didn't accomplish this before because HDFS does not support the ByteBuffer pread interface, also because of its complexity. For the ByteBuffer pread, we have issue HDFS-3246 to track this, so further HDFS can also be easy as the 3.1 part described. ### 3.3 Make downstream API can accept ByteBuff or ByteBuffer as arguments The first obstacle when implementing the block off-heap reading is: many downstream of them into ByteBuff or NIO ByteBuffer interfaces. The three main API we need to refactor are: ## #1 ByteBuffer positional read interface (HBASE-21946); The ByteBuffer pread issue HDFS-3246 is still

AsynchronousFileChannel fileChannel = AsynchronousFileChannel.open(path, StandardOpenOption.READ); ByteBuffer buffer = ByteBuffer.allocate(1024); long position = 0; Future operation = fileChannel.read(buffer CompletionHandlerbytebuffer="">() { // Once the read operation finishes the CompletionHandler's completed() method will be called. @Override public void completed(Integer result, ByteBuffer attachment) method of the CompletionHandler will get called instead. @Override public void failed(Throwable exc, ByteBuffer attachment) { } ### 3. Writing Data ## • Writing Data Via a Future Path path = Paths.get("data/test-write

Integer.MAX_VALUE; } 如果启用 transientStorePoolEnable 机制，返回当前可用的 ByteBuffer 个数，即整个 isTransientStorePoolDeficient 方法的用意是是否还存在可用的 ByteBuffer，如果不存在，即表示 pageCache 繁忙。那什么是 transientStorePoolEnable 机制呢？ ### 3 ，该机制的控制参数就是 transientStorePoolEnable。 ## MappedFile 重点关注 MappedFile 的 ByteBuffer writeBuffer、MappedByteBuffer mapped ByteBuffer 这两个属性的初始化，因为这两个方法是写消息与查消息操作的直接数据结构。  两个关键点如下： • ByteBuffer writeBuffer 如果开启了 transientStorePoolEnable, 则使用 ByteBuffer.allocateDirect(fileSize), 创建(java.nio 的内存映射机制)。如果未开启, 则为空。 ## • MappedByteBuffer

Context ctx, RemotingCommand remotingCommand, ByteBuf out throws Exception { try { ByteBuffer header = remotingCommand.encodeHeader(); out.writeBytes(header); byte[] body = == frame) { return null; } ByteBuffer byteBuffer = frame.nioBuffer(); return RemotingCommand.decode(byteBuffer); } } ## 五 ：通信层的整体交互 ![Image](/uploads/documents/

java.nio.ByteBuffer, etc.) and is what all codecs work on. See Data Buffers and Codecs in the "Spring Core" section for more on this topic. The spring-core module provides byte[], ByteBuffer, DataBuffer and metadata values. By default only the basic codecs from spring-core for String, byte[], and ByteBuffer are registered. Adding spring-web provides access to more that can be registered as follows: Java

provided scope to avoid compile warnings. ### Chapter 8. Data Buffers and Codecs Java NIO provides ByteBuffer but many libraries build their own byte buffer API on top, especially for network operations where implementations of DataBuffer can grow and shrink on demand. 2. Wrap an existing byte[] or java.nio.ByteBuffer, which decorates the given data with a DataBuffer implementation and that does not involve allocation for others. #### 8.2. DataBuffer The DataBuffer interface offers similar operations as java.nio.ByteBuffer but also brings a few additional benefits some of which are inspired by the Netty ByteBuf. Below

and metadata values. By default only the basic codecs from spring-core for String, byte[], and ByteBuffer are registered. Adding spring-web provides access to more that can be registered as follows: Java

e7659ba76c4ea2f0c80ce7a723a/p226_3.jpg) 优化2 1. Unsafe 调用。由于大部分的数据通过 ByteBuffer 访问，这里带来的额外开销对最终性能也有很大影响。Java lib 中的 ByteBuffer 访问接口是非常安全的，但安全也意味着低效，一次访问会有很多次的边界检查，而且多层函数的调用也有很多额外开销。如果访问逻辑相对简单，对数据边界控制很有信心的情况下，可以直接调用

959eb/p571_1.jpg) HPROF 文件映射到内存的过程： // 1. 构建内存映射的 HprofBuffer 针对大文件的一种快速的读取方式，其原理是将文件流的通 道与 ByteBuffer 建立起关联，并只在真正发生读取时才从磁盘读取内容出来。 HprofBuffer buffer = new MemoryMappedFileBuffer(heapDumpFile); // 2

源码缩略不进行展示：初始化一些需要的对象 val (rdd, func) = ser.deserialize([RDD[T], (TaskContext, Iterator[T])] => U]) ByteBuffer.wrap(taskBinary.value), Thread.currentThread. getContextClassLoader) _executor DeserializeTime