@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)
JobConfigurable
JobConf
.configure
in interface JobConfigurable
job
- the configurationpublic void close() throws IOException
close
in interface Closeable
close
in interface AutoCloseable
IOException
public void reduce(Text key, Iterator<Text> values, OutputCollector<Text,Text> output, Reporter reporter) throws IOException
Reducer
The 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 © 2015 Apache Software Foundation. All rights reserved.