单节点部署环境，主要用于学习与调试。集群化部署方案，请访问「深入浅出 Kafka（三）集群化部署」；若部署完单节点想进一步学习，请转向「深入浅出 Kafka（四）架构深入」。
- CentOS 7.4
- Kafka 2.11
下载
wget https://mirrors.huaweicloud.com/apache/zookeeper/zookeeper-3.4.10/zookeeper-3.4.10.tar.gz启动
sh zkServer.sh start从官网下载Kafka 安装包，解压安装，或直接使用命令下载。
wget https://mirrors.huaweicloud.com/apache/kafka/1.1.0/kafka_2.12-1.1.0.tgz解压安装
tar -zvxf kafka_2.11-1.0.0.tgz -C /usr/local/
cd /usr/local/kafka_2.11-1.0.0/修改配置文件
vim config/server.properties
修改其中
log.dirs=data/kafka-logs
listeners=PLAINTEXT://192.168.72.133:9092
另外 advertised.listeners，是暴露给外部的 listeners，如果没有设置，会用 listeners
使用安装包中的脚本启动单节点 Zookeeper 实例：
bin/zookeeper-server-start.sh -daemon config/zookeeper.properties
使用 kafka-server-start.sh 启动 kafka 服务
前台启动
bin/kafka-server-start.sh config/server.properties
后台启动
bin/kafka-server-start.sh -daemon config/server.properties
使用 kafka-topics.sh 创建但分区单副本的 topic test
bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test
bin/kafka-topics.sh --list --zookeeper localhost:2181
使用 kafka-console-producer.sh 发送消息
bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test
使用 kafka-console-consumer.sh 接收消息并在终端打印
bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning
bin/kafka-topics.sh --delete --zookeeper localhost:2181 --topic test
[root@localhost kafka_2.11-1.0.0]# bin/kafka-topics.sh --describe --zookeeper
Topic:test PartitionCount:1 ReplicationFactor:1 Configs:
Topic: test Partition: 0 Leader: 1 Replicas: 1 Isr: 1第一行给出了所有分区的摘要，每个附加行给出了关于一个分区的信息。 由于我们只有一个分区，所以只有一行。
-
Leader
- 是负责给定分区的所有读取和写入的节点。 每个节点将成为分区随机选择部分的领导者。
-
Replicas
- 是复制此分区日志的节点列表，无论它们是否是领导者，或者即使他们当前处于活动状态。
-
Isr
- 是一组 “同步” 副本。这是复制品列表的子集，当前活着并被引导到领导者。
在上述的篇幅中，实现了宿主机上部署单节点环境（1 Zookeeper + 1 Kafka）。但是在不同环境配置上具有差异性，初学者入门需要进行复杂的配置，可能会造成配置失败。
使用 Docker 容器化部署可以实现开箱即用，免去了很多安装配置的时间。
以 wurstmeister/kafka - Docker Hub 为例，使用 docker-compose 运行一个只有一个 ZooKeeper node 和一个 Kafka broker 的开发环境：
version: '2'
services:
zoo1:
image: wurstmeister/zookeeper
restart: unless-stopped
hostname: zoo1
ports:
- "2181:2181"
container_name: zookeeper
# kafka version: 1.1.0
# scala version: 2.12
kafka1:
image: wurstmeister/kafka
ports:
- "9092:9092"
environment:
KAFKA_ADVERTISED_HOST_NAME: localhost
KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://192.168.72.133:9092
KAFKA_ZOOKEEPER_CONNECT: "zoo1:2181"
KAFKA_BROKER_ID: 1
KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
KAFKA_CREATE_TOPICS: "stream-in:1:1,stream-out:1:1"
depends_on:
- zoo1
container_name: kafka 这里利用了 wurstmeister/kafka 提供的环境参数 KAFKA_CREATE_TOPICS 使Kafka运行后自动创建 topics。
可以使用 docker exec 命令直接调用 kafka 容器内的脚本来进行创建/删除 topic，启动 console producer 等等操作。
如果本地存有与容器内相同的 Kafka 版本文件，也可以直接使用本地脚本文件。如上述 docker-compose.yml 文件所示，kafka1 的 hostname 即是 kafka1，端口为 9092，通过 kafka1:9092 就可以连接到容器内的 Kafka 服务。
列出所有 topics (在本地 kafka 路径下)
$ bin/kafka-topics.sh --zookeeper localhost:2181 --list列出所有 Kafka brokers
$ docker exec zookeeper bin/zkCli.sh ls /brokers/ids详细：server.properties - Kafka 中文文档 - ApacheCN
# 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=0
############################# 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://192.168.72.133:9092
# 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 separated 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 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.
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=localhost: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- advertised.listeners and listeners 两个配置文件的区别：kafka - advertised.listeners and listeners - fxjwind - 博客园