- 概述
- 文件下载
- 系统环境搭建和配置
- kafka demo
-
参考
-
概述
- kafka是一个分布式的消息缓存系统
- kafka集群中的服务器都叫做broker
- kafka有两类客户端，一类叫producer（消息生产者），一类叫做consumer（消息消费者），客户端和broker服务器之间采用tcp协议连接
- kafka中不同业务系统的消息可以通过topic进行区分，而且每一个消息topic都会被分区，以分担消息读写的负载
- 每一个分区都可以有多个副本，以防止数据的丢失
- 某一个分区中的数据如果需要更新，都必须通过该分区所有副本中的leader来更新
- 消费者可以分组，比如有两个消费者组A和B，共同消费一个topic：order_info,A和B所消费的消息不会重复 ，比如 order_info 中有100个消息，每个消息有一个id,编号从0-99，那么，如果A组消费0-49号，B组就消费50-99号
- 消费者在具体消费某个topic中的消息时，可以指定起始偏移量
-
文件下载
-
系统环境搭建和配置
- java7配置省略
- zookeeper配置（此处略，参考：http://blog.csdn.net/lxf20054658/article/details/74452755）
- kafka配置
- 上传kafka_2.11-0.11.0.0.tgz到centos服务器
- 解压，tar -zxvf kafka_2.11-0.11.0.0.tgz，mv kafka_2.11-0.11.0.0 /usr/lib/apache-kafka
- 配置，cd /usr/lib/apache-kafka/config，vi server.properties，配置示例（参考颜色标注的地方即可）：
-
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# see kafka.server.KafkaConfig for additional details and defaults
############################# Server Basics #############################
# The id of the broker. This must be set to a unique integer for each broker.
broker.id=1
# Switch to enable topic deletion or not, default value is false
#delete.topic.enable=true
############################# Socket Server Settings #############################
# The address the socket server listens on. It will get the value returned from
# java.net.InetAddress.getCanonicalHostName() if not configured.
# FORMAT:
# listeners = listener_name://host_name:port
# EXAMPLE:
# listeners = PLAINTEXT://your.host.name:9092
#listeners=PLAINTEXT://:9092
# Hostname and port the broker will advertise to producers and consumers. If not set,
# it uses the value for "listeners" if configured. Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092
# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL
# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3
# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400
# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600
############################# Log Basics #############################
# A comma seperated list of directories under which to store log files
log.dirs=/tmp/kafka-logs
# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1
# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1
############################# Internal Topic Settings #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
############################# Log Flush Policy #############################
# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
# 1. Durability: Unflushed data may be lost if you are not using replication.
# 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
# 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.
# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000
# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000
############################# Log Retention Policy #############################
# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.
# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes. Functions independently of log.retention.hours.
#log.retention.bytes=1073741824
# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824
# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000
############################# Zookeeper #############################
# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=hadooplearn:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
############################# Group Coordinator Settings #############################
# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0 * 启动broker
bin/kafka-server-start.sh config/server.properties
* 在kafka集群中创建一个topic
bin/kafka-topics.sh –create –zookeeper hadooplearn:2181 –replication-factor 1 –partitions 1 –topic order
* 查看topic
bin/kafka-topics.sh –list –zookeeper hadooplearn:2181
* 用一个producer向某一个topic中写入消息（往话题order写消息）
bin/kafka-console-producer.sh –broker-list hadooplearn:9092 –topic order
* 用一个comsumer从某一个topic中读取信息
bin/kafka-console-consumer.sh –zookeeper hadooplearn:2181 –from-beginning –topic order
* 查看一个topic的分区及副本状态信息
bin/kafka-topics.sh –describe –zookeeper hadooplearn:2181 –topic order
1. kafka demo
注：基于kafka_2.11-0.11.0.0.tgz包
生产者：
package cn.itcast.kafka;
import java.util.Properties;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;
/**
* see http://kafka.apache.org/090/javadoc/index.html?org/apache/kafka/clients/producer/KafkaProducer.html
* @author xfli
*
*/
public class ProducerDemo {
/**
* @param args
*/
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "hadooplearn:9092");
props.put("metadata.broker.list","hadooplearn:9092");
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
Producer<String, String> producer = new KafkaProducer<>(props);
// 发送业务消息
// 读取文件 读取内存数据库 读socket端口
for (int i = 1; i <= 100; i++) {
try {
Thread.sleep(500);
} catch (InterruptedException e) {
e.printStackTrace();
}
producer.send(new ProducerRecord<String, String>("wordcount",
i+" said "+ i + " love you baby for " + i + " times,will you have a nice day with me tomorrow"));
}
}
}消费者：
package cn.itcast.kafka;
import java.util.Arrays;
import java.util.Properties;
import java.util.concurrent.atomic.AtomicBoolean;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.errors.WakeupException;
/**
* see http://kafka.apache.org/090/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaConsumer.html
* consumer/KafkaConsumer.html
*
* @author xfli
*
*/
public class ConsumerDemo implements Runnable {
private final AtomicBoolean closed = new AtomicBoolean(false);
KafkaConsumer<String, String> consumer;// = new KafkaConsumer<>(props);
public void run() {
try {
Properties props = new Properties();
props.put("bootstrap.servers", "hadooplearn:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("session.timeout.ms", "30000");
props.put("key.deserializer",
"org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer",
"org.apache.kafka.common.serialization.StringDeserializer");
consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("wordcount"));
while (!closed.get()) {
ConsumerRecords<String, String> records = consumer.poll(10000);
// Handle new records
for (final ConsumerRecord<String, String> rc : records) {
System.out.println("msg=" + rc.value());
}
try {
Thread.sleep(500);
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
} catch (WakeupException e) {
// Ignore exception if closing
if (!closed.get())
throw e;
} finally {
consumer.close();
}
}
// Shutdown hook which can be called from a separate thread
public void shutdown() {
closed.set(true);
consumer.wakeup();
}
/**
* @param args
*/
public static void main(String[] args) {
// TODO Auto-generated method stub
ConsumerDemo sub1 = new ConsumerDemo();
Thread tsub1 = new Thread(sub1);
tsub1.start();
}
}运行结果示例：
msg=56 said 56 love you baby for 56 times,will you have a nice day with me tomorrow
msg=57 said 57 love you baby for 57 times,will you have a nice day with me tomorrow
msg=58 said 58 love you baby for 58 times,will you have a nice day with me tomorrow
msg=59 said 59 love you baby for 59 times,will you have a nice day with me tomorrow
msg=60 said 60 love you baby for 60 times,will you have a nice day with me tomorrow
msg=61 said 61 love you baby for 61 times,will you have a nice day with me tomorrow
msg=62 said 62 love you baby for 62 times,will you have a nice day with me tomorrow
msg=63 said 63 love you baby for 63 times,will you have a nice day with me tomorrow
msg=64 said 64 love you baby for 64 times,will you have a nice day with me tomorrow
msg=65 said 65 love you baby for 65 times,will you have a nice day with me tomorrow参考：
http://kafka.apache.org/090/javadoc/index.html?org/apache/kafka/clients/producer/KafkaProducer.html
http://kafka.apache.org/090/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaConsumer.html