【电商实践第二问】

统计各个省份的浏览量 （需要解析IP）

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一、pandas是什么？

示例：pandas 是基于NumPy 的一种工具，该工具是为了解决数据分析任务而创建的。

二、使用步骤

1.新建类

代码如下（示例）：

ProvinceMapper

import com.baomidou.mybatisplus.core.toolkit.StringUtils;
import com.bigdata.hadoop.project.utils.IPParser;
import com.bigdata.hadoop.project.utils.LogParser;
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;
import java.util.Map;

public class ProvinceMapper extends Mapper<LongWritable, Text, Text, IntWritable> {

    private static final IntWritable one = new IntWritable(1);
    private Text city = new Text();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException, IOException {
        // Split the input line into fields based on the delimiter
        String[] fields = value.toString().split("\u0001");

        if (fields.length > 13) {
            // Assuming the IP address is in the 14th field (index 13)
            String ip = fields[13];
            String log = value.toString();
            LogParser parser = new LogParser();

            Map<String, String> logInfo = parser.parse(log);

            if (StringUtils.isNotBlank(logInfo.get("ip"))) {
                IPParser.RegionInfo regionInfo = IPParser.getInstance().analyseIp(logInfo.get("ip"));
                String province = regionInfo.getProvince();
                if (StringUtils.isNotBlank(province)) {
                    context.write(new Text(province), new IntWritable(1));
                } else {
                    context.write(new Text("-"), new IntWritable(1));
                }
            } else {
                context.write(new Text("+"), new IntWritable(1));
            }

        }
    }

}

ProvinceReducer

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

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

    private IntWritable result = new IntWritable();

    @Override
    protected 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);
    }
}

ProvinceDriver

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;

public class ProvinceDriver {

    public static void main(String[] args) throws Exception {
        if (args.length != 2) {
            System.err.println("Usage: ProvinceDriver <input path> <output path>");
            System.exit(-1);
        }

        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf, "Province View Count");

        job.setJarByClass(ProvinceDriver.class);
        job.setMapperClass(ProvinceMapper.class);
        job.setCombinerClass(ProvinceReducer.class);
        job.setReducerClass(ProvinceReducer.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

2.打包jar包：

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3.在结果中查询