旧 的 HBase 接口逻辑与传统 JDBC 方式很不相同，新的接口与传统 JDBC 的逻辑更加相像，具有更加清晰的 Connection 管理方式。

同时，在旧的接口中，客户端何时将 Put 写到服务端也需要设置，一个 Put 马上写到服务端，还是攒到一批写到服务端，新用户往往对此不太清楚。

在新的接口中，引入了 BufferedMutator，可以提供更加高效清晰的写操作。

HBase 0.98 与 HBase 1.0 接口名称对比

举一个例子，旧的 API 写入操作的代码：

新的 API 写入操作的代码：

可以看到，在操作前，首先建立连接，然后拿到一个对应表的句柄，之后再进行一系列操作。以上两个是同步写操作。

下面看一下批量异步写入接口：

org.apache.hadoop.hbase.client.BufferedMutator主要用来对HBase的单个表进行操作。它和Put类的作用差不多，但是主要用来实现批量的异步写操作。

BufferedMutator替换了HTable的setAutoFlush(false)的作用。

可以从Connection的实例中获取BufferedMutator的实例。在使用完成后需要调用close()方法关闭连接。对BufferedMutator进行配置需要通过BufferedMutatorParams完成。

MapReduce Job的是BufferedMutator使用的典型场景。MapReduce作业需要批量写入，但是无法找到恰当的点执行flush。

BufferedMutator接收MapReduce作业发送来的Put数据后，会根据某些因素（比如接收的Put数据的总量）启发式地执行Batch Put操作，且会异步的提交Batch Put请求，这样MapReduce作业的执行也不会被打断。

BufferedMutator也可以用在一些特殊的情况上。MapReduce作业的每个线程将会拥有一个独立的BufferedMutator对象。

一个独立的BufferedMutator也可以用在大容量的在线系统上来执行批量Put操作，但是这时需要注意一些极端情况比如JVM异常或机器故障，此时有可能造成数据丢失。

官方源码路径：/hbase-2.0.4/hbase-examples/src/main/java/org/apache/hadoop/hbase/client/example/BufferedMutatorExample.java

/** * * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements.  See the NOTICE file * distributed with this work for additional information * regarding copyright ownership.  The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License.  You may obtain a copy of the License at * *     http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */package org.apache.hadoop.hbase.client.example;import java.io.IOException;import java.util.ArrayList;import java.util.List;import java.util.concurrent.Callable;import java.util.concurrent.ExecutionException;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;import java.util.concurrent.Future;import java.util.concurrent.TimeUnit;import java.util.concurrent.TimeoutException;import org.apache.hadoop.conf.Configured;import org.apache.hadoop.hbase.TableName;import org.apache.hadoop.hbase.client.BufferedMutator;import org.apache.hadoop.hbase.client.BufferedMutatorParams;import org.apache.hadoop.hbase.client.Connection;import org.apache.hadoop.hbase.client.ConnectionFactory;import org.apache.hadoop.hbase.client.Put;import org.apache.hadoop.hbase.client.RetriesExhaustedWithDetailsException;import org.apache.hadoop.hbase.util.Bytes;import org.apache.hadoop.util.Tool;import org.apache.hadoop.util.ToolRunner;import org.apache.yetus.audience.InterfaceAudience;import org.slf4j.Logger;import org.slf4j.LoggerFactory;/** * An example of using the {
     @link BufferedMutator} interface. */@InterfaceAudience.Privatepublic class BufferedMutatorExample extends Configured implements Tool {  private static final Logger LOG = LoggerFactory.getLogger(BufferedMutatorExample.class);  private static final int POOL_SIZE = 10;  private static final int TASK_COUNT = 100;  private static final TableName TABLE = TableName.valueOf("foo");  private static final byte[] FAMILY = Bytes.toBytes("f");  @Override  public int run(String[] args) throws InterruptedException, ExecutionException, TimeoutException {    /** a callback invoked when an asynchronous write fails. */    final BufferedMutator.ExceptionListener listener = new BufferedMutator.ExceptionListener() {      @Override      public void onException(RetriesExhaustedWithDetailsException e, BufferedMutator mutator) {        for (int i = 0; i < e.getNumExceptions(); i++) {          LOG.info("Failed to sent put " + e.getRow(i) + ".");        }      }    };    BufferedMutatorParams params = new BufferedMutatorParams(TABLE)        .listener(listener);    //    // step 1: create a single Connection and a BufferedMutator, shared by all worker threads.    //    try (final Connection conn = ConnectionFactory.createConnection(getConf());         final BufferedMutator mutator = conn.getBufferedMutator(params)) {      /** worker pool that operates on BufferedTable instances */      final ExecutorService workerPool = Executors.newFixedThreadPool(POOL_SIZE);      List
      
       
        > futures = new ArrayList<>(TASK_COUNT);      for (int i = 0; i < TASK_COUNT; i++) {        futures.add(workerPool.submit(new Callable
        
         () {          @Override          public Void call() throws Exception {            //            // step 2: each worker sends edits to the shared BufferedMutator instance. They all use            // the same backing buffer, call-back "listener", and RPC executor pool.            //            Put p = new Put(Bytes.toBytes("someRow"));            p.addColumn(FAMILY, Bytes.toBytes("someQualifier"), Bytes.toBytes("some value"));            mutator.mutate(p);            // do work... maybe you want to call mutator.flush() after many edits to ensure any of            // this worker's edits are sent before exiting the Callable            return null;          }        }));      }      //      // step 3: clean up the worker pool, shut down.      //      for (Future
         
           f : futures) {        f.get(5, TimeUnit.MINUTES);      }      workerPool.shutdown();    } catch (IOException e) {      // exception while creating/destroying Connection or BufferedMutator      LOG.info("exception while creating/destroying Connection or BufferedMutator", e);    } // BufferedMutator.close() ensures all work is flushed. Could be the custom listener is      // invoked from here.    return 0;  }  public static void main(String[] args) throws Exception {    ToolRunner.run(new BufferedMutatorExample(), args);  }}