介绍
http://kafka.apache.org
kafka是一种高吞吐量的分布式发布订阅消息系统
kafka是linkedin用于日志处理的分布式消息队列，linkedin的日志数据容量大，但对可靠性要求不高，其日志数据主要包括用户行为（登录、浏览、点击、分享、喜欢）以及系统运行日志（CPU、内存、磁盘、网络、系统及进程状态）
当前很多的消息队列服务提供可靠交付保证，并默认是即时消费（不适合离线）。
高可靠交付对linkedin的日志不是必须的，故可通过降低可靠性来提高性能，同时通过构建分布式的集群，允许消息在系统中累积，使得kafka同时支持离线和在线日志处理
测试环境
kafka_2.10-0.8.1.1 3个节点做的集群
zookeeper-3.4.5 一个实例节点
代码示例
消息生产者代码示例
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
|
import
java.util.Collections;
import
java.util.Date;
import
java.util.Properties;
import
java.util.Random;
import
kafka.javaapi.producer.Producer;
import
kafka.producer.KeyedMessage;
import
kafka.producer.ProducerConfig;
/**
* 详细可以参考：https://cwiki.apache.org/confluence/display/KAFKA/0.8.0+Producer+Example
* @author Fung
*
*/
public
class
ProducerDemo {
public
static
void
main(String[] args) {
Random rnd =
new
Random();
int
events=
100
;
// 设置配置属性
Properties props =
new
Properties();
props.put(
"metadata.broker.list"
,
"172.168.63.221:9092,172.168.63.233:9092,172.168.63.234:9092"
);
props.put(
"serializer.class"
,
"kafka.serializer.StringEncoder"
);
// key.serializer.class默认为serializer.class
props.put(
"key.serializer.class"
,
"kafka.serializer.StringEncoder"
);
// 可选配置，如果不配置，则使用默认的partitioner
props.put(
"partitioner.class"
,
"com.catt.kafka.demo.PartitionerDemo"
);
// 触发acknowledgement机制，否则是fire and forget，可能会引起数据丢失
// 值为0,1,-1,可以参考
// http://kafka.apache.org/08/configuration.html
props.put(
"request.required.acks"
,
"1"
);
ProducerConfig config =
new
ProducerConfig(props);
// 创建producer
Producer<String, String> producer =
new
Producer<String, String>(config);
// 产生并发送消息
long
start=System.currentTimeMillis();
for
(
long
i =
0
; i < events; i++) {
long
runtime =
new
Date().getTime();
String ip =
"192.168.2."
+ i;
//rnd.nextInt(255);
String msg = runtime +
",www.example.com,"
+ ip;
//如果topic不存在，则会自动创建，默认replication-factor为1，partitions为0
KeyedMessage<String, String> data =
new
KeyedMessage<String, String>(
"page_visits"
, ip, msg);
producer.send(data);
}
System.out.println(
"耗时:"
+ (System.currentTimeMillis() - start));
// 关闭producer
producer.close();
}
}
|
消息消费者代码示例
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
|
import
java.util.HashMap;
import
java.util.List;
import
java.util.Map;
import
java.util.Properties;
import
java.util.concurrent.ExecutorService;
import
java.util.concurrent.Executors;
import
kafka.consumer.Consumer;
import
kafka.consumer.ConsumerConfig;
import
kafka.consumer.KafkaStream;
import
kafka.javaapi.consumer.ConsumerConnector;
/**
* 详细可以参考：https://cwiki.apache.org/confluence/display/KAFKA/Consumer+Group+Example
*
* @author Fung
*
*/
public
class
ConsumerDemo {
private
final
ConsumerConnector consumer;
private
final
String topic;
private
ExecutorService executor;
public
ConsumerDemo(String a_zookeeper, String a_groupId, String a_topic) {
consumer = Consumer.createJavaConsumerConnector(createConsumerConfig(a_zookeeper,a_groupId));
this
.topic = a_topic;
}
public
void
shutdown() {
if
(consumer !=
null
)
consumer.shutdown();
if
(executor !=
null
)
executor.shutdown();
}
public
void
run(
int
numThreads) {
Map<String, Integer> topicCountMap =
new
HashMap<String, Integer>();
topicCountMap.put(topic,
new
Integer(numThreads));
Map<String, List<KafkaStream<
byte
[],
byte
[]>>> consumerMap = consumer
.createMessageStreams(topicCountMap);
List<KafkaStream<
byte
[],
byte
[]>> streams = consumerMap.get(topic);
// now launch all the threads
executor = Executors.newFixedThreadPool(numThreads);
// now create an object to consume the messages
//
int
threadNumber =
0
;
for
(
final
KafkaStream stream : streams) {
executor.submit(
new
ConsumerMsgTask(stream, threadNumber));
threadNumber++;
}
}
private
static
ConsumerConfig createConsumerConfig(String a_zookeeper,
String a_groupId) {
Properties props =
new
Properties();
props.put(
"zookeeper.connect"
, a_zookeeper);
props.put(
"group.id"
, a_groupId);
props.put(
"zookeeper.session.timeout.ms"
,
"400"
);
props.put(
"zookeeper.sync.time.ms"
,
"200"
);
props.put(
"auto.commit.interval.ms"
,
"1000"
);
return
new
ConsumerConfig(props);
}
public
static
void
main(String[] arg) {
String[] args = {
"172.168.63.221:2188"
,
"group-1"
,
"page_visits"
,
"12"
};
String zooKeeper = args[
0
];
String groupId = args[
1
];
String topic = args[
2
];
int
threads = Integer.parseInt(args[
3
]);
ConsumerDemo demo =
new
ConsumerDemo(zooKeeper, groupId, topic);
demo.run(threads);
try
{
Thread.sleep(
10000
);
}
catch
(InterruptedException ie) {
}
demo.shutdown();
}
}
|
消息处理类
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
|
import
kafka.consumer.ConsumerIterator;
import
kafka.consumer.KafkaStream;
public
class
ConsumerMsgTask
implements
Runnable {
private
KafkaStream m_stream;
private
int
m_threadNumber;
public
ConsumerMsgTask(KafkaStream stream,
int
threadNumber) {
m_threadNumber = threadNumber;
m_stream = stream;
}
public
void
run() {
ConsumerIterator<
byte
[],
byte
[]> it = m_stream.iterator();
while
(it.hasNext())
System.out.println(
"Thread "
+ m_threadNumber +
": "
+
new
String(it.next().message()));
System.out.println(
"Shutting down Thread: "
+ m_threadNumber);
}
}
|
Partitioner类示例
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
|
import
kafka.producer.Partitioner;
import
kafka.utils.VerifiableProperties;
public
class
PartitionerDemo
implements
Partitioner {
public
PartitionerDemo(VerifiableProperties props) {
}
@Override
public
int
partition(Object obj,
int
numPartitions) {
int
partition =
0
;
if
(obj
instanceof
String) {
String key=(String)obj;
int
offset = key.lastIndexOf(
'.'
);
if
(offset >
0
) {
partition = Integer.parseInt(key.substring(offset +
1
)) % numPartitions;
}
}
else
{
partition = obj.toString().length() % numPartitions;
}
return
partition;
}
}
|
pom.xml文件
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
|
<project xmlns=
"http://maven.apache.org/POM/4.0.0"
xmlns:xsi=
"http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation=
"http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"
>
<modelVersion>
4.0
.
0
</modelVersion>
<groupId>com.xxx</groupId>
<artifactId>kafka-demo</artifactId>
<version>
0.0
.
1
-SNAPSHOT</version>
<packaging>jar</packaging>
<name>kafka-demo</name>
<url>http:
//maven.apache.org</url>
<properties>
<project.build.sourceEncoding>UTF-
8
</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.
10
</artifactId>
<version>
0.8
.
1.1
</version>
<exclusions>
<exclusion>
<artifactId>jmxtools</artifactId>
<groupId>com.sun.jdmk</groupId>
</exclusion>
<exclusion>
<artifactId>jmxri</artifactId>
<groupId>com.sun.jmx</groupId>
</exclusion>
<exclusion>
<artifactId>jms</artifactId>
<groupId>javax.jms</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>
1.2
.
15
</version>
<exclusions>
<exclusion>
<artifactId>jmxtools</artifactId>
<groupId>com.sun.jdmk</groupId>
</exclusion>
<exclusion>
<artifactId>jmxri</artifactId>
<groupId>com.sun.jmx</groupId>
</exclusion>
<exclusion>
<artifactId>jms</artifactId>
<groupId>javax.jms</groupId>
</exclusion>
<exclusion>
<artifactId>mail</artifactId>
<groupId>javax.mail</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>
4.11
</version>
<scope>test</scope>
</dependency>
</dependencies>
</project>
|