scala练习

共同好友案例

Scala package com.doit.day03 import scala.io.{BufferedSource, Source} /**  * 数据如下  :每个字母代表一个人 ,  统计任意一个人和其他人的共同好友  * A:B,C,D,F,E,O  * B:A,C,E,K  * C:F,A,D,I  * D:A,E,F,L  * E:B,C,D,M,L  * F:A,B,C,D,E,O,M  * G:A,C,D,E,F  * H:A,C,D,E,O  * I:A,O  * J:B,O  * K:A,C,D  * L:D,E,F  * M:E,F,G  * O:A,H,I,J  */ object SameFriends {   def main(args: Array[String]): Unit = {      val lines: Iterator[String] = Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\friends").getLines()      val myAndFriends: List[(String, Array[String])] = lines.toList.map(line => {         //        A:B,C,D,F,E,O   :前面的是我自己，：后面的是我的朋友们         val arr: Array[String] = line.split(":")         //获取到我自己         val user: String = arr(0)         //获取到我的朋友们，朋友们都放在数组里面，里面的元素就是一个个的朋友对象         val friends: Array[String] = arr(1).split(",")         (user, friends)      })      //获取共同好友。。。      for(i <- 0 until myAndFriends.length){         for(j <- i+1 until myAndFriends.length){            //从第一个元素开始取            val tuple: (String, Array[String]) = myAndFriends(i)            val tuple1: (String, Array[String]) = myAndFriends(j)            //看是不是有共同好友，是不是取交集            val sameFriends: Array[String] = tuple._2.intersect(tuple1._2)            println("用户："+tuple._1+"用户："+tuple1._1+"的共同好友是："+sameFriends.mkString(","))         }      }   } }

需求四：SQL join语法案例

Data

Plain Text order.txt order011,u001,300 order012,u002,200 order023,u006,100 order056,u007,300 order066,u003,500 order055,u004,300 order021,u005,300 order014,u001,100 order025,u005,300 order046,u007,30 order067,u003,340 order098,u008,310 user.txt u001,hls,22,fengjie u002,wangwu,31,lisi u003,zhangyanru,22,tananpengyou u004,laocao,26,fengyi u005,mengqi,12,nvmengqi u006,haolei,38,sb u007,wanghongjing,24,wife u009,wanghongjing,24,wife 返回一个结果：order011  u001   300  hls  22   fengjie

代码示例：

Scala package com.doit.day03 import scala.io.{BufferedSource, Source} object JoinDemo {   def main(args: Array[String]): Unit = {     //u001,hls,22,fengjie     val bs1= Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\user.txt")/*.getLines().toList*/     //order011,u001,300     val bs2 = Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\order.txt")/*.getLines().toList*/     //实现left join /*     //将用户数据转换成map集合     val users: Iterator[String] = bs1.getLines()     val iters: Iterator[(String, (String, String, String, String))] = users.map(_.split(",", -1)).map(x => (x(0), (x(0), x(1), x(2), x(3))))     val map: Map[String, (String, String, String, String)] = iters.toMap     // 将订单数据转换成list集合     val orders: Iterator[String] = bs2.getLines()     val iters2: Iterator[(String, (String, String))] = orders.map(_.split(",", -1)).map(x => (x(1), (x(0), x(1))))     val list2: List[(String, (String, String))] = iters2.toList     //遍历每个订单  拼接用户信息     var r = list2.map(x => {       val user = map.getOrElse(x._1, ("null", "null", "null", "null"))       (user._1, user._2, user._3, user._4, x._2._1)     })     // 打印结果     r.sortBy(_._1).foreach(println)     */     //实现join     /*     val userTuple: List[(String, String, String, String)] = users.map(line => {       val arr: Array[String] = line.split(",")       //user_id，user_name，age,name       (arr(0), arr(1), arr(2), arr(3))     })     val orderTuple: List[(String, String, String)] = orders.map(line => {       val arr: Array[String] = line.split(",")       //order_id  user_id   amount       (arr(0), arr(1), arr(2))     })     //join关联条件是user_id = user_id     for (user <- userTuple) {       for (order <- orderTuple) {         if(user._1 == order._2){           println(user._1,user._2,user._3,user._4,order._1,order._3)         }       }     } */   } }

需求五：pv，uv案例

数据：

Plain Text site1,user1,2018-03-01 02:12:22 site1,user2,2018-03-05 04:12:22 site1,user2,2018-03-05 04:13:22 site1,user2,2018-03-05 04:14:22 site1,user2,2018-03-05 04:15:22 site4,user7, site1,user2,2018-03-05 05:15:22 site1,user2,2018-03-05 08:15:22 site1,user3,2018-03-05 04:15:22 site1,user4,2018-03-05 05:15:22 site1,user3,2018-03-07 11:12:22 site1,user3,2018-03-08 11:12:22 site2,user4,2018-03-07 15:12:22 site3,user5,2018-03-07 08:12:22 site3,user6,2018-03-05 08:12:22 site1,user1,2018-03-08 11:12:22 site1,,2018-03-08 11:12:22 site2,user2,2018-03-07 15:12:22 site3,user5,2018-03-07 08:12:22 site3,user5,2018-03-07 18:12:22 site3,user6,2018-03-05 08:12:22 site4,user7,2018-03-03 10:12:22 site2,,2018-03-08 11:12:22 site3,user5,2018-03-07 08:12:22 site3,user6,2018-03-05 08:12:22 site4,user5,2018-03-03 10:12:22 site4,user7,2018-02-20 11:12:22

代码：

Scala package com.doit.day03 import scala.io.{BufferedSource, Source} /**  * 需求：计算每天的pv和uv  * pv：浏览次数  * uv：访客数  */ object PVUVDemo {   def main(args: Array[String]): Unit = {     val source: BufferedSource = Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\pvuv.txt")     val list: List[String] = source.getLines().toList     //过滤一些脏数据     val filtered: List[String] = list.filter(line => {       val arr: Array[String] = line.split(",",-1)       arr.length >= 0 && !arr.exists(_.isEmpty)     })     val events: List[(String, String, String)] = filtered.map(line => {       val arr: Array[String] = line.split(",")       val date: String = arr(2).substring(0, 10)       //site1,user1,2018-03-01 02:12:22       (arr(0), arr(1),date)     })     //pv：该页面被浏览了多少次     val tuples: List[((String, String), String)] = events.map(tp => {       ((tp._3, tp._1), tp._2)     })     val pv: Map[(String, String), Int] = tuples.groupBy(_._1).map(tp => (tp._1, tp._2.size))     val uv: Map[(String, String), Int] = tuples.groupBy(_._1).map(tp => (tp._1, tp._2.distinct.size))     println("============pv================")     pv.foreach(println)     println("============uv================")     uv.foreach(println)   } }

需求五：线段重叠案例

data：

Plain Text 1,4 2,5 4,6 2,4 3,6 4,6 1,5

代码：

Scala package com.doit.day03 import scala.io.Source object LineDemo {   def main(args: Array[String]): Unit = {     val list: List[String] = Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\line.txt").getLines().toList     //生成一个个的点     val points: List[Range.Inclusive] = list.map(line => {       val arr: Array[String] = line.split(",")       val start: String = arr(0)       val end: String = arr(1)       //按照起始得位置确定这一行中一共有哪些点，后面才能判断哪些点是重合的       //根据开始和结束得点       val range: Range.Inclusive = start.toInt to end.toInt       range     })     //将点压平     val flattened: List[Int] = points.flatten     //对点分组     val intToInts: Map[Int, List[Int]] = flattened.groupBy(point => point)     //获取到最后的个数     val res: Map[Int, Int] = intToInts.map(tp => (tp._1, tp._2.size))     res.foreach(println)   } }