版本
| springboot | 2.1.5.RELEASE |
| kafka | 2.2 |
遇到的坑
- 用最新的springboot就要用最新的kafka版本！
- 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
- 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=0 ############################# 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=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=/root/mysoftware/kafka_2.12-2.2.0/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
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); } }
