我的地圖可降低結構錯誤而鏈接的Map Reduce作業
public class ChainingMapReduce {
public static class ChainingMapReduceMapper
extends Mapper<Object, Text, Text, IntWritable>{
public void map(Object key, Text value, Context context
) throws IOException, InterruptedException {
// code
}
}
}
public static class ChainingMapReduceReducer
extends Reducer<Text,IntWritable,Text,IntWritable> {
public void reduce(Text key, Iterable<IntWritable> values,
Context context
) throws IOException, InterruptedException {
//code
}
}
public static class ChainingMapReduceMapper1
extends Mapper<Object, Text, Text, IntWritable>{
public void map(Object key, Text value, Context context
) throws IOException, InterruptedException {
//code
}
}
}
public static class ChainingMapReduceReducer1
extends Reducer<Text,IntWritable,Text,IntWritable> {
public void reduce(Text key, Iterable<IntWritable> values,
Context context
) throws IOException, InterruptedException {
//code
}
}
public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException {
Configuration conf = new Configuration();
Job job = new Job(conf, "First");
job.setJarByClass(ChainingMapReduce.class);
job.setMapperClass(ChainingMapReduceMapper.class);
job.setCombinerClass(ChainingMapReduceReducer.class);
job.setReducerClass(ChainingMapReduceReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path("/home/Desktop/log"));
FileOutputFormat.setOutputPath(job, new Path("/home/Desktop/temp/output"));
job.waitForCompletion(true);
System.out.println("First Job Completed.....Starting Second Job");
System.out.println(job.isSuccessful());
/* FileSystem hdfs = FileSystem.get(conf);
Path fromPath = new Path("/home/Desktop/temp/output/part-r-00000");
Path toPath = new Path("/home/Desktop/temp/output1");
hdfs.rename(fromPath, toPath);
conf.clear();
*/
if(job.isSuccessful()){
Configuration conf1 = new Configuration();
Job job1 = new Job(conf1,"Second");
job1.setJarByClass(ChainingMapReduce.class);
job1.setMapperClass(ChainingMapReduceMapper1.class);
job1.setCombinerClass(ChainingMapReduceReducer1.class);
job1.setReducerClass(ChainingMapReduceReducer1.class);
job1.setOutputKeyClass(Text.class);
job1.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path("/home/Desktop/temp/output/part-r-00000)");
FileOutputFormat.setOutputPath(job, new Path("/home/Desktop/temp/output1"));
System.exit(job1.waitForCompletion(true) ? 0 : 1);
}
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
當我運行這個程序...首先,工作完美地得到執行,並且下面的錯誤後,來了:
第一份工作已完成。 ....啓動第二個工作true
12/01/27 15:24:21信息jvm.JvmMetrics:無法初始化JVM度量標準 with processName = JobTracker,sessionId = - 已經初始化12/01/27 15:24:21警告mapred.JobClient:使用GenericOptionsParser解析 參數。應用程序應該實現相同的工具。 12/01/27 15:24:21警告mapred.JobClient:沒有作業jar文件集。可能找不到用戶 的類。請參閱JobConf(Class)或 JobConf#setJar(String)。 12/01/27 15:24:21信息mapred.JobClient: 清理分段區域 file:/tmp/hadoop/mapred/staging/4991311720439552/.staging/job_local_0002 線程「main」中的異常 org.apache .hadoop.mapred.InvalidJobConfException:輸出目錄不是 集。在 org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:123) 在org.apache.hadoop.mapred.JobClient $ 2.run(JobClient.java:872)在 org.apache .hadoop.mapred.JobClient $ 2.run(JobClient.java:833)at java.security.AccessController.doPrivileged(Native Method)at javax.security.auth.Subject.doAs(Subject.java:396)at org .apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1127) at org.apache.hadoop.mapreduce.Job上的org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:833) 。提交(Job.java:476) org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:506)at Chaini ngMapReduce.main(ChainingMapReduce.java:129)
我嘗試使用「conf」作業和「conf」「conf1」作爲各自的作業。
謝謝..我弄錯了.. – pradeep 2012-01-27 08:20:52