kafka发送消息-生产者发送消息的分区策略（消息发送到哪个分区中？是什么策略）

生产者发送消息的分区策略（消息发送到哪个分区中？是什么策略）

1、默认策略，程序自动计算并指定分区
- 1.1、指定key，不指定分区
- 1.2、不指定key，不指定分区
2、轮询分配策略RoundRobinPartitioner
- 2.1、创建配置类
- 2.2、application.yml文件
- 2.3、生产者
- 2.4、测试类
- 2.5、执行结果
3、自定义分区分配策略
- 3.1、创建自定义分配策略类
- 3.2、修改kafka配置类
- 3.3、application.yml文件
- 3.4、生产者
- 3.5、测试类
- 3.6、测试结果
- 3.7、总结

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1、默认策略，程序自动计算并指定分区

1.1、指定key，不指定分区

生产者：在编写代码发送消息时我们先不指定分区，即分区设为null，看看程序最终会把消息发送到哪个分区。

package com.power.producer;import com.power.model.User;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.header.Headers;
import org.apache.kafka.common.header.internals.RecordHeaders;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.KafkaHeaders;
import org.springframework.kafka.support.SendResult;
import org.springframework.messaging.Message;
import org.springframework.messaging.support.MessageBuilder;
import org.springframework.stereotype.Component;
import org.springframework.util.concurrent.ListenableFuture;import javax.annotation.Resource;
import java.nio.charset.StandardCharsets;
import java.util.Date;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutionException;@Component
public class EventProducer {@Resourceprivate KafkaTemplate<String,Object> kafkaTemplate2;public void send9(){User user = User.builder().id(1208).phone("16767667676").birthday(new Date()).build();//分区是null，让kafka自己去决定把消息发送到哪个分区kafkaTemplate2.send("heTopic",null,System.currentTimeMillis(),"k9",user);}
}

测试类：

package com.power;import com.power.model.User;
import com.power.producer.EventProducer;
import org.junit.jupiter.api.Test;
import org.springframework.boot.test.context.SpringBootTest;import javax.annotation.Resource;
import java.util.Date;@SpringBootTest
public class SpringBoot01KafkaBaseApplication {@Resourceprivate EventProducer eventProducer;@Testvoid send9(){eventProducer.send9();}
}

程序最终是通过以下代码进行目标分区计算的：

Utils.toPositive(Utils.murmur2(keyBytes)) % numPartitions;

通过调试发现，程序是通过以下代码进行目标分区计算的：
程序自动读取生产者发送消息时的key（本次发送时值为“key9”），将key生成一个32位的HASH值，将该HASH值与默认分区数（这个topic中有9个分区）取余数（余数结果一定在0-8之间），进而计算得出消息默认发送到的分区值

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1.2、不指定key，不指定分区

生产者：
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测试类：

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此时时通过随机数与默认分区取余数计算默认分区的

使用随机数 % numPartitions

2、轮询分配策略RoundRobinPartitioner

通过查看kafka源码发现，分区接口有一个轮询分配策略相关实现类。
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在application.yml配置文件中生产者配置项，我发现并生产者并没有相关轮询分配策略的配置，那么该如何试下轮询指定分区的配置呢？
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需要编写代码试下轮询指定分区策略：

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2.1、创建配置类

package com.power.config;import org.apache.kafka.clients.admin.NewTopic;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.RoundRobinPartitioner;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;import java.util.HashMap;
import java.util.Map;@Configuration
public class KafkaConfig {@Value("${spring.kafka.bootstrap-servers}")private String bootstrapServers;@Value("${spring.kafka.producer.key-serializer}")private String keySerializer;@Value("${spring.kafka.producer.value-serializer}")private String valueSerializer;public Map<String, Object> producerConfigs() {Map<String, Object> props = new HashMap<>();props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, keySerializer);props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, valueSerializer);props.put(ProducerConfig.PARTITIONER_CLASS_CONFIG, RoundRobinPartitioner.class);return props;}public ProducerFactory<String, ?> producerFactory() {return new DefaultKafkaProducerFactory<>(producerConfigs());}@Beanpublic KafkaTemplate<String, ?> kafkaTemplate() {return new KafkaTemplate<>(producerFactory());}//第二次创建@Beanpublic NewTopic newTopic9() {return new NewTopic("heTopic", 9, (short) 1);}
}

2.2、application.yml文件

spring:application:#应用名称name: spring-boot-01-kafka-base#kafka连接地址（ip+port）kafka:bootstrap-servers: <你的kafka服务器IP>:9092#配置生产者(有24个配置)producer:#key默认是StringSerializer序列化key-serializer: org.apache.kafka.common.serialization.StringSerializer#value默认是ToStringSerializer序列化value-serializer: org.springframework.kafka.support.serializer.ToStringSerializer#配置消费者(有24个配置)consumer:auto-offset-reset: earliesttemplate:default-topic: default-topic

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2.3、生产者

package com.power.producer;import com.power.model.User;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.header.Headers;
import org.apache.kafka.common.header.internals.RecordHeaders;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.KafkaHeaders;
import org.springframework.kafka.support.SendResult;
import org.springframework.messaging.Message;
import org.springframework.messaging.support.MessageBuilder;
import org.springframework.stereotype.Component;
import org.springframework.util.concurrent.ListenableFuture;import javax.annotation.Resource;
import java.nio.charset.StandardCharsets;
import java.util.Date;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutionException;@Component
public class EventProducer {@Resourceprivate KafkaTemplate<String,Object> kafkaTemplate2;public void send10(){User user = User.builder().id(1208).phone("16767667676").birthday(new Date()).build();//分区是null，让kafka自己去决定把消息发送到哪个分区kafkaTemplate2.send("heTopic",user);}
}

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2.4、测试类

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package com.power;import com.power.model.User;
import com.power.producer.EventProducer;
import org.junit.jupiter.api.Test;
import org.springframework.boot.test.context.SpringBootTest;import javax.annotation.Resource;
import java.util.Date;@SpringBootTest
public class SpringBoot01KafkaBaseApplication {@Resourceprivate EventProducer eventProducer;@Testvoid send10(){for (int i = 0; i <5 ; i++) {eventProducer.send10();}}}

2.5、执行结果

执行完测试类，发现5次请求分别发送到了kafka的heTopic主题的5个不同分区中：
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3、自定义分区分配策略

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3.1、创建自定义分配策略类

package com.power.config;import org.apache.kafka.clients.producer.Partitioner;
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.utils.Utils;import java.util.List;
import java.util.Map;
import java.util.concurrent.atomic.AtomicInteger;public class CustomerPartitioner implements Partitioner {private AtomicInteger nextPartition = new AtomicInteger(0);@Overridepublic int partition(String topic, Object key, byte[] keyBytes, Object value, byte[] valueBytes, Cluster cluster) {List<PartitionInfo> partitions = cluster.partitionsForTopic(topic);int numPartitions = partitions.size();if(key==null){//使用轮询方式选择分区int next = nextPartition.getAndIncrement();if(next>=numPartitions){nextPartition.compareAndSet(next,0);}if(next>0){next--;}System.out.println("分区值："+next);return next;}else {//如果key不为inull,则使用默认的分区策略return Utils.toPositive(Utils.murmur2(keyBytes)) % numPartitions;}}@Overridepublic void close() {}@Overridepublic void configure(Map<String, ?> configs) {}
}

3.2、修改kafka配置类

指定使用自定义的分区分配类
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3.3、application.yml文件

spring:application:#应用名称name: spring-boot-01-kafka-base#kafka连接地址（ip+port）kafka:bootstrap-servers: <你的kafka服务器IP>:9092#配置生产者(有24个配置)producer:#key默认是StringSerializer序列化key-serializer: org.apache.kafka.common.serialization.StringSerializer#value默认是ToStringSerializer序列化value-serializer: org.springframework.kafka.support.serializer.ToStringSerializer#配置消费者(有24个配置)consumer:auto-offset-reset: earliesttemplate:default-topic: default-topic

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3.4、生产者

package com.power.producer;import com.power.model.User;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.header.Headers;
import org.apache.kafka.common.header.internals.RecordHeaders;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.KafkaHeaders;
import org.springframework.kafka.support.SendResult;
import org.springframework.messaging.Message;
import org.springframework.messaging.support.MessageBuilder;
import org.springframework.stereotype.Component;
import org.springframework.util.concurrent.ListenableFuture;import javax.annotation.Resource;
import java.nio.charset.StandardCharsets;
import java.util.Date;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutionException;@Component
public class EventProducer {@Resourceprivate KafkaTemplate<String,Object> kafkaTemplate2;public void send10(){User user = User.builder().id(1208).phone("16767667676").birthday(new Date()).build();//分区是null，让kafka自己去决定把消息发送到哪个分区kafkaTemplate2.send("heTopic",user);}
}

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3.5、测试类

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package com.power;import com.power.model.User;
import com.power.producer.EventProducer;
import org.junit.jupiter.api.Test;
import org.springframework.boot.test.context.SpringBootTest;import javax.annotation.Resource;
import java.util.Date;@SpringBootTest
public class SpringBoot01KafkaBaseApplication {@Resourceprivate EventProducer eventProducer;@Testvoid send10(){for (int i = 0; i <5 ; i++) {eventProducer.send10();}}}

3.6、测试结果

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3.7、总结

使用自定义分区策略类尝试发送消息，发现发送的5次消息，并没有连续发送到5个挨着的分区中，查看kafka源码的org.apache.kafka.clients.producer.KafkaProducer类的doSend方法发现，每一次发送前，调用了两次计算分区的方法，导致第一个得到的分区并不会正在的发送消息。

doSend方法；

private Future<RecordMetadata> doSend(ProducerRecord<K, V> record, Callback callback) {TopicPartition tp = null;try {throwIfProducerClosed();// first make sure the metadata for the topic is availablelong nowMs = time.milliseconds();ClusterAndWaitTime clusterAndWaitTime;try {clusterAndWaitTime = waitOnMetadata(record.topic(), record.partition(), nowMs, maxBlockTimeMs);} catch (KafkaException e) {if (metadata.isClosed())throw new KafkaException("Producer closed while send in progress", e);throw e;}nowMs += clusterAndWaitTime.waitedOnMetadataMs;long remainingWaitMs = Math.max(0, maxBlockTimeMs - clusterAndWaitTime.waitedOnMetadataMs);Cluster cluster = clusterAndWaitTime.cluster;byte[] serializedKey;try {serializedKey = keySerializer.serialize(record.topic(), record.headers(), record.key());} catch (ClassCastException cce) {throw new SerializationException("Can't convert key of class " + record.key().getClass().getName() +" to class " + producerConfig.getClass(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG).getName() +" specified in key.serializer", cce);}byte[] serializedValue;try {serializedValue = valueSerializer.serialize(record.topic(), record.headers(), record.value());} catch (ClassCastException cce) {throw new SerializationException("Can't convert value of class " + record.value().getClass().getName() +" to class " + producerConfig.getClass(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG).getName() +" specified in value.serializer", cce);}int partition = partition(record, serializedKey, serializedValue, cluster);tp = new TopicPartition(record.topic(), partition);setReadOnly(record.headers());Header[] headers = record.headers().toArray();int serializedSize = AbstractRecords.estimateSizeInBytesUpperBound(apiVersions.maxUsableProduceMagic(),compressionType, serializedKey, serializedValue, headers);ensureValidRecordSize(serializedSize);long timestamp = record.timestamp() == null ? nowMs : record.timestamp();if (log.isTraceEnabled()) {log.trace("Attempting to append record {} with callback {} to topic {} partition {}", record, callback, record.topic(), partition);}// producer callback will make sure to call both 'callback' and interceptor callbackCallback interceptCallback = new InterceptorCallback<>(callback, this.interceptors, tp);if (transactionManager != null && transactionManager.isTransactional()) {transactionManager.failIfNotReadyForSend();}RecordAccumulator.RecordAppendResult result = accumulator.append(tp, timestamp, serializedKey,serializedValue, headers, interceptCallback, remainingWaitMs, true, nowMs);if (result.abortForNewBatch) {int prevPartition = partition;partitioner.onNewBatch(record.topic(), cluster, prevPartition);partition = partition(record, serializedKey, serializedValue, cluster);tp = new TopicPartition(record.topic(), partition);if (log.isTraceEnabled()) {log.trace("Retrying append due to new batch creation for topic {} partition {}. The old partition was {}", record.topic(), partition, prevPartition);}// producer callback will make sure to call both 'callback' and interceptor callbackinterceptCallback = new InterceptorCallback<>(callback, this.interceptors, tp);result = accumulator.append(tp, timestamp, serializedKey,serializedValue, headers, interceptCallback, remainingWaitMs, false, nowMs);}if (transactionManager != null && transactionManager.isTransactional())transactionManager.maybeAddPartitionToTransaction(tp);if (result.batchIsFull || result.newBatchCreated) {log.trace("Waking up the sender since topic {} partition {} is either full or getting a new batch", record.topic(), partition);this.sender.wakeup();}return result.future;// handling exceptions and record the errors;// for API exceptions return them in the future,// for other exceptions throw directly} catch (ApiException e) {log.debug("Exception occurred during message send:", e);if (callback != null)callback.onCompletion(null, e);this.errors.record();this.interceptors.onSendError(record, tp, e);return new FutureFailure(e);} catch (InterruptedException e) {this.errors.record();this.interceptors.onSendError(record, tp, e);throw new InterruptException(e);} catch (KafkaException e) {this.errors.record();this.interceptors.onSendError(record, tp, e);throw e;} catch (Exception e) {// we notify interceptor about all exceptions, since onSend is called before anything else in this methodthis.interceptors.onSendError(record, tp, e);throw e;}
}