Kafka - 消费接口分析
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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：
<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>
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：
/**
* @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, 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).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, 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) {
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
这篇博客就和大家分享到这里，如果大家在研究学习的过程当中有什么问题，可以加群进行讨论或发送邮件给我，我会尽我所能为您解答，与君共勉！
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