@InterfaceAudience.Public @InterfaceStability.Stable public class FieldSelectionMapReduce<K,V> extends Object implements Mapper<K,V,Text,Text>, Reducer<Text,Text,Text,Text>
| Modifier and Type | Field and Description | 
|---|---|
| static org.apache.commons.logging.Log | LOG | 
| Constructor and Description | 
|---|
| FieldSelectionMapReduce() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | close() | 
| void | configure(JobConf job)Initializes a new instance from a  JobConf. | 
| void | map(K key,
      V val,
      OutputCollector<Text,Text> output,
      Reporter reporter)The identify function. | 
| void | reduce(Text key,
            Iterator<Text> values,
            OutputCollector<Text,Text> output,
            Reporter reporter)Reduces values for a given key. | 
public static final org.apache.commons.logging.Log LOG
public FieldSelectionMapReduce()
public void map(K key, V val, OutputCollector<Text,Text> output, Reporter reporter) throws IOException
public void configure(JobConf job)
JobConfigurableJobConf.configure in interface JobConfigurablejob - the configurationpublic void close() throws IOException
close in interface Closeableclose in interface AutoCloseableIOExceptionpublic void reduce(Text key, Iterator<Text> values, OutputCollector<Text,Text> output, Reporter reporter) throws IOException
ReducerThe framework calls this method for each 
 <key, (list of values)> pair in the grouped inputs.
 Output values must be of the same type as input values.  Input keys must 
 not be altered. The framework will reuse the key and value objects
 that are passed into the reduce, therefore the application should clone
 the objects they want to keep a copy of. In many cases, all values are 
 combined into zero or one value.
 
Output pairs are collected with calls to  
 OutputCollector.collect(Object,Object).
Applications can use the Reporter provided to report progress 
 or just indicate that they are alive. In scenarios where the application 
 takes a significant amount of time to process individual key/value 
 pairs, this is crucial since the framework might assume that the task has 
 timed-out and kill that task. The other way of avoiding this is to set 
 
 mapreduce.task.timeout to a high-enough value (or even zero for no 
 time-outs).
Copyright © 2017 Apache Software Foundation. All rights reserved.