producer内存管理分析

1 概述

kafka producer调用RecordAccumulator#append来将消息存到本地内存。消息以TopicPartition为key分组存放，每个TopicPartition对应一个Deque；RcordBatch的消息实际存储在MemoryRecords中；MemoryRecords有Compressor和ByteBuffer两个主要的属性，消息就是存储在ByteBuffer中，Compressor用来将消息写进到ByteBuffer中。消息在生产内存中的模型大致如下：

2 RecordAccumulator#append

producer调用send方法的时候，调用RecordAccumulator#append将消息存放到内存中。这里需要注意的是，append获取了两次锁，这样做是为了减少锁的范围。

public RecordAppendResult append(TopicPartition tp,
                                     long timestamp,
                                     byte[] key,
                                     byte[] value,
                                     Callback callback,
                                     long maxTimeToBlock) throws InterruptedException {
        appendsInProgress.incrementAndGet();
        try {
            Deque<RecordBatch> dq = getOrCreateDeque(tp); // 获取tp对应的Deque<RecordBatch>
            synchronized (dq) { // 关键, 获取Deque<RecordBatch>的锁才操作
                if (closed)
                    throw new IllegalStateException("Cannot send after the producer is closed.");
            Deque<RecordBatch> dq = getOrCreateDeque(tp); // 获取tp对应的Deque<RecordBatch>
                RecordBatch last = dq.peekLast(); // 往最后一个RecordBatch添加
                if (last != null) { // 尝试添加，后面会详细讲
                    FutureRecordMetadata future = last.tryAppend(timestamp, key, value, callback, time.milliseconds());
                    if (future != null) //添加成功就返回了
                        return new RecordAppendResult(future, dq.size() > 1 || last.records.isFull(), false);
                }
            }
            // 没有添加成功，说明最后一个RecordBatch空间不足或者last == null
            // 关键, 如果消息体大于batchsize，那么会创建消息体大小的RecordBatch，即RecordBatch不一定和batchsize相等
            int size = Math.max(this.batchSize, Records.LOG_OVERHEAD + Record.recordSize(key, value));
            // 从BufferPool中分配内存，后面会详细讲
            ByteBuffer buffer = free.allocate(size, maxTimeToBlock);
            synchronized (dq) { // 重新获取锁，因为allocate的时候不需要锁dq，这里也是尽量减少锁粒度的一种思想
                if (closed)
                    throw new IllegalStateException("Cannot send after the producer is closed.");
                RecordBatch last = dq.peekLast();
                if (last != null) { // 可能在重新获取锁之前其他线程释放了内存，所以这里重新获取下
                    FutureRecordMetadata future = last.tryAppend(timestamp, key, value, callback, time.milliseconds());
                    if (future != null) {
                        free.deallocate(buffer);
                        return new RecordAppendResult(future, dq.size() > 1 || last.records.isFull(), false);
                    }
                }
                // 还没有获取到RecordBatch则申请内存创建新的RecordBatch
                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();
        }
    }

3 Compressor

上述代码调用RecordBatch#tryAppend尝试将消息放到RecordBatch，而RecordBatch#tryAppend又调用MemoryRecords#append。

public long append(long offset, long timestamp, byte[] key, byte[] value) {
        if (!writable)
            throw new IllegalStateException("Memory records is not writable");
        int size = Record.recordSize(key, value);
        compressor.putLong(offset);
        compressor.putInt(size);
        long crc = compressor.putRecord(timestamp, key, value);
        compressor.recordWritten(size + Records.LOG_OVERHEAD);
        return crc;
}

这里的关键是compressor，来分析下Compressor，以putInt为例，实际上是调用了DataOutputStream#writeInt方法

public void putInt(final int value) {
        try {
            appendStream.writeInt(value); // appendStream是DataOutputStream类型
        } catch (IOException e) {
            throw new KafkaException("I/O exception when writing to the append stream, closing", e);
        }
    }

看下Compressor是如何初始化的:

public Compressor(ByteBuffer buffer, CompressionType type) {
        // ...
        // create the stream
        bufferStream = new ByteBufferOutputStream(buffer);
        appendStream = wrapForOutput(bufferStream, type, COMPRESSION_DEFAULT_BUFFER_SIZE);
}
static public DataOutputStream wrapForOutput(ByteBufferOutputStream buffer, CompressionType type, int bufferSize) {
        try {
            switch (type) {
                case NONE:
                    return new DataOutputStream(buffer); // 封装了ByteBufferOutputStream
                case GZIP:
                    return new DataOutputStream(new GZIPOutputStream(buffer, bufferSize));
                case SNAPPY:
                    try {
                        OutputStream stream = (OutputStream) snappyOutputStreamSupplier.get().newInstance(buffer, bufferSize);
                        return new DataOutputStream(stream);
                    } catch (Exception e) {
                        throw new KafkaException(e);
                    }
                case LZ4:
                    try {
                        OutputStream stream = (OutputStream) lz4OutputStreamSupplier.get().newInstance(buffer);
                        return new DataOutputStream(stream);
                    } catch (Exception e) {
                        throw new KafkaException(e);
                    }
                default:
                    throw new IllegalArgumentException("Unknown compression type: " + type);
            }
        } catch (IOException e) {
            throw new KafkaException(e);
        }
    }

从上面代码可以看到，和ByteBuffer直接关联的是ByteBufferOutputStream；而DataOutputStream封装了ByteBufferOutputStream，负责处理压缩数据，直观上来看如下图：

4 BufferPool

BufferPool用于管理producer缓存池，使用配置项buffer.memory来指定缓存池的大小，默认是32M。

4.1 allocate

BufferPool#allocate用于从缓存池中申请内存。BufferPool维护了一个ByteBuffer的双端队列free，表示空闲的ByteBuffer，只有大小为batch.size的内存申请才会从free中去拿去，也就是说free中维护的ByteBuffer都是batch.size大小。

BufferPool几个关键属性

private final long totalMemory;
    private final int poolableSize; // 一块连续内存的大小，等于batch.size
    private final ReentrantLock lock;
    private final Deque<ByteBuffer> free; // 空闲的ByteBuffer列表，每个ByteBuffer都是batch.size大小，只有申请的内存等于batch.size大小才会从free中获取
    private final Deque<Condition> waiters;
    private long availableMemory; // 还有多少内存可以用，即buffer.memory-已用内存
    // ...
}

public ByteBuffer allocate(int size, long maxTimeToBlockMs) throws InterruptedException {
        if (size > this.totalMemory)
            throw new IllegalArgumentException("Attempt to allocate " + size
                                               + " bytes, but there is a hard limit of "
                                               + this.totalMemory
                                               + " on memory allocations.");
        this.lock.lock();
        try {
            if (size == poolableSize && !this.free.isEmpty()) // 关键，只有大小等于batch.size的时候才会从free中获取
                return this.free.pollFirst();
            int freeListSize = this.free.size() * this.poolableSize;
            // 剩余总内存够用，但是不能从free中获取，则将free释放一些，然后申请对应大小的内存
            if (this.availableMemory + freeListSize >= size) {
                freeUp(size); // 释放
                this.availableMemory -= size;
                lock.unlock();
                return ByteBuffer.allocate(size);
            } else {
                // 关键，剩余总内存不够了，则会阻塞，直到有足够的内存
                int accumulated = 0;
                ByteBuffer buffer = null;
                Condition moreMemory = this.lock.newCondition();
                long remainingTimeToBlockNs = TimeUnit.MILLISECONDS.toNanos(maxTimeToBlockMs);
                this.waiters.addLast(moreMemory); // 添加到等待队列尾
                while (accumulated < size) {
                    long startWaitNs = time.nanoseconds();
                    long timeNs;
                    boolean waitingTimeElapsed;
                    try {
                        waitingTimeElapsed = !moreMemory.await(remainingTimeToBlockNs, TimeUnit.NANOSECONDS); // 阻塞
                    } catch (InterruptedException e) {
                        this.waiters.remove(moreMemory);
                        throw e;
                    } finally {
                        long endWaitNs = time.nanoseconds();
                        timeNs = Math.max(0L, endWaitNs - startWaitNs);
                        this.waitTime.record(timeNs, time.milliseconds());
                    }
                    if (waitingTimeElapsed) {
                        this.waiters.remove(moreMemory);
                        throw new TimeoutException("Failed to allocate memory within the configured max blocking time " + maxTimeToBlockMs + " ms.");
                    }
                    remainingTimeToBlockNs -= timeNs;
                    // check if we can satisfy this request from the free list,
                    // otherwise allocate memory
                    if (accumulated == 0 && size == this.poolableSize && !this.free.isEmpty()) {
                        // just grab a buffer from the free list
                        buffer = this.free.pollFirst();
                        accumulated = size;
                    } else {
                        freeUp(size - accumulated);
                        int got = (int) Math.min(size - accumulated, this.availableMemory);
                        this.availableMemory -= got;
                        accumulated += got;
                    }
                }
                Condition removed = this.waiters.removeFirst(); // 从头部获取，后面详细讲
                if (removed != moreMemory)
                    throw new IllegalStateException("Wrong condition: this shouldn't happen.");
                // 如果分配后还有剩余空间，即唤醒后续的等待线程
                if (this.availableMemory > 0 || !this.free.isEmpty()) {
                    if (!this.waiters.isEmpty())
                        this.waiters.peekFirst().signal(); // 唤醒头部
                }
                // unlock and return the buffer
                lock.unlock();
                if (buffer == null)
                    return ByteBuffer.allocate(size);
                else
                    return buffer;
            }
        } finally {
            if (lock.isHeldByCurrentThread())
                lock.unlock();
        }
    }

对于allocate有几点需要注意

只有大小为batch.size的内存申请才会从free中获取，所以消息大小尽量不要大于batch.size，这样才能充分利用缓存池。为什么申请的内存会不等于batch.size呢，原因是在RecordAccumulator#append中有一句 int size = Math.max(this.batchSize, Records.LOG_OVERHEAD + Record.recordSize(key, value)), 即如果消息大小大于batch.size则会使用消息的大小申请内存。
下面代码可能有点疑惑, moreMemory是添加到waiters的尾部的，为什么获取的时候是从头部获取呢？这个原因是，线程唤醒只会唤醒waiters头部的线程，所以当线程被唤醒后，他肯定是已经在waiters头部了，也就是说排在他前面的线程都已经在他之前被唤醒并移除waiters了。
```
Condition removed = this.waiters.removeFirst(); // 从头部获取，后面详细讲
             if (removed != moreMemory)
                 throw new IllegalStateException("Wrong condition: this shouldn't happen.");
```
申请的总内存查过buffer.memory的时候会阻塞或者抛出异常

4.2 deallocate

BufferPool#deallocate用于将内存释放并放回到缓存池。同allocate一样，只有大小等于batch.size的内存块才会放到free中。

public void deallocate(ByteBuffer buffer) {
        deallocate(buffer, buffer.capacity());
}
public void deallocate(ByteBuffer buffer, int size) {
        lock.lock();
        try {
            if (size == this.poolableSize && size == buffer.capacity()) {
                buffer.clear();
                this.free.add(buffer);// 只有大小等于batch.size的内存块才会放到free中
            } else { // 否则的话只是availableMemory改变，无用的ByteBuffer会被GC清理掉
                this.availableMemory += size;
            }
            Condition moreMem = this.waiters.peekFirst(); // 唤醒waiters的头结点
            if (moreMem != null)
                moreMem.signal();
        } finally {
            lock.unlock();
        }
}