org.apache.hadoop.mapred.lib

类 FieldSelectionMapReduce<K,V>

java.lang.Object

org.apache.hadoop.mapred.lib.FieldSelectionMapReduce<K,V>

所有已实现的接口:

Closeable, AutoCloseable, JobConfigurable, Mapper<K,V,Text,Text>, Reducer<Text,Text,Text,Text>

public class FieldSelectionMapReduce<K,V>
extends Object
implements Mapper<K,V,Text,Text>, Reducer<Text,Text,Text,Text>

This class implements a mapper/reducer class that can be used to perform field selections in a manner similar to unix cut. The input data is treated as fields separated by a user specified separator (the default value is "\t"). The user can specify a list of fields that form the map output keys, and a list of fields that form the map output values. If the inputformat is TextInputFormat, the mapper will ignore the key to the map function. and the fields are from the value only. Otherwise, the fields are the union of those from the key and those from the value. The field separator is under attribute "mapred.data.field.separator" The map output field list spec is under attribute "map.output.key.value.fields.spec". The value is expected to be like "keyFieldsSpec:valueFieldsSpec" key/valueFieldsSpec are comma (,) separated field spec: fieldSpec,fieldSpec,fieldSpec ... Each field spec can be a simple number (e.g. 5) specifying a specific field, or a range (like 2-5) to specify a range of fields, or an open range (like 3-) specifying all the fields starting from field 3. The open range field spec applies value fields only. They have no effect on the key fields. Here is an example: "4,3,0,1:6,5,1-3,7-". It specifies to use fields 4,3,0 and 1 for keys, and use fields 6,5,1,2,3,7 and above for values. The reduce output field list spec is under attribute "reduce.output.key.value.fields.spec". The reducer extracts output key/value pairs in a similar manner, except that the key is never ignored.

字段概要

字段

限定符和类型	字段和说明
static org.apache.commons.logging.Log	LOG

构造器概要

构造器

构造器和说明
FieldSelectionMapReduce()

方法概要

方法

限定符和类型	方法和说明
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.

从类继承的方法 java.lang.Object

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

字段详细资料

LOG

public static final org.apache.commons.logging.Log LOG

构造器详细资料

FieldSelectionMapReduce

public FieldSelectionMapReduce()

方法详细资料

map

public void map(K key,
       V val,
       OutputCollector<Text,Text> output,
       Reporter reporter)
         throws IOException

The identify function. Input key/value pair is written directly to output.

指定者:

map 在接口中 Mapper<K,V,Text,Text>

参数:

key - the input key.

val - the input value.

output - collects mapped keys and values.

reporter - facility to report progress.

抛出:

IOException

configure

public void configure(JobConf job)

从接口复制的说明: JobConfigurable

Initializes a new instance from a JobConf.

指定者:

configure 在接口中 JobConfigurable

参数:

job - the configuration

close

public void close()
           throws IOException

指定者:

close 在接口中 Closeable

指定者:

close 在接口中 AutoCloseable

抛出:

IOException

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).

指定者:

reduce 在接口中 Reducer<Text,Text,Text,Text>

参数:

key - the key.

values - the list of values to reduce.

output - to collect keys and combined values.

reporter - facility to report progress.

抛出:

IOException