推荐算法

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package com.pan.sparksqlimport org.apache.spark.{SparkConf, SparkContext}import org.apache.spark.mllib.recommendation.{ALS, Rating}import org.apache.spark.sql.Rowimport org.apache.spark.sql.hive.HiveContext/**  * Created by pan on 2016/11/11.  */object Demo {  val map1 = Map("" -> i);  val map2 = Map("" -> j);  var i = 0;  var j = 0;  def f(row: Row): Row = {    val r0 = row.get(0).toString;    val r1 = row.get(1).toString;    if (!map1.contains(r0)) {      i += 1;    }    map1 + (r0 -> i)    if (!map2.contains(r1)) {      j+= 1;    }    map2 + (r1 ->j)    return Row(i, j, 1);  }  def main(args: Array[String]) {    val conf = new SparkConf()    val sc = new SparkContext(conf)    val sqlContext = new HiveContext(sc)    sqlContext.sql("use edw")    val ratings = sqlContext.sql("select item_type,part_id from tt_asc_bo_sale_part ");    val newRatings = ratings.map(f)    val mapRatings = newRatings.map(row => Rating(row.getInt(0), row.getInt(1), row.getInt(2)))    val model = ALS.train(mapRatings, 50, 10, 0.01)    val p = model.recommendProducts(100, 10)    System.out.print(p.mkString(";  "))    System.out.println("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa")    System.out.println("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa")    System.out.println("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa")    System.out.println("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa")    System.out.println("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa")    System.out.println("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa")      }}
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