Hadoop入门——MapReduce自定义RecordReader

妖狐艹你老母 2021-09-27 07:22 524阅读 0赞

# 一.背景 #

RecordReader表示以怎样的方式从分片中读取一条记录，每读取一条记录都会调用RecordReader类，系统默认的RecordReader是LineRecordReader，它是TextInputFormat对应的RecordReader；而SequenceFileInputFormat对应的RecordReader是SequenceFileRecordReader。LineRecordReader是每行的偏移量作为读入map的key，每行的内容作为读入map的value。很多时候hadoop内置的RecordReader并不能满足我们的需求，比如我们在读取记录的时候，希望Map读入的Key值不是偏移量而是行号或者是文件名，这时候就需要我们自定义RecordReader。

#  二.技术实现 #

**(1)：**继承抽象类RecordReader，实现RecordReader的一个实例。

**(2)：**实现自定义InputFormat类，重写InputFormat中的CreateRecordReader()方法，返回值是自定义的RecordReader实例。

**(3)：**配置job.setInputFormatClass()为自定义的InputFormat实例。

**\#需求：统计data文件中奇数行和偶数行的和：**

10
    20
    50
    15
    30
    100

**实现代码如下：**

**MyRecordReader.java：**

public class MyRecordReader extends RecordReader<LongWritable, Text>{
     
    	//起始位置(相对整个分片而言)
    	private long start;
    	//结束位置(相对整个分片而言)
    	private long end;
    	//当前位置
    	private long pos;
    	//文件输入流
    	private FSDataInputStream fin = null;
    	//key、value
    	private LongWritable key = null;
    	private Text value = null;
    	//定义行阅读器(hadoop.util包下的类)
    	private LineReader reader = null;
    	
    	@Override
    	public void initialize(InputSplit split, TaskAttemptContext context) throws IOException, InterruptedException {
    		
    		//获取分片
    		FileSplit fileSplit = (FileSplit) split;
    		//获取起始位置
    		start = fileSplit.getStart();
    		//获取结束位置
    		end = start + fileSplit.getLength();
    		//创建配置
    		Configuration conf = context.getConfiguration();
    		//获取文件路径
    		Path path = fileSplit.getPath();
    		//根据路径获取文件系统
    		FileSystem fileSystem = path.getFileSystem(conf);
    		//打开文件输入流
    		fin = fileSystem.open(path);
    		//找到开始位置开始读取
    		fin.seek(start);
    		//创建阅读器
    		reader = new LineReader(fin);
    		//将当期位置置为1
    		pos = 1;
    		
    	}
     
    	@Override
    	public boolean nextKeyValue() throws IOException, InterruptedException {
    		if (key == null){
    			key = new LongWritable();
    		}
    		key.set(pos);
    		if (value == null){
    			value = new Text();
    		}
    		if (reader.readLine(value) == 0){
    			return false;
    		}
    		pos ++;
    		
    		return true;
    	}
     
    	@Override
    	public LongWritable getCurrentKey() throws IOException, InterruptedException {
    		return key;
    	}
     
    	@Override
    	public Text getCurrentValue() throws IOException, InterruptedException {
    		return value ;
    	}
     
    	@Override
    	public float getProgress() throws IOException, InterruptedException {
    		
    		return 0;
    	}
     
    	@Override
    	public void close() throws IOException {
    		fin.close();
    		
    	}
    }

**MyInputFormat.java**

public class MyInputFormat extends FileInputFormat<LongWritable, Text>{
     
     
    	@Override
    	public RecordReader<LongWritable, Text> createRecordReader(InputSplit split, TaskAttemptContext context) throws IOException, InterruptedException {
    		//返回自定义的RecordReader
    		return new MyRecordReader();
    	}
     
    	/**
    	 * 为了使得切分数据的时候行号不发生错乱
    	 * 这里设置为不进行切分
    	 */
    	protected boolean isSplitable(FileSystem fs, Path filename) {
    		return false;
    	}
     
    }

**MyPartitioner.java**

public class MyPartitioner extends Partitioner<LongWritable, Text>{
     
    	@Override
    	public int getPartition(LongWritable key, Text value, int numPartitions) {
    		//偶数放到第二个分区进行计算
    		if (key.get() % 2 == 0){
    			//将输入到reduce中的key设置为1
    			key.set(1);
    			return 1;
    		} else {//奇数放在第一个分区进行计算
    			//将输入到reduce中的key设置为0
    			key.set(0);
    			return 0;
    		}
    	}
     
    }

**主类 RecordReaderTest.java**

public class RecordReaderTest {
     
    	// 定义输入路径
    	private static String IN_PATH = "";
    	// 定义输出路径
    	private static String OUT_PATH = "";
     
    	public static void main(String[] args) {
     
    		try {
    			// 创建配置信息
    			Configuration conf = new Configuration();
    			// 获取命令行的参数
    			String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
    			// 当参数违法时，中断程序
    			if (otherArgs.length != 2) {
    				System.err.println("Usage:wordcount<in> <out>");
    				System.exit(1);
    			}
     
    			// 给路径赋值
    			IN_PATH = otherArgs[0];
    			OUT_PATH = otherArgs[1];
    			// 创建文件系统
    			FileSystem fileSystem = FileSystem.get(new URI(OUT_PATH), conf);
    			// 如果输出目录存在，我们就删除
    			if (fileSystem.exists(new Path(new URI(OUT_PATH)))) {
    				fileSystem.delete(new Path(new URI(OUT_PATH)), true);
    			}
     
    			// 创建任务
    			Job job = new Job(conf, RecordReaderTest.class.getName());
    			// 打成jar包运行，这句话是关键
    			job.setJarByClass(RecordReaderTest.class);
    			// 1.1 设置输入目录和设置输入数据格式化的类
    			FileInputFormat.setInputPaths(job, IN_PATH);
    			job.setInputFormatClass(MyInputFormat.class);
     
    			// 1.2 设置自定义Mapper类和设置map函数输出数据的key和value的类型
    			job.setMapperClass(RecordReaderMapper.class);
    			job.setMapOutputKeyClass(LongWritable.class);
    			job.setMapOutputValueClass(Text.class);
     
    			// 1.3 设置分区和reduce数量(reduce的数量，和分区的数量对应，因为分区为一个，所以reduce的数量也是一个)
    			job.setPartitionerClass(MyPartitioner.class);
    			job.setNumReduceTasks(2);
     
    			// 1.4 排序
    			// 1.5 归约
    			// 2.1 Shuffle把数据从Map端拷贝到Reduce端。
    			// 2.2 指定Reducer类和输出key和value的类型
    			job.setReducerClass(RecordReaderReducer.class);
    			job.setOutputKeyClass(Text.class);
    			job.setOutputValueClass(LongWritable.class);
     
    			// 2.3 指定输出的路径和设置输出的格式化类
    			FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));
    			job.setOutputFormatClass(TextOutputFormat.class);
     
    			// 提交作业 退出
    			System.exit(job.waitForCompletion(true) ? 0 : 1);
     
    		} catch (Exception e) {
    			e.printStackTrace();
    		}
    	}
     
    	public static class RecordReaderMapper extends Mapper<LongWritable, Text, LongWritable, Text> {
    		@Override
    		protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, LongWritable, Text>.Context context) throws IOException,
    				InterruptedException {
    			// 直接将读取的记录写出去
    			context.write(key, value);
    		}
    	}
     
    	public static class RecordReaderReducer extends Reducer<LongWritable, Text, Text, LongWritable> {
     
    		// 创建写出去的key和value
    		private Text outKey = new Text();
    		private LongWritable outValue = new LongWritable();
     
    		protected void reduce(LongWritable key, Iterable<Text> values, Reducer<LongWritable, Text, Text, LongWritable>.Context context) throws IOException,
    				InterruptedException {
    			
    			System.out.println("奇数行还是偶数行：" + key);
    			
    			// 定义求和的变量
    			long sum = 0;
    			// 遍历value求和
    			for (Text val : values) {
    				// 累加
    				sum += Long.parseLong(val.toString());
    			}
     
    			// 判断奇偶数
    			if (key.get() == 0) {
    				outKey.set("奇数之和为：");
    			} else {
    				outKey.set("偶数之和为：");
     
    			}
    			// 设置value
    			outValue.set(sum);
     
    			// 把结果写出去
    			context.write(outKey, outValue);
    		}
    	}
    }

**程序运行结果：**

![20150123131010911][]

![20150123130952671][]

原文转自：[https://blog.csdn.net/lzm1340458776/article/details/43054037][https_blog.csdn.net_lzm1340458776_article_details_43054037]

[20150123131010911]: /images/20210923/07d3d4c8a7574a19bd6dc329b07666dc.png
[20150123130952671]: /images/20210923/d8f9e4346c644d37878ca0cc1b16b707.png
[https_blog.csdn.net_lzm1340458776_article_details_43054037]: https://blog.csdn.net/lzm1340458776/article/details/43054037