搞定springboot项目连接远程服务器上kafka遇到的坑以及完整的例子

版本

springboot	2.1.5.RELEASE
kafka	2.2

遇到的坑

1. 用最新的springboot就要用最新的kafka版本！
2. 当我启动云服务器上的zk后，再启动kafka后台日志也没报错，只感觉EndPoint日志信息有点奇怪，然后springboot项目连接kafka，老是有warn级别的日志："Connection to node -1 could not be established. Broker may not be available."，这是未连接上kafka
3. springboot项目控制台抛出ip地址不合法的异常。

telnet一下云服务器的9092端口没有响应，然后看云服务器安全组里也添加了啊，netstat也看到9092被监听，到底咋回事？

原来是kafka配置文件的问题，导致9092端口未被正确监听，ip地址的问题就是要绑定kafka服务器的ip地址。

注意下面红色三项配置很重要，解决了我所有的问题！

advertised.host.name必须写kafka服务器的ip地址！如果写localhost，并且项目运行的服务器和kafka运行的不是同一台服务器，会连接不上。

将kafka服务端的配置文件修改如下：

############################# Server Basics #############################
 
# The id of the broker. This must be set to a unique integer for each broker.
#broker的全局唯一编号，不能重复
broker.id=
 
############################# Socket Server Settings #############################
 
#监听的端口
listeners=PLAINTEXT://:9092
# 客户端连接的ip地址，必须要写成服务器的ip地址！advertised.host.name
advertised.host.name = 47.XX.XX.XX
host.name=localhost
 
# 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=
 
# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=
 
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=
 
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=
 
# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=
 
############################# Log Basics #############################
 
# A comma separated list of directories under which to store log files
log.dirs=/root/mysoftware/kafka_2.-2.2./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=
 
# 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=
 
############################# 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  is recommended for to ensure availability such as .
offsets.topic.replication.factor=
transaction.state.log.replication.factor=
transaction.state.log.min.isr=
 
############################# 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:
#    . Durability: Unflushed data may be lost if you are not using replication.
#    . 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.
#    . 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=
 
# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=
 
############################# 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=
 
# 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=
 
# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=
 
# 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=
 
############################# 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:
 
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=
 
############################# 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  seconds.
# We override this to  here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of  seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=

代码

pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>2.1.5.RELEASE</version>
        <relativePath/> <!-- lookup parent from repository -->
    </parent>
    <groupId>xy.study</groupId>
    <artifactId>kafka-demo</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>kafka-demo</name>
    <description>Kafka demo project for Spring Boot</description>
 
    <properties>
        <java.version>1.8</java.version>
    </properties>
 
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka</artifactId>
        </dependency>
 
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-devtools</artifactId>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.47</version>
        </dependency>
 
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
 
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
 
</project>

application.properties

#============== kafka ===================
# 指定kafka 代理地址，可以多个
spring.kafka.bootstrap-servers=47.XX.XX.XX:9092
 
#=============== provider  =======================
 
spring.kafka.producer.retries=0
# 每次批量发送消息的数量
spring.kafka.producer.batchSize=16384
spring.kafka.producer.bufferMemory=33554432
 
# 指定消息key和消息体的编解码方式
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer
 
#=============== consumer  =======================
# 指定默认消费者group id
spring.kafka.consumer.group-id=consumer-group-test
 
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.enable-auto-commit=true
spring.kafka.consumer.auto-commit-interval=100
 
# 指定消息key和消息体的编解码方式
spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer

生产者和消费者

@Component
@Slf4j
public class KafkaProducer {
 
    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;
 
    public void sendADotaHero() {
        DotaHero dotaHero = new DotaHero("虚空假面", "敏捷", "男");
 
        ListenableFuture<SendResult<String, String>> future = kafkaTemplate.send(KafkaTopic.A_DOTA_HERO, JSONObject.toJSONString(dotaHero));
 
        future.addCallback(new ListenableFutureCallback<SendResult<String, String>>() {
            @Override
            public void onFailure(Throwable throwable) {
                log.error("kafka sendMessage error, throwable = {}, topic = {}, data = {}", throwable, KafkaTopic.A_DOTA_HERO, dotaHero);
            }
 
            @Override
            public void onSuccess(SendResult<String, String> stringDotaHeroSendResult) {
                log.info("kafka sendMessage success topic = {}, data = {}",KafkaTopic.A_DOTA_HERO, dotaHero);
            }
        });
 
        log.info("kafka sendMessage end");
 
    }
 
}

@Slf4j
@Component
public class KafkaConsumer {
 
    @KafkaListener(topics = KafkaTopic.A_DOTA_HERO, groupId = "${spring.kafka.consumer.group-id}")
    private void kafkaConsumer(ConsumerRecord<String, DotaHero> consumerRecord) {
 
        log.info("kafkaConsumer: topic = {}, msg = {}", consumerRecord.topic(), consumerRecord.value());
 
    }
}

@Data
@AllArgsConstructor
@NoArgsConstructor
public class DotaHero {
 
    private String name;
    private String kind;
    private String sex;
 
    /**
     * 返回一个不同元素的数组
     * @return
     */
    public static List<DotaHero> bulidDiffObjectList(){
        List<DotaHero> list = new ArrayList<>();
        list.add(new DotaHero("影魔", "敏捷", "男"));
        list.add(new DotaHero("小黑", "敏捷", "女"));
        list.add(new DotaHero("马尔斯", "力量", "男"));
 
        return list;
    }
}

public class KafkaTopic {
    public static final String A_DOTA_HERO = "a_dota_hero";
 
    private KafkaTopic() {
    }
}

测试

当启动完springboot项目后，再运行test启动生产者：

@Slf4j
@RunWith(SpringRunner.class)
@SpringBootTest
public class KafkaDemoApplicationTests {
 
    @Autowired
    private KafkaProducer kafkaProducer;
 
    private Clock clock = Clock.systemDefaultZone();
    private long begin;
    private long end;
 
    @Before
    public void init(){
 
        begin = clock.millis();
    }
 
    @Test
    public void send(){
        kafkaProducer.sendADotaHero();
    }
 
    @After
    public void end(){
        end = clock.millis();
        log.info("Spend {} millis .", end-begin);
    }
 
}