Package org.apache.hadoop.mapred.lib

Class FieldSelectionMapReduce<K,V>

java.lang.Object
org.apache.hadoop.mapred.lib.FieldSelectionMapReduce<K,V>
All Implemented Interfaces:
Closeable, AutoCloseable, Closeable, JobConfigurable, Mapper<K,V,Text,Text>, Reducer<Text,Text,Text,Text>
@Public @Stable 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 "mapreduce.fieldsel.data.field.separator" The map output field list spec is under attribute "mapreduce.fieldsel.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 "mapreduce.fieldsel.reduce.output.key.value.fields.spec". The reducer extracts output key/value pairs in a similar manner, except that the key is never ignored.

  • Field Details

    • LOG

      public static final org.slf4j.Logger LOG

  • Constructor Details

    • FieldSelectionMapReduce

      public FieldSelectionMapReduce()

  • Method Details

    • 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.
      Specified by:
      map in interface Mapper<K,V,Text,Text>
      Parameters:
      key - the input key.
      val - the input value.
      output - collects mapped keys and values.
      reporter - facility to report progress.
      Throws:
      IOException

    • configure

      public void configure(JobConf job)
      Description copied from interface: JobConfigurable
      Initializes a new instance from a JobConf.
      Specified by:
      configure in interface JobConfigurable
      Parameters:
      job - the configuration

    • close

      public void close() throws IOException
      Specified by:
      close in interface AutoCloseable
      Specified by:
      close in interface Closeable
      Throws:
      IOException

    • 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).

      Specified by:
      reduce in interface Reducer<Text,Text,Text,Text>
      Parameters:
      key - the key.
      values - the list of values to reduce.
      output - to collect keys and combined values.
      reporter - facility to report progress.
      Throws:
      IOException