win setup kafka 3.6.2 Step-by-Step Guide

At the end of the document, some bugs are recorded

setup

from https://kafka.apache.org/downloads download .tgz binary package to local and extract

Prerequisites

  1. Kafka Installed: Ensure Kafka is installed and running.
  2. Java Installed: Kafka requires Java. Make sure having the JDK installed.

edit config file

  • edit config/server.properties file:

    broker.id=0

    log.dirs=/tmp/kafka-logs # or in window use D:\\tmp\\kafka-logs

    zookeeper.connect=localhost:2181

    listeners=PLAINTEXT://:9092

  • edit config/zookeeper.properties file:

    dataDir=/bigdata/zk # in win use D:\\bigdata\\zk

1. Start Kafka Server

Make sure Zookeeper and Kafka server are running.

Start Zookeeper:
.\bin\windows\zookeeper-server-start.bat .\config\zookeeper.properties
Start Kafka server:
.\bin\windows\kafka-server-start.bat .\config\server.properties

2. Create a Kafka Topic

Before producing and consuming messages, need a topic.

.\bin\windows\kafka-topics.bat --create --topic test --bootstrap-server localhost:9092 --partitions 1 --replication-factor 1

3. Set Up Kafka Producer

use the Kafka console producer to send messages to the topic.

Open a new Command Prompt and run:

.\bin\windows\kafka-console-producer.bat --topic test --bootstrap-server localhost:9092

Type messages in the console to send them to the Kafka topic.

4. Set Up Kafka Consumer

Open another Command Prompt to start the consumer that reads messages from the topic.

.\bin\windows\kafka-console-consumer.bat --topic test --bootstrap-server localhost:9092 --from-beginning

should see messages in the consumer console as type them in the producer console.

Connecting Kafka with Code

Here are examples in Java and Python.

Java Example

First, add Kafka client dependencies topom.xml if using Maven:

<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>3.6.2</version>
</dependency>

Producer Example

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;

import java.util.Properties;

public class KafkaProducerExample {
    public static void main(String[] args) {
        Properties props = new Properties();
        props.put("bootstrap.servers", "localhost:9092");
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");

        KafkaProducer<String, String> producer = new KafkaProducer<>(props);
        producer.send(new ProducerRecord<>("test", "key", "value"));
        producer.close();
    }
}

Consumer Example

import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;

import java.time.Duration;
import java.util.Collections;
import java.util.Properties;

public class KafkaConsumerExample {
    public static void main(String[] args) {
        Properties props = new Properties();
        props.put("bootstrap.servers", "localhost:9092");
        props.put("group.id", "test-group");
        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<>(props);
        consumer.subscribe(Collections.singletonList("test"));

        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
            records.forEach(record -> {
                System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
            });
        }
    }
}
Python Example

First, install the Kafka Python client:

pip install kafka-python

Producer Example

from kafka import KafkaProducer

producer = KafkaProducer(bootstrap_servers='localhost:9092')
producer.send('test', b'Hello, Kafka!')
producer.close()

Consumer Example

from kafka import KafkaConsumer

consumer = KafkaConsumer('test', bootstrap_servers='localhost:9092', auto_offset_reset='earliest')
for message in consumer:
    print(f"Key: {message.key}, Value: {message.value}")

Note

  • Start Zookeeper and Kafka server: Ensure they are running correctly.
  • Create topics: Use Kafka commands to create the required topics.

some bug

'wmic' is not recognized as an internal or external command, operable program or batch file

click Environment Variables. In the section for system variables, find PATH (or any capitalization thereof). Add this entry to it:

%SystemRoot%\System32\Wbem

ERROR Exiting Kafka due to fatal exception during startup. (kafka.Kafka$) java.nio.file.InvalidPathException: Illegal char < > at index 2: D: mpdownloadkafkakafka_2.13-3.6.2log\meta.properties.tmp

Correct the Path Format:

Ensure that the path specified in configuration does not contain illegal characters or spaces. Paths in Windows should use double backslashes \ or a single forward slash /.

WARN [SocketServer listenerType=ZK_BROKER, nodeId=0] Unexpected error from /0:0:0:0:0:0:0:1 (channelId=0:0:0:0:0:0:0:1:9092-0:0:0:0:0:0:0:1:62710-1); closing connection (org.apache.kafka.common.network.Selector) org.apache.kafka.common.network.InvalidReceiveException: Invalid receive (size = 1195725856 larger than 104857600)

  • Edit server.properties:

    Open the server.properties file in Kafka config directory and increase the max.request.size property. Add or modify the following lines:

    max.request.size=209715200 # Increase this value as needed, default is 104857600 (100MB)

    socket.request.max.bytes=209715200 # Ensure this matches or exceeds max.request.size

  • Edit consumer.properties and producer.properties (if applicable):

    If have consumer and producer configurations, ensure that these properties are set appropriately there as well:

    max.request.size=209715200

相关推荐
龙洋静1 小时前
RabbitMQ中常用的三种交换机【Fanout、Direct、Topic】
分布式·rabbitmq
java6666688881 小时前
使用RabbitMQ实现可靠的消息传递机制
分布式·rabbitmq·ruby
szc17671 小时前
RabbitMq 消息确认和退回机制
分布式·rabbitmq
我非夏日2 小时前
基于Hadoop平台的电信客服数据的处理与分析④项目实现:任务18: 数据展示
大数据·hadoop·分布式·大数据技术开发
武子康2 小时前
Hadoop-12-Hive 基本介绍 下载安装配置 MariaDB安装 3台云服务Hadoop集群 架构图 对比SQL HQL
java·大数据·hive·hadoop·分布式·hdfs·mariadb
一座野山2 小时前
Hive 高可用分布式部署详细步骤
数据仓库·hive·hadoop·分布式
一座野山2 小时前
hadoop分布式中某个 节点报错的解决案例
大数据·hadoop·分布式
华子w9089258592 小时前
基于大数据技术Hadoop的气象分析可视化大屏设计和实现
大数据·论文阅读·hadoop·分布式
武子康2 小时前
Hadoop-11-MapReduce JOIN 操作的Java实现 Driver Mapper Reducer具体实现逻辑 模拟SQL进行联表操作
java·大数据·hadoop·分布式·sql·mapreduce
重庆大傑3 小时前
Kafka(一)基础介绍
分布式·kafka