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：
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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,
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;
}
}
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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！
