Spring Boot整合Kafka-蒲公英云

Kafka是一个分布式的、可分区的、可复制的消息系统，下面是Kafka的几个基本术语：

Kafka将消息以topic为单位进行归纳；
将向Kafka topic发布消息的程序成为producers；
将预订topics并消费消息的程序成为consumer；
Kafka以集群的方式运行，可以由一个或多个服务组成，每个服务叫做一个broker。

producers通过网络将消息发送到Kafka集群，集群向消费者提供消息，如下图所示：

创建一个topic时，可以指定partitions（分区）数目，partitions数越多，其吞吐量也越大，但是需要的资源也越多，同时也会导致更高的不可用性，kafka在接收到producers发送的消息之后，会根据均衡策略将消息存储到不同的partitions中：

$log\_anatomy.png$

在每个partitions中，消息以顺序存储，最晚接收的的消息会最后被消费。

producers在向kafka集群发送消息的时候，可以通过指定partitions来发送到指定的partitions中。也可以通过指定均衡策略来将消息发送到不同的partitions中。如果不指定，就会采用默认的随机均衡策略，将消息随机的存储到不同的partitions中。

在consumer消费消息时，kafka使用offset来记录当前消费的位置：

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在kafka的设计中，可以有多个不同的group来同时消费同一个topic下的消息，如图，我们有两个不同的group同时消费，他们的的消费的记录位置offset各不项目，不互相干扰。

对于一个group而言，consumer的数量不应该多于partitions的数量，因为在一个group中，每个partitions至多只能绑定到一个consumer上，即一个consumer可以消费多个partitions，一个partitions只能给一个consumer消费。因此，若一个group中的consumer数量大于partitions数量的话，多余的consumer将不会收到任何消息。

format_png

Kafka安装使用

这里演示在Windows下Kafka安装与使用。Kafka下载地址：http://kafka.apache.org/downloads，选择二进制文件下载（Binary downloads），然后解压即可。

Kafka的配置文件位于config目录下，因为Kafka集成了Zookeeper（Kafka存储消息的地方），所以config目录下除了有Kafka的配置文件server.properties外，还可以看到一个Zookeeper配置文件zookeeper.properties：

QQ截图20190326103520.png

打开server.properties，将broker.id的值修改为1，每个broker的id都必须设置为Integer类型，且不能重复。Zookeeper的配置保持默认即可。

接下来开始使用Kafka。

启动Zookeeper

在Windows下执行下面这些命令可能会出现找不到或无法加载主类的问题，解决方案可参考：https://blog.csdn.net/cx2932350/article/details/78870135。

在Kafka根目录下使用cmd执行下面这条命令，启动ZK：

1	bin\windows\zookeeper-server-start.bat config\zookeeper.properties

在Linux下，可以使用后台进程的方式启动ZK：

1	bin/zookeeper-server-start.sh -daemon config/zookeeper.properties

启动Kafka

执行下面这条命令启动Kafka：

1	bin\windows\kafka-server-start.bat config\server.properties

Linux对应命令：

1	bin/kafka-server-start.sh config/server.properties

当看到命令行打印如下信息，说明启动完毕:

QQ截图20190326110506.png

创建Topic

执行下面这条命令创建一个Topic

1	bin\windows\kafka-topics.bat —create —zookeeper localhost:2181 —replication-factor 1 —partitions 1 —topic test

这条命令的意思是，创建一个Topic到ZK（指定ZK的地址），副本个数为1，分区数为1，Topic的名称为test。

Linux对应的命令为:

1	bin/kafka-topics.sh —create —zookeeper localhost:2181 —replication-factor 1 —partitions 1 —topic test

创建好后我们可以查看Kafka里的Topic列表：

1	bin\windows\kafka-topics.bat —list —zookeeper localhost:2181

QQ截图20190326111559.png

可看到目前只包含一个我们刚创建的test Topic。

Linux对应的命令为：

1	bin/kafka-topics.sh —list —zookeeper localhost:2181

查看test Topic的具体信息：

1	bin\windows\kafka-topics.bat —describe —zookeeper localhost:2181 —topic test

QQ截图20190326111928.png

Linux对应的命令为：

1	bin/kafka-topics.sh —describe —zookeeper localhost:2181 —topic test

生产消息和消费消息

启动Producers

1	bin\windows\kafka-console-producer.bat —broker-list localhost:9092 —topic test

9092为生产者的默认端口号。这里启动了生产者，准备往test Topic里发送数据。

Linux下对应的命令为：

1	bin/kafka-console-producer.sh —broker-list localhost:9092 —topic test

启动Consumers

接着启动一个消费者用于消费生产者生产的数据，新建一个cmd窗口，输入下面这条命令：

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

from-beginning表示从头开始读取数据。

Linux下对应的命令为：

1	bin/kafka-console-consumer.sh —bootstrap-server localhost:9092 —topic test —from-beginning

启动好生产者和消费者后我们在生产者里生产几条数据:

QQ截图20190326113911.png

消费者成功接收到数据：

QQ截图20190326113950.png

Spring Boot整合Kafaka

上面简单介绍了Kafka的使用，下面我们开始在Spring Boot里使用Kafka。

新建一个Spring Boot项目，版本为2.1.3.RELEASE，并引入如下依赖:

 <dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
</dependency>

生产者配置

新建一个Java配置类KafkaProducerConfig，用于配置生产者：

@Configuration
public class KafkaProducerConfig {

    @Value(“${spring.kafka.bootstrap-servers}”)
    private String bootstrapServers;

    @Bean
    public ProducerFactory<String, String> producerFactory() {
        Map<String, Object> configProps = new HashMap<>();
        configProps.put(
                ProducerConfig.BOOTSTRAP_SERVERS_CONFIG,
                bootstrapServers);
        configProps.put(
                ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,
                StringSerializer.class);
        configProps.put(
                ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,
                StringSerializer.class);
        return new DefaultKafkaProducerFactory<>(configProps);
    }

    @Bean
    public KafkaTemplate<String, String> kafkaTemplate() {
        return new KafkaTemplate<>(producerFactory());
    }
}

首先我们配置了一个producerFactory，方法里配置了Kafka Producer实例的策略。bootstrapServers为Kafka生产者的地址，我们在配置文件application.yml里配置它：

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spring:
  kafka:
    bootstrap-servers: localhost:9092

ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG和ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG指定了key，value序列化策略，这里指定为Kafka提供的StringSerializer，因为我们暂时只发送简单的String类型的消息。

接着我们使用producerFactory配置了kafkaTemplate，其包含了发送消息的便捷方法，后面我们就用这个对象来发送消息。

发布消息

配置好生产者，我们就可以开始发布消息了。

新建一个SendMessageController：

@RestController
public class SendMessageController {

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @GetMapping(“send/{message}”)
    public void send(@PathVariable String message) {
        this.kafkaTemplate.send(“test”, message);
    }
}

我们注入了kafkaTemplate对象，key-value都为String类型，并通过它的send方法来发送消息。其中test为Topic的名称，上面我们已经使用命令创建过这个Topic了。

send方法是一个异步方法，我们可以通过回调的方式来确定消息是否发送成功，我们改造SendMessageController：

@RestController
public class SendMessageController {

    private Logger logger = LoggerFactory.getLogger(this.getClass());

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @GetMapping(“send/{message}”)
    public void send(@PathVariable String message) {
        ListenableFuture<SendResult<String, String>> future = this.kafkaTemplate.send(“test”, message);
        future.addCallback(new ListenableFutureCallback<SendResult<String, String>>() {
            @Override
            public void onSuccess(SendResult<String, String> result) {
                logger.info(“成功发送消息：{}，offset=[{}]”, message, result.getRecordMetadata().offset());
            }

            @Override
            public void onFailure(Throwable ex) {
                logger.error(“消息：{} 发送失败，原因：{}”, message, ex.getMessage());
            }
        });
    }
}

消息发送成功后，会回调onSuccess方法，发送失败后回调onFailure方法。

消费者配置

接着我们来配置消费者，新建一个Java配置类KafkaConsumerConfig：

@EnableKafka
@Configuration
public class KafkaConsumerConfig {

    @Value(“${spring.kafka.bootstrap-servers}”)
    private String bootstrapServers;

    @Value(“${spring.kafka.consumer.group-id}”)
    private String consumerGroupId;

    @Value(“${spring.kafka.consumer.auto-offset-reset}”)
    private String autoOffsetReset;

    @Bean
    public ConsumerFactory<String, String> consumerFactory() {
        Map<String, Object> props = new HashMap<>();
        props.put(
                ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,
                bootstrapServers);
        props.put(
                ConsumerConfig.GROUP_ID_CONFIG,
                consumerGroupId);
        props.put(
                ConsumerConfig.AUTO_OFFSET_RESET_CONFIG,
                autoOffsetReset);
        props.put(
                ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG,
                StringDeserializer.class);
        props.put(
                ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,
                StringDeserializer.class);
        return new DefaultKafkaConsumerFactory<>(props);
    }

    @Bean
    public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<String, String> factory
                = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory());
        return factory;
    }
}

consumerGroupId和autoOffsetReset需要在application.yml里配置：

spring:
  kafka:
    consumer:
      group-id: test-consumer
      auto-offset-reset: latest

其中group-id将消费者进行分组（你也可以不进行分组），组名为test-consumer，并指定了消息读取策略，包含四个可选值：

QQ截图20190326154735.png

earliest:当各分区下有已提交的offset时，从提交的offset开始消费；无提交的offset时，从头开始消费
latest:当各分区下有已提交的offset时，从提交的offset开始消费；无提交的offset时，消费新产生的该分区下的数据
none:topic各分区都存在已提交的offset时，从offset后开始消费；只要有一个分区不存在已提交的offset，则抛出异常
exception:直接抛出异常

在KafkaConsumerConfig中我们配置了ConsumerFactory和KafkaListenerContainerFactory。当这两个Bean成功注册到Spring IOC容器中后，我们便可以使用@KafkaListener注解来监听消息了。

配置类上需要@EnableKafka注释才能在Spring托管Bean上检测@KafkaListener注解。

消息消费

配置好消费者，我们就可以开始消费消息了，新建KafkaMessageListener：

@Component
public class KafkaMessageListener {

    private Logger logger = LoggerFactory.getLogger(this.getClass());

    @KafkaListener(topics = “test”, groupId = “test-consumer”)
    public void listen(String message) {
        logger.info(“接收消息: {}”, message);
    }
}

我们通过@KafkaListener注解来监听名称为test的Topic，消费者分组的组名为test-consumer。

演示

启动Spring Boot项目，启动过程中，控制台会输出Kafka的配置，启动好后，访问http://localhost:8080/send/hello,mrbird，控制台输出如下：

QQ截图20190326155948.png

@KafkaListener详解

@KafkaListener除了可以指定Topic名称和分组id外，我们还可以同时监听来自多个Topic的消息:

1	@KafkaListener(topics = “topic1, topic2”)

我们还可以通过@Header注解来获取当前消息来自哪个分区（partitions）:

@KafkaListener(topics = “test”, groupId = “test-consumer”)
public void listen(@Payload String message,
                   @Header(KafkaHeaders.RECEIVED_PARTITION_ID) int partition) {
    logger.info(“接收消息: {}，partition：{}”, message, partition);
}

重启项目，再次访问http://localhost:8080/send/hello,mrbird，控制台输出如下：

QQ图片20190326162014.png

因为我们没有进行分区，所以test Topic只有一个区，下标为0。

我们可以通过@KafkaListener来指定只接收来自特定分区的消息：

@KafkaListener(groupId = “test-consumer”,
        topicPartitions = @TopicPartition(topic = “test”,
                partitionOffsets = {
                        @PartitionOffset(partition = “0”, initialOffset = “0”)
            }))
public void listen(@Payload String message,
                   @Header(KafkaHeaders.RECEIVED_PARTITION_ID) int partition) {
    logger.info(“接收消息: {}，partition：{}”, message, partition);
}

如果不需要指定initialOffset，上面代码可以简化为：

1 2	@KafkaListener(groupId = “test-consumer”, topicPartitions = @TopicPartition(topic = “test”, partitions = { “0”, “1” }))

消息过滤器

我们可以为消息监听添加过滤器来过滤一些特定的信息。我们在消费者配置类KafkaConsumerConfig的kafkaListenerContainerFactory方法里配置过滤规则：

@Bean
public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
    ConcurrentKafkaListenerContainerFactory<String, String> factory
            = new ConcurrentKafkaListenerContainerFactory<>();
    factory.setConsumerFactory(consumerFactory());
    // ———- 过滤配置 ————
    factory.setRecordFilterStrategy(
            r -> r.value().contains(“fuck”)
    );
    return factory;
}

setRecordFilterStrategy接收RecordFilterStrategy<K, V>，他是一个函数式接口：

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public interface RecordFilterStrategy<K, V> {
    boolean filter(ConsumerRecord<K, V> var1);
}

所以我们用lambda表达式指定了上面这条规则，即如果消息内容包含fuck这个粗鄙之语的时候，则不接受消息。

配置好后我们重启项目，分别发送下面这两条请求：

http://localhost:8080/send/fuck,mrbird
http://localhost:8080/send/love,mrbird

观察控制台：

QQ截图20190326163502.png

可以看到，fuck,mrbird这条消息没有被接收。

发送复杂的消息

截至目前位置我们只发送了简单的字符串类型的消息，我们可以自定义消息转换器来发送复杂的消息。

定义消息实体

创建一个Message类：

public class Message implements Serializable {
    private static final long serialVersionUID = 6678420965611108427L;

    private String from;

    private String message;

    public Message() {

    }

    public Message(String from, String message) {
        this.from = from;
        this.message = message;
    }

    @Override
    public String toString() {
        return “Message{“ +
                “from=’” + from + ‘\’’ +
                “, message=’” + message + ‘\’’ +
                ‘}’;
    }

    // get set 略
}

改造消息生产者配置

@Configuration
public class KafkaProducerConfig {

    @Value(“${spring.kafka.bootstrap-servers}”)
    private String bootstrapServers;

    @Bean
    public ProducerFactory<String, Message> producerFactory() {
        Map<String, Object> configProps = new HashMap<>();
        configProps.put(
                ProducerConfig.BOOTSTRAP_SERVERS_CONFIG,
                bootstrapServers);
        configProps.put(
                ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,
                StringSerializer.class);
        configProps.put(
                ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,
                JsonSerializer.class);
        return new DefaultKafkaProducerFactory<>(configProps);
    }

    @Bean
    public KafkaTemplate<String, Message> kafkaTemplate() {
        return new KafkaTemplate<>(producerFactory());
    }
}

我们将value序列化策略指定为了Kafka提供的JsonSerializer，并且kafkaTemplate返回类型为KafkaTemplate<String, Message>。

发送新的消息

在SendMessageController里发送复杂的消息:

@Autowired
private KafkaTemplate<String, Message> kafkaTemplate;

@GetMapping(“send/{message}”)
public void sendMessage(@PathVariable String message) {
    this.kafkaTemplate.send(“test”, new Message(“mrbird”, message));
}

修改消费者配置

修改消费者配置KafkaConsumerConfig：

@EnableKafka
@Configuration
public class KafkaConsumerConfig {

    @Value(“${spring.kafka.bootstrap-servers}”)
    private String bootstrapServers;

    @Value(“${spring.kafka.consumer.group-id}”)
    private String consumerGroupId;

    @Value(“${spring.kafka.consumer.auto-offset-reset}”)
    private String autoOffsetReset;

    @Bean
    public ConsumerFactory<String, Message> consumerFactory() {
        Map<String, Object> props = new HashMap<>();
        props.put(
                ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,
                bootstrapServers);
        props.put(
                ConsumerConfig.GROUP_ID_CONFIG,
                consumerGroupId);
        props.put(
                ConsumerConfig.AUTO_OFFSET_RESET_CONFIG,
                autoOffsetReset);
        return new DefaultKafkaConsumerFactory<>(
                props,
                new StringDeserializer(),
                new JsonDeserializer<>(Message.class));
    }

    @Bean
    public ConcurrentKafkaListenerContainerFactory<String, Message> kafkaListenerContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<String, Message> factory
                = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory());
        return factory;
    }
}

修改消息监听

修改KafkaMessageListener：

@KafkaListener(topics = “test”, groupId = “test-consumer”)
public void listen(Message message) {
    logger.info(“接收消息: {}”, message);
}

重启项目，访问http://localhost:8080/send/hello，控制台输出如下：

QQ截图20190326171125.png

更多配置

spring.kafka.admin.client-id= # ID to pass to the server when making requests. Used for server-side logging.
spring.kafka.admin.fail-fast=false # Whether to fail fast if the broker is not available on startup.
spring.kafka.admin.properties.= # Additional admin-specific properties used to configure the client.
spring.kafka.admin.ssl.key-password= # Password of the private key in the key store file.
spring.kafka.admin.ssl.key-store-location= # Location of the key store file.
spring.kafka.admin.ssl.key-store-password= # Store password for the key store file.
spring.kafka.admin.ssl.key-store-type= # Type of the key store.
spring.kafka.admin.ssl.protocol= # SSL protocol to use.
spring.kafka.admin.ssl.trust-store-location= # Location of the trust store file.
spring.kafka.admin.ssl.trust-store-password= # Store password for the trust store file.
spring.kafka.admin.ssl.trust-store-type= # Type of the trust store.
spring.kafka.bootstrap-servers= # Comma-delimited list of host:port pairs to use for establishing the initial connections to the Kafka cluster. Applies to all components unless overridden.
spring.kafka.client-id= # ID to pass to the server when making requests. Used for server-side logging.
spring.kafka.consumer.auto-commit-interval= # Frequency with which the consumer offsets are auto-committed to Kafka if ‘enable.auto.commit’ is set to true.
spring.kafka.consumer.auto-offset-reset= # What to do when there is no initial offset in Kafka or if the current offset no longer exists on the server.
spring.kafka.consumer.bootstrap-servers= # Comma-delimited list of host:port pairs to use for establishing the initial connections to the Kafka cluster. Overrides the global property, for consumers.
spring.kafka.consumer.client-id= # ID to pass to the server when making requests. Used for server-side logging.
spring.kafka.consumer.enable-auto-commit= # Whether the consumer’s offset is periodically committed in the background.
spring.kafka.consumer.fetch-max-wait= # Maximum amount of time the server blocks before answering the fetch request if there isn’t sufficient data to immediately satisfy the requirement given by “fetch-min-size”.
spring.kafka.consumer.fetch-min-size= # Minimum amount of data the server should return for a fetch request.
spring.kafka.consumer.group-id= # Unique string that identifies the consumer group to which this consumer belongs.
spring.kafka.consumer.heartbeat-interval= # Expected time between heartbeats to the consumer coordinator.
spring.kafka.consumer.key-deserializer= # Deserializer class for keys.
spring.kafka.consumer.max-poll-records= # Maximum number of records returned in a single call to poll().
spring.kafka.consumer.properties.= # Additional consumer-specific properties used to configure the client.
spring.kafka.consumer.ssl.key-password= # Password of the private key in the key store file.
spring.kafka.consumer.ssl.key-store-location= # Location of the key store file.
spring.kafka.consumer.ssl.key-store-password= # Store password for the key store file.
spring.kafka.consumer.ssl.key-store-type= # Type of the key store.
spring.kafka.consumer.ssl.protocol= # SSL protocol to use.
spring.kafka.consumer.ssl.trust-store-location= # Location of the trust store file.
spring.kafka.consumer.ssl.trust-store-password= # Store password for the trust store file.
spring.kafka.consumer.ssl.trust-store-type= # Type of the trust store.
spring.kafka.consumer.value-deserializer= # Deserializer class for values.
spring.kafka.jaas.control-flag=required # Control flag for login configuration.
spring.kafka.jaas.enabled=false # Whether to enable JAAS configuration.
spring.kafka.jaas.login-module=com.sun.security.auth.module.Krb5LoginModule # Login module.
spring.kafka.jaas.options= # Additional JAAS options.
spring.kafka.listener.ack-count= # Number of records between offset commits when ackMode is “COUNT” or “COUNT_TIME”.
spring.kafka.listener.ack-mode= # Listener AckMode. See the spring-kafka documentation.
spring.kafka.listener.ack-time= # Time between offset commits when ackMode is “TIME” or “COUNT_TIME”.
spring.kafka.listener.client-id= # Prefix for the listener’s consumer client.id property.
spring.kafka.listener.concurrency= # Number of threads to run in the listener containers.
spring.kafka.listener.idle-event-interval= # Time between publishing idle consumer events (no data received).
spring.kafka.listener.log-container-config= # Whether to log the container configuration during initialization (INFO level).
spring.kafka.listener.monitor-interval= # Time between checks for non-responsive consumers. If a duration suffix is not specified, seconds will be used.
spring.kafka.listener.no-poll-threshold= # Multiplier applied to “pollTimeout” to determine if a consumer is non-responsive.
spring.kafka.listener.poll-timeout= # Timeout to use when polling the consumer.
spring.kafka.listener.type=single # Listener type.
spring.kafka.producer.acks= # Number of acknowledgments the producer requires the leader to have received before considering a request complete.
spring.kafka.producer.batch-size= # Default batch size.
spring.kafka.producer.bootstrap-servers= # Comma-delimited list of host:port pairs to use for establishing the initial connections to the Kafka cluster. Overrides the global property, for producers.
spring.kafka.producer.buffer-memory= # Total memory size the producer can use to buffer records waiting to be sent to the server.
spring.kafka.producer.client-id= # ID to pass to the server when making requests. Used for server-side logging.
spring.kafka.producer.compression-type= # Compression type for all data generated by the producer.
spring.kafka.producer.key-serializer= # Serializer class for keys.
spring.kafka.producer.properties.= # Additional producer-specific properties used to configure the client.
spring.kafka.producer.retries= # When greater than zero, enables retrying of failed sends.
spring.kafka.producer.ssl.key-password= # Password of the private key in the key store file.
spring.kafka.producer.ssl.key-store-location= # Location of the key store file.
spring.kafka.producer.ssl.key-store-password= # Store password for the key store file.
spring.kafka.producer.ssl.key-store-type= # Type of the key store.
spring.kafka.producer.ssl.protocol= # SSL protocol to use.
spring.kafka.producer.ssl.trust-store-location= # Location of the trust store file.
spring.kafka.producer.ssl.trust-store-password= # Store password for the trust store file.
spring.kafka.producer.ssl.trust-store-type= # Type of the trust store.
spring.kafka.producer.transaction-id-prefix= # When non empty, enables transaction support for producer.
spring.kafka.producer.value-serializer= # Serializer class for values.
spring.kafka.properties.= # Additional properties, common to producers and consumers, used to configure the client.
spring.kafka.ssl.key-password= # Password of the private key in the key store file.
spring.kafka.ssl.key-store-location= # Location of the key store file.
spring.kafka.ssl.key-store-password= # Store password for the key store file.
spring.kafka.ssl.key-store-type= # Type of the key store.
spring.kafka.ssl.protocol= # SSL protocol to use.
spring.kafka.ssl.trust-store-location= # Location of the trust store file.
spring.kafka.ssl.trust-store-password= # Store password for the trust store file.
spring.kafka.ssl.trust-store-type= # Type of the trust store.
spring.kafka.streams.application-id= # Kafka streams application.id property; default spring.application.name.
spring.kafka.streams.auto-startup=true # Whether or not to auto-start the streams factory bean.
spring.kafka.streams.bootstrap-servers= # Comma-delimited list of host:port pairs to use for establishing the initial connections to the Kafka cluster. Overrides the global property, for streams.
spring.kafka.streams.cache-max-size-buffering= # Maximum memory size to be used for buffering across all threads.
spring.kafka.streams.client-id= # ID to pass to the server when making requests. Used for server-side logging.
spring.kafka.streams.properties.*= # Additional Kafka properties used to configure the streams.
spring.kafka.streams.replication-factor= # The replication factor for change log topics and repartition topics created by the stream processing application.
spring.kafka.streams.ssl.key-password= # Password of the private key in the key store file.
spring.kafka.streams.ssl.key-store-location= # Location of the key store file.
spring.kafka.streams.ssl.key-store-password= # Store password for the key store file.
spring.kafka.streams.ssl.key-store-type= # Type of the key store.
spring.kafka.streams.ssl.protocol= # SSL protocol to use.
spring.kafka.streams.ssl.trust-store-location= # Location of the trust store file.
spring.kafka.streams.ssl.trust-store-password= # Store password for the trust store file.
spring.kafka.streams.ssl.trust-store-type= # Type of the trust store.
spring.kafka.streams.state-dir= # Directory location for the state store.
spring.kafka.template.default-topic= # Default topic to which messages are sent.