• Kafka

    转自： http://www.cnblogs.com/smartloli/p/5241067.html#top

     

    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：

     1 <dependency>
 2     <groupId>org.apache.kafka</groupId>
 3     <artifactId>kafka_2.11</artifactId>
 4     <version>0.8.2.1</version>
 5     <exclusions>
 6         <exclusion>
 7             <groupId>org.apache.zookeeper</groupId>
 8             <artifactId>zookeeper</artifactId>
 9     </exclusion>
10     <exclusion>
11             <groupId>log4j</groupId>
12             <artifactId>log4j</artifactId>
13     </exclusion>
14     </exclusions>
15 </dependency>

    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：

    　　

      1 public class SimpleKafkaConsumer {
  2     private static Logger log = LoggerFactory.getLogger(SimpleKafkaConsumer.class);
  3     private List<String> m_replicaBrokers = new ArrayList<String>();
  4  
  5     public SimpleKafkaConsumer() {
  6         m_replicaBrokers = new ArrayList<String>();
  7     }
  8  
  9     public static void main(String[] args) {
 10         SimpleKafkaConsumer example = new SimpleKafkaConsumer();
 11         // Max read number
 12         long maxReads = SystemConfig.getIntProperty("kafka.read.max");
 13         // To subscribe to the topic
 14         String topic = SystemConfig.getProperty("kafka.topic");
 15         // Find partition
 16         int partition = SystemConfig.getIntProperty("kafka.partition");
 17         // Broker node's ip
 18         List<String> seeds = new ArrayList<String>();
 19         String[] hosts = SystemConfig.getPropertyArray("kafka.server.host", ",");
 20         for (String host : hosts) {
 21             seeds.add(host);
 22         }
 23         int port = SystemConfig.getIntProperty("kafka.server.port");
 24         try {
 25             example.run(maxReads, topic, partition, seeds, port);
 26         } catch (Exception e) {
 27             log.error("Oops:" + e);
 28             e.printStackTrace();
 29         }
 30     }
 31  
 32     public void run(long a_maxReads, String a_topic, int a_partition, List<String> a_seedBrokers, int a_port)
 33             throws Exception {
 34         // Get point topic partition's meta
 35         PartitionMetadata metadata = findLeader(a_seedBrokers, a_port, a_topic, a_partition);
 36         if (metadata == null) {
 37             log.info("[SimpleKafkaConsumer.run()] - Can't find metadata for Topic and Partition. Exiting");
 38             return;
 39         }
 40         if (metadata.leader() == null) {
 41             log.info("[SimpleKafkaConsumer.run()] - Can't find Leader for Topic and Partition. Exiting");
 42             return;
 43         }
 44         String leadBroker = metadata.leader().host();
 45         String clientName = "Client_" + a_topic + "_" + a_partition;
 46  
 47         SimpleConsumer consumer = new SimpleConsumer(leadBroker, a_port, 100000, 64 * 1024, clientName);
 48         long readOffset = getLastOffset(consumer, a_topic, a_partition, kafka.api.OffsetRequest.EarliestTime(),
 49                 clientName);
 50         int numErrors = 0;
 51         while (a_maxReads > 0) {
 52             if (consumer == null) {
 53                 consumer = new SimpleConsumer(leadBroker, a_port, 100000, 64 * 1024, clientName);
 54             }
 55             FetchRequest req = new FetchRequestBuilder().clientId(clientName)
 56                     .addFetch(a_topic, a_partition, readOffset, 100000).build();
 57             FetchResponse fetchResponse = consumer.fetch(req);
 58  
 59             if (fetchResponse.hasError()) {
 60                 numErrors++;
 61                 // Something went wrong!
 62                 short code = fetchResponse.errorCode(a_topic, a_partition);
 63                 log.info("[SimpleKafkaConsumer.run()] - Error fetching data from the Broker:" + leadBroker
 64                         + " Reason: " + code);
 65                 if (numErrors > 5)
 66                     break;
 67                 if (code == ErrorMapping.OffsetOutOfRangeCode()) {
 68                     // We asked for an invalid offset. For simple case ask for
 69                     // the last element to reset
 70                     readOffset = getLastOffset(consumer, a_topic, a_partition, kafka.api.OffsetRequest.LatestTime(),
 71                             clientName);
 72                     continue;
 73                 }
 74                 consumer.close();
 75                 consumer = null;
 76                 leadBroker = findNewLeader(leadBroker, a_topic, a_partition, a_port);
 77                 continue;
 78             }
 79             numErrors = 0;
 80  
 81             long numRead = 0;
 82             for (MessageAndOffset messageAndOffset : fetchResponse.messageSet(a_topic, a_partition)) {
 83                 long currentOffset = messageAndOffset.offset();
 84                 if (currentOffset < readOffset) {
 85                     log.info("[SimpleKafkaConsumer.run()] - Found an old offset: " + currentOffset + " Expecting: "
 86                             + readOffset);
 87                     continue;
 88                 }
 89  
 90                 readOffset = messageAndOffset.nextOffset();
 91                 ByteBuffer payload = messageAndOffset.message().payload();
 92  
 93                 byte[] bytes = new byte[payload.limit()];
 94                 payload.get(bytes);
 95                 System.out.println(String.valueOf(messageAndOffset.offset()) + ": " + new String(bytes, "UTF-8")); // Message deal enter
 96                 numRead++;
 97                 a_maxReads--;
 98             }
 99  
100             if (numRead == 0) {
101                 try {
102                     Thread.sleep(1000);
103                 } catch (InterruptedException ie) {
104                 }
105             }
106         }
107         if (consumer != null)
108             consumer.close();
109     }
110  
111     public static long getLastOffset(SimpleConsumer consumer, String topic, int partition, long whichTime,
112             String clientName) {
113         TopicAndPartition topicAndPartition = new TopicAndPartition(topic, partition);
114         Map<TopicAndPartition, PartitionOffsetRequestInfo> requestInfo = new HashMap<TopicAndPartition, PartitionOffsetRequestInfo>();
115         requestInfo.put(topicAndPartition, new PartitionOffsetRequestInfo(whichTime, 1));
116         kafka.javaapi.OffsetRequest request = new kafka.javaapi.OffsetRequest(requestInfo,
117                 kafka.api.OffsetRequest.CurrentVersion(), clientName);
118         OffsetResponse response = consumer.getOffsetsBefore(request);
119  
120         if (response.hasError()) {
121             log.info("[SimpleKafkaConsumer.getLastOffset()] - Error fetching data Offset Data the Broker. Reason: "
122                     + response.errorCode(topic, partition));
123             return 0;
124         }
125         long[] offsets = response.offsets(topic, partition);
126         return offsets[0];
127     }
128  
129     /**
130      * @param a_oldLeader
131      * @param a_topic
132      * @param a_partition
133      * @param a_port
134      * @return String
135      * @throws Exception
136      *             find next leader broker
137      */
138     private String findNewLeader(String a_oldLeader, String a_topic, int a_partition, int a_port) throws Exception {
139         for (int i = 0; i < 3; i++) {
140             boolean goToSleep = false;
141             PartitionMetadata metadata = findLeader(m_replicaBrokers, a_port, a_topic, a_partition);
142             if (metadata == null) {
143                 goToSleep = true;
144             } else if (metadata.leader() == null) {
145                 goToSleep = true;
146             } else if (a_oldLeader.equalsIgnoreCase(metadata.leader().host()) && i == 0) {
147                 // first time through if the leader hasn't changed give
148                 // ZooKeeper a second to recover
149                 // second time, assume the broker did recover before failover,
150                 // or it was a non-Broker issue
151                 //
152                 goToSleep = true;
153             } else {
154                 return metadata.leader().host();
155             }
156             if (goToSleep) {
157                 try {
158                     Thread.sleep(1000);
159                 } catch (InterruptedException ie) {
160                 }
161             }
162         }
163         throw new Exception("Unable to find new leader after Broker failure. Exiting");
164     }
165  
166     private PartitionMetadata findLeader(List<String> a_seedBrokers, int a_port, String a_topic, int a_partition) {
167         PartitionMetadata returnMetaData = null;
168         loop: for (String seed : a_seedBrokers) {
169             SimpleConsumer consumer = null;
170             try {
171                 consumer = new SimpleConsumer(seed, a_port, 100000, 64 * 1024, "leaderLookup");
172                 List<String> topics = Collections.singletonList(a_topic);
173                 TopicMetadataRequest req = new TopicMetadataRequest(topics);
174                 kafka.javaapi.TopicMetadataResponse resp = consumer.send(req);
175  
176                 List<TopicMetadata> metaData = resp.topicsMetadata();
177                 for (TopicMetadata item : metaData) {
178                     for (PartitionMetadata part : item.partitionsMetadata()) {
179                         if (part.partitionId() == a_partition) {
180                             returnMetaData = part;
181                             break loop;
182                         }
183                     }
184                 }
185             } catch (Exception e) {
186                 log.error("Error communicating with Broker [" + seed + "] to find Leader for [" + a_topic + ", "
187                         + a_partition + "] Reason: " + e);
188             } finally {
189                 if (consumer != null)
190                     consumer.close();
191             }
192         }
193         if (returnMetaData != null) {
194             m_replicaBrokers.clear();
195             for (kafka.cluster.Broker replica : returnMetaData.replicas()) {
196                 m_replicaBrokers.add(replica.host());
197             }
198         }
199         return returnMetaData;
200     }
201 }

    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。
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  • 原文地址：https://www.cnblogs.com/XQiu/p/5241464.html
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