org.apache.hadoop.mapred.lib.aggregate
Class 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>
- All Implemented Interfaces:
- Closeable, JobConfigurable, Mapper<K1,V1,Text,Text>, Reducer<Text,Text,Text,Text>
@InterfaceAudience.Public
@InterfaceStability.Stable
public class ValueAggregatorReducer<K1 extends WritableComparable,V1 extends Writable>
- extends ValueAggregatorJobBase<K1,V1>
This class implements the generic reducer of Aggregate.
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
ValueAggregatorReducer
public ValueAggregatorReducer()
reduce
public void reduce(Text key,
Iterator<Text> values,
OutputCollector<Text,Text> output,
Reporter reporter)
throws IOException
- Description copied from interface:
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 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).
- Parameters:
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.
- Throws:
IOException
map
public void map(K1 arg0,
V1 arg1,
OutputCollector<Text,Text> arg2,
Reporter arg3)
throws IOException
- Do nothing. Should not be called
- Parameters:
arg0
- the input key.arg1
- the input value.arg2
- collects mapped keys and values.arg3
- facility to report progress.
- Throws:
IOException
Copyright © 2014 Apache Software Foundation. All Rights Reserved.