kafka消费者低级实例

半兽人 发表于: 2015-03-03   最后更新时间: 2016-10-25 22:23:01  
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kafka消费者低级实例


为什么使用SimpleConsumer?

使用“SimpleConsumer”的主要原因是你想比使用“消费者分组”更好的控制分区消费。

比如你想:

  1. 多次读取消息
  2. 在一个处理过程中只消费Partition其中的一部分消息
  3. 添加事务管理机制以保证消息被处理且仅被处理一次

使用SimpleConsumer有哪些弊端呢

这个SimpleConsumer确实需要很大的工作量：

  1. 必须在程序中跟踪offset值.
  2. 必须找出指定Topic(主题) Partition(分区)中的lead broker.
  3. 必须处理broker的变动.

使用SimpleConsumer的步骤

  1. 从所有活跃的broker中找出哪个是指定Topic（主题） Partition（分区）中的leader broker
  2. 找出指定Topic Partition中的所有备份broker
  3. 构造请求
  4. 发送请求获取数据
  5. 处理leader broker变更

寻找 Lead Broker 的Topic(主题)和Partition(分区)

这些不需要broker在集群中，你可以开始寻找活着的broker来查询Leader的信息。 

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, 100000, 64 * 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) {
                System.out.println("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;
    }

调用topicMetadata()方法连接到broker中查找到我们感兴趣的topic.

partitionsMetadata循环所有分区，直到找到我们需要的。.

查找读取起始偏移量

现在定义从哪里开始读取数据。kafka包括两个常数，kafka.api.OffsetRequest.EarliestTime()发现日志中的数据的开始，kafka.api.OffsetRequest.LatestTime()将只流新消息。不要以为补偿0开始偏移。 

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()) {
            System.out.println("Error fetching data Offset Data the Broker. Reason: " + response.errorCode(topic, partition) );
            return 0;
        }
        long[] offsets = response.offsets(topic, partition);
        return offsets[0];
    }

差错处理

由于SimpleConsumer不处理lead broker的失败，你必须写一些代码来处理它。 

if (fetchResponse.hasError()) {
     numErrors++;
     // Something went wrong!
     short code = fetchResponse.errorCode(a_topic, a_partition);
     System.out.println("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;
 }
在这里，一旦获取返回的一个错误，我们记录原因，关闭消费者，然后试图找出新的leader。 
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) {
               }
           }
       }
       System.out.println("Unable to find new leader after Broker failure. Exiting");
       throw new Exception("Unable to find new leader after Broker failure. Exiting");
   }

此方法使用前面定义找到新领导者的findLeader（）的逻辑，但在这里我们只尝试连接到该topic(主题)/partition(分区)的副本之一。这样，如果我们不能找到需要的数据，则退出。


因为它可能需要很短的时间内Zookeeper发现领袖失效并分配一个新的领导人,如果我们没有得到响应，则休眠。事实上,Zookeeper故障转移很快,所以你从不休眠。

读取数据

最后我们读取传输回来的数据，并把它写出来. 

// When calling FetchRequestBuilder, it's important NOT to call .replicaId(), which is meant for internal use only.
// Setting the replicaId incorrectly will cause the brokers to behave incorrectly.
FetchRequest req = new FetchRequestBuilder()
        .clientId(clientName)
        .addFetch(a_topic, a_partition, readOffset, 100000)
        .build();
FetchResponse fetchResponse = consumer.fetch(req);
 
if (fetchResponse.hasError()) {
        // See code in previous section
}
numErrors = 0;
 
long numRead = 0;
for (MessageAndOffset messageAndOffset : fetchResponse.messageSet(a_topic, a_partition)) {
    long currentOffset = messageAndOffset.offset();
    if (currentOffset < readOffset) {
        System.out.println("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"));
    numRead++;
    a_maxReads--;
}
 
if (numRead == 0) {
    try {
        Thread.sleep(1000);
    } catch (InterruptedException ie) {
    }
}

请注意，“readOffset”询问最后一次读取的消息的下一个偏移。当消息块被处理，我们就知道从哪里开始获取下一个。

还要注意的是，检查正在读取的偏移量不小于我们要求的偏移。这是必要的，因为如果kafka被压缩的消息，读取请求将返回整个压缩的块，即使请求偏移量不是压缩块的开头。还需要注意的是，我们要求fetchSize 100000bytes。如果kafka生产商正在大批量生产，这可能是不够的并可能会返回一个空的消息集。在这种情况下，应增加 fetchSize，直到返回非空的集合。.

最后，我们跟中读取信息#，如果我们没有在最后一次请求读取到消息，我们就进行休眠。

运行示例

该示例预计以下参数:

  • 消息的最大数量阅读（所以我们没有永远循环下去）
  • 从Topic（主题）读取
  • 从Partition（分区）读取
  • 一个broker用于Metadata的查询
  • Broker端口监听

完整源码 

package com.test.simple;
 
import kafka.api.FetchRequest;
import kafka.api.FetchRequestBuilder;
import kafka.api.PartitionOffsetRequestInfo;
import kafka.common.ErrorMapping;
import kafka.common.TopicAndPartition;
import kafka.javaapi.*;
import kafka.javaapi.consumer.SimpleConsumer;
import kafka.message.MessageAndOffset;
 
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
 
public class SimpleExample {
    public static void main(String args[]) {
        SimpleExample example = new SimpleExample();
        long maxReads = Long.parseLong(args[0]);
        String topic = args[1];
        int partition = Integer.parseInt(args[2]);
        List<String> seeds = new ArrayList<String>();
        seeds.add(args[3]);
        int port = Integer.parseInt(args[4]);
        try {
            example.run(maxReads, topic, partition, seeds, port);
        } catch (Exception e) {
            System.out.println("Oops:" + e);
             e.printStackTrace();
        }
    }
 
    private List<String> m_replicaBrokers = new ArrayList<String>();
 
    public SimpleExample() {
        m_replicaBrokers = new ArrayList<String>();
    }
 
    public void run(long a_maxReads, String a_topic, int a_partition, List<String> a_seedBrokers, int a_port) throws Exception {
        // find the meta data about the topic and partition we are interested in
        //
        PartitionMetadata metadata = findLeader(a_seedBrokers, a_port, a_topic, a_partition);
        if (metadata == null) {
            System.out.println("Can't find metadata for Topic and Partition. Exiting");
            return;
        }
        if (metadata.leader() == null) {
            System.out.println("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, 100000, 64 * 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, 100000, 64 * 1024, clientName);
            }
            FetchRequest req = new FetchRequestBuilder()
                    .clientId(clientName)
                    .addFetch(a_topic, a_partition, readOffset, 100000) // Note: this fetchSize of 100000 might need to be increased if large batches are written to Kafka
                    .build();
            FetchResponse fetchResponse = consumer.fetch(req);
 
            if (fetchResponse.hasError()) {
                numErrors++;
                // Something went wrong!
                short code = fetchResponse.errorCode(a_topic, a_partition);
                System.out.println("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) {
                    System.out.println("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"));
                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()) {
            System.out.println("Error fetching data Offset Data the Broker. Reason: " + response.errorCode(topic, partition) );
            return 0;
        }
        long[] offsets = response.offsets(topic, partition);
        return offsets[0];
    }
 
    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) {
                }
            }
        }
        System.out.println("Unable to find new leader after Broker failure. Exiting");
        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, 100000, 64 * 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) {
                System.out.println("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;
    }
}


更新于 2016-10-25
半兽人

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