本篇内容介绍了“hadoop怎么合并sequcefie并在map中读取”的有关知识，在实际案例的操作过程中，不少人都会遇到这样的困境，接下来就让小编带领大家学习一下如何处理这些情况吧！希望大家仔细阅读，能够学有所成！
package hgs.sequencefile;import java.io.IOException;import java.net.URI;import java.net.URISyntaxException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FSDataInputStream;import org.apache.hadoop.fs.FileStatus;import org.apache.hadoop.fs.FileSystem;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IOUtils;import org.apache.hadoop.io.SequenceFile;import org.apache.hadoop.io.Text;//合并小文件public class SequenceMain {public static void main(String[] args) throws IOException, URISyntaxException {Configuration conf = new Configuration();FileSystem fs = FileSystem.get(new URI("hdfs://192.168.6.129:9000"),conf);//获得该文件夹下的所有的文件FileStatus[] fstats = fs.listStatus(new Path("/words"));//System.out.println(fstats.length);Text key = new Text();Text value = new Text();@SuppressWarnings("deprecation")//创建一个sequecewriter//merge.seq是文件名SequenceFile.Writer writer = SequenceFile.createWriter(fs, conf, new Path("/sequence/merge.seq"), key.getClass(), value.getClass());//循环遍历每个文件 for(FileStatus fis : fstats) {//将每个文件以key value的形式写入到sequencefile中FSDataInputStream finput = fs.open(fis.getPath());byte[] buffer = new byte[(int)fis.getLen()];IOUtils.readFully(finput, buffer, 0, buffer.length);//文件名为key 文件内容为valuekey.set(fis.getPath().getName());value.set(buffer);writer.append(key, value);finput.close();}writer.close();fs.close();}}package hgs.sequencefile;import java.io.IOException;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Mapper;public class SequnceMapper extends Mapper<Text, Text, Text, Text> {@Overrideprotected void map(Text key, Text value, Mapper<Text, Text, Text, Text>.Context context)throws IOException, InterruptedException {context.write(key, value);}}package hgs.sequencefile;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapred.SequenceFileOutputFormat;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.SequenceFileAsTextInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;public class SequenceDriver {public static void main(String[] args) throws Exception {Configuration conf = new Configuration();Job job = Job.getInstance(conf, "read_sequence_file");job.setJarByClass(hgs.sequencefile.SequenceDriver.class);// TODO: specify a mapperjob.setMapperClass(SequnceMapper.class);// TODO: specify a reducer//job.setReducerClass(Reducer.class);// TODO: specify output typesjob.setOutputKeyClass(Text.class);job.setOutputValueClass(Text.class);//在这个设置读取sequencefile的inputformat，该类读取的是String泪习惯的key value//SequenceFileAsBinaryInputFormat 该类独处的ByteWritable的key valuejob.setInputFormatClass(SequenceFileAsTextInputFormat.class);// TODO: specify input and output DIRECTORIES (not files)FileInputFormat.setInputPaths(job, new Path("hdfs://192.168.6.129:9000/sequence"));FileOutputFormat.setOutputPath(job, new Path("hdfs://192.168.6.129:9000/seqresult"));if (!job.waitForCompletion(true))return;}}“hadoop怎么合并sequcefie并在map中读取”的内容就介绍到这里了，感谢大家的阅读。如果想了解更多行业相关的知识可以关注编程网网站，小编将为大家输出更多高质量的实用文章！
