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2.hadoop和hadoop有什么区别?
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hadoop和hadoop有什么区别?
1、运行模式不同:单机模式是调试Hadoop的默认模式。这种模式在一台单机上运行,源码没有分布式文件系统,调试批量挂qq源码而是源码直接读写本地操作系统的文件系统。
伪分布模式这种模式也是调试在一台单机上运行,但用不同的源码Java进程模仿分布式运行中的各类结点。
2、调试配置不同:
单机模式(standalone)首次解压Hadoop的源码源码包时,Hadoop无法了解硬件安装环境,调试便保守地选择了最小配置。源码ubuntu如何下载源码在这种默认模式下所有3个XML文件均为空。调试当配置文件为空时,源码Hadoop会完全运行在本地。调试
伪分布模式在“单节点集群”上运行Hadoop,源码其中所有的ubuntu源码下载vim守护进程都运行在同一台机器上。
3、节点交互不同:
单机模式因为不需要与其他节点交互,单机模式就不使用HDFS,也不加载任何Hadoop的守护进程。该模式主要用于开发调试MapReduce程序的手机借贷网站源码应用逻辑。
伪分布模式在单机模式之上增加了代码调试功能,允许你检查内存使用情况,HDFS输入输出,以及其他的守护进程交互。
扩展资料:
核心架构:
1、c 机器视觉源码HDFS:
HDFS对外部客户机而言,HDFS就像一个传统的分级文件系统。可以创建、删除、移动或重命名文件,等等。存储在 HDFS 中的文件被分成块,然后将这些块复制到多个计算机中(DataNode)。这与传统的 RAID 架构大不相同。块的大小和复制的块数量在创建文件时由客户机决定。
2、NameNode
NameNode 是一个通常在 HDFS 实例中的单独机器上运行的软件。它负责管理文件系统名称空间和控制外部客户机的访问。NameNode 决定是否将文件映射到 DataNode 上的复制块上。
3、DataNode
DataNode 也是在 HDFS实例中的单独机器上运行的软件。Hadoop 集群包含一个 NameNode 和大量 DataNode。DataNode 通常以机架的形式组织,机架通过一个交换机将所有系统连接起来。Hadoop 的一个假设是:机架内部节点之间的传输速度快于机架间节点的传输速度。
百度百科-Hadoop
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Java代ç
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
解å³åæ³:
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Java代ç private static String checkHadoopHome() {
// first check the Dflag hadoop.home.dir with JVM scope
//System.setProperty("hadoop.home.dir", "...");
String home = System.getProperty("hadoop.home.dir");
// fall back to the system/user-global env variable
if (home == null) {
home = System.getenv("HADOOP_HOME");
}
try {
// couldn't find either setting for hadoop's home directory
if (home == null) {
throw new IOException("HADOOP_HOME or hadoop.home.dir are not set.");
}
if (home.startsWith("\"") && home.endsWith("\"")) {
home = home.substring(1, home.length()-1);
}
// check that the home setting is actually a directory that exists
File homedir = new File(home);
if (!homedir.isAbsolute() || !homedir.exists() || !homedir.isDirectory()) {
throw new IOException("Hadoop home directory " + homedir
+ " does not exist, is not a directory, or is not an absolute path.");
}
home = homedir.getCanonicalPath();
} catch (IOException ioe) {
if (LOG.isDebugEnabled()) {
LOG.debug("Failed to detect a valid hadoop home directory", ioe);
}
home = null;
}
//åºå®æ¬æºçhadoopå°å
home="D:\\hadoop-2.2.0";
return home;
}
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Java代ç Exception in thread "main" java.lang.IllegalArgumentException: Wrong FS: hdfs://...:/user/hmail/output/part-, expected: file:///
at org.apache.hadoop.fs.FileSystem.checkPath(FileSystem.java:)
at org.apache.hadoop.fs.RawLocalFileSystem.pathToFile(RawLocalFileSystem.java:)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:)
at org.apache.hadoop.fs.ChecksumFileSystem$ChecksumFSInputChecker.<init>(ChecksumFileSystem.java:)
at org.apache.hadoop.fs.ChecksumFileSystem.open(ChecksumFileSystem.java:)
at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:)
at com.netease.hadoop.HDFSCatWithAPI.main(HDFSCatWithAPI.java:)
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Java代ç Exception in thread "main" java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
åºç°è¿ä¸ªå¼å¸¸ï¼ä¸è¬æ¯ç±äºHADOOP_HOMEçç¯å¢åéé ç½®çæé®é¢ï¼å¨è¿éæ£ä»ç¹å«è¯´æä¸ä¸ï¼å¦ææ³å¨Winä¸çeclipseä¸æåè°è¯Hadoop2.2ï¼å°±éè¦å¨æ¬æºçç¯å¢åéä¸ï¼æ·»å å¦ä¸çç¯å¢åéï¼
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Java代ç package com.qin.wordcount;
import java.io.IOException;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobConf;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
/***
*
* Hadoop2.2.0æµè¯
* æ¾WordCountçä¾å
*
* @author qindongliang
*
* hadoopææ¯äº¤æµç¾¤ï¼
*
*
* */
public class MyWordCount {
/**
* Mapper
*
* **/
private static class WMapper extends Mapper<LongWritable, Text, Text, IntWritable>{
private IntWritable count=new IntWritable(1);
private Text text=new Text();
@Override
protected void map(LongWritable key, Text value,Context context)
throws IOException, InterruptedException {
String values[]=value.toString().split("#");
//System.out.println(values[0]+"========"+values[1]);
count.set(Integer.parseInt(values[1]));
text.set(values[0]);
context.write(text,count);
}
}
/**
* Reducer
*
* **/
private static class WReducer extends Reducer<Text, IntWritable, Text, Text>{
private Text t=new Text();
@Override
protected void reduce(Text key, Iterable<IntWritable> value,Context context)
throws IOException, InterruptedException {
int count=0;
for(IntWritable i:value){
count+=i.get();
}
t.set(count+"");
context.write(key,t);
}
}
/**
* æ¹å¨ä¸
* (1)shellæºç éæ·»å checkHadoopHomeçè·¯å¾
* (2)è¡ï¼FileUtilséé¢
* **/
public static void main(String[] args) throws Exception{
// String path1=System.getenv("HADOOP_HOME");
// System.out.println(path1);
// System.exit(0);
JobConf conf=new JobConf(MyWordCount.class);
//Configuration conf=new Configuration();
//conf.set("mapred.job.tracker","...:");
//读åpersonä¸çæ°æ®å段
// conf.setJar("tt.jar");
//注æè¿è¡ä»£ç æ¾å¨æåé¢ï¼è¿è¡åå§åï¼å¦åä¼æ¥
/**Jobä»»å¡**/
Job job=new Job(conf, "testwordcount");
job.setJarByClass(MyWordCount.class);
System.out.println("模å¼ï¼ "+conf.get("mapred.job.tracker"));;
// job.setCombinerClass(PCombine.class);
// job.setNumReduceTasks(3);//设置为3
job.setMapperClass(WMapper.class);
job.setReducerClass(WReducer.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
String path="hdfs://...:/qin/output";
FileSystem fs=FileSystem.get(conf);
Path p=new Path(path);
if(fs.exists(p)){
fs.delete(p, true);
System.out.println("è¾åºè·¯å¾åå¨ï¼å·²å é¤ï¼");
}
FileInputFormat.setInputPaths(job, "hdfs://...:/qin/input");
FileOutputFormat.setOutputPath(job,p );
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
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Java代ç INFO - Configuration.warnOnceIfDeprecated() | mapred.job.tracker is deprecated. Instead, use mapreduce.jobtracker.address
模å¼ï¼ local
è¾åºè·¯å¾åå¨ï¼å·²å é¤ï¼
INFO - Configuration.warnOnceIfDeprecated() | session.id is deprecated. Instead, use dfs.metrics.session-id
INFO - JvmMetrics.init() | Initializing JVM Metrics with processName=JobTracker, sessionId=
WARN - JobSubmitter.copyAndConfigureFiles() | Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
WARN - JobSubmitter.copyAndConfigureFiles() | No job jar file set. User classes may not be found. See Job or Job#setJar(String).
INFO - FileInputFormat.listStatus() | Total input paths to process : 1
INFO - JobSubmitter.submitJobInternal() | number of splits:1
INFO - Configuration.warnOnceIfDeprecated() | user.name is deprecated. Instead, use mapreduce.job.user.name
INFO - Configuration.warnOnceIfDeprecated() | mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
INFO - Configuration.warnOnceIfDeprecated() | mapred.mapoutput.value.class is deprecated. Instead, use mapreduce.map.output.value.class
INFO - Configuration.warnOnceIfDeprecated() | mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
INFO - C