【kafka】kafka集群的搭建、用户的设置和权限的控制
准备
我们准备起码三个实例，你可以在一台设备上操作，但是起码要有三个实例。我这边准备了三台设备，分别为192.168.5.1,192.168.5.2,192.168.5.3。然后是kafka的包和zookeeper的包，kafka和zookeeper的版本要适配。我这里准备的是kafka_2.12-2.4.0.tgz和apache-zookeeper-3.5.8-bin.tar.gz。
zookeeper集群的搭建
kafka的运行依赖zookeeper，考虑到高可用的能力，所以需要搭建一个zookeeper的集群。
分别在三台设备上传到zookeeper的安装包，解压后，复制zookeeper目录下conf下的zoo_sample.cfg为zoo.cfg，编辑zoo.cfg。
# The number of milliseconds of each tick
tickTime=2000
# The number of ticks that the initial
# synchronization phase can take
initLimit=10
# The number of ticks that can pass between
# sending a request and getting an acknowledgement
syncLimit=5
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just
# example sakes.
# 此处一定要修改，修改为合适的路径，如果是同一台设备的不同实例，也要分开
dataDir=/home/wjx/zkData
# the port at which the clients will connect
# 如果需要修改zookeeper的默认2181端口，修改这个
clientPort=2181
# 增加这个配置，其中的2888是kafka集群之间的通讯和数据同步端口，3888是集群节点leader的选举通信端口。
server.1=192.168.5.1:2888:3888
server.2=192.168.5.2:2888:3888
server.3=192.168.5.3:2888:3888
# the maximum number of client connections.
# increase this if you need to handle more clients
#maxClientCnxns=60
#
# Be sure to read the maintenance section of the
# administrator guide before turning on autopurge.
#
# http://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_maintenance
#
# The number of snapshots to retain in dataDir
#autopurge.snapRetainCount=3
# Purge task interval in hours
# Set to "0" to disable auto purge feature
#autopurge.purgeInterval=1
保存退出后，启动zookeeper，启动脚本在zookeeper的bin目录下：
bin/zkServer.sh start conf/zoo.cfg &
执行命令后，zookeeper会在后台进行运行，同理修改剩下的两台设备中zookeeper的配置文件并启动，zookeeper集群搭建完毕。
kafka集群的搭建
分别在三台设备上传到kafka的安装包，解压后，修改kafka目录下config下的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.
# kafka的通讯器ID，集群中的每一台设备都要不一样
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://: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
# 一定要修改这个配置，指定kafka的日志存放，同一台设备的不同实例也要不一样，否则启动会报错，提示日志目录不为空
log.dirs=/home/wjx/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.
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.
# 配置zookeeper的集群，格式为 IP:PORT ，有多台的用,分隔
zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181
# 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
# 如果要修改kafka的通讯端口，可以加一个配置，这里只是示意，本案例还是用的默认端口9092。
port=19092
保存退出后，启动kakfa，启动脚本在kafka的bin目录下，启动命令：
bin/kafka-server-start.sh -daemon config/server.properties
同理，剩下的两台设备的kafka都修改配置文件启动完成后，kafka集群就搭建完成。如果不需要用户认证和topic的读写权限设置，kafka已经可以使用。
如果要修改kafka的默认堆内存，防止数据量大的情况下频繁GC，需要修改bin/kafka-server-start.sh这个启动脚本
#!/bin/bash
# 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.
if [ $# -lt 1 ];
then
echo "USAGE: $0 [-daemon] server.properties [--override property=value]*"
exit 1
fi
base_dir=$(dirname $0)
if [ "x$KAFKA_LOG4J_OPTS" = "x" ]; then
export KAFKA_LOG4J_OPTS="-Dlog4j.configuration=file:$base_dir/../config/log4j.properties"
fi
# 就是这个地方的1G，根据实际情况改成需要的堆内存大小
if [ "x$KAFKA_HEAP_OPTS" = "x" ]; then
export KAFKA_HEAP_OPTS="-Xmx1G -Xms1G"
fi
EXTRA_ARGS=${EXTRA_ARGS-'-name kafkaServer -loggc'}
COMMAND=$1
case $COMMAND in
-daemon)
EXTRA_ARGS="-daemon "$EXTRA_ARGS
shift
;;
*)
;;
esac
exec $base_dir/kafka-run-class.sh $EXTRA_ARGS kafka.Kafka "$@"
用户的设置和权限的认证
还是用刚才搭建好的kafka集群，现在我们加上用户和读写权限的设置。我们现在要创建三个用户，分别是管理用户admin，生产者writer和消费者reader。我们随便登录一台搭建了kafka设备，进入kafka的目录，开始创建三个用户。
创建管理用户admin，密码是admin
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --alter --add-config 'SCRAM-SHA-256=[iterations=8192,password=admin],SCRAM-SHA-512=[password=admin]' --entity-type users --entity-name admin
提示完成用户的创建。
创建生产者writer，密码是writerpwd
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --alter --add-config 'SCRAM-SHA-256=[iterations=8192,password=writerpwd],SCRAM-SHA-512=[password=writerpwd]' --entity-type users --entity-name writer
提示完成用户的创建。
创建消费者reader，密码是readerpwd
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --alter --add-config 'SCRAM-SHA-256=[iterations=8192,password=readerpwd],SCRAM-SHA-512=[password=readerpwd]' --entity-type users --entity-name reader
提示完成用户的创建。
我们可以用以下命令查看用户信息确定是否创建成功，比如查看writer用户信息：
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --describe --entity-type users --entity-name writer
接下来我们要配置kafka通讯器，在kafka的config目录下创建一个kafka-broker-jaas.conf文件，文件内容如下：
KafkaServer {
org.apache.kafka.common.security.scram.ScramLoginModule required
username="admin"
password="admin";
};
其中的用户名密码就是我们配置的管理员，这个用户接着还要用到。注意：每一行的最后不要有空格，否则会有错误！（本人的血泪教训）
接下来继续修改config目录下的server.properties，在文件的最后加上：
# 启用ACL
authorizer.class.name=kafka.security.auth.SimpleAclAuthorizer
# 设置admin为超级用户
super.users=User:admin
# 启用SCRAM机制，采用SCRAM-SHA-512算法
sasl.enabled.mechanisms=SCRAM-SHA-512
# 为broker间通讯开启SCRAM机制，采用SCRAM-SHA-512算法
sasl.mechanism.inter.broker.protocol=SCRAM-SHA-512
# broker间通讯使用PLAINTEXT，本例中不演示SSL配置
security.inter.broker.protocol=SASL_PLAINTEXT
# 配置listeners使用SASL_PLAINTEXT，ip改成实际的本机ip
listeners=SASL_PLAINTEXT://192.168.5.1:9092
# 配置advertised.listeners，ip改成实际的本机ip
advertised.listeners=SASL_PLAINTEXT://192.168.5.1:9092
# 禁止自动创建topic
auto.create.topics.enable=false
然后我们重启kafka，这次启动要带上新加的kafka-broker-jaas.conf文件
KAFKA_OPTS=-Djava.security.auth.login.config=xxx/config/kafka-broker-jaas.conf bin/kafka-server-start.sh config/server.properties &
剩下两台也是重复以上除了创建用户的操作，最后重启。这样我们的kafka就有了用户和权限的限制。接着我们创建一个kafka的单分区单副本topic用于测试：
bin/kafka-topics.sh --create --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --topic test --partitions 1 --replication-factor 1
接下来我们用脚本来演示数据的生产和消费，同时配置用户的读写权限。
首先我们尝试向test这个topic发送数据
bin/kafka-console-producer.sh --broker-list 192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092 --topic test
输入任意字符发现会提示报错，ErrorLoggingCallback表示登录失败。
接着我们创建一个生产者的配置文件，然后用writer用户发送数据。配置文件producer.conf内容如下：
security.protocol=SASL_PLAINTEXT
sasl.mechanism=SCRAM-SHA-512
sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="writer" password="writerpwd";
执行生产者的脚本：
bin/kafka-console-producer.sh --broker-list 192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092 --topic test --producer.config xx/producer.conf
输入任意字符会发现新的报错，此时就是因为权限的缘故了。因为writer用户是没有对test这个topic的写权限的，我们给它加上：
bin/kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --add --allow-principal User:writer --operation Write --topic test
执行后会打印操作的结果，以及当前这个topic的用户权限情况。
我们再次执行生产者的脚本：
bin/kafka-console-producer.sh --broker-list 192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092 --topic test --producer.config xx/producer.conf
输入任意字符后会发现没有报错，说明发送成功！
同理的操作，我们需要对reader用户进行读topic的权限配置，先创建一个consumer.conf的文件：
security.protocol=SASL_PLAINTEXT
sasl.mechanism=SCRAM-SHA-512
sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="reader" password="readerpwd";
添加test的读权限：
bin/kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --add --allow-principal User:reader --operation Read --topic test
我们执行消费者脚本尝试读取test里面的数据：
bin/kafka-console-consumer.sh --bootstrap-server 192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092 --topic test --from-beginning --consumer.config xxx/consumer.conf --group test-group
发现报错，提示我们没有访问用户组的权限，所以我们加一下权限：
bin/kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --add --allow-principal User:reader --operation Read --group test-group
再次执行消费者脚本读取test里面的数据：
bin/kafka-console-consumer.sh --bootstrap-server 192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092 --topic test --from-beginning --consumer.config xxx/consumer.conf --group test-group
可以看到数据读取成功。
至此，我们生产和消费数据的kafka权限就配置完成了。
zookeeper的ACL登录认证
基本信息
zookeeper的bin目录下有zkCli.sh可以直接连接zookeeper，可以对zk的节点进行任何操作，这在生产环境中是及其危险的，所以需要对zk进行目录的权限限定
通过zkCli.sh可以登录指定的zk
./bin/zkCli.sh 192.168.5.1:2181
通过命令查看节点的权限
[zk: localhost:2181(CONNECTED) 0] getAcl /brokers
'world,'anyone
: cdrwa
可以看到/brokers这个节点是world:anyone的用户范围，这个也就是所有人可以操作，后面的cdrwa就是可以的操作，c-create（创建）,d-delete（删除）,r-read（读取）,w-write（写入）,a-auth（设置权限）
如果是获取一个无权限的节点信息则是如下：
[zk: localhost:2181(CONNECTED) 4] getAcl /
Authentication is not valid : /
设置权限
如果要设置权限，操作步骤如下：
- 登录用户，账号usera，密码userpwd
addauth digest usera:userpwd
这个登录准确也不叫登录，而是一种用户信息的创建，这个用户不需要存在，可以调用多次来同时登录多个用户
- 设置权限
setAcl / auth:usera:userpwd:cdrwa
这个命令就是将根目录/设置用户账号和密码，以及权限
- 查看权限
getAcl /
这个命令就是查看目录的权限
- 清除目录权限
setAcl / world:anyone:crdwa
清除目录权限的命令和设置权限的命令类似，但是没有用户前面的auth
忘记用户密码
以上都是设置权限的方法，但是有一个问题，就是设置节点的权限后忘了用户的账号密码，导致别的用户都无法操作这个节点。所以需要一个方法重置权限。这个方法就是开启一个超级账号去操作，超级账号没有权限限制，所以操作完记得关闭。
- 创建超级用户 useradmin 密码 userpwd
设备上输入以下命令
echo -n useradmin:userpwd | openssl dgst -binary -sha1 | openssl base64
回显会得到密码的密文4pOzGFD5H++TMb0bB7hp2AD5+6U=，记录一下
- 修改zkServer.sh，即zk的启动脚本，找到脚本中的start方法部分，在指定参数的位置加上
"-Dzookeeper.DigestAuthenticationProvider.superDigest=useradmin:4pOzGFD5H++TMb0bB7hp2AD5+6U="
- 重启zk
- 再次用zkCli.sh连接zk，然后用登录命令登录：
addauth digest useradmin:userpwd
这个时候就会发现可以任意操作任何节点，可以用重置节点权限的命令重置节点，然后重新设置权限
5.另外的方法
如果是单纯忘记了节点的用户是谁，账号密码对应的还是记得的，可以通过暂时关闭acl验证来查看权限用户是谁。为了安全，使用完后记得删除或者注释配置，然后重启zk。
先修改zoo.conf配置文件，在最底下加上：
skipACL=yes
然后重启zk，用zkCli.sh连接zk，就能发现任何节点的权限信息都可以查看了，但是不能修改权限。
kafka脚本使用
- 查看topic消费情况
注意：如果没有权限，那么该命令最后的–command-config admin.conf不需要配置
bin/kafka-consumer-groups.sh --bootstrap-server 192.168.5.1:9092,192.168.5.2:9092:192.168.5.3:9092 --describe --group test-group --command-config admin.conf
admin.conf的内容为：
security.protocol=SASL_PLAINTEXT
sasl.mechanism=SCRAM-SHA-512
sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="admin" password="admin";
PS:因为我们在kafka中配置了超级用户是admin，所以这里一定要配置admin，用其他的用户会因为权限的问题而失败
整理文档：
启动zookeeper
bin/zkServer.sh start conf/zoo.cfg &
启动kafka
KAFKA_OPTS=-Djava.security.auth.login.config=xxx/config/kafka-broker-jaas.conf bin/kafka-server-start.sh config/server.properties &
创建topic
bin/kafka-topics.sh --create --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --topic test --partitions 1 --replication-factor 1
新增生产者：
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --alter --add-config 'SCRAM-SHA-256=[iterations=8192,password=writerpwd],SCRAM-SHA-512=[password=writerpwd]' --entity-type users --entity-name writer
设置写权限：
bin/kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --add --allow-principal User:writer --operation Write --topic test
新增消费者：
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --alter --add-config 'SCRAM-SHA-256=[iterations=8192,password=readerpwd],SCRAM-SHA-512=[password=readerpwd]' --entity-type users --entity-name reader
设置读权限：
bin/kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --add --allow-principal User:reader --operation Read --topic test
设置消费组权限：
bin/kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties zookeeper.connect=192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --add --allow-principal User:reader --operation Read --group test-group
删除用户：
bin/kafka-configs.sh --zookeeper 192.168.5.1:2181,192.168.5.2:2181,192.168.5.3:2181 --alter --delete-config 'SCRAM-SHA-256' --entity-type users --entity-name writer
Java代码demo：
生产者
package com.wangjx.message.kafka;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
import java.util.UUID;
import java.util.concurrent.TimeUnit;
/**
* @program: swallow
* @description:
* @author: wangjiaxing
* @created: 2020/10/30 11:43
*/
public class KafkaSender {
public static void main(String[] args) throws InterruptedException {
Properties properties = new Properties();
properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092");
properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringSerializer");//key 序列化方式
properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringSerializer");//value
//此处设置kafka的消费者配置文件
System.setProperty("java.security.auth.login.config", "./kafka/kafka-client-jaas.conf");
//如果system这个配置已经被占用，可以使用下面注释的方式进行设置
//properties.put("sasl.jaas.config", "org.apache.kafka.common.security.scram.ScramLoginModule required username=\"writer\" password=\"writerpwd\";");
//安全协议
properties.put("security.protocol", "SASL_PLAINTEXT");
//加密方式
properties.put("sasl.mechanism", "SCRAM-SHA-512");
properties.put(ProducerConfig.BATCH_SIZE_CONFIG, "10");
properties.put(ProducerConfig.COMPRESSION_TYPE_CONFIG, "gzip");
properties.put(ProducerConfig.LINGER_MS_CONFIG, "50");
properties.put(ProducerConfig.ACKS_CONFIG, "all");
properties.put(ProducerConfig.RETRIES_CONFIG, 30);
properties.put(ProducerConfig.RETRY_BACKOFF_MS_CONFIG, 20000);
properties.put(ProducerConfig.RECONNECT_BACKOFF_MS_CONFIG, 20000);
KafkaProducer<String, String> producer = new KafkaProducer(properties);
while (true) {
String topic = "test";
String k = UUID.randomUUID().toString();
Long v = System.currentTimeMillis();
producer.send(new ProducerRecord(topic, k, Long.toString(v)));
System.out.println("send to topic > "+topic+" : "+k+" | "+v+"");
TimeUnit.SECONDS.sleep(1);
}
}
}
消费者
package com.wangjx.message.kafka;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.time.Duration;
import java.util.ArrayList;
import java.util.List;
import java.util.Properties;
/**
* @program: swallow
* @description:
* @author: wangjiaxing
* @created: 2020/10/30 11:43
*/
public class KafkaReceiver {
public static void main(String[] args) throws InterruptedException {
Properties properties = new Properties();
properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.5.1:9092,192.168.5.2:9092,192.168.5.3:9092");
properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");//key 反序列化方式
properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");//value
//此处设置kafka的消费者配置文件
System.setProperty("java.security.auth.login.config", "./kafka/kafka-client-jaas.conf");
//如果system这个配置已经被占用，可以使用下面注释的方式进行设置
//properties.put("sasl.jaas.config", "org.apache.kafka.common.security.scram.ScramLoginModule required username=\"reader\" password=\"readerpwd\";");
properties.put("security.protocol", "SASL_PLAINTEXT");
properties.put("sasl.mechanism", "SCRAM-SHA-512");
properties.put(ConsumerConfig.RETRY_BACKOFF_MS_CONFIG, 20000);
properties.put(ConsumerConfig.RECONNECT_BACKOFF_MS_CONFIG, 20000);
properties.put(ConsumerConfig.GROUP_ID_CONFIG, "test-group");
KafkaConsumer<String, String> consumer = new KafkaConsumer(properties);
List<String> topics = new ArrayList<>();
String topic = "test";
topics.add(topic);
consumer.subscribe(topics);
while (true) {
ConsumerRecords<String, String> records = consumer.poll(Duration.ofSeconds(10));
// 消息处理
for (ConsumerRecord<String, String> record : records) {
System.out.println("receive message from topic "+topic+", key = "+record.key()+", offset = "+record.offset()+", message = "+record.value());
}
}
}
}