hadoop面试题目

1 .  找共同朋友，数据格式如下

A B C D E F
B A C D E
C A B E
D A B E
E A B C D
F A

第一字母表示本人，其他是他的朋友，找出有共同朋友的人，和共同朋友是谁

答案如下：

AB E:C:D
AC E:B
AD B:E
AE C:B:D
BC A:E
BD A:E
BE C:D:A
BF A
CD E:A:B
CE A:B
CF A
DE B:A
DF A
EF A

程序代码：

import java.io.IOException;
import java.util.Set;
import java.util.StringTokenizer;
import java.util.TreeSet;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.Mapper.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class FindFriend {

	public static class ChangeMapper extends Mapper {
		
		@Override
		public void map(Object key, Text value, Context context) throws
		IOException, InterruptedException {
			StringTokenizer itr = new StringTokenizer(value.toString());
			Text owner = new Text();
			Set set = new TreeSet();
			owner.set(itr.nextToken());
			while (itr.hasMoreTokens()) {
				set.add(itr.nextToken());
			}
			String[] friends = new String[set.size()];
			friends = set.toArray(friends);
			for(int i=0; i {
		
		public void reduce(Text key, Iterable values, Context context) throws 
		IOException,InterruptedException {
			
			String commonfriends ="";
			for (Text val : values) {
				if(commonfriends == "") {
					commonfriends = val.toString();
				} else {
					commonfriends =
					commonfriends+":"+val.toString();
				}
			}
			context.write(key, new Text(commonfriends));
		}
		
	}

	public static void main(String[] args) throws IOException, 
	InterruptedException, ClassNotFoundException {
		
		Configuration conf = new Configuration();
		String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
		if (otherArgs.length < 2) {
			System.err.println("args error");
			System.exit(2);
		}
		Job job = new Job(conf, "FindFriend");
		job.setJarByClass(FindFriend.class);
		job.setMapperClass(ChangeMapper.class);
		job.setCombinerClass(FindReducer.class);
		job.setReducerClass(FindReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(Text.class);
		for (int i = 0; i < otherArgs.length - 1; ++i) {
			FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
		}
		FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}

2 . 随意使用各种类型的脚本语言实现：批量将/etc目录下的所有文件中的$HADOOP_HOME替换成/home/local/hadoop

find /etc/ -exec sed -i 's/\$HADOOP_HOME/\/home\/local\/hadoop/g' {} \;

3 . combine发生在那个过程中？以及作用是什么？

                                 map->combine->partition->shuffle->reduce

        combiner仅作用于单个Mapper任务，每个Map任务可能会产生大量的输出，combiner的作用就是在Map端对输出先做一次合并，以减少传输到Reducer的数据量。使用combiner实现本地key的聚合，提升速度,减轻io压力。

4 . 杀死一个job

hadoop job -list拿到job-id
hadoop job -kill job-id

5 . hbase常用基本命令，创建表，添加记录，查看记录，删除记录

create '表名称','列族名称1','列名族称2','列名族称N'
put '表名','行名','列名','值'
get '表名','行名'
delete '表名','行名称','列名称'