使用java Mapreduce处理JSON

首先,您尝试使用的JSON对象不适用于您.要解决这个问题:

到这里下载为zip:https://github.com/douglascrockford/JSON-java

提取到子目录org/json/*中的sources文件夹

接下来,代码的第一行生成一个包"org.json",这是不正确的,你要创建一个单独的包,例如"my.books".

第三,在这里使用组合器是没用的.

这是我最终得到的代码,它可以解决您的问题:

package my.books;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
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.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;
import org.apache.hadoop.util.GenericOptionsParser;
import org.json.*;

import javax.security.auth.callback.TextInputCallback;

public class CombineBooks {

    public static class Map extends Mapper<LongWritable, Text, Text, Text>{

        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{

            String author;
            String book;
            String line = value.toString();
            String[] tuple = line.split("\\n");
            try{
                for(int i=0;i<tuple.length; i++){
                    JSONObject obj = new JSONObject(tuple[i]);
                    author = obj.getString("author");
                    book = obj.getString("book");
                    context.write(new Text(author), new Text(book));
                }
            }catch(JSONException e){
                e.printStackTrace();
            }
        }
    }

    public static class Reduce extends Reducer<Text,Text,NullWritable,Text>{

        public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException{

            try{
                JSONObject obj = new JSONObject();
                JSONArray ja = new JSONArray();
                for(Text val : values){
                    JSONObject jo = new JSONObject().put("book", val.toString());
                    ja.put(jo);
                }
                obj.put("books", ja);
                obj.put("author", key.toString());
                context.write(NullWritable.get(), new Text(obj.toString()));
            }catch(JSONException e){
                e.printStackTrace();
            }
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        if (args.length != 2) {
            System.err.println("Usage: CombineBooks <in> <out>");
            System.exit(2);
        }

        Job job = new Job(conf, "CombineBooks");
        job.setJarByClass(CombineBooks.class);
        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);
        job.setOutputKeyClass(NullWritable.class);
        job.setOutputValueClass(Text.class);
        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);

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

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

这是我项目的文件夹结构:

src
src/my
src/my/books
src/my/books/CombineBooks.java
src/org
src/org/json
src/org/json/zip
src/org/json/zip/BitReader.java
...
src/org/json/zip/None.java
src/org/json/JSONStringer.java
src/org/json/JSONML.java
...
src/org/json/JSONException.java

这是输入

[localhost:CombineBooks]$ hdfs dfs -cat /example.txt
{"author":"author1", "book":"book1"}
{"author":"author1", "book":"book2"}
{"author":"author1", "book":"book3"}
{"author":"author2", "book":"book4"}
{"author":"author2", "book":"book5"}
{"author":"author3", "book":"book6"}

要运行的命令:

hadoop jar ./bookparse.jar my.books.CombineBooks /example.txt /test_output

这是输出:

[pivhdsne:CombineBooks]$ hdfs dfs -cat /test_output/part-r-00000
{"books":[{"book":"book3"},{"book":"book2"},{"book":"book1"}],"author":"author1"}
{"books":[{"book":"book5"},{"book":"book4"}],"author":"author2"}
{"books":[{"book":"book6"}],"author":"author3"}

您可以使用三个选项将org.json.*类放入集群中:

将org.json.*类打包到jar文件中(可以使用GUI IDE轻松完成).这是我在答案中使用的选项

将包含org.json.*每个集群节点上的类的jar文件放入其中一个CLASSPATH目录中(请参阅yarn.application.classpath)

将包含的jar文件org.json.*放入HDFS(hdfs dfs -put <org.json jar> <hdfs path>)并使用job.addFileToClassPath对此jar文件的调用可用于在集群上执行作业的所有任务.在我的回答你应该添加job.addFileToClassPath(new Path("<jar_file_on_hdfs_location>"));到main