Java Consumer.createJavaConsumerConnector方法代码示例

import kafka.consumer.Consumer; //导入方法依赖的package包/类
@Override
public ConsumerConnector newConsumerConnector(String name, ConsumerConfig configOverrides) {

    Properties mergedProps = new Properties();

    Map<String, String> config = configs.get(name);

    if (config != null) {
        mergedProps.putAll(config);
    }

    if (configOverrides != null) {
        mergedProps.putAll(configOverrides.createConsumerConfig());
    }

    return Consumer.createJavaConsumerConnector(new kafka.consumer.ConsumerConfig(mergedProps));
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
public void open(Map map, TopologyContext topologyContext, SpoutOutputCollector spoutOutputCollector) {
    _collector = spoutOutputCollector;
    Properties props = new Properties();
    props.put("zookeeper.connect", conf.get(OSMIngest.ZOOKEEPERS));
    props.put("group.id", groupId);
    props.put("zookeeper.sync.time.ms", "200");
    props.put("auto.commit.interval.ms", "1000");
    ConsumerConfig consumerConfig = new ConsumerConfig(props);
    ConsumerConnector consumer = Consumer.createJavaConsumerConnector(consumerConfig);
    Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
    topicCountMap.put(topic, 1);
    Map<String, List<KafkaStream<String, String>>> consumerMap = consumer.createMessageStreams(topicCountMap, new StringDecoder(new VerifiableProperties()), new StringDecoder(new VerifiableProperties()));
    List<KafkaStream<String, String>> streams = consumerMap.get(topic);
    KafkaStream<String, String> stream = null;
    if (streams.size() == 1) {
        stream = streams.get(0);
    } else {
        log.error("Streams should be of size 1");
    }
    kafkaIterator = stream.iterator();
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
/**
 * 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;
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
public KtGroup(Config config) {
	// Because we are not pushing names to zookeeper random names should be fine
	String groupId = config.getGroupId();
	if (groupId == null) {
		// default to a unique group id
		groupId = "Kt-" + UUID.randomUUID();
	}

	String offset = "largest";
	if (config.getLocation().equals("tail")) {
		offset = "smallest";
	}
	log.info("Starting consumer at '{}' offset", offset);
	consumer = Consumer.createJavaConsumerConnector(createConsumerConfig(config.getZookeeper(), groupId, offset));
	this.topic = config.getTopic();
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
public List<KafkaStream<byte[], byte[]>> createKafkaStream(
    String zookeeperConnectString,
    String topic,
    int partitions
) {
  //create consumer
  Properties consumerProps = new Properties();
  consumerProps.put("zookeeper.connect", zookeeperConnectString);
  consumerProps.put("group.id", "testClient");
  consumerProps.put("zookeeper.session.timeout.ms", "6000");
  consumerProps.put("zookeeper.sync.time.ms", "200");
  consumerProps.put("auto.commit.interval.ms", "1000");
  consumerProps.put("consumer.timeout.ms", "500");
  ConsumerConfig consumerConfig = new ConsumerConfig(consumerProps);
  ConsumerConnector consumer = Consumer.createJavaConsumerConnector(consumerConfig);
  Map<String, Integer> topicCountMap = new HashMap<>();
  topicCountMap.put(topic, partitions);
  Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumer.createMessageStreams(topicCountMap);
  return consumerMap.get(topic);
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
@Override
public CompletionService<Histogram> startConsumers() {
    final ConsumerConfig consumerConfig = new ConsumerConfig(props);

    consumerConnector = Consumer.createJavaConsumerConnector(consumerConfig);

    // Create message streams
    final Map<String, Integer> topicMap = new HashMap<>();
    topicMap.put(topic, numThreads);

    final Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumerConnector.createMessageStreams(topicMap);
    final List<KafkaStream<byte[], byte[]>> streams = consumerMap.get(topic);

    // Pass each stream to a consumer that will read from the stream in its own thread.
    for (final KafkaStream<byte[], byte[]> stream : streams) {
        executorCompletionService.submit(new BlockingKafkaMessageConsumer(stream));
    }

    return executorCompletionService;
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
@Bean
protected KafkaStream<String, float[]> kafkaStream() {

    final String topicName = retrieveTopicNameFromGatewayAddress(gatewayUrl());

    ConsumerConnector consumerConnector =
            Consumer.createJavaConsumerConnector(consumerConfig());
    Map<String, Integer> topicCounts = new HashMap<>();
    topicCounts.put(topicName, 1);
    VerifiableProperties emptyProps = new VerifiableProperties();
    StringDecoder keyDecoder = new StringDecoder(emptyProps);
    FeatureVectorDecoder valueDecoder = new FeatureVectorDecoder();
    Map<String, List<KafkaStream<String, float[]>>> streams =
            consumerConnector.createMessageStreams(topicCounts, keyDecoder, valueDecoder);
    List<KafkaStream<String, float[]>> streamsByTopic = streams.get(topicName);
    Preconditions.checkNotNull(streamsByTopic, String.format("Topic %s not found in streams map.", topicName));
    Preconditions.checkElementIndex(0, streamsByTopic.size(),
            String.format("List of streams of topic %s is empty.", topicName));
    return streamsByTopic.get(0);
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
public static List<KafkaStream<byte[], byte[]>> createKafkaStream(String zookeeperConnectString, String topic, int partitions) {
  //create consumer
  Properties consumerProps = new Properties();
  consumerProps.put("zookeeper.connect", zookeeperConnectString);
  consumerProps.put("group.id", "testClient");
  consumerProps.put("zookeeper.session.timeout.ms", "6000");
  consumerProps.put("zookeeper.sync.time.ms", "200");
  consumerProps.put("auto.commit.interval.ms", "1000");
  consumerProps.put("consumer.timeout.ms", "500");
  ConsumerConfig consumerConfig = new ConsumerConfig(consumerProps);
  ConsumerConnector consumer = Consumer.createJavaConsumerConnector(consumerConfig);
  Map<String, Integer> topicCountMap = new HashMap<>();
  topicCountMap.put(topic, partitions);
  Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumer.createMessageStreams(topicCountMap);
  return consumerMap.get(topic);

}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
/**
 * {@inheritDoc}
 */
@Override
public void initialize()
    throws StreamingException
{
    ConsumerConfig consumerConfig = new ConsumerConfig(kafkaProperties);
    consumerConnector = Consumer.createJavaConsumerConnector(consumerConfig);

    Map<String, Integer> topicCountMap = Maps.newHashMap();
    topicCountMap.put(topic, TOPIC_COUNT);

    Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap =
        consumerConnector.createMessageStreams(topicCountMap);
    KafkaStream<byte[], byte[]> stream = consumerMap.get(topic).get(0);
    consumerIterator = stream.iterator();
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
public static ConsumerConnector getConsumer(String groupId) {
	//加上线程名字的考虑是：保证每个线程只有一个Consumer，但是每个线程又可以有一个独立的Consumer，从而消费不同的partition
	String consumerKey = groupId + "|" + Thread.currentThread().getName();
	ConsumerConnector msgConnector = groupConsumers.get(consumerKey);
	if (msgConnector == null) {
		try {
			consumerLock.lock();
			msgConnector = groupConsumers.get(consumerKey);
			if (msgConnector == null) {
				msgConnector = Consumer.createJavaConsumerConnector(getConsumerRealConfig(groupId));
				groupConsumers.put(consumerKey, msgConnector);
			}
		} finally {
			consumerLock.unlock();
		}
	}

	return msgConnector;
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
@Override
public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {
  logger.info("Opened");
  this.collector = collector;
  logger.info(" topic = " + kafkaSpoutConfig.kafkaConsumerConfiguration.getTopic());
  this.spoutName = String.format("%s-%d", context.getThisComponentId(), context.getThisTaskId());

  Properties kafkaProperties =
      KafkaConsumerProperties.createKafkaProperties(kafkaSpoutConfig.kafkaConsumerConfiguration);
  // Have to use a different consumer.id for each spout so use the storm taskId. Otherwise,
  // zookeeper complains about a conflicted ephemeral node when there is more than one spout
  // reading from a topic
  kafkaProperties.setProperty("consumer.id", String.valueOf(context.getThisTaskId()));
  ConsumerConfig consumerConfig = new ConsumerConfig(kafkaProperties);
  this.consumerConnector = Consumer.createJavaConsumerConnector(consumerConfig);
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
KafkaConsumerSuite(String zkConnectString, String topic)
{
  _topic = topic;
  Properties consumeProps = new Properties();
  consumeProps.put("zookeeper.connect", zkConnectString);
  consumeProps.put("group.id", _topic+"-"+System.nanoTime());
  consumeProps.put("zookeeper.session.timeout.ms", "10000");
  consumeProps.put("zookeeper.sync.time.ms", "10000");
  consumeProps.put("auto.commit.interval.ms", "10000");
  consumeProps.put("_consumer.timeout.ms", "10000");

  _consumer = Consumer.createJavaConsumerConnector(new ConsumerConfig(consumeProps));

  Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap =
      _consumer.createMessageStreams(ImmutableMap.of(this._topic, 1));
  List<KafkaStream<byte[], byte[]>> streams = consumerMap.get(this._topic);
  _stream = streams.get(0);
  _iterator = _stream.iterator();
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
public MessageReader(SecorConfig config, OffsetTracker offsetTracker) throws
        UnknownHostException {
    mConfig = config;
    mOffsetTracker = offsetTracker;

    mConsumerConnector = Consumer.createJavaConsumerConnector(createConsumerConfig());

    if (!mConfig.getKafkaTopicBlacklist().isEmpty() && !mConfig.getKafkaTopicFilter().isEmpty()) {
        throw new RuntimeException("Topic filter and blacklist cannot be both specified.");
    }
    TopicFilter topicFilter = !mConfig.getKafkaTopicBlacklist().isEmpty()? new Blacklist(mConfig.getKafkaTopicBlacklist()):
            new Whitelist(mConfig.getKafkaTopicFilter());
    LOG.debug("Use TopicFilter {}({})", topicFilter.getClass(), topicFilter);
    List<KafkaStream<byte[], byte[]>> streams =
        mConsumerConnector.createMessageStreamsByFilter(topicFilter);
    KafkaStream<byte[], byte[]> stream = streams.get(0);
    mIterator = stream.iterator();
    mLastAccessTime = new HashMap<TopicPartition, Long>();
    StatsUtil.setLabel("secor.kafka.consumer.id", IdUtil.getConsumerId());
    mTopicPartitionForgetSeconds = mConfig.getTopicPartitionForgetSeconds();
    mCheckMessagesPerSecond = mConfig.getMessagesPerSecond() / mConfig.getConsumerThreads();
    mKafkaMessageTimestampFactory = new KafkaMessageTimestampFactory(mConfig.getKafkaMessageTimestampClass());
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
/**
 * 初始化Kafka消费者客户端, 并获取Topic对应的Stream
 */
private void openKafkaStream() {
	logger.info("开始初始化Kafka消费客户端");

	this.consumer = Consumer.createJavaConsumerConnector(getConsumerConfig());

	StringDecoder decoder = new StringDecoder(null);
	Map<String, Integer> topicCountMap = Maps.of(topic, 1);
	Map<String, List<KafkaStream<String, String>>> consumerMap = consumer.createMessageStreams(topicCountMap,
			decoder, decoder);

	List<KafkaStream<String, String>> streams = consumerMap.get(topic);
	this.stream = streams.get(0);

	Assert.notNull(stream);
}
 

import kafka.consumer.Consumer; //导入方法依赖的package包/类
/**
 * Create a Kafka consumer.
 */
@Override
public void open() {

    // these consumers use ZooKeeper for commit, offset and segment consumption tracking
    // TODO: consider using SimpleConsumer the same way the Hadoop consumer job does to avoid ZK dependency
    // TODO: use the task details from TopologyContext in the normal open method
    ConsumerConfig consumerConfig = new ConsumerConfig(kafkaProperties);
    consumerConnector = Consumer.createJavaConsumerConnector(consumerConfig);

    // consumer with just one thread since the real parallelism is handled by Storm already
    Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
    topicCountMap.put(topic, new Integer(1));

    Map<String, List<KafkaMessageStream>> consumerMap = consumerConnector.createMessageStreams(topicCountMap);
    KafkaMessageStream stream = consumerMap.get(topic).get(0);

    consumerIterator = stream.iterator();
}