使用Old Consumer High Level API编写consumer
第一步：编写具体处理消息的类
import java.io.UnsupportedEncodingException;import org.slf4j.Logger;import org.slf4j.LoggerFactory;import kafka.consumer.ConsumerIterator;import kafka.consumer.KafkaStream;import kafka.message.MessageAndMetadata;public class Consumerwork implements Runnable { private static Logger LOG = LoggerFactory.getLogger(Consumerwork.class); @SuppressWarnings("rawtypes") private KafkaStream m_stream; private int m_threadNumber; @SuppressWarnings("rawtypes") public Consumerwork(KafkaStream a_stream,int a_threadNumber) { // TODO Auto-generated constructor stub m_threadNumber = a_threadNumber; m_stream = a_stream; } @SuppressWarnings("unchecked") @Override public void run() { // TODO Auto-generated method stub ConsumerIterator it = m_stream.iterator(); while (it.hasNext()) try { MessageAndMetadata thisMetadata=it.next(); String jsonStr = new String(thisMetadata.message(),"utf-8") ; LOG.info("Thread " + m_threadNumber + ": " +jsonStr); LOG.info("partion"+thisMetadata.partition()+",offset:"+thisMetadata.offset()); try { Thread.sleep(1000); } catch (InterruptedException e) { // TODO Auto-generated catch block e.printStackTrace(); } } catch (UnsupportedEncodingException e) { // TODO Auto-generated catch block e.printStackTrace(); } }} 第二步：编写启动Consumer主类
import java.util.HashMap;import java.util.List;import java.util.Map;import java.util.Properties;import java.util.Scanner;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;import java.util.concurrent.TimeUnit;import org.slf4j.Logger;import org.slf4j.LoggerFactory;import kafka.consumer.ConsumerConfig;import kafka.consumer.KafkaStream;import kafka.javaapi.consumer.ConsumerConnector;public class ConsumerGroup { private final ConsumerConnector consumer; private final String topic; private ExecutorService executor; private static Logger LOG = LoggerFactory.getLogger(ConsumerGroup.class); public ConsumerGroup(String a_zookeeper, String a_groupId, String a_topic) { consumer = kafka.consumer.Consumer.createJavaConsumerConnector(createConsumerConfig(a_zookeeper, a_groupId)); this.topic = a_topic; } public static void main(String[] args) { Scanner sc = new Scanner(System.in); System.out.println("请输入zookeeper集群地址(如zk1:2181,zk2:2181,zk3:2181)："); String zooKeeper = sc.nextLine(); System.out.println("请输入指定的消费group名称："); String groupId = sc.nextLine(); System.out.println("请输入指定的消费topic名称："); String topic = sc.nextLine(); System.out.println("请输入指定的消费处理线程数："); int threads = sc.nextInt(); LOG.info("Starting consumer kafka messages with zk:" + zooKeeper + " and the topic is " + topic); ConsumerGroup example = new ConsumerGroup(zooKeeper, groupId, topic); example.run(threads); try { Thread.sleep(1000); } catch (InterruptedException ie) { } // example.shutdown(); } private void shutdown() { // TODO Auto-generated method stub if (consumer != null) consumer.shutdown(); if (executor != null) executor.shutdown(); try { if (!executor.awaitTermination(5000, TimeUnit.MILLISECONDS)) { LOG.info("Timed out waiting for consumer threads to shut down, exiting uncleanly"); } } catch (InterruptedException e) { LOG.info("Interrupted during shutdown, exiting uncleanly"); } } private void run(int a_numThreads) { // TODO Auto-generated method stub Map topicCountMap = new HashMap (); topicCountMap.put(topic, new Integer(a_numThreads)); Map >> consumerMap = consumer.createMessageStreams(topicCountMap); List > streams = consumerMap.get(topic); // now launch all the threads // executor = Executors.newFixedThreadPool(a_numThreads); // now create an object to consume the messages // int threadNumber = 0; LOG.info("the streams size is "+streams.size()); for (final KafkaStream stream : streams) { executor.submit(new com.goodix.kafka.oldconsumer.Consumerwork(stream, threadNumber)); // consumer.commitOffsets(); threadNumber++; } } private ConsumerConfig createConsumerConfig(String a_zookeeper, String a_groupId) { // TODO Auto-generated method stub Properties props = new Properties(); props.put("zookeeper.connect", a_zookeeper); props.put("group.id", a_groupId); props.put("zookeeper.session.timeout.ms", "60000"); props.put("zookeeper.sync.time.ms", "200"); props.put("auto.commit.interval.ms", "1000"); props.put("auto.offset.reset", "smallest");// props.put("rebalance.max.retries", "5");// props.put("rebalance.backoff.ms", "15000"); return new ConsumerConfig(props); }} 1. topicCountMap.put(topic, new Integer(a_numThreads)) 是告诉Kafka我有多少个线程来处理消息。
(1). 这个线程数必须是小等于topic的partition分区数；可以通过
(2). kafka会根据partition.assignment.strategy指定的分配策略来指定线程消费那些分区的消息；这里没有单独配置该项即是采用的默认值range策略（按照阶段平均分配）。比如分区有10个、线程数有3个，则线程 1消费0,1,2,3，线程2消费4,5,6,线程3消费7,8,9。另外一种是roundrobin(循环分配策略)，官方文档中写有使用该策略有两个前提条件的，所以一般不要去设定。 (3). 经过测试：consumerMap.get(topic).size()，应该是获得的目前该topic有数据的分区数 (4). stream即指的是来自一个或多个服务器上的一个或者多个partition的消息。每一个stream都对应一个单线程处理。因此，client能够设置满足自己需求的stream数目。总之，一个stream也许代表了多个服务器partion的消息的聚合，但是每一个 partition都只能到一个stream./kafka-topics.sh --describe --zookeeper "172.16.49.173:2181" --topic "producer_test"命令来查看分区的情况2. Executors.newFixedThreadPool(a_numThreads)是创建一个创建固定容量大小的缓冲池：每次提交一个任务就创建一个线程，直到线程达到线程池的最大大小。线程池的大小一旦达到最大值就会保持不变，如果某个线程因为执行异常而结束，那么线程池会补充一个新线程。
3. props.put(“auto.offset.reset”, “smallest”) 是指定从最小没有被消费offset开始；如果没有指定该项则是默认的为largest，这样的话该consumer就得不到生产者先产生的消息。
4. 要使用old consumer API需要引用kafka_2.11以及kafka-clients。
org.apache.kafka kafka_2.11 0.10.0.0 org.apache.kafka kafka-clients 0.10.0.0
使用Old SimpleConsumerAPI编写consumer
使用的场景
这是一个更加底层和复杂的API，由于使用该API需要自己控制的项比较多，也比较复杂，官方给出了一些合适的适用场景，也可以理解成为这些场景是High Level Consumer API 不能够做到的
1. 针对一个消息读取多次
2. 在一个process中，仅仅处理一个topic中的一个partitions
3. 使用事务，确保每个消息只被处理一次
需要处理的事情
1. 必须在程序中跟踪offset值
2. 必须找出指定Topic Partition中的lead broker
3. 必须处理broker的变动
使用SimpleConsumer的步骤
首先，你必须知道读哪个topic的哪个partition 然后，找到负责该partition的broker leader，从而找到存有该partition副本的那个broker
再者，自己去写request并fetch数据 最终，还要注意需要识别和处理broker leader的改变
package com.goodix.kafka.oldconsumer;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;import java.util.Scanner;import org.slf4j.Logger;import org.slf4j.LoggerFactory;public class SimpleExample { private static Logger LOG = LoggerFactory.getLogger(SimpleExample.class); public static void main(String args[]) { SimpleExample example = new SimpleExample(); Scanner sc = new Scanner(System.in); System.out.println("请输入broker节点的ip地址(如172.16.49.173)"); String brokerIp = sc.nextLine(); List seeds = new ArrayList (); seeds.add(brokerIp); System.out.println("请输入broker节点端口号(如9092)"); int port = Integer.parseInt( sc.nextLine()); System.out.println("请输入要订阅的topic名称(如test)"); String topic = sc.nextLine(); System.out.println("请输入要订阅要查找的分区(如0)"); int partition = Integer.parseInt( sc.nextLine()); System.out.println("请输入最大读取消息数量(如10000)"); long maxReads = Long.parseLong( sc.nextLine()); try { example.run(maxReads, topic, partition, seeds, port); } catch (Exception e) { LOG.error("Oops:" + e); e.printStackTrace(); } } private List m_replicaBrokers = new ArrayList (); public SimpleExample() { m_replicaBrokers = new ArrayList (); } public void run(long a_maxReads, String a_topic, int a_partition, List a_seedBrokers, int a_port) throws Exception { // find the meta data about the topic and partition we are interested in //获取指定Topic partition的元数据 PartitionMetadata metadata = findLeader(a_seedBrokers, a_port, a_topic, a_partition); if (metadata == null) { LOG.error("Can't find metadata for Topic and Partition. Exiting"); return; } if (metadata.leader() == null) { LOG.error("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); LOG.error("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.error("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); LOG.info("the messag's offset is :"+String.valueOf(messageAndOffset.offset()) + " and the value is :" + 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 requestInfo = new HashMap (); 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.error("Error fetching data Offset Data the Broker. Reason: " + response.errorCode(topic, partition) ); return 0; } long[] offsets = response.offsets(topic, partition); return offsets[0]; } /** * 找一个leader broker * 遍历每个broker，取出该topic的metadata，然后再遍历其中的每个partition metadata，如果找到我们要找的partition就返回 * 根据返回的PartitionMetadata.leader().host()找到leader broker * @param a_oldLeader * @param a_topic * @param a_partition * @param a_port * @return * @throws Exception */ 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) { } } } LOG.error("Unable to find new leader after Broker failure. Exiting"); throw new Exception("Unable to find new leader after Broker failure. Exiting"); } /** * * @param a_seedBrokers * @param a_port * @param a_topic * @param a_partition * @return */ private PartitionMetadata findLeader(List a_seedBrokers, int a_port, String a_topic, int a_partition) { PartitionMetadata returnMetaData = null; loop: for (String seed : a_seedBrokers) { //遍历每个broker SimpleConsumer consumer = null; try { // 创建Simple Consumer， consumer = new SimpleConsumer(seed, a_port, 100000, 64 * 1024, "leaderLookup"); List topics = Collections.singletonList(a_topic); TopicMetadataRequest req = new TopicMetadataRequest(topics); //发送TopicMetadata Request请求 kafka.javaapi.TopicMetadataResponse resp = consumer.send(req); //取到Topic的Metadata List metaData = resp.topicsMetadata(); //遍历每个partition的metadata for (TopicMetadata item : metaData) { for (PartitionMetadata part : item.partitionsMetadata()) { // 判断是否是要找的partition if (part.partitionId() == a_partition) { returnMetaData = part; //找到就返回 break loop; } } } } catch (Exception e) { LOG.info("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.BrokerEndPoint replica : returnMetaData.replicas()) { m_replicaBrokers.add(replica.host()); } } return returnMetaData; }}