kafka源码解析——第一篇：producer

妖狐艹你老母 2021-09-21 02:08 313阅读 0赞

**1.生产者代码**

import org.apache.kafka.clients.producer.Callback;
    import org.apache.kafka.clients.producer.KafkaProducer;
    import org.apache.kafka.clients.producer.ProducerRecord;
    import org.apache.kafka.clients.producer.RecordMetadata;
    
    import java.util.Properties;
    
    
    public class Producer { 
        private static final String TOPIC = "test1115";
        private static final String BROKER_LIST = "localhost:9092";
        private static KafkaProducer<String, String> producer = null;
    
        static { 
            Properties configs = initConfig();//初始化参数
            producer = new KafkaProducer<String, String>(configs);//生产者实例化
        }
    
        private static Properties initConfig() { 
            Properties props = new Properties();
            props.put("bootstrap.servers", "localhost:9092");
            props.put("acks", "all");
            props.put("retries", 0);
            props.put("batch.size", 16384);
            props.put("linger.ms", 1);
            props.put("buffer.memory", 33554432);
            //序列化方式
            props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
            props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
            return props;
        }
    
        public static void main(String[] args) { 
            try { 
                String message = "hello world";
                while (true) { 
                    ProducerRecord<String, String> record = new ProducerRecord<String, String>(TOPIC, "0", message);
                    producer.send(record);
                    System.out.println(1);
                    Thread.sleep(1000);
                }
            } catch (Exception e) { 
                e.printStackTrace();
            } finally { 
                producer.close();
            }
        }
    }

**2.kafka生产者原理**  
客户端把消息放入队列中，然后由一个消息发送线程从队列中拉取消息，以批量的方式发送消息给服务端。  
RecordAccumulator----记录收集器(缓存生产者客户端产生的消息)  
Sender线程----读取记录收集器的批量信息，通过网络发送给服务端  
Selector----选择器(处理网络连接和读写处理)  
NetworkClient-----处理客户端网络请求  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80MzI5MTA1NQ_size_16_color_FFFFFF_t_70]  
流程分析：

public Future<RecordMetadata> send(ProducerRecord<K, V> record, Callback callback) { 
            ProducerRecord<K, V> interceptedRecord = this.interceptors.onSend(record);//拦截处理
            return this.doSend(interceptedRecord, callback);
        }

private Future<RecordMetadata> doSend(ProducerRecord<K, V> record, Callback callback) { 
            TopicPartition tp = null;
    
            try { 
                this.throwIfProducerClosed();
    
                KafkaProducer.ClusterAndWaitTime clusterAndWaitTime;
                try { 
                    clusterAndWaitTime = this.waitOnMetadata(record.topic(), record.partition(), this.maxBlockTimeMs);//获取metadata元数据
                } catch (KafkaException var19) { 
                    if (this.metadata.isClosed()) { 
                        throw new KafkaException("Producer closed while send in progress", var19);
                    }
    
                    throw var19;
                }
    
                long remainingWaitMs = Math.max(0L, this.maxBlockTimeMs - clusterAndWaitTime.waitedOnMetadataMs);
                Cluster cluster = clusterAndWaitTime.cluster;
    			//序列化相关，key、value
                byte[] serializedKey;
                try { 
                    serializedKey = this.keySerializer.serialize(record.topic(), record.headers(), record.key());
                } catch (ClassCastException var18) { 
                    throw new SerializationException("Can't convert key of class " + record.key().getClass().getName() + " to class " + this.producerConfig.getClass("key.serializer").getName() + " specified in key.serializer", var18);
                }
    
                byte[] serializedValue;
                try { 
                    serializedValue = this.valueSerializer.serialize(record.topic(), record.headers(), record.value());
                } catch (ClassCastException var17) { 
                    throw new SerializationException("Can't convert value of class " + record.value().getClass().getName() + " to class " + this.producerConfig.getClass("value.serializer").getName() + " specified in value.serializer", var17);
                }
    			
                int partition = this.partition(record, serializedKey, serializedValue, cluster);//选择合适分区
                tp = new TopicPartition(record.topic(), partition);
                this.setReadOnly(record.headers());
                Header[] headers = record.headers().toArray();
                int serializedSize = AbstractRecords.estimateSizeInBytesUpperBound(this.apiVersions.maxUsableProduceMagic(), this.compressionType, serializedKey, serializedValue, headers);
                this.ensureValidRecordSize(serializedSize);
                long timestamp = record.timestamp() == null ? this.time.milliseconds() : record.timestamp();
                this.log.trace("Sending record {} with callback {} to topic {} partition {}", new Object[]{ record, callback, record.topic(), partition});
                Callback interceptCallback = new KafkaProducer.InterceptorCallback(callback, this.interceptors, tp);
                if (this.transactionManager != null && this.transactionManager.isTransactional()) { 
                    this.transactionManager.maybeAddPartitionToTransaction(tp);
                }
                //将数据追加到消息缓存中
                RecordAppendResult result = this.accumulator.append(tp, timestamp, serializedKey, serializedValue, headers, interceptCallback, remainingWaitMs);
                if (result.batchIsFull || result.newBatchCreated) { 
                    this.log.trace("Waking up the sender since topic {} partition {} is either full or getting a new batch", record.topic(), partition);
                    this.sender.wakeup();//将数据发送出去
                }
    
                return result.future;
            } catch (ApiException var20) { 
                this.log.debug("Exception occurred during message send:", var20);
                if (callback != null) { 
                    callback.onCompletion((RecordMetadata)null, var20);
                }
    
                this.errors.record();
                this.interceptors.onSendError(record, tp, var20);
                return new KafkaProducer.FutureFailure(var20);
            } catch (InterruptedException var21) { 
                this.errors.record();
                this.interceptors.onSendError(record, tp, var21);
                throw new InterruptException(var21);
            } catch (BufferExhaustedException var22) { 
                this.errors.record();
                this.metrics.sensor("buffer-exhausted-records").record();
                this.interceptors.onSendError(record, tp, var22);
                throw var22;
            } catch (KafkaException var23) { 
                this.errors.record();
                this.interceptors.onSendError(record, tp, var23);
                throw var23;
            } catch (Exception var24) { 
                this.interceptors.onSendError(record, tp, var24);
                throw var24;
            }
        }

参考：  
kafka技术内幕  
kafka源码分析  
✨新鲜出炉~ Kafka训练营课件链接：  
链接：https://pan.baidu.com/s/1sPdmkDM3P74BfTc9VchZbw  
提取码：1beu

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