大数据技术之Hadoop_HDFS
参考：《尚硅谷》大数据学习，日常总结。
第1章 HDFS概述
1.1 HDFS产出背景及定义
1.2 HDFS优缺点
1.3 HDFS组成架构
1.4 HDFS文件块大小（面试重点）
第2章 HDFS的Shell操作（开发重点）
1．基本语法
bin/hadoop fs 具体命令
或者
bin/hdfs dfs 具体命令dfs是fs的实现类：
[[email protected] hadoop-2.7.2]$ hdfs dfs
Usage: hadoop fs [generic options]
[-appendToFile <localsrc> ... <dst>]
[-cat [-ignoreCrc] <src> ...]
[-checksum <src> ...]
[-chgrp [-R] GROUP PATH...]
[-chmod [-R] <MODE[,MODE]... | OCTALMODE> PATH...]
[-chown [-R] [OWNER][:[GROUP]] PATH...]
[-copyFromLocal [-f] [-p] [-l] <localsrc> ... <dst>]
[-copyToLocal [-p] [-ignoreCrc] [-crc] <src> ... <localdst>]
[-count [-q] [-h] <path> ...]
[-cp [-f] [-p | -p[topax]] <src> ... <dst>]
[-createSnapshot <snapshotDir> [<snapshotName>]]
[-deleteSnapshot <snapshotDir> <snapshotName>]
[-df [-h] [<path> ...]]
[-du [-s] [-h] <path> ...]
[-expunge]
[-find <path> ... <expression> ...]
[-get [-p] [-ignoreCrc] [-crc] <src> ... <localdst>]
[-getfacl [-R] <path>]
[-getfattr [-R] {-n name | -d} [-e en] <path>]
[-getmerge [-nl] <src> <localdst>]
[-help [cmd ...]]
[-ls [-d] [-h] [-R] [<path> ...]]
[-mkdir [-p] <path> ...]
[-moveFromLocal <localsrc> ... <dst>]
[-moveToLocal <src> <localdst>]
[-mv <src> ... <dst>]
[-put [-f] [-p] [-l] <localsrc> ... <dst>]
[-renameSnapshot <snapshotDir> <oldName> <newName>]
[-rm [-f] [-r|-R] [-skipTrash] <src> ...]
[-rmdir [--ignore-fail-on-non-empty] <dir> ...]
[-setfacl [-R] [{-b|-k} {-m|-x <acl_spec>} <path>]|[--set <acl_spec> <path>]]
[-setfattr {-n name [-v value] | -x name} <path>]
[-setrep [-R] [-w] <rep> <path> ...]
[-stat [format] <path> ...]
[-tail [-f] <file>]
[-test -[defsz] <path>]
[-text [-ignoreCrc] <src> ...]
[-touchz <path> ...]
[-truncate [-w] <length> <path> ...]
[-usage [cmd ...]]Generic options supported are
-conf <configuration file> specify an application configuration file
-D <property=value> use value for given property
-fs <local|namenode:port> specify a namenode
-jt <local|resourcemanager:port> specify a ResourceManager
-files <comma separated list of files> specify comma separated files to be copied to the map reduce cluster
-libjars <comma separated list of jars> specify comma separated jar files to include in the classpath.
-archives <comma separated list of archives> specify comma separated archives to be unarchived on the compute machines.The general command line syntax is
bin/hadoop command [genericOptions] [commandOptions][[email protected] hadoop-2.7.2]$ hadoop fs
Usage: hadoop fs [generic options]
[-appendToFile <localsrc> ... <dst>]
[-cat [-ignoreCrc] <src> ...]
[-checksum <src> ...]
[-chgrp [-R] GROUP PATH...]
[-chmod [-R] <MODE[,MODE]... | OCTALMODE> PATH...]
[-chown [-R] [OWNER][:[GROUP]] PATH...]
[-copyFromLocal [-f] [-p] [-l] <localsrc> ... <dst>]
[-copyToLocal [-p] [-ignoreCrc] [-crc] <src> ... <localdst>]
[-count [-q] [-h] <path> ...]
[-cp [-f] [-p | -p[topax]] <src> ... <dst>]
[-createSnapshot <snapshotDir> [<snapshotName>]]
[-deleteSnapshot <snapshotDir> <snapshotName>]
[-df [-h] [<path> ...]]
[-du [-s] [-h] <path> ...]
[-expunge]
[-find <path> ... <expression> ...]
[-get [-p] [-ignoreCrc] [-crc] <src> ... <localdst>]
[-getfacl [-R] <path>]
[-getfattr [-R] {-n name | -d} [-e en] <path>]
[-getmerge [-nl] <src> <localdst>]
[-help [cmd ...]]
[-ls [-d] [-h] [-R] [<path> ...]]
[-mkdir [-p] <path> ...]
[-moveFromLocal <localsrc> ... <dst>]
[-moveToLocal <src> <localdst>]
[-mv <src> ... <dst>]
[-put [-f] [-p] [-l] <localsrc> ... <dst>]
[-renameSnapshot <snapshotDir> <oldName> <newName>]
[-rm [-f] [-r|-R] [-skipTrash] <src> ...]
[-rmdir [--ignore-fail-on-non-empty] <dir> ...]
[-setfacl [-R] [{-b|-k} {-m|-x <acl_spec>} <path>]|[--set <acl_spec> <path>]]
[-setfattr {-n name [-v value] | -x name} <path>]
[-setrep [-R] [-w] <rep> <path> ...]
[-stat [format] <path> ...]
[-tail [-f] <file>]
[-test -[defsz] <path>]
[-text [-ignoreCrc] <src> ...]
[-touchz <path> ...]
[-truncate [-w] <length> <path> ...]
[-usage [cmd ...]]Generic options supported are
-conf <configuration file> specify an application configuration file
-D <property=value> use value for given property
-fs <local|namenode:port> specify a namenode
-jt <local|resourcemanager:port> specify a ResourceManager
-files <comma separated list of files> specify comma separated files to be copied to the map reduce cluster
-libjars <comma separated list of jars> specify comma separated jar files to include in the classpath.
-archives <comma separated list of archives> specify comma separated archives to be unarchived on the compute machines.The general command line syntax is
bin/hadoop command [genericOptions] [commandOptions][[email protected] hadoop-2.7.2]$
注： hadoop fs 是 dfs 的父类，两个都差不多。
2．命令大全
[[email protected] hadoop-2.7.2]$ bin/hadoop fs
[-appendToFile <localsrc> ... <dst>]
[-cat [-ignoreCrc] <src> ...]
[-checksum <src> ...]
[-chgrp [-R] GROUP PATH...]
[-chmod [-R] <MODE[,MODE]... | OCTALMODE> PATH...]
[-chown [-R] [OWNER][:[GROUP]] PATH...]
[-copyFromLocal [-f] [-p] <localsrc> ... <dst>]
[-copyToLocal [-p] [-ignoreCrc] [-crc] <src> ... <localdst>]
[-count [-q] <path> ...]
[-cp [-f] [-p] <src> ... <dst>]
[-createSnapshot <snapshotDir> [<snapshotName>]]
[-deleteSnapshot <snapshotDir> <snapshotName>]
[-df [-h] [<path> ...]]
[-du [-s] [-h] <path> ...]
[-expunge]
[-get [-p] [-ignoreCrc] [-crc] <src> ... <localdst>]
[-getfacl [-R] <path>]
[-getmerge [-nl] <src> <localdst>]
[-help [cmd ...]]
[-ls [-d] [-h] [-R] [<path> ...]]
[-mkdir [-p] <path> ...]
[-moveFromLocal <localsrc> ... <dst>]
[-moveToLocal <src> <localdst>]
[-mv <src> ... <dst>]
[-put [-f] [-p] <localsrc> ... <dst>]
[-renameSnapshot <snapshotDir> <oldName> <newName>]
[-rm [-f] [-r|-R] [-skipTrash] <src> ...]
[-rmdir [--ignore-fail-on-non-empty] <dir> ...]
[-setfacl [-R] [{-b|-k} {-m|-x <acl_spec>} <path>]|[--set <acl_spec> <path>]]
[-setrep [-R] [-w] <rep> <path> ...]
[-stat [format] <path> ...]
[-tail [-f] <file>]
[-test -[defsz] <path>]
[-text [-ignoreCrc] <src> ...]
[-touchz <path> ...]
[-usage [cmd ...]]
3．常用命令实操
（0）启动Hadoop集群（方便后续的测试）
[[email protected] hadoop-2.7.2]$ sbin/start-dfs.sh
[[email protected] hadoop-2.7.2]$ sbin/start-yarn.sh
（1）-help：输出这个命令参数
[[email protected] hadoop-2.7.2]$ hadoop fs -help rm
（2）-ls: 显示目录信息
[[email protected] hadoop-2.7.2]$ hadoop fs -ls /
（3）-mkdir：在HDFS上创建目录
[[email protected] hadoop-2.7.2]$ hadoop fs -mkdir -p /sanguo/shuguo
（4）-moveFromLocal：从本地剪切粘贴到HDFS
[[email protected] hadoop-2.7.2]$ touch kongming.txt
[[email protected] hadoop-2.7.2]$ hadoop fs -moveFromLocal ./kongming.txt /sanguo/shuguo
（5）-appendToFile：追加一个文件到已经存在的文件末尾
[[email protected] hadoop-2.7.2]$ touch liubei.txt
[[email protected] hadoop-2.7.2]$ vi liubei.txt
输入
san gu mao lu
[[email protected] hadoop-2.7.2]$ hadoop fs -appendToFile liubei.txt /sanguo/shuguo/kongming.txt
（6）-cat：显示文件内容
[[email protected] hadoop-2.7.2]$ hadoop fs -cat /sanguo/shuguo/kongming.txt
（7）-chgrp 、-chmod、-chown：Linux文件系统中的用法一样，修改文件所属权限
[[email protected] hadoop-2.7.2]$ hadoop fs -chmod 666 /sanguo/shuguo/kongming.txt
[[email protected] hadoop-2.7.2]$ hadoop fs -chown atguigu:atguigu /sanguo/shuguo/kongming.txt
（8）-copyFromLocal：从本地文件系统中拷贝文件到HDFS路径去
[[email protected] hadoop-2.7.2]$ hadoop fs -copyFromLocal README.txt /
（9）-copyToLocal：从HDFS拷贝到本地
[[email protected] hadoop-2.7.2]$ hadoop fs -copyToLocal /sanguo/shuguo/kongming.txt ./
（10）-cp ：从HDFS的一个路径拷贝到HDFS的另一个路径
[[email protected] hadoop-2.7.2]$ hadoop fs -cp /sanguo/shuguo/kongming.txt /zhuge.txt
（11）-mv：在HDFS目录中移动文件
[[email protected] hadoop-2.7.2]$ hadoop fs -mv /zhuge.txt /sanguo/shuguo/
（12）-get：等同于copyToLocal，就是从HDFS下载文件到本地
[[email protected] hadoop-2.7.2]$ hadoop fs -get /sanguo/shuguo/kongming.txt ./
（13）-getmerge：合并下载多个文件，比如HDFS的目录 /user/atguigu/test下有多个文件:log.1, log.2,log.3,...
[[email protected] hadoop-2.7.2]$ hadoop fs -getmerge /user/atguigu/test/* ./zaiyiqi.txt
（14）-put：等同于copyFromLocal
[[email protected] hadoop-2.7.2]$ hadoop fs -put ./zaiyiqi.txt /user/atguigu/test/
（15）-tail：显示一个文件的末尾
[[email protected] hadoop-2.7.2]$ hadoop fs -tail /sanguo/shuguo/kongming.txt
（16）-rm：删除文件或文件夹
[[email protected] hadoop-2.7.2]$ hadoop fs -rm /user/atguigu/test/jinlian2.txt
（17）-rmdir：删除空目录
[[email protected] hadoop-2.7.2]$ hadoop fs -mkdir /test
[[email protected] hadoop-2.7.2]$ hadoop fs -rmdir /test
（18）-du统计文件夹的大小信息
[[email protected] hadoop-2.7.2]$ hadoop fs -du -s -h /user/atguigu/test
2.7 K /user/atguigu/test[[email protected] hadoop-2.7.2]$ hadoop fs -du -h /user/atguigu/test
1.3 K /user/atguigu/test/README.txt
15 /user/atguigu/test/jinlian.txt
1.4 K /user/atguigu/test/zaiyiqi.txt
（19）-setrep：设置HDFS中文件的副本数量
[[email protected] hadoop-2.7.2]$ hadoop fs -setrep 10 /sanguo/shuguo/kongming.txt
注：这里设置的副本数只是记录在NameNode的元数据中，是否真的会有这么多副本，还得看DataNode的数量。因为目前只有3台设备，最多也就3个副本，只有节点数的增加到10台时，副本数才能达到10。
第3章 HDFS客户端操作（开发重点）
3.1 HDFS客户端环境准备
1．根据自己电脑的操作系统拷贝对应的编译后的hadoop jar包到非中文路径（例如：D:\Develop\hadoop-2.7.2）。
2．配置HADOOP_HOME环境变量。HADOOP_HOME=安装路径
3. 配置Path环境变量。%HADOOP_HOME%\bin
4．创建一个Maven工程HdfsClientDemo
注：只需要填写前面两个即可。
5．导入相应的依赖坐标+日志添加
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.atguigu</groupId>
<artifactId>Hdfs-0529</artifactId>
<version>0.0.1-SNAPSHOT</version><dependencies>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>RELEASE</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>2.8.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>jdk.tools</groupId>
<artifactId>jdk.tools</artifactId>
<version>1.8</version>
<scope>system</scope>
<systemPath>${JAVA_HOME}/lib/tools.jar</systemPath>
</dependency>
</dependencies>
</project>
注意：如果Eclipse/Idea打印不出日志，在控制台上只显示
1.log4j:WARN No appenders could be found for logger (org.apache.hadoop.util.Shell).
2.log4j:WARN Please initialize the log4j system properly.
3.log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
需要在项目的src/main/resources目录下，新建一个文件，命名为“log4j.properties”，在文件中填入
log4j.rootLogger=INFO, stdout
log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=%d %p [%c] - %m%n
log4j.appender.logfile=org.apache.log4j.FileAppender
log4j.appender.logfile.File=target/spring.log
log4j.appender.logfile.layout=org.apache.log4j.PatternLayout
log4j.appender.logfile.layout.ConversionPattern=%d %p [%c] - %m%n
6．创建包名：com.atguigu.hdfs
7．创建HdfsClient类
public class HdfsClient{
@Test
public void testMkdirs() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
// 配置在集群上运行
// configuration.set("fs.defaultFS", "hdfs://hadoop102:9000");
// FileSystem fs = FileSystem.get(configuration);
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 创建目录
fs.mkdirs(new Path("/1108/daxian/banzhang"));
// 3 关闭资源
fs.close();
}
}
8．执行程序
运行时需要配置用户名称
客户端去操作HDFS时，是有一个用户身份的。默认情况下，HDFS客户端API会从JVM中获取一个参数来作为自己的用户身份：-DHADOOP_USER_NAME=atguigu，atguigu为用户名称。
3.2 HDFS的API操作
3.2.1 HDFS文件上传（测试参数优先级）
1．编写源代码
@Test
public void testCopyFromLocalFile() throws IOException, InterruptedException, URISyntaxException {
// 1 获取文件系统
Configuration configuration = new Configuration();
configuration.set("dfs.replication", "2");
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 上传文件
fs.copyFromLocalFile(new Path("e:/banzhang.txt"), new Path("/banzhang.txt"));
// 3 关闭资源
fs.close();
System.out.println("over");
}
2．将hdfs-site.xml拷贝到项目的根目录下
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
</configuration>
3．参数优先级
参数优先级排序：（1）客户端代码中设置的值 >（2）ClassPath下的用户自定义配置文件 >（3）然后是服务器的默认配置
3.2.2 HDFS文件下载
@Test
public void testCopyToLocalFile() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 执行下载操作
// boolean delSrc 指是否将原文件删除
// Path src 指要下载的文件路径
// Path dst 指将文件下载到的路径
// boolean useRawLocalFileSystem 是否开启文件校验
fs.copyToLocalFile(false, new Path("/banzhang.txt"), new Path("e:/banhua.txt"), true);
// 3 关闭资源
fs.close();
}
3.2.3 HDFS文件夹删除
@Test
public void testDelete() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 执行删除
fs.delete(new Path("/0508/"), true);
// 3 关闭资源
fs.close();
}
3.2.4 HDFS文件名更改
@Test
public void testRename() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 修改文件名称
fs.rename(new Path("/banzhang.txt"), new Path("/banhua.txt"));
// 3 关闭资源
fs.close();
}
3.2.5 HDFS文件详情查看
查看文件名称、权限、长度、块信息
@Test
public void testListFiles() throws IOException, InterruptedException, URISyntaxException{
// 1获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 获取文件详情
RemoteIterator<LocatedFileStatus> listFiles = fs.listFiles(new Path("/"), true);
while(listFiles.hasNext()){
LocatedFileStatus status = listFiles.next();
// 输出详情
// 文件名称
System.out.println("文件名称: "+status.getPath().getName());
// 路径
System.out.println("路径: "+status.getPath());
// 长度
System.out.println("长度: "+status.getLen());
// 权限
System.out.println("权限: "+status.getPermission());
// 分组
System.out.println("分组: "+status.getGroup());
// 获取存储的块信息
BlockLocation[] blockLocations = status.getBlockLocations();
for (BlockLocation blockLocation : blockLocations) {
// 获取块存储的主机节点
String[] hosts = blockLocation.getHosts();
for (String host : hosts) {
System.out.println("存储的主机节点: "+host);
}
}
System.out.println("-----------班长的分割线----------");
}
// 3 关闭资源
fs.close();
}
3.2.6 HDFS文件和文件夹判断
@Test
public void testListStatus() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件配置信息
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 判断是文件还是文件夹
FileStatus[] listStatus = fs.listStatus(new Path("/"));
for (FileStatus fileStatus : listStatus) {
// 如果是文件
if (fileStatus.isFile()) {
System.out.println("f:"+fileStatus.getPath().getName());
}else {
System.out.println("d:"+fileStatus.getPath().getName());
}
}
// 3 关闭资源
fs.close();
}
3.3 HDFS的I/O流操作
上面我们学的API操作HDFS系统都是框架封装好的。那么如果我们想自己实现上述API的操作该怎么实现呢？
我们可以采用IO流的方式实现数据的上传和下载。
3.3.1 HDFS文件上传
1．需求：把本地e盘上的banhua.txt文件上传到HDFS根目录
2．编写代码
@Test
public void putFileToHDFS() throws IOException, InterruptedException, URISyntaxException {
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 创建输入流
FileInputStream fis = new FileInputStream(new File("e:/banhua.txt"));
// 3 获取输出流
FSDataOutputStream fos = fs.create(new Path("/banhua.txt"));
// 4 流对拷
IOUtils.copyBytes(fis, fos, configuration);
// 5 关闭资源
IOUtils.closeStream(fos);
IOUtils.closeStream(fis);
fs.close();
}
3.3.2 HDFS文件下载
1．需求：从HDFS上下载banhua.txt文件到本地e盘上
2．编写代码
// 文件下载
@Test
public void getFileFromHDFS() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 获取输入流
FSDataInputStream fis = fs.open(new Path("/banhua.txt"));
// 3 获取输出流
FileOutputStream fos = new FileOutputStream(new File("e:/banhua.txt"));
// 4 流的对拷
IOUtils.copyBytes(fis, fos, configuration);
// 5 关闭资源
IOUtils.closeStream(fos);
IOUtils.closeStream(fis);
fs.close();
}
3.3.3 定位文件读取
1．需求：分块读取HDFS上的大文件，比如根目录下的/hadoop-2.7.2.tar.gz
2．编写代码
（1）下载第一块
@Test
public void readFileSeek1() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 获取输入流
FSDataInputStream fis = fs.open(new Path("/hadoop-2.7.2.tar.gz"));
// 3 创建输出流
FileOutputStream fos = new FileOutputStream(new File("e:/hadoop-2.7.2.tar.gz.part1"));
// 4 流的拷贝
byte[] buf = new byte[1024];
for(int i =0 ; i < 1024 * 128; i++){
fis.read(buf);
fos.write(buf);
}
// 5关闭资源
IOUtils.closeStream(fis);
IOUtils.closeStream(fos);
fs.close();
}
（2）下载第二块
@Test
public void readFileSeek2() throws IOException, InterruptedException, URISyntaxException{
// 1 获取文件系统
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop102:9000"), configuration, "atguigu");
// 2 打开输入流
FSDataInputStream fis = fs.open(new Path("/hadoop-2.7.2.tar.gz"));
// 3 定位输入数据位置
fis.seek(1024*1024*128);
// 4 创建输出流
FileOutputStream fos = new FileOutputStream(new File("e:/hadoop-2.7.2.tar.gz.part2"));
// 5 流的对拷
IOUtils.copyBytes(fis, fos, configuration);
// 6 关闭资源
IOUtils.closeStream(fis);
IOUtils.closeStream(fos);
}
（3）合并文件
在Window命令窗口中进入到目录E:\，然后执行如下命令，对数据进行合并
type hadoop-2.7.2.tar.gz.part2 >> hadoop-2.7.2.tar.gz.part1
合并完成后，将hadoop-2.7.2.tar.gz.part1重新命名为hadoop-2.7.2.tar.gz。解压发现该tar包非常完整。