错误:java.io.IOException:错误的值类:类org.apache.hadoop.io.Text不是类Myclass

时间:2014-01-27 09:20:38

标签: java hadoop elastic-map-reduce

我的mapper和redurs如下所示。但我得到了一些奇怪的例外。 我无法弄清楚为什么会抛出这种异常。

public static class MyMapper implements Mapper<LongWritable, Text, Text, Info> {

    @Override
    public void map(LongWritable key, Text value,
        OutputCollector<Text, Info> output, Reporter reporter)
        throws IOException {
        Text text = new Text("someText")
            //process 
        output.collect(text, infoObjeject);
    }

}

public static class MyReducer implements Reducer<Text, Info, Text, Text> {

    @Override
    public void reduce(Text key, Iterator<Info> values,
        OutputCollector<Text, Text> output, Reporter reporter)
        throws IOException {
        String value = "xyz" //derived in some way
        //process
        output.collect(key, new Text(value)); //exception occurs at this line
    }

}

System.out.println("Starting v14 ");
JobConf conf = new JobConf(RouteBuilderJob.class);
conf.setJobName("xyz");

String jarLocation =ClassUtil.findContainingJar(getClass());

System.out.println("path of jar file = " + jarLocation);

conf.setJarByClass(RouteBuilderJob.class);

conf.setMapOutputKeyClass(Text.class);
conf.setMapOutputValueClass(Info.class);

conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(Text.class);

//am i missing something here???

conf.setMapperClass(RouteBuilderJob.RouteMapper.class);
conf.setCombinerClass(RouteBuilderJob.RouteReducer.class);
conf.setReducerClass(RouteBuilderJob.RouteReducer.class);


conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);

FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));

JobClient.runJob(conf);

我得到一个例外:

Error: java.io.IOException: wrong value class: class org.apache.hadoop.io.Text is not class com.xyz.mypackage.Info
at org.apache.hadoop.mapred.IFile$Writer.append(IFile.java:199)
at org.apache.hadoop.mapred.Task$CombineOutputCollector.collect(Task.java:1307)
at com.xyz.mypackage.job.MyJob$RouteReducer.reduce(MyJob.java:156)
at com.xyz.mypackage.job.MyJob$RouteReducer.reduce(MyJob.java:1)

使用Writable

序列化内部信息对象(实现Text
@Override
public void write(DataOutput out) throws IOException {
    Gson gson = new Gson();
    String searlizedStr = gson.toJson(this);
    Text.writeString(out, searlizedStr);
}

@Override
public void readFields(DataInput in) throws IOException {
    String s = Text.readString(in);
    Gson gson = new Gson();
    JsonReader jsonReader = new JsonReader(new StringReader(s));
    jsonReader.setLenient(true);

Info info = gson.fromJson(jsonReader, Info.class);
    //set fields using this.somefield = info.getsomefield() 
}

1 个答案:

答案 0 :(得分:7)

从技术上讲,reduce的输出类型应与输入类型相同。如果使用合成器,合并器的输出被送入减速器,则必须如此。