e.getMessage());
- }
- }
-
- // ------------------------------------------------------------------------
-
- public static class CustomPartitioner extends KafkaPartitioner<Tuple2<Long, String>> implements Serializable {
-
- private final int expectedPartitions;
-
- public CustomPartitioner(int expectedPartitions) {
- this.expectedPartitions = expectedPartitions;
- }
-
-
- @Override
- public int partition(Tuple2<Long, String> next, byte[] serializedKey, byte[] serializedValue, int numPartitions) {
- assertEquals(expectedPartitions, numPartitions);
-
- return (int) (next.f0 % numPartitions);
- }
- }
-}