【总结】Hadoop中的MultipleOutputs实践
本例子采用hadoop1.1.2版本,附件中有例子的数据文件
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采用气象数据作为处理数据
1、MultipleOutputs例子,具体解释在代码中有注释
package StationPatitioner; import java.io.IOException; import java.util.Iterator; import org.apache.hadoop.conf.Configured; 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.mapred.FileInputFormat; import org.apache.hadoop.mapred.FileOutputFormat; import org.apache.hadoop.mapred.JobClient; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.MapReduceBase; import org.apache.hadoop.mapred.Mapper; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reducer; import org.apache.hadoop.mapred.Reporter; import org.apache.hadoop.mapred.TextOutputFormat; import org.apache.hadoop.mapred.lib.MultipleOutputs; import org.apache.hadoop.mapred.lib.NullOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; /** * hadoop Version 1.1.2 * MultipleOutputs例子 * @author 巧克力黑 * */ public class PatitionByStationUsingMultipleOutputs extends Configured implements Tool { enum Counter { LINESKIP, //出错的行 } static class StationMapper extends MapReduceBase implements Mapper{ private NcdcRecordParser parser = new NcdcRecordParser(); @Override public void map(LongWritable key, Text value, OutputCollector output, Reporter reporter) throws IOException { try { parser.parse(value); output.collect(new Text(parser.getStationid()), value); } catch (Exception e) { reporter.getCounter(Counter.LINESKIP).increment(1); //出错令计数器+1 } } } static class MultipleOutputReducer extends MapReduceBase implements Reducer { private MultipleOutputs multipleOutputs; @Override public void configure(JobConf jobconf) { multipleOutputs = new MultipleOutputs(jobconf);//初始化一个MultipleOutputs } @Override public void reduce(Text key, Iterator values, OutputCollector output, Reporter reporter) throws IOException { //得到OutputCollector OutputCollector collector = multipleOutputs.getCollector("station", key.toString().replace("-", ""), reporter); while(values.hasNext()){ collector.collect(NullWritable.get(), values.next());//MultipleOutputs用OutputCollector输出数据 } } @Override public void close() throws IOException { multipleOutputs.close(); } } @Override public int run(String[] as) throws Exception { System.setProperty("HADOOP_USER_NAME", "root");//windows下用户与linux用户不一直,采用此方法避免报Permission相关错误 JobConf conf = new JobConf(); conf.setMapperClass(StationMapper.class); conf.setReducerClass(MultipleOutputReducer.class); conf.setMapOutputKeyClass(Text.class); conf.setOutputKeyClass(NullWritable.class); conf.setOutputFormat(NullOutputFormat.class); FileInputFormat.setInputPaths(conf, new Path("hdfs://ubuntu:9000/sample1.txt"));//input路径 FileOutputFormat.setOutputPath(conf, new Path("hdfs://ubuntu:9000/temperature"));//output路径 MultipleOutputs.addMultiNamedOutput(conf, "station", TextOutputFormat.class, NullWritable.class, Text.class); JobClient.runJob(conf); return 0; } public static void main(String[] args) throws Exception{ int exitCode = ToolRunner.run(new PatitionByStationUsingMultipleOutputs(), args); System.exit(exitCode); } }
2、解析气象数据的类
package StationPatitioner; import org.apache.hadoop.io.Text; public class NcdcRecordParser { private static final int MISSING_TEMPERATURE = 9999; private String year; private int airTemperature; private String quality; private String stationid; public void parse(String record) { stationid = record.substring(0, 5); year = record.substring(15, 19); String airTemperatureString; // Remove leading plus sign as parseInt doesn't like them if (record.charAt(87) == '+') { airTemperatureString = record.substring(88, 92); } else { airTemperatureString = record.substring(87, 92); } airTemperature = Integer.parseInt(airTemperatureString); quality = record.substring(92, 93); } public String getStationid(){ return stationid; } public void parse(Text record) { parse(record.toString()); } public boolean isValidTemperature() { return airTemperature != MISSING_TEMPERATURE && quality.matches("[01459]"); } public String getYear() { return year; } public int getAirTemperature() { return airTemperature; } }
文章标题:【总结】Hadoop中的MultipleOutputs实践
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