Scala练习题

SQL join语法案例

Data:

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:

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)
        }
      }
    }
*/
  }
}

pv,uv案例

数据:

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:

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)
  }
}

线段重叠案例

data:

1,4
2,5
4,6
2,4
3,6
4,6
1,5

代码:

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)
  }
}

热门相关:流鱼无恙   前任无双   回眸医笑,冷王的神秘嫡妃   重生野性时代   天神诀