kafka单机安装测试-原创-本机测试过

安装环境:vmware 安装的centos6.8   安装IP地址:192.168.52.136

kafka和zookeeper版本：kafka_2.13-2.4.0.tgz  和zookeeper-3.4.5.tar.gz  

centos安装目录:

zookeeper 配置和启动就不说了 

./zkServer.sh start

　　

启动kafka

 /usr/local/kafka/bin/kafka-server-start.sh  /usr/local/kafka/config/server.properties

　

查看实时消息

./kafka-console-consumer.sh --bootstrap-server 192.168.52.136:9092 --topic test3 --from-beginning

　　

server.properties

# 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
# 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://192.168.52.136:9092
hostname=192.168.52.136
listeners=PLAINTEXT://192.168.52.136:9092


############################# 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
# 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://192.168.52.36:9092
#listeners=PLAINTEXT://localhost: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 separated list of directories under which to store log files  不是日志
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 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 excessive 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 unless the remaining
# segments 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.
#1G大小
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=192.168.52.136:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=60000


############################# 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

　　

java测试项目 采用maven 组织方式

<dependencies>
		<dependency>
			<groupId>junit</groupId>
			<artifactId>junit</artifactId>
			<version>3.8.1</version>
			<scope>test</scope>
		</dependency>
		<dependency>
			<groupId>org.apache.kafka</groupId>
			<artifactId>kafka-clients</artifactId>
			<version>2.4.0</version>
		</dependency>
	<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>2.4.0</version>
   </dependency>
</dependencies>

生产消息代码

public class ProducerDemo {
 
    private final KafkaProducer<String, String> producer;
 
    public final static String TOPIC = "test3";
 
    private ProducerDemo() {
    	
        Properties props = new Properties();
        props.put("bootstrap.servers", "192.168.52.136:9092");//xxx服务器ip
        props.put("acks", "all");//所有follower都响应了才认为消息提交成功，即"committed"
        props.put("retries", 0);//retries = MAX 无限重试，直到你意识到出现了问题:)
        props.put("batch.size", 16384);//producer将试图批处理消息记录，以减少请求次数.默认的批量处理消息字节数
        //batch.size当批量的数据大小达到设定值后，就会立即发送，不顾下面的linger.ms
        props.put("linger.ms", 1);//延迟1ms发送，这项设置将通过增加小的延迟来完成--即，不是立即发送一条记录，producer将会等待给定的延迟时间以允许其他消息记录发送，这些消息记录可以批量处理
        props.put("buffer.memory", 33554432);//producer可以用来缓存数据的内存大小。
       props.put("key.serializer","org.apache.kafka.common.serialization.IntegerSerializer");
        props.put("value.serializer","org.apache.kafka.common.serialization.StringSerializer");
 
        producer = new KafkaProducer<String, String>(props);
    }
 
    public void produce() {
        int messageNo = 1;
        final int COUNT = 5;
 
        while(messageNo < COUNT) {
            String key = String.valueOf(messageNo);
            String data = String.format("hello KafkaProducer message %s from hubo liuyahui ", key);
            
            try {
				Future f=producer.send(new ProducerRecord<String, String>(TOPIC, data));
				System.out.println(f.get());
            } catch (Exception e) {
                e.printStackTrace();
            }
            messageNo++;
        }
        producer.close();
    }
    public static void main(String[] args) {
         new ProducerDemo().produce();
    }
}

　　

消费消息代码

public class ConsumrTest {
	 
    public static void main(String[] args) {
        
        String topicNmae="test3";
        String groupID="test-group";
        Properties props= new Properties();
        props.put("bootstrap.servers","192.168.52.136:9092");
        props.put("group.id",groupID);
        props.put("enable.auto.commit","true");
        props.put("auto.commit.interval.ms","1000");
        props.put("auto.offset.reset","earliest");
        props.put("key.deserializer","org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer","org.apache.kafka.common.serialization.StringDeserializer");
 
        KafkaConsumer<String,String> consumer=new KafkaConsumer<String, String>(props);
        consumer.subscribe(Arrays.asList(topicNmae));
        try {
            while (true){
                ConsumerRecords<String,String> records=consumer.poll(1000);
                for (ConsumerRecord<String,String> record:records){
                    System.out.printf("offset = %d ,key =%s, value= %s%n" ,record.offset(),record.key(),record.value());
                }
            }
        }finally {
            consumer.close();
        }
    }