org.apache.hadoop.mapred.lib.aggregate

类 ValueAggregatorReducer<K1 extends WritableComparable,V1 extends Writable>

java.lang.Object

org.apache.hadoop.mapred.lib.aggregate.ValueAggregatorJobBase<K1,V1>

org.apache.hadoop.mapred.lib.aggregate.ValueAggregatorReducer<K1,V1>

所有已实现的接口:

Closeable, AutoCloseable, JobConfigurable, Mapper<K1,V1,Text,Text>, Reducer<Text,Text,Text,Text>

public class ValueAggregatorReducer<K1 extends WritableComparable,V1 extends Writable>
extends ValueAggregatorJobBase<K1,V1>

This class implements the generic reducer of Aggregate.

字段概要

从类继承的字段 org.apache.hadoop.mapred.lib.aggregate.ValueAggregatorJobBase

aggregatorDescriptorList

构造器概要

构造器

构造器和说明
ValueAggregatorReducer()

方法概要

方法

限定符和类型	方法和说明
void	map(K1 arg0, V1 arg1, OutputCollector<Text,Text> arg2, Reporter arg3) Do nothing.
void	reduce(Text key, Iterator<Text> values, OutputCollector<Text,Text> output, Reporter reporter) Reduces values for a given key.

从类继承的方法 org.apache.hadoop.mapred.lib.aggregate.ValueAggregatorJobBase

close, configure, logSpec

从类继承的方法 java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

构造器详细资料

ValueAggregatorReducer

public ValueAggregatorReducer()

方法详细资料

reduce

public void reduce(Text key,
          Iterator<Text> values,
          OutputCollector<Text,Text> output,
          Reporter reporter)
            throws IOException

从接口复制的说明: Reducer

Reduces values for a given key.

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 an insignificant 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 mapred.task.timeout to a high-enough value (or even zero for no time-outs).

参数:

key - the key is expected to be a Text object, whose prefix indicates the type of aggregation to aggregate the values. In effect, data driven computing is achieved. It is assumed that each aggregator's getReport method emits appropriate output for the aggregator. This may be further customiized.

values - the list of values to reduce.

output - to collect keys and combined values.

reporter - facility to report progress.

抛出:

IOException

map

public void map(K1 arg0,
       V1 arg1,
       OutputCollector<Text,Text> arg2,
       Reporter arg3)
         throws IOException

Do nothing. Should not be called

参数:

arg0 - the input key.

arg1 - the input value.

arg2 - collects mapped keys and values.

arg3 - facility to report progress.

抛出:

IOException