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parent
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@ -54,7 +54,7 @@
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3. [集群资源管理器——YARN](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-YARN.md)
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4. [Hadoop单机伪集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/hadoop%E5%8D%95%E6%9C%BA%E7%89%88%E6%9C%AC%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md)
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5. [HDFS常用Shell命令](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HDFS常用Shell命令.md)
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6. HDFS Java API详解
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6. [HDFS Java API的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HDFS-Java-API.md)
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## 二、Hive
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@ -1,5 +1,6 @@
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# HDFS Java API
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<nav>
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# HDFS Java API
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<nav>
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<a href="#一-简介">一、 简介</a><br/>
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<a href="#二API的使用">二、API的使用</a><br/>
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<a href="#21-FileSystem">2.1 FileSystem</a><br/>
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@ -18,370 +19,372 @@
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<a href="#214-查看文件的块信息">2.14 查看文件的块信息</a><br/>
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</nav>
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## 一、 简介
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Hadoop提供了简单易用的Java API用于操作HDFS。通过这些API,我们可以通过编程来更灵活的操作HDFS。同时从编程体验上来说,这些API的设计确实非常人性化,基本上你只需要一行代码就能完成相应的操作。
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想要使用HDFS API,你只需要导入`hadoop-client`这个依赖包即可。以下关于API的操作我均使用单元测试的方法进行演示,完整的POM文件如下:
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```xml
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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0
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http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<groupId>com.heibaiying</groupId>
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<artifactId>hdfs-java-api</artifactId>
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<version>1.0</version>
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<properties>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<hadoop.version>2.6.0-cdh5.15.2</hadoop.version>
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</properties>
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<!---配置CDH仓库地址-->
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<repositories>
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<repository>
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<id>cloudera</id>
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<url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
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</repository>
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</repositories>
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<dependencies>
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<!--Hadoop-client-->
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<dependency>
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<groupId>org.apache.hadoop</groupId>
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<artifactId>hadoop-client</artifactId>
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<version>${hadoop.version}</version>
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</dependency>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>
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<version>4.12</version>
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<scope>test</scope>
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</dependency>
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</dependencies>
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</project>
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```
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## 二、API的使用
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### 2.1 FileSystem
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FileSystem是操作HDFS的入口,通过FileSystem我们可以完成对HDFS上文件和目录的所有操作。在使用前需要获取它,这里由于之后的每个单元测试都需要用到FileSystem,所以使用`@Before`注解进行标注。
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```java
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private static final String HDFS_PATH = "hdfs://192.168.0.106:8020";
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private static final String HDFS_USER = "root";
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private static FileSystem fileSystem;
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@Before
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public void prepare() {
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try {
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Configuration configuration = new Configuration();
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// 这里我启动的是单节点的Hadoop,副本系数可以设置为1,不设置的话默认值为3
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configuration.set("dfs.replication", "1");
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fileSystem = FileSystem.get(new URI(HDFS_PATH), configuration, HDFS_USER);
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} catch (IOException e) {
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e.printStackTrace();
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} catch (InterruptedException e) {
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e.printStackTrace();
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} catch (URISyntaxException e) {
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e.printStackTrace();
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}
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}
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@After
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public void destroy() {
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fileSystem = null;
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}
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```
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### 2.2 创建目录
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这里目录可以是多级,支持递归创建。
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```java
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@Test
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public void mkDir() throws Exception {
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fileSystem.mkdirs(new Path("/hdfs-api/test0/"));
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}
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```
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### 2.3 创建指定权限的目录
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这里`FsPermission(FsAction u, FsAction g, FsAction o)` 的三个参数分别对应创建者权限,同组其他用户权限,其他用户权限,可以使用`FsAction`枚举类中的值进行指定。
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```java
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@Test
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public void mkDirWithPermission() throws Exception {
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fileSystem.mkdirs(new Path("/hdfs-api/test1/"),
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new FsPermission(FsAction.READ_WRITE, FsAction.READ, FsAction.READ));
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}
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```
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### 2.4 创建文件,并写入内容
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```java
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@Test
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public void create() throws Exception {
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// 如果文件存在,默认会覆盖, 可以通过第二个参数进行控制。第三个参数可以控制使用缓冲区的大小
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FSDataOutputStream out = fileSystem.create(new Path("/hdfs-api/test/a.txt"),
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true, 4096);
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out.write("hello hadoop!".getBytes());
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out.write("hello spark!".getBytes());
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out.write("hello flink!".getBytes());
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// 强制将缓冲区中内容刷出
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out.flush();
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out.close();
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}
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```
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### 2.5 判断文件是否存在
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```java
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@Test
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public void exist() throws Exception {
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boolean exists = fileSystem.exists(new Path("/hdfs-api/test/a.txt"));
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System.out.println(exists);
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}
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```
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### 2.6 查看文件内容
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这里我们查看的是一个小文件的内容,所以直接转换成字符串后输出,对于大文件,还是应该从输出流中读取数据,分批处理。
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```java
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@Test
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public void readToString() throws Exception {
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FSDataInputStream inputStream = fileSystem.open(new Path("/hdfs-api/test/a.txt"));
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String context = inputStreamToString(inputStream, "utf-8");
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System.out.println(context);
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}
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```
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inputStreamToString 是一个自定义方法,实现如下:
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```java
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/**
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* 把输入流转换为指定编码的字符
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*
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* @param inputStream 输入流
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* @param encode 指定编码类型
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*/
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private static String inputStreamToString(InputStream inputStream, String encode) {
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try {
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if (encode == null || ("".equals(encode))) {
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encode = "utf-8";
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}
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BufferedReader reader = new BufferedReader(new InputStreamReader(inputStream, encode));
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StringBuilder builder = new StringBuilder();
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String str = "";
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while ((str = reader.readLine()) != null) {
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builder.append(str).append("\n");
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}
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return builder.toString();
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} catch (IOException e) {
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e.printStackTrace();
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}
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return null;
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}
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```
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### 2.7 文件重命名
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```java
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@Test
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public void rename() throws Exception {
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Path oldPath = new Path("/hdfs-api/test/a.txt");
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Path newPath = new Path("/hdfs-api/test/b.txt");
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boolean result = fileSystem.rename(oldPath, newPath);
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System.out.println(result);
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}
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```
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### 2.8 删除目录或文件
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```java
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public void delete() throws Exception {
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/*
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* 第二个参数代表是否递归删除
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* + 如果path是一个目录且递归删除为true, 则删除该目录及其中所有文件;
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* + 如果path是一个目录但递归删除为false,则会则抛出异常。
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*/
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boolean result = fileSystem.delete(new Path("/hdfs-api/test/b.txt"), true);
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System.out.println(result);
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}
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```
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### 2.9 上传文件到HDFS
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```java
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@Test
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public void copyFromLocalFile() throws Exception {
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// 如果指定的是目录,则会把目录及其中的文件都复制到指定目录下
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Path src = new Path("D:\\BigData-Notes\\notes\\installation");
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Path dst = new Path("/hdfs-api/test/");
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fileSystem.copyFromLocalFile(src, dst);
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}
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```
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### 2.10 上传大文件并显示上传进度
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```java
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@Test
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public void copyFromLocalBigFile() throws Exception {
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File file = new File("D:\\kafka.tgz");
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final float fileSize = file.length();
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InputStream in = new BufferedInputStream(new FileInputStream(file));
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FSDataOutputStream out = fileSystem.create(new Path("/hdfs-api/test/kafka5.tgz"),
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new Progressable() {
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long fileCount = 0;
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public void progress() {
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fileCount++;
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// progress方法每上传大约64KB的数据后就会被调用一次
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System.out.println("上传进度:" + (fileCount * 64 * 1024 / fileSize) * 100 + " %");
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}
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});
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IOUtils.copyBytes(in, out, 4096);
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}
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```
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### 2.11 从HDFS上下载文件
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```java
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@Test
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public void copyToLocalFile() throws Exception {
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Path src = new Path("/hdfs-api/test/kafka.tgz");
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Path dst = new Path("D:\\app\\");
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/*
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* 第一个参数控制下载完成后是否删除源文件,默认是true,即删除;
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* 最后一个参数表示是否将RawLocalFileSystem用作本地文件系统;
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* RawLocalFileSystem默认为false,通常情况下可以不设置,
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* 但如果你在执行时候抛出NullPointerException异常,则代表你的文件系统与程序可能存在不兼容的情况(window下常见),
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* 此时可以将RawLocalFileSystem设置为true
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||||
*/
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||||
fileSystem.copyToLocalFile(false, src, dst, true);
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}
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```
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||||
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||||
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||||
|
||||
### 2.12 查看指定目录下所有文件的信息
|
||||
|
||||
```java
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public void listFiles() throws Exception {
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FileStatus[] statuses = fileSystem.listStatus(new Path("/hdfs-api"));
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||||
for (FileStatus fileStatus : statuses) {
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||||
//fileStatus的toString方法被重写过,直接打印可以看到所有信息
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||||
System.out.println(fileStatus.toString());
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||||
}
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||||
}
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||||
```
|
||||
|
||||
FileStatus中包含了文件的基本信息,比如文件路径,是否是文件夹,修改时间,访问时间,所有者,所属组,文件权限,是否是符号链接等,输出内容示例如下(这里为了直观,我对输出进行了换行显示):
|
||||
|
||||
```properties
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||||
FileStatus{
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||||
path=hdfs://192.168.0.106:8020/hdfs-api/test;
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||||
isDirectory=true;
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||||
modification_time=1556680796191;
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||||
access_time=0;
|
||||
owner=root;
|
||||
group=supergroup;
|
||||
permission=rwxr-xr-x;
|
||||
isSymlink=false
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.13 递归查看指定目录下所有文件的信息
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void listFilesRecursive() throws Exception {
|
||||
RemoteIterator<LocatedFileStatus> files = fileSystem.listFiles(new Path("/hbase"), true);
|
||||
while (files.hasNext()) {
|
||||
System.out.println(files.next());
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
这里输出和上面类似,只是多了文本大小,副本系数,块大小等信息。
|
||||
|
||||
```properties
|
||||
LocatedFileStatus{
|
||||
path=hdfs://192.168.0.106:8020/hbase/hbase.version;
|
||||
isDirectory=false;
|
||||
length=7;
|
||||
replication=1;
|
||||
blocksize=134217728;
|
||||
modification_time=1554129052916;
|
||||
access_time=1554902661455;
|
||||
owner=root; group=supergroup;
|
||||
permission=rw-r--r--;
|
||||
isSymlink=false}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.14 查看文件的块信息
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void getFileBlockLocations() throws Exception {
|
||||
|
||||
FileStatus fileStatus = fileSystem.getFileStatus(new Path("/hdfs-api/test/kafka.tgz"));
|
||||
BlockLocation[] blocks = fileSystem.getFileBlockLocations(fileStatus, 0, fileStatus.getLen());
|
||||
for (BlockLocation block : blocks) {
|
||||
System.out.println(block);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
块输出信息比较简单,第一个值是文件的起始偏移量(offset),第二个值是文件大小(length),第三个是块所在的主机名(hosts)。
|
||||
|
||||
```
|
||||
0,57028557,hadoop001
|
||||
```
|
||||
|
||||
这里我上传的文件比较小,只有57M(小于128M),且程序中设置了副本系数为1,所有只有一个块信息,如果文件很大,则这里会输出文件所有块的信息。
|
||||
|
||||
|
||||
|
||||
## 一、 简介
|
||||
|
||||
Hadoop提供了简单易用的Java API用于操作HDFS。通过这些API,我们可以通过编程来更灵活的操作HDFS。同时从编程体验上来说,这些API的设计确实非常人性化,基本上你只需要一行代码就能完成相应的操作。
|
||||
|
||||
想要使用HDFS API,你只需要导入`hadoop-client`这个依赖包即可。以下关于API的操作我均使用单元测试的方法进行演示,完整的POM文件如下:
|
||||
|
||||
```xml
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<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.heibaiying</groupId>
|
||||
<artifactId>hdfs-java-api</artifactId>
|
||||
<version>1.0</version>
|
||||
|
||||
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<hadoop.version>2.6.0-cdh5.15.2</hadoop.version>
|
||||
</properties>
|
||||
|
||||
|
||||
<!---配置CDH仓库地址-->
|
||||
<repositories>
|
||||
<repository>
|
||||
<id>cloudera</id>
|
||||
<url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
|
||||
</repository>
|
||||
</repositories>
|
||||
|
||||
|
||||
<dependencies>
|
||||
<!--Hadoop-client-->
|
||||
<dependency>
|
||||
<groupId>org.apache.hadoop</groupId>
|
||||
<artifactId>hadoop-client</artifactId>
|
||||
<version>${hadoop.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>junit</groupId>
|
||||
<artifactId>junit</artifactId>
|
||||
<version>4.12</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
</project>
|
||||
```
|
||||
|
||||
|
||||
|
||||
## 二、API的使用
|
||||
|
||||
### 2.1 FileSystem
|
||||
|
||||
FileSystem是操作HDFS的入口,通过FileSystem我们可以完成对HDFS上文件和目录的所有操作。在使用前需要获取它,这里由于之后的每个单元测试都需要用到FileSystem,所以使用`@Before`注解进行标注。
|
||||
|
||||
```java
|
||||
private static final String HDFS_PATH = "hdfs://192.168.0.106:8020";
|
||||
private static final String HDFS_USER = "root";
|
||||
private static FileSystem fileSystem;
|
||||
|
||||
@Before
|
||||
public void prepare() {
|
||||
try {
|
||||
Configuration configuration = new Configuration();
|
||||
// 这里我启动的是单节点的Hadoop,副本系数可以设置为1,不设置的话默认值为3
|
||||
configuration.set("dfs.replication", "1");
|
||||
fileSystem = FileSystem.get(new URI(HDFS_PATH), configuration, HDFS_USER);
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
} catch (InterruptedException e) {
|
||||
e.printStackTrace();
|
||||
} catch (URISyntaxException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@After
|
||||
public void destroy() {
|
||||
fileSystem = null;
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.2 创建目录
|
||||
|
||||
这里目录可以是多级,支持递归创建。
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void mkDir() throws Exception {
|
||||
fileSystem.mkdirs(new Path("/hdfs-api/test0/"));
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.3 创建指定权限的目录
|
||||
|
||||
这里`FsPermission(FsAction u, FsAction g, FsAction o)` 的三个参数分别对应创建者权限,同组其他用户权限,其他用户权限,可以使用`FsAction`枚举类中的值进行指定。
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void mkDirWithPermission() throws Exception {
|
||||
fileSystem.mkdirs(new Path("/hdfs-api/test1/"),
|
||||
new FsPermission(FsAction.READ_WRITE, FsAction.READ, FsAction.READ));
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.4 创建文件,并写入内容
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void create() throws Exception {
|
||||
// 如果文件存在,默认会覆盖, 可以通过第二个参数进行控制。第三个参数可以控制使用缓冲区的大小
|
||||
FSDataOutputStream out = fileSystem.create(new Path("/hdfs-api/test/a.txt"),
|
||||
true, 4096);
|
||||
out.write("hello hadoop!".getBytes());
|
||||
out.write("hello spark!".getBytes());
|
||||
out.write("hello flink!".getBytes());
|
||||
// 强制将缓冲区中内容刷出
|
||||
out.flush();
|
||||
out.close();
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.5 判断文件是否存在
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void exist() throws Exception {
|
||||
boolean exists = fileSystem.exists(new Path("/hdfs-api/test/a.txt"));
|
||||
System.out.println(exists);
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.6 查看文件内容
|
||||
|
||||
这里我们查看的是一个小文件的内容,所以直接转换成字符串后输出,对于大文件,还是应该从输出流中读取数据,分批处理。
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void readToString() throws Exception {
|
||||
FSDataInputStream inputStream = fileSystem.open(new Path("/hdfs-api/test/a.txt"));
|
||||
String context = inputStreamToString(inputStream, "utf-8");
|
||||
System.out.println(context);
|
||||
}
|
||||
```
|
||||
|
||||
inputStreamToString 是一个自定义方法,实现如下:
|
||||
|
||||
```java
|
||||
/**
|
||||
* 把输入流转换为指定编码的字符
|
||||
*
|
||||
* @param inputStream 输入流
|
||||
* @param encode 指定编码类型
|
||||
*/
|
||||
private static String inputStreamToString(InputStream inputStream, String encode) {
|
||||
try {
|
||||
if (encode == null || ("".equals(encode))) {
|
||||
encode = "utf-8";
|
||||
}
|
||||
BufferedReader reader = new BufferedReader(new InputStreamReader(inputStream, encode));
|
||||
StringBuilder builder = new StringBuilder();
|
||||
String str = "";
|
||||
while ((str = reader.readLine()) != null) {
|
||||
builder.append(str).append("\n");
|
||||
}
|
||||
return builder.toString();
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
return null;
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.7 文件重命名
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void rename() throws Exception {
|
||||
Path oldPath = new Path("/hdfs-api/test/a.txt");
|
||||
Path newPath = new Path("/hdfs-api/test/b.txt");
|
||||
boolean result = fileSystem.rename(oldPath, newPath);
|
||||
System.out.println(result);
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.8 删除目录或文件
|
||||
|
||||
```java
|
||||
public void delete() throws Exception {
|
||||
/*
|
||||
* 第二个参数代表是否递归删除
|
||||
* + 如果path是一个目录且递归删除为true, 则删除该目录及其中所有文件;
|
||||
* + 如果path是一个目录但递归删除为false,则会则抛出异常。
|
||||
*/
|
||||
boolean result = fileSystem.delete(new Path("/hdfs-api/test/b.txt"), true);
|
||||
System.out.println(result);
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.9 上传文件到HDFS
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void copyFromLocalFile() throws Exception {
|
||||
// 如果指定的是目录,则会把目录及其中的文件都复制到指定目录下
|
||||
Path src = new Path("D:\\BigData-Notes\\notes\\installation");
|
||||
Path dst = new Path("/hdfs-api/test/");
|
||||
fileSystem.copyFromLocalFile(src, dst);
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.10 上传大文件并显示上传进度
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void copyFromLocalBigFile() throws Exception {
|
||||
|
||||
File file = new File("D:\\kafka.tgz");
|
||||
final float fileSize = file.length();
|
||||
InputStream in = new BufferedInputStream(new FileInputStream(file));
|
||||
|
||||
FSDataOutputStream out = fileSystem.create(new Path("/hdfs-api/test/kafka5.tgz"),
|
||||
new Progressable() {
|
||||
long fileCount = 0;
|
||||
|
||||
public void progress() {
|
||||
fileCount++;
|
||||
// progress方法每上传大约64KB的数据后就会被调用一次
|
||||
System.out.println("上传进度:" + (fileCount * 64 * 1024 / fileSize) * 100 + " %");
|
||||
}
|
||||
});
|
||||
|
||||
IOUtils.copyBytes(in, out, 4096);
|
||||
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.11 从HDFS上下载文件
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void copyToLocalFile() throws Exception {
|
||||
Path src = new Path("/hdfs-api/test/kafka.tgz");
|
||||
Path dst = new Path("D:\\app\\");
|
||||
/*
|
||||
* 第一个参数控制下载完成后是否删除源文件,默认是true,即删除;
|
||||
* 最后一个参数表示是否将RawLocalFileSystem用作本地文件系统;
|
||||
* RawLocalFileSystem默认为false,通常情况下可以不设置,
|
||||
* 但如果你在执行时候抛出NullPointerException异常,则代表你的文件系统与程序可能存在不兼容的情况(window下常见),
|
||||
* 此时可以将RawLocalFileSystem设置为true
|
||||
*/
|
||||
fileSystem.copyToLocalFile(false, src, dst, true);
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.12 查看指定目录下所有文件的信息
|
||||
|
||||
```java
|
||||
public void listFiles() throws Exception {
|
||||
FileStatus[] statuses = fileSystem.listStatus(new Path("/hdfs-api"));
|
||||
for (FileStatus fileStatus : statuses) {
|
||||
//fileStatus的toString方法被重写过,直接打印可以看到所有信息
|
||||
System.out.println(fileStatus.toString());
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
FileStatus中包含了文件的基本信息,比如文件路径,是否是文件夹,修改时间,访问时间,所有者,所属组,文件权限,是否是符号链接等,输出内容示例如下(这里为了直观,我对输出进行了换行显示):
|
||||
|
||||
```properties
|
||||
FileStatus{
|
||||
path=hdfs://192.168.0.106:8020/hdfs-api/test;
|
||||
isDirectory=true;
|
||||
modification_time=1556680796191;
|
||||
access_time=0;
|
||||
owner=root;
|
||||
group=supergroup;
|
||||
permission=rwxr-xr-x;
|
||||
isSymlink=false
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.13 递归查看指定目录下所有文件的信息
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void listFilesRecursive() throws Exception {
|
||||
RemoteIterator<LocatedFileStatus> files = fileSystem.listFiles(new Path("/hbase"), true);
|
||||
while (files.hasNext()) {
|
||||
System.out.println(files.next());
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
这里输出和上面类似,只是多了文本大小,副本系数,块大小等信息。
|
||||
|
||||
```properties
|
||||
LocatedFileStatus{
|
||||
path=hdfs://192.168.0.106:8020/hbase/hbase.version;
|
||||
isDirectory=false;
|
||||
length=7;
|
||||
replication=1;
|
||||
blocksize=134217728;
|
||||
modification_time=1554129052916;
|
||||
access_time=1554902661455;
|
||||
owner=root; group=supergroup;
|
||||
permission=rw-r--r--;
|
||||
isSymlink=false}
|
||||
```
|
||||
|
||||
|
||||
|
||||
### 2.14 查看文件的块信息
|
||||
|
||||
```java
|
||||
@Test
|
||||
public void getFileBlockLocations() throws Exception {
|
||||
|
||||
FileStatus fileStatus = fileSystem.getFileStatus(new Path("/hdfs-api/test/kafka.tgz"));
|
||||
BlockLocation[] blocks = fileSystem.getFileBlockLocations(fileStatus, 0, fileStatus.getLen());
|
||||
for (BlockLocation block : blocks) {
|
||||
System.out.println(block);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
块输出信息比较简单,第一个值是文件的起始偏移量(offset),第二个值是文件大小(length),第三个是块所在的主机名(hosts)。
|
||||
|
||||
```
|
||||
0,57028557,hadoop001
|
||||
```
|
||||
|
||||
这里我上传的文件比较小,只有57M(小于128M),且程序中设置了副本系数为1,所有只有一个块信息,如果文件很大,则这里会输出文件所有块的信息。
|
||||
|
||||
<br/>
|
||||
|
||||
<br/>
|
||||
|
||||
**以上所有测试用例源码可以从本仓库进行下载**:[HDFS Java API](https://github.com/heibaiying/BigData-Notes/tree/master/code/Hadoop/hdfs-java-api)
|
Loading…
x
Reference in New Issue
Block a user