Github user tfournier314 commented on a diff in the pull request:

    https://github.com/apache/flink/pull/2740#discussion_r87295380
  
    --- Diff: 
flink-libraries/flink-ml/src/main/scala/org/apache/flink/ml/preprocessing/StringIndexer.scala
 ---
    @@ -0,0 +1,108 @@
    +package org.apache.flink.ml.preprocessing
    +
    +import org.apache.flink.api.scala._
    +import org.apache.flink.api.scala.extensions.acceptPartialFunctions
    +import org.apache.flink.api.scala.utils._
    +import org.apache.flink.ml.common.{Parameter, ParameterMap}
    +import org.apache.flink.ml.pipeline.{FitOperation, 
TransformDataSetOperation, Transformer}
    +import org.apache.flink.ml.preprocessing.StringIndexer.HandleInvalid
    +
    +import scala.collection.immutable.Seq
    +
    +/**
    +  * String Indexer
    +  */
    +class StringIndexer extends Transformer[StringIndexer] {
    +
    +  private[preprocessing] var metricsOption: Option[DataSet[(String, 
Long)]] = None
    +
    +
    +  def setHandleInvalid(value: String): this.type ={
    +    parameters.add( HandleInvalid, value )
    +    this
    +  }
    +
    +}
    +
    +object StringIndexer {
    +
    +  case object HandleInvalid extends Parameter[String] {
    +    val defaultValue: Option[String] = Some( "skip" )
    +  }
    +
    +  // ==================================== Factory methods 
==========================================
    +
    +  def apply(): StringIndexer ={
    +    new StringIndexer( )
    +  }
    +
    +  // ====================================== Operations 
=============================================
    +
    +  /**
    +    * Trains [[StringIndexer]] by learning the count of each string in the 
input DataSet.
    +    */
    +
    +  implicit def fitStringIndexer ={
    +    new FitOperation[StringIndexer, String] {
    +      def fit(instance: StringIndexer, fitParameters: ParameterMap, input: 
DataSet[String]):Unit ={
    +        val metrics = extractIndices( input )
    +        instance.metricsOption = Some( metrics )
    +      }
    +    }
    +  }
    +
    +  private def extractIndices(input: DataSet[String]): DataSet[(String, 
Long)] = {
    +
    +    val mapping = input
    +      .mapWith( s => (s, 1) )
    +      .groupBy( 0 )
    +      .reduce( (a, b) => (a._1, a._2 + b._2) )
    +      .partitionByRange( 1 )
    --- End diff --
    
    Indeed, I need to do a global sort, because mapping is a sorted 
DataSet[(String,Long)] of (labels,index), where the most frequent item has 
index = 0.
    
    I need to sort a dataSet of (labels,frequency), then zipWithIndex to get 
the associated index.
    
    I've just realised that sortPartition() will only sort my partitions 
locally, so how can I achieve a global sort this way ? 
    
    



---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---

Reply via email to