用户画像:最喜爱的明星前3名

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package com.profile.main

import java.math.BigDecimal
import com.profile.comment.Comments
import com.profile.tools._
import org.apache.commons.lang3.StringUtils
import scala.collection.mutable.ListBuffer
import com.profile.main
/**
* listBuffer(userid,;;;;)-->,userId+"|"+actor+"|"+playtime
* 用户画像:7)最喜爱的明星前3名
* @param userId
* @param actor
* @param playtime
*/
case class most_love_actors(userId:String,actor:String,playtime:Int){
override def toString: String = {
userId+"|"+actor+"|"+playtime
}
}
/**
* 7)最喜爱的明星前3名,用户画像最喜欢的演员
* @author denghd
* date 2017-11-08 16:16
*/
object UserLoveActors {

def main(args: Array[String]): Unit = {
val date=if(args.length==1) args(0) else DateTools.getYestodayDate //yyyy-MM-dd
val sc=SparkTools.getSparkContext
val vodProgramMap = sc.broadcast(JdbcTools.getLoveVodProgramMap) //点播节目
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext.implicits._
val rdd=if(args.length==1) ReadData.readDataFromHdfs(sc,Comments.ilogslave_log_hdfs_path+date) else ReadData.readDataFromLocal(sc,"E:\\logs\\2017-11-07")
val listRDD = rdd.filter(x=> x.contains("vod") && x.contains("VideoPlay")) //x=>"vod".equals(LogTools.getKeywords(x,"ProgramMethod")
.map(x=>{
val userId = LogTools.getKeywords(x,Comments.UserId)
val ProgramID = if(LogTools.getKeywords(x,Comments.ProgramID) !="") new BigDecimal(LogTools.getKeywords(x,Comments.ProgramID)) else new BigDecimal(0)
val playTime = LogTools.getKeywords(x,Comments.PlayS)
val actors = vodProgramMap.value.get(ProgramID)
val actor = if(null == actors || StringUtils.isBlank(actors)) "" else actors
(userId,actor,playTime)
}).filter(x=>StringUtils.isNoneBlank(x._2) && null !=x._2)
.map(x=>{
val listBuffer = ListBuffer[(String,String,Int)]()
if(x._2.contains("|")){
for (actor <- x._2.split("\\|")){
listBuffer +=((x._1,actor,x._3.toInt))
}
}else{
listBuffer +=((x._1,x._2,x._3.toInt))
}
listBuffer.toList
})
listRDD.flatMap(x=>x).map(x=>{
most_love_actors(x._1,x._2,x._3)
}).toDF().registerTempTable("most_love_actors") // userId+"|"+actor+"|"+playtime
val most_love_actors_df = sqlContext.sql("select ‘"+date+"‘ as date,userId,actor,sum(playtime) as playtime from most_love_actors group by userId,actor")
most_love_actors_df.toDF("date","userId","actor","playtime").show(10)
most_love_actors_df.map(r=>{
(r.getAs[String]("userId"),(r.getAs[String]("actor"),r.getAs[Long]("playtime")))
}).groupByKey().map(x=>{
val i2 = x._2.toBuffer
val i2_2 = i2.sortBy(_._2) //按时长从大到小排序
if (i2_2.length > Comments.top_N_love_actor) i2_2.remove(0, (i2_2.length - Comments.top_N_love_actor))
(x._1, i2_2.toIterable)
}).flatMap(x => {
val y = x._2
for (w <- y) yield (x._1, w._1, w._2)
}).toDF("userId","actor","playtime").registerTempTable("most_love_actors")
val most_love_actors_df2=sqlContext.sql("select ‘"+date+"‘ as date,userId,actor,playtime from most_love_actors")
SparkTools.writeDataframeToPhoenixHbase(most_love_actors_df2,Comments.hbase_t_user_most_love_actor)
}

}

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