猫眼电影网站电影数分析与可视化

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

//keyin:行号 , valuein:Text,
public class maoyanMapper extends Mapper<LongWritable,Text,Text, IntWritable> {
    public static String spiltRtoL(String s) {

        StringBuffer sb = new StringBuffer();
        int length = s.length();
        char[] c = new char[length];
        for (int i = 0; i < length; i++) {
            c[i] = s.charAt(i);
        }
        for (int i = length - 1; i >= 0; i--) {
            sb.append(c[i]);
        }

        return sb.toString();
    }

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //supper.map(key,value,context);
        //一行一行读，然后将每一行文本转成字符串
        String line=value.toString();
        //分割每一行
        String l = spiltRtoL(line);
        String y=l.substring(0,4);
        String year = spiltRtoL(y);

        context.write(new Text(year),new IntWritable(1));

    }
}

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class maoyanReducer extends Reducer<Text,IntWritable,Text,IntWritable> {

    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        //super.reduce(key, values, context);
        int sum=0;   //是每个地区的岗位数量和
        for(IntWritable i :values){
            sum+=i.get();   //i.get()是把IntWritable转成int
        }
        context.write(key,new IntWritable(sum));  //reducer的输出结果
    }
}

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.FileOutputStream;
import java.io.IOException;

public class maoyanRunner {
    public static  void  main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf=new Configuration();
        //创建job
        Job job= Job.getInstance(conf,"movie6");
        //设置输入输出路径
        FileInputFormat.addInputPath(job,new Path(args[0]));
        FileOutputFormat.setOutputPath(job,new Path(args[1]));
        //设置运行类
        job.setJarByClass(maoyanRunner.class);
        job.setMapperClass(maoyanMapper.class);
        job.setReducerClass(maoyanReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        System.exit(job.waitForCompletion(true)?0:1);

    }
}

import pandas as pd
import matplotlib
import matplotlib.pyplot as plt

matplotlib.rcParams['font.family']='SimHei'   
matplotlib.rcParams['font.sans-serif'] = ['SimHei']

data=pd.read_csv(r"E:\output6\part-r-00000",sep='\t',header=None)
data.columns=['年份','电影数目']
data.head()

plt.figure(figsize=(9,6))
y=data['电影数目']
plt.plot(y,label='年份')
plt.xlabel('时间（年）')
plt.ylabel("上映数量")
plt.legend()
plt.title("电影年份对应的上映电影数目趋势表")
plt.show()