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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