标签:http result common 查询 log 技术 alt count inf
不知道为啥不是很想学习MapReduce方面的知识,不过现在这么想可能过段时间还是免不了去学,这边先记录下一个MapReduce的实例wordcount代码。
1、
pom.xml:
<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>2.8.3</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.8.3</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.8.3</version>
</dependency>
</dependencies>
2、
WordCountMapper:
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
Text k = new Text();
IntWritable v = new IntWritable(1);
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//获取一行文本
String line = value.toString();
//根据分隔符切分
String[] words = line.split(" ");
//输出
for (String word : words) {
k.set(word);
context.write(k, v);
}
}
}
3、
WordCountReducer:
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
int sum;
IntWritable v = new IntWritable();
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
//累加求和
sum = 0;
for (IntWritable count : values) {
sum += count.get();
}
//输出
v.set(sum);
context.write(key, v);
}
}
4、
WordCountDriver:
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.io.IOException;
public class WordCountDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
//获取配置信息及封装任务
Configuration configuration = new Configuration();
Job job = Job.getInstance(configuration);
//设置jar加载路径
job.setJarByClass(WordCountDriver.class);
//设置map和reduce类
job.setMapperClass(WordCountMapper.class);
job.setReducerClass(WordCountReducer.class);
//设置map输出
job.setMapOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
//设置reduce输出
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
//设置输入和输出路径
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
//提交
boolean result = job.waitForCompletion(true);
System.exit(result ? 0 : 1);
}
}
5、参数设置:
6、结果查询:
MapReduce简单实例:wordcount--大数据纪录片第五记
标签:http result common 查询 log 技术 alt count inf
原文地址:https://www.cnblogs.com/qugemingzihaonan13/p/9860673.html