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Kafka - 消费接口分析

更新时间:2022-09-15 17:14:35

1.概述

  在 Kafka 中,官方对外提供了两种消费 API,一种是高等级消费 API,另一种是低等级的消费 API。在 《高级消费 API》一文中,介绍了其高级消费的 API 实现。今天给大家介绍另一种消费 API。

2.内容

  在使用过 Kafka 的高级消费 API 后,我们知道它是一种高度抽象的消费 API,使用起来简单,方便,但是对于某些特殊的需求我们可能要用到第二种更加底层的 API。那么,我们首先需要知道低级消费 API 的作用。它能帮助我们去做那些事情:

  • 一个消息进行多次读取
  • 在处理过程中只消费 Partition 其中的某一部分消息
  • 添加事物管理机制以保证消息仅被处理一次

  当然,在使用的过程当中也是有些弊端的,其内容如下:

  • 必须在程序中跟踪 Offset 的值
  • 必须找出指定的 Topic Partition 中的 Lead Broker
  • 必须处理 Broker 的变动

  使用其 API 的思路步骤如下所示:

  • 从所有处于 Active 状态的 Broker 中找出哪个是指定 Topic Partition 中的 Lead Broker
  • 找出指定 Topic Partition 中的所有备份 Broker
  • 构造请求
  • 发送请求并查询数据
  • 处理 Leader Broker 的变动

3.代码实现

3.1 Java Project

  若是使用 Java Project 工程去实现该部分代码,需要添加相关以来 JAR 文件,其内容包含如下:

  • scala-xml_${version}-${version}.jar
  • scala-library-${version}.jar
  • metrics-core-${version}.jar
  • kafka-client-${version}.jar
  • kafka_${version}-${version}.jar

  针对 Java Project 工程,需要自己筛选 JAR 去添加。保证代码的顺利执行。

3.2 Maven Project

  对 Maven 工程,在 pom.xml 文件中添加相应的依赖信息即可,简单方便。让 Maven 去管理相应的依赖 JAR 文件。内容如下所示:

Kafka - 消费接口分析
<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka_2.11</artifactId>
    <version>0.8.2.1</version>
    <exclusions>
        <exclusion>
            <groupId>org.apache.zookeeper</groupId>
            <artifactId>zookeeper</artifactId>
    </exclusion>
    <exclusion>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
    </exclusion>
    </exclusions>
</dependency>
Kafka - 消费接口分析

  这样在 Maven 工程中相应的依赖 JAR 文件就添加完成了。

3.3 代码实现

  在低级消费 API 中,实现代码如下所示:

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/**
 * @Date Mar 2, 2016
 *
 * @Author dengjie
 *
 * @Note Simple consumer api
 */
public class SimpleKafkaConsumer {
    private static Logger log = LoggerFactory.getLogger(SimpleKafkaConsumer.class);
    private List<String> m_replicaBrokers = new ArrayList<String>();
 
    public SimpleKafkaConsumer() {
        m_replicaBrokers = new ArrayList<String>();
    }
 
    public static void main(String[] args) {
        SimpleKafkaConsumer example = new SimpleKafkaConsumer();
        // Max read number
        long maxReads = SystemConfig.getIntProperty("kafka.read.max");
        // To subscribe to the topic
        String topic = SystemConfig.getProperty("kafka.topic");
        // Find partition
        int partition = SystemConfig.getIntProperty("kafka.partition");
        // Broker node's ip
        List<String> seeds = new ArrayList<String>();
        String[] hosts = SystemConfig.getPropertyArray("kafka.server.host"",");
        for (String host : hosts) {
            seeds.add(host);
        }
        int port = SystemConfig.getIntProperty("kafka.server.port");
        try {
            example.run(maxReads, topic, partition, seeds, port);
        catch (Exception e) {
            log.error("Oops:" + e);
            e.printStackTrace();
        }
    }
 
    public void run(long a_maxReads, String a_topic, int a_partition, List<String> a_seedBrokers, int a_port)
            throws Exception {
        // Get point topic partition's meta
        PartitionMetadata metadata = findLeader(a_seedBrokers, a_port, a_topic, a_partition);
        if (metadata == null) {
            log.info("[SimpleKafkaConsumer.run()] - Can't find metadata for Topic and Partition. Exiting");
            return;
        }
        if (metadata.leader() == null) {
            log.info("[SimpleKafkaConsumer.run()] - Can't find Leader for Topic and Partition. Exiting");
            return;
        }
        String leadBroker = metadata.leader().host();
        String clientName = "Client_" + a_topic + "_" + a_partition;
 
        SimpleConsumer consumer = new SimpleConsumer(leadBroker, a_port, 10000064 1024, clientName);
        long readOffset = getLastOffset(consumer, a_topic, a_partition, kafka.api.OffsetRequest.EarliestTime(),
                clientName);
        int numErrors = 0;
        while (a_maxReads > 0) {
            if (consumer == null) {
                consumer = new SimpleConsumer(leadBroker, a_port, 10000064 1024, clientName);
            }
            FetchRequest req = new FetchRequestBuilder().clientId(clientName)
                    .addFetch(a_topic, a_partition, readOffset, 100000).build();
            FetchResponse fetchResponse = consumer.fetch(req);
 
            if (fetchResponse.hasError()) {
                numErrors++;
                // Something went wrong!
                short code = fetchResponse.errorCode(a_topic, a_partition);
                log.info("[SimpleKafkaConsumer.run()] - Error fetching data from the Broker:" + leadBroker
                        " Reason: " + code);
                if (numErrors > 5)
                    break;
                if (code == ErrorMapping.OffsetOutOfRangeCode()) {
                    // We asked for an invalid offset. For simple case ask for
                    // the last element to reset
                    readOffset = getLastOffset(consumer, a_topic, a_partition, kafka.api.OffsetRequest.LatestTime(),
                            clientName);
                    continue;
                }
                consumer.close();
                consumer = null;
                leadBroker = findNewLeader(leadBroker, a_topic, a_partition, a_port);
                continue;
            }
            numErrors = 0;
 
            long numRead = 0;
            for (MessageAndOffset messageAndOffset : fetchResponse.messageSet(a_topic, a_partition)) {
                long currentOffset = messageAndOffset.offset();
                if (currentOffset < readOffset) {
                    log.info("[SimpleKafkaConsumer.run()] - Found an old offset: " + currentOffset + " Expecting: "
                            + readOffset);
                    continue;
                }
 
                readOffset = messageAndOffset.nextOffset();
                ByteBuffer payload = messageAndOffset.message().payload();
 
                byte[] bytes = new byte[payload.limit()];
                payload.get(bytes);
                System.out.println(String.valueOf(messageAndOffset.offset()) + ": " new String(bytes, "UTF-8")); // Message deal enter
                numRead++;
                a_maxReads--;
            }
 
            if (numRead == 0) {
                try {
                    Thread.sleep(1000);
                catch (InterruptedException ie) {
                }
            }
        }
        if (consumer != null)
            consumer.close();
    }
 
    public static long getLastOffset(SimpleConsumer consumer, String topic, int partition, long whichTime,
            String clientName) {
        TopicAndPartition topicAndPartition = new TopicAndPartition(topic, partition);
        Map<TopicAndPartition, PartitionOffsetRequestInfo> requestInfo = new HashMap<TopicAndPartition, PartitionOffsetRequestInfo>();
        requestInfo.put(topicAndPartition, new PartitionOffsetRequestInfo(whichTime, 1));
        kafka.javaapi.OffsetRequest request = new kafka.javaapi.OffsetRequest(requestInfo,
                kafka.api.OffsetRequest.CurrentVersion(), clientName);
        OffsetResponse response = consumer.getOffsetsBefore(request);
 
        if (response.hasError()) {
            log.info("[SimpleKafkaConsumer.getLastOffset()] - Error fetching data Offset Data the Broker. Reason: "
                    + response.errorCode(topic, partition));
            return 0;
        }
        long[] offsets = response.offsets(topic, partition);
        return offsets[0];
    }
 
    /**
     * @param a_oldLeader
     * @param a_topic
     * @param a_partition
     * @param a_port
     * @return String
     * @throws Exception
     *             find next leader broker
     */
    private String findNewLeader(String a_oldLeader, String a_topic, int a_partition, int a_port) throws Exception {
        for (int i = 0; i < 3; i++) {
            boolean goToSleep = false;
            PartitionMetadata metadata = findLeader(m_replicaBrokers, a_port, a_topic, a_partition);
            if (metadata == null) {
                goToSleep = true;
            else if (metadata.leader() == null) {
                goToSleep = true;
            else if (a_oldLeader.equalsIgnoreCase(metadata.leader().host()) && i == 0) {
                // first time through if the leader hasn't changed give
                // ZooKeeper a second to recover
                // second time, assume the broker did recover before failover,
                // or it was a non-Broker issue
                //
                goToSleep = true;
            else {
                return metadata.leader().host();
            }
            if (goToSleep) {
                try {
                    Thread.sleep(1000);
                catch (InterruptedException ie) {
                }
            }
        }
        throw new Exception("Unable to find new leader after Broker failure. Exiting");
    }
 
    private PartitionMetadata findLeader(List<String> a_seedBrokers, int a_port, String a_topic, int a_partition) {
        PartitionMetadata returnMetaData = null;
        loop: for (String seed : a_seedBrokers) {
            SimpleConsumer consumer = null;
            try {
                consumer = new SimpleConsumer(seed, a_port, 10000064 1024"leaderLookup");
                List<String> topics = Collections.singletonList(a_topic);
                TopicMetadataRequest req = new TopicMetadataRequest(topics);
                kafka.javaapi.TopicMetadataResponse resp = consumer.send(req);
 
                List<TopicMetadata> metaData = resp.topicsMetadata();
                for (TopicMetadata item : metaData) {
                    for (PartitionMetadata part : item.partitionsMetadata()) {
                        if (part.partitionId() == a_partition) {
                            returnMetaData = part;
                            break loop;
                        }
                    }
                }
            catch (Exception e) {
                log.error("Error communicating with Broker [" + seed + "] to find Leader for [" + a_topic + ", "
                        + a_partition + "] Reason: " + e);
            finally {
                if (consumer != null)
                    consumer.close();
            }
        }
        if (returnMetaData != null) {
            m_replicaBrokers.clear();
            for (kafka.cluster.Broker replica : returnMetaData.replicas()) {
                m_replicaBrokers.add(replica.host());
            }
        }
        return returnMetaData;
    }
}

4.总结

  在使用 Kafka 低级消费 API 时,要明确我们所使用的业务场景,一般建议还是使用高级消费 API,除非遇到特殊需要。另外,在使用过程中,注意 Leader Broker 的处理,和 Offset 的管理。

5.结束语

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本文转自哥不是小萝莉博客园博客,原文链接:http://www.cnblogs.com/smartloli/,如需转载请自行联系原作者