京公网安备 11010802034615号
经营许可证编号:京B2-20210330
rm -rf /opt/linuxsir/hadoop/logs/*.*
ssh root@192.168.31.132 rm -rf /opt/linuxsir/hadoop/logs/*.*
ssh root@192.168.31.133 rm -rf /opt/linuxsir/hadoop/logs/*.*
clear
cd /opt/linuxsir/hadoop/sbin
./start-dfs.sh
./start-yarn.sh
clear
jps
ssh root@192.168.31.132 jps
ssh root@192.168.31.133 jps
在eclipse里面操作如下:
New-Java Project,名称自定义即可,如 java-prjNew-Package,名称自定义为com.pai.hdfs_demoNew-Class,名称自定义为ReadWriteHDFSExamplepackage com.pai.hdfs_demo;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import java.io.*;
import java.nio.charset.StandardCharsets;
public class ReadWriteHDFSExample {
// main 新建一个类ReadWriteHDFSExample,编写main函数如下。main函数调用其它函数,创建目录,写入数据,添加数据,然后再读取数据
public static void main(String[] args) throws IOException {
// ReadWriteHDFSExample.checkExists();
ReadWriteHDFSExample.createDirectory();
ReadWriteHDFSExample.writeFileToHDFS();
ReadWriteHDFSExample.appendToHDFSFile();
ReadWriteHDFSExample.readFileFromHDFS();
}
// readFileFromHDFS 该函数读取文件内容,以字符串形式显示出来
public static void readFileFromHDFS() throws IOException {
Configuration configuration = new Configuration();
configuration.set("fs.defaultFS", "hdfs://192.168.31.131:9000");
FileSystem fileSystem = FileSystem.get(configuration);
// Create a path
String fileName = "read_write_hdfs_example.txt";
Path hdfsReadPath = new Path("/javareadwriteexample/" + fileName);
// initialize input stream
FSDataInputStream inputStream = fileSystem.open(hdfsReadPath);
// Classical input stream usage
String out = IOUtils.toString(inputStream, "UTF-8");
System.out.println(out);
// BufferedReader bufferedReader = new BufferedReader(
// new InputStreamReader(inputStream, StandardCharsets.UTF_8));
// String line = null;
// while ((line=bufferedReader.readLine())!=null){
// System.out.println(line);
// }
inputStream.close();
fileSystem.close();
}
// writeFileToHDFS writeFileToHDFS函数打开文件,写入一行文本
public static void writeFileToHDFS() throws IOException {
Configuration configuration = new Configuration();
configuration.set("fs.defaultFS", "hdfs://192.168.31.131:9000");
FileSystem fileSystem = FileSystem.get(configuration);
// Create a path
String fileName = "read_write_hdfs_example.txt";
Path hdfsWritePath = new Path("/javareadwriteexample/" + fileName);
FSDataOutputStream fsDataOutputStream = fileSystem.create(hdfsWritePath, true);
BufferedWriter bufferedWriter = new BufferedWriter(
new OutputStreamWriter(fsDataOutputStream, StandardCharsets.UTF_8));
bufferedWriter.write("Java API to write data in HDFS");
bufferedWriter.newLine();
bufferedWriter.close();
fileSystem.close();
}
// appendToHDFSFile 函数打开文件,添加一行文本。需要注意的是,需要对Configuration类的对象configuration进行适当设置,否则出错
public static void appendToHDFSFile() throws IOException {
Configuration configuration = new Configuration();
configuration.set("fs.defaultFS", "hdfs://192.168.31.131:9000");
//configuration.setBoolean("dfs.client.block.write.replace-datanode-on-failure.enabled", true);
configuration.set("dfs.client.block.write.replace-datanode-on-failure.policy","NEVER");
configuration.set("dfs.client.block.write.replace-datanode-on-failure.enable","true");
FileSystem fileSystem = FileSystem.get(configuration);
// Create a path
String fileName = "read_write_hdfs_example.txt";
Path hdfsWritePath = new Path("/javareadwriteexample/" + fileName);
FSDataOutputStream fsDataOutputStream = fileSystem.append(hdfsWritePath);
BufferedWriter bufferedWriter = new BufferedWriter(
new OutputStreamWriter(fsDataOutputStream, StandardCharsets.UTF_8));
bufferedWriter.write("Java API to append data in HDFS file");
bufferedWriter.newLine();
bufferedWriter.close();
fileSystem.close();
}
// createDirectory 函数创建一个目录
public static void createDirectory() throws IOException {
Configuration configuration = new Configuration();
configuration.set("fs.defaultFS", "hdfs://192.168.31.131:9000");
FileSystem fileSystem = FileSystem.get(configuration);
String directoryName = "/javareadwriteexample";
Path path = new Path(directoryName);
fileSystem.mkdirs(path);
}
// checkExists checkExists检查目录或者文件是否存在。注意如下代码的最后一个括号是ReadWriteHDFSExample类的结束括号
public static void checkExists() throws IOException {
Configuration configuration = new Configuration();
configuration.set("fs.defaultFS", "hdfs://192.168.31.131:9000");
FileSystem fileSystem = FileSystem.get(configuration);
String directoryName = "/javareadwriteexample";
Path path = new Path(directoryName);
if (fileSystem.exists(path)) {
System.out.println("File/Folder Exists : " + path.getName());
} else {
System.out.println("File/Folder does not Exists : " + path.getName());
}
}
}
为了编译通过上述Java代码,需要把如下目录下的jar包导入Eclipse项目的Build Path
操作序列为 右键点击Eclipse里的Java项目→Properties→Java Build Path →Libraries→Add External Jars
# 添加如下路径的包
D:hadoop-2.7.3sharehadoopcommonlib
D:hadoop-2.7.3sharehadoopcommon
D:hadoop-2.7.3sharehadoophdfs
D:hadoop-2.7.3sharehadoophdfslib
D:hadoop-2.7.3sharehadoopmapreducelib
D:hadoop-2.7.3sharehadoopmapreduce
D:hadoop-2.7.3sharehadoopyarnlib
D:hadoop-2.7.3sharehadoopyarn
就可以愉快地执行了,执行完毕上述代码后,在hd-master主机上可以通过如下命令,检查已经写入的文件
[root@hd-master bin]# cd /opt/linuxsir/hadoop/bin
[root@hd-master bin]# ./hdfs dfs -ls /javareadwriteexample/read_write_hdfs_example.txt
-rw-r--r-- 3 root supergroup 70 2024-10-10 04:47 /javareadwriteexample/read_write_hdfs_example.txt
[root@hd-master bin]# ./hdfs dfs -cat /javareadwriteexample/read_write_hdfs_example.txt
Java API to write data in HDFS
Java API to append data in HDFS file
为了多次进行实验(或者为了调试代码),可以把HDFS文件删除,然后再执行或者调试Java代码,否则一经存在该目录,执行创建目录的代码就会出错
cd /opt/linuxsir/hadoop/bin
./hdfs dfs -rm /javareadwriteexample/*
./hdfs dfs -rmdir /javareadwriteexample
cd /opt/linuxsir/hadoop/sbin
./stop-yarn.sh
./stop-dfs.sh
jps
ssh root@192.168.31.132 jps
ssh root@192.168.31.133 jps
package mywordcount;
import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
public class WordCount {
//定义WordCount类的内部类TokenizerMapper 该类实现了map函数,把从文件读取的每个word变成一个形式为<word,1>的Key Value对,输出到map函数的参数context对象,由执行引擎完成Shuffle
public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
word.set(itr.nextToken());
context.write(word, one);
}
}
}
//定义WordCount类的内部类IntSumReducer 该类实现了reduce函数,它收拢所有相同key的、形式为<word,1>的Key-Value对,对Value部分进行累加,输出一个计数
public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
String thekey = key.toString();
int thevalue = sum;
}
}
// WordCount类的main函数,负责配置Job的若干关键的参数,并且启动这个Job。在main函数中,conf对象包含了一个属性即“fs.defaultFS”,它的值为“hdfs://192.168.31.131:9000”,使得WordCount程序知道如何存取HDFS
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
conf.set("fs.defaultFS", "hdfs://192.168.31.131:9000");
Job job = new Job(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
[root@hd-master bin]# ./hdfs dfs -ls /output1
Found 2 items
-rw-r--r-- 3 root supergroup 0 2024-10-10 05:17 /output1/_SUCCESS
-rw-r--r-- 3 root supergroup 89 2024-10-10 05:17 /output1/part-r-00000
[root@hd-master bin]# ./hdfs dfs -cat /output1/part-r-00000
I 1
apache 1
cloudera 1
google 1
hadoop 8
hortonworks 1
ibm 1
intel 1
like 1
microsoft 1
数据分析咨询请扫描二维码
若不方便扫码,搜微信号:CDAshujufenxi
在Excel数据分析中,数据透视表是汇总、整理海量数据的高效工具,而公式则是实现数据二次计算、逻辑判断的核心功能。实际操作中 ...
2026-04-30Excel透视图是数据分析中不可或缺的工具,它能将透视表中的数据快速可视化,帮助我们直观捕捉数据规律、呈现分析结果。但在实际 ...
2026-04-30 很多数据分析师能熟练地计算指标、搭建标签体系,但当被问到“画像到底在解决什么问题”“画像和标签是什么关系”“画像如何 ...
2026-04-30在中介效应分析中,人口统计学变量(如年龄、性别、学历、收入、职业等)是常见的控制变量或调节变量,其处理方式直接影响分析结 ...
2026-04-29在SQL数据库实操中,日期数据的存储与显示是高频需求,而“数字日期”(如20240520、20241231、45321)是很多开发者、数据分析师 ...
2026-04-29 很多分析师在设计标签时思路清晰,但真到落地环节却面临“数据在手,不知如何转化为可用标签”的困境:或因加工方式选择不当 ...
2026-04-29在手游行业竞争日趋白热化的当下,“流量为王”早已升级为“留存为王”,而付费用户留存率更是衡量一款手游盈利能力、运营质量的 ...
2026-04-28在日常MySQL数据库运维与开发中,经常会遇到“同一台服务器上,两个不同数据库(以下简称“源库”“目标库”)的表数据需要保持 ...
2026-04-28 很多分析师每天和数据打交道,但当被问到“标签是什么”“标签和指标有什么区别”“标签体系如何设计”时,却常常答不上来。 ...
2026-04-28箱线图(Box Plot)作为一种经典的数据可视化工具,广泛应用于统计学、数据分析、科研实证等领域,核心价值在于直观呈现数据的集 ...
2026-04-27实证分析是社会科学、自然科学、经济管理等领域开展研究的核心范式,其核心逻辑是通过对多维度数据的收集、分析与解读,揭示变量 ...
2026-04-27 很多数据分析师精通Excel函数和数据透视表,但当被问到“数据从哪里来”“表和视图有什么区别”“数据库管理系统和SQL是什么 ...
2026-04-27在大数据技术飞速迭代、数字营销竞争日趋激烈的今天,“精准触达、高效转化、成本可控”已成为企业营销的核心诉求。传统广告投放 ...
2026-04-24在游戏行业竞争白热化的当下,用户流失已成为制约游戏生命周期、影响营收增长的核心痛点。据行业报告显示,2024年移动游戏平均次 ...
2026-04-24 很多业务负责人开会常说“我们要数据驱动”,最后却变成“看哪张报表数据多就用哪个”,往往因为缺乏一套结构性的方法去搭建 ...
2026-04-24在Power BI数据可视化分析中,切片器是连接用户与数据的核心交互工具,其核心价值在于帮助使用者快速筛选目标数据、聚焦分析重点 ...
2026-04-23以数为据,以析促优——数据分析结果指导临床技术改进的实践路径 临床技术是医疗服务的核心载体,其水平直接决定患者诊疗效果、 ...
2026-04-23很多数据分析师每天盯着GMV、DAU、转化率,但当被问到“哪些指标是所有企业都需要的”“哪些指标是因行业而异的”“北极星指标和 ...
2026-04-23近日,由 CDA 数据科学研究院重磅发布的《2026 全球数智化人才指数报告》,被中国教育科学研究院官方账号正式收录, ...
2026-04-22在数字化时代,客户每一次点击、浏览、下单、咨询等行为,都在传递其潜在需求与决策倾向——这些按时间顺序串联的行为轨迹,构成 ...
2026-04-22