我得到了一些类似垃圾的值,而不是我想用作分布式缓存的文件中的数据。
作业配置如下:
Configuration config5 = new Configuration();
JobConf conf5 = new JobConf(config5, Job5.class);
conf5.setJobName("Job5");
conf5.setOutputKeyClass(Text.class);
conf5.setOutputValueClass(Text.class);
conf5.setMapperClass(MapThree4c.class);
conf5.setReducerClass(ReduceThree5.class);
conf5.setInputFormat(TextInputFormat.class);
conf5.setOutputFormat(TextOutputFormat.class);
DistributedCache.addCacheFile(new URI("/home/users/mlakshm/ap1228"), conf5);
FileInputFormat.setInputPaths(conf5, new Path(other_args.get(5)));
FileOutputFormat.setOutputPath(conf5, new Path(other_args.get(6)));
JobClient.runJob(conf5);
在映射器中,我有以下代码:
public class MapThree4c extends MapReduceBase implements Mapper<LongWritable, Text,
Text, Text >{
private Set<String> prefixCandidates = new HashSet<String>();
Text a = new Text();
public void configure(JobConf conf5) {
Path[] dates = new Path[0];
try {
dates = DistributedCache.getLocalCacheFiles(conf5);
System.out.println("candidates: "+candidates);
String astr = dates.toString();
a = new Text(astr);
} catch (IOException ioe) {
System.err.println("Caught exception while getting cached files: " +
StringUtils.stringifyException(ioe));
}
}
public void map(LongWritable key, Text value, OutputCollector<Text, Text> output,
Reporter reporter) throws IOException {
String line = value.toString();
StringTokenizer st = new StringTokenizer(line);
st.nextToken();
String t = st.nextToken();
String uidi = st.nextToken();
String uidj = st.nextToken();
String check = null;
output.collect(new Text(line), a);
}
}
我从这个映射器得到的输出值是:[Lorg.apache.hadoop.fs.Path;@786c1a82
而不是分布式缓存文件中的值。