hadoop 之 InputFormat类 --- KeyValueTextInputFormat 实例
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KeyValueTextInputFormat 介绍
文本由任务读取时,需要一种格式读入,KeyValueTextInputFormat 是InputFormat 类的一个具体子类,他定义的读取格式是这样的:
- 一行是一条记录;
- 读取后按照(key,value)对表示一条记录;
- 一行中可能被分成多个区域(可能是制表符、逗号或者其他作为分隔符),第一个区域作为key,其他区域作为value。
应用实例
1.要处理的数据,tradeinfoIn文件
zhangsan@163.com 6000 0 2014-02-20lisi@163.com 2000 0 2014-02-20lisi@163.com 0 100 2014-02-20zhangsan@163.com 3000 0 2014-02-20wangwu@126.com 9000 0 2014-02-20wangwu@126.com 0 200 2014-02-20
2.被Job任务读入后的格式:
<zhangsan@163.com, 6000 0 2014-02-20><lisi@163.com,2000 0 2014-02-20><lisi@163.com,0 100 2014-02-20><zhangsan@163.com,3000 0 2014-02-20><wangwu@126.com,9000 0 2014-02-20><wangwu@126.com,0 200 2014-02-20>
3.代码
代码中关于KeyValueTextInputFormat的关键代码
job.setInputFormatClass(KeyValueTextInputFormat.class);
来设置文件被Job读入时的格式。
import java.io.IOException;import java.util.HashMap;import java.util.Map;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.conf.Configured;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.Mapper;import org.apache.hadoop.mapreduce.Partitioner;import org.apache.hadoop.mapreduce.Reducer;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import org.apache.hadoop.util.Tool;import org.apache.hadoop.util.ToolRunner;import mapreduce.bean.InfoBeanMy;public class SumStepByTool extends Configured implements Tool{ public static class SumStepByToolMapper extends Mapper<Text, Text, Text, InfoBeanMy>{ private InfoBeanMy outBean = new InfoBeanMy(); private Text k = new Text(); @Override protected void map(Text key, Text value, Context context) throws IOException, InterruptedException{ String line = value.toString(); String[] fields = line.split("\t"); String account = key.toString(); double income = Double.parseDouble(fields[0]); double expense = Double.parseDouble(fields[1]); outBean.setFields(account, income, expense); k.set(account); context.write(key, outBean); } } public static class SumStepByToolReducer extends Reducer<Text, InfoBeanMy, Text, InfoBeanMy>{ private InfoBeanMy outBean = new InfoBeanMy(); @Override protected void reduce(Text key, Iterable<InfoBeanMy> values, Context context) throws IOException, InterruptedException{ double income_sum = 0; double expense_sum = 0; for(InfoBeanMy infoBeanMy : values) { income_sum += infoBeanMy.getIncome(); expense_sum += infoBeanMy.getExpense(); } outBean.setFields("", income_sum, expense_sum); context.write(key, outBean); } } public static class SumStepByToolPartitioner extends Partitioner<Text, InfoBeanMy>{ private static Map<String, Integer> accountMap = new HashMap<String, Integer>(); static { accountMap.put("zhangsan", 1); accountMap.put("lisi", 2); accountMap.put("wangwu", 3); } @Override public int getPartition(Text key, InfoBeanMy value, int numPartitions) { String keyString = key.toString(); String name = keyString.substring(0, keyString.indexOf("@")); Integer part = accountMap.get(name); if (part == null ) { part = 0; } return part; } } public int run(String[] args) throws Exception { Configuration conf = getConf(); Job job = Job.getInstance(conf); job.setJarByClass(this.getClass()); job.setJobName("SumStepByTool"); //job.setInputFormatClass(TextInputFormat.class); //这个是默认的输入格式 job.setInputFormatClass(KeyValueTextInputFormat.class); //这个把一行记录的第一个区域当做key,其他区域作为value job.setMapperClass(SumStepByToolMapper.class); job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(InfoBeanMy.class); job.setReducerClass(SumStepByToolReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(InfoBeanMy.class); job.setNumReduceTasks(3); FileInputFormat.setInputPaths(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); return job.waitForCompletion(true) ? 0:-1; } public static void main(String[] args) throws Exception { int exitCode = ToolRunner.run(new SumStepByTool(),args); System.exit(exitCode); }}
注意
- 跟默认的格式(TextInputFormat)不一样的地方在于,key不再是字符的偏移量;
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