之前咱们剖析了Producer的配置解析、组件剖析、拉取元数据、音讯的初步序列化形式、音讯的路由策略。如下图:
这一节咱们持续剖析发送音讯的内存缓冲器原理—RecordAccumulator.append()。
如何将音讯放入内存缓冲器的?
在doSend中的,拉取元数据、音讯的初步序列化形式、音讯的路由策略之后就是accumulator.append()。
如下代码所示:(去除了多余的日志和异样解决,截取了外围代码)
private Future<RecordMetadata> doSend(ProducerRecord<K, V> record, Callback callback) { TopicPartition tp = null; try { //拉取元数据、音讯的初步序列化形式、音讯的路由策略 long waitedOnMetadataMs = waitOnMetadata(record.topic(), this.maxBlockTimeMs); long remainingWaitMs = Math.max(0, this.maxBlockTimeMs - waitedOnMetadataMs); byte[] serializedKey = keySerializer.serialize(record.topic(), record.key()); byte[] serializedValue = valueSerializer.serialize(record.topic(), record.value()); int serializedSize = Records.LOG_OVERHEAD + Record.recordSize(serializedKey, serializedValue); ensureValidRecordSize(serializedSize); tp = new TopicPartition(record.topic(), partition); long timestamp = record.timestamp() == null ? time.milliseconds() : record.timestamp(); Callback interceptCallback = this.interceptors == null ? callback : new InterceptorCallback<>(callback, this.interceptors, tp); // 将路由后果、初步序列化的音讯放入到音讯内存缓冲器中 RecordAccumulator.RecordAppendResult result = accumulator.append(tp, timestamp, serializedKey, serializedValue, interceptCallback, remainingWaitMs); if (result.batchIsFull || result.newBatchCreated) { this.sender.wakeup(); } return result.future; } catch (Exception e) { throw e; } //省略其余各种异样捕捉 }
accumulator.append() 它次要是将路由后果、初步序列化的音讯放入到音讯内存缓冲器中。
剖析如何将音讯放入内存缓冲器之前,须要回顾下它外部的根本构造。之前组件剖析的时候,咱们初步剖析过RecordAccumulator的大体构造,如下图:
1)设置了一些参数 batchSize、totalSize、retryBackoffMs、lingerMs、compression等
2)初始化了一些数据结构,比方batches是一个 new CopyOnWriteMap<>()
3)初始化了BufferPool和IncompleteRecordBatches
回顾了RecordAccumulator这个组件之后,咱们就来看看到底如何将音讯放入内存缓冲器的数据结构中的。
public RecordAppendResult append(TopicPartition tp, long timestamp, byte[] key, byte[] value, Callback callback, long maxTimeToBlock) throws InterruptedException { // We keep track of the number of appending thread to make sure we do not miss batches in // abortIncompleteBatches(). appendsInProgress.incrementAndGet(); try { // check if we have an in-progress batch Deque<RecordBatch> dq = getOrCreateDeque(tp); synchronized (dq) { if (closed) throw new IllegalStateException("Cannot send after the producer is closed."); RecordAppendResult appendResult = tryAppend(timestamp, key, value, callback, dq); if (appendResult != null) return appendResult; } // we don't have an in-progress record batch try to allocate a new batch int size = Math.max(this.batchSize, Records.LOG_OVERHEAD + Record.recordSize(key, value)); log.trace("Allocating a new {} byte message buffer for topic {} partition {}", size, tp.topic(), tp.partition()); ByteBuffer buffer = free.allocate(size, maxTimeToBlock); synchronized (dq) { // Need to check if producer is closed again after grabbing the dequeue lock. if (closed) throw new IllegalStateException("Cannot send after the producer is closed."); RecordAppendResult appendResult = tryAppend(timestamp, key, value, callback, dq); if (appendResult != null) { // Somebody else found us a batch, return the one we waited for! Hopefully this doesn't happen often... free.deallocate(buffer); return appendResult; } MemoryRecords records = MemoryRecords.emptyRecords(buffer, compression, this.batchSize); RecordBatch batch = new RecordBatch(tp, records, time.milliseconds()); FutureRecordMetadata future = Utils.notNull(batch.tryAppend(timestamp, key, value, callback, time.milliseconds())); dq.addLast(batch); incomplete.add(batch); return new RecordAppendResult(future, dq.size() > 1 || batch.records.isFull(), true); } } finally { appendsInProgress.decrementAndGet(); }}
整个办法的脉络,看着逻辑比拟多,波及了很多数据结构,咱们一步一步来剖析下。第一次看的话,大体你能够梳理如下脉络:
1)getOrCreateDeque 这个办法应该是才创立一个双端队列,队列放的每一个元素不是单条音讯Record,而是音讯的汇合RecordBatch。
2)free.allocate 应该是在分配内存缓冲器中的内存
3)tryAppend 应该是将音讯放入内存中
创立寄存音讯汇合的队列
在将音讯放入内存缓冲器之前,首先通过getOrCreateDeque 创立的是一个寄存音讯汇合的队列。代码如下:
private final ConcurrentMap<TopicPartition, Deque<RecordBatch>> batches;public RecordAccumulator(int batchSize, long totalSize, CompressionType compression, long lingerMs, long retryBackoffMs, Metrics metrics, Time time) { //省略... this.batches = new CopyOnWriteMap<>(); //省略...}/** * Get the deque for the given topic-partition, creating it if necessary. */private Deque<RecordBatch> getOrCreateDeque(TopicPartition tp) { Deque<RecordBatch> d = this.batches.get(tp); if (d != null) return d; d = new ArrayDeque<>(); Deque<RecordBatch> previous = this.batches.putIfAbsent(tp, d); if (previous == null) return d; else return previous;}
这个创立的内存构造能够看到,是一个变量 batches,它是一个CopyOnWriteMap。这个数据结构之前咱们组件图初步剖析过。再联合这段代码,不难理解它的脉络:
这个map次要依据Topic分区信息作为key,value是一个队列外围数据结构是RecordBatch,因为是第一次给某个topic分区发送的音讯,value为空,须要初始化队列,否则阐明已经给这个topic的分区发送给数据,value非空,间接返回之前的队列。
因为咱们这里是第一次向test-topic发送音讯,所以能够失去下图的数据结构:
之后执行了一段加锁逻辑,之前提到,tryAppend应该是将音讯放入内存中。然而因为队列是刚创立的,deque.peekLast();必定是空,所以这段加锁的代码不会执行。
synchronized (dq) { if (closed) throw new IllegalStateException("Cannot send after the producer is closed."); RecordAppendResult appendResult = tryAppend(timestamp, key, value, callback, dq); if (appendResult != null) return appendResult; } private RecordAppendResult tryAppend(long timestamp, byte[] key, byte[] value, Callback callback, Deque<RecordBatch> deque){ RecordBatch last = deque.peekLast(); if (last != null) { FutureRecordMetadata future = last.tryAppend(timestamp, key, value, callback, time.milliseconds()); if (future == null) last.records.close(); else return new RecordAppendResult(future, deque.size() > 1 || last.records.isFull(), false); } return null; }
然而到这里你会发现代码一个显著的特点,应用了synchronized加锁和线程平安的内存构造CopyOnWriteMap,这些都是显著线程平安的管制。
为什么呢?因为同一个Producer能够应用多线程进行发送音讯,必然要思考线程平安的很多货色。
为什么选用CopyOnWriteMap,而不必ConcurrentHashMap呢?你能够思考下。(这里给个提醒,JDK成长记提到过,CopyOnWriteMap它的底层是写时复制,适宜读多写少的场景)
synchronized加锁代码块应用了,分段加锁,并没有暴力的在办法上加synchronized。这也是一个应用亮点。
写在结尾的话
到这里,你会发现在中间件会大量的见到并发包下的组件的应用,工作中你用到可能都是百里挑一,这些组件的应用是咱们钻研中间件源码值得学习的一点。
你肯定要多思考为什么,不要停留在是什么,怎么用上,这个思维须要刻意训练,心愿你能够缓缓养成。
好了,明天的内容就到这里,之前有同学反馈,每一节的只是太过于干了,实实在在的干货!看起来有时候会比拟吃力,所以之后的章节尽量会防止上万字的大章节,会管制在6000字左右。
另外,除了成长记外,我偶然也会分享我本人的故事和行业中遇见的事件,心愿大家从我的经验中能够有另一番成长和播种,比方我是如何学习和晋升技术的?我是如何画图的?我如何做技术分享的等等。
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