Scala练习题

SQL join语法案例

Data:

1. order.txt
3. order011,u001,300
4. order012,u002,200
5. order023,u006,100
6. order056,u007,300
7. order066,u003,500
8. order055,u004,300
9. order021,u005,300
10. order014,u001,100
11. order025,u005,300
12. order046,u007,30
13. order067,u003,340
14. order098,u008,310
16. user.txt
18. u001,hls,22,fengjie
19. u002,wangwu,31,lisi
20. u003,zhangyanru,22,tananpengyou
21. u004,laocao,26,fengyi
22. u005,mengqi,12,nvmengqi
23. u006,haolei,38,sb
24. u007,wanghongjing,24,wife
25. u009,wanghongjing,24,wife
29. 返回一个结果：order011  u001   300  hls  22   fengjie

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代码示例：

1. package com.doit.day03
3. import scala.io.{BufferedSource, Source}
5. object JoinDemo {
6.   def main(args: Array[String]): Unit = {
8.     //u001,hls,22,fengjie
9.     val bs1= Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\user.txt")/*.getLines().toList*/
11.     //order011,u001,300
12.     val bs2 = Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\order.txt")/*.getLines().toList*/
14.     //实现left join
15. /*
16.     //将用户数据转换成map集合
17.     val users: Iterator[String] = bs1.getLines()
18.     val iters: Iterator[(String, (String, String, String, String))] = users.map(_.split(",", -1)).map(x => (x(0), (x(0), x(1), x(2), x(3))))
19.     val map: Map[String, (String, String, String, String)] = iters.toMap
20.     // 将订单数据转换成list集合
21.     val orders: Iterator[String] = bs2.getLines()
22.     val iters2: Iterator[(String, (String, String))] = orders.map(_.split(",", -1)).map(x => (x(1), (x(0), x(1))))
23.     val list2: List[(String, (String, String))] = iters2.toList
25.     //遍历每个订单  拼接用户信息
26.     var r = list2.map(x => {
27.       val user = map.getOrElse(x._1, ("null", "null", "null", "null"))
28.       (user._1, user._2, user._3, user._4, x._2._1)
29.     })
30.     // 打印结果
31.     r.sortBy(_._1).foreach(println)
33.     */
35.     //实现join
36.     /*
37.     val userTuple: List[(String, String, String, String)] = users.map(line => {
38.       val arr: Array[String] = line.split(",")
39.       //user_id，user_name，age,name
40.       (arr(0), arr(1), arr(2), arr(3))
41.     })
43.     val orderTuple: List[(String, String, String)] = orders.map(line => {
44.       val arr: Array[String] = line.split(",")
45.       //order_id  user_id   amount
46.       (arr(0), arr(1), arr(2))
47.     })
49.     //join关联条件是user_id = user_id
51.     for (user <- userTuple) {
52.       for (order <- orderTuple) {
53.         if(user._1 == order._2){
54.           println(user._1,user._2,user._3,user._4,order._1,order._3)
55.         }
56.       }
57.     }
58. */
59.   }
60. }

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线段重叠案例

data：

1. site1,user1,2018-03-01 02:12:22
2. site1,user2,2018-03-05 04:12:22
3. site1,user2,2018-03-05 04:13:22
4. site1,user2,2018-03-05 04:14:22
5. site1,user2,2018-03-05 04:15:22
6. site4,user7,
7. site1,user2,2018-03-05 05:15:22
8. site1,user2,2018-03-05 08:15:22
9. site1,user3,2018-03-05 04:15:22
10. site1,user4,2018-03-05 05:15:22
11. site1,user3,2018-03-07 11:12:22
12. site1,user3,2018-03-08 11:12:22
13. site2,user4,2018-03-07 15:12:22
14. site3,user5,2018-03-07 08:12:22
15. site3,user6,2018-03-05 08:12:22
16. site1,user1,2018-03-08 11:12:22
17. site1,,2018-03-08 11:12:22
18. site2,user2,2018-03-07 15:12:22
19. site3,user5,2018-03-07 08:12:22
20. site3,user5,2018-03-07 18:12:22
21. site3,user6,2018-03-05 08:12:22
22. site4,user7,2018-03-03 10:12:22
23. site2,,2018-03-08 11:12:22
24. site3,user5,2018-03-07 08:12:22
25. site3,user6,2018-03-05 08:12:22
26. site4,user5,2018-03-03 10:12:22
27. site4,user7,2018-02-20 11:12:22

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代码：

1. package com.doit.day03
2. import scala.io.{BufferedSource, Source}
3. /**
4. * 需求：计算每天的pv和uv
5. * pv：浏览次数
6. * uv：访客数
7. */
8. object PVUVDemo {
9.   def main(args: Array[String]): Unit = {
11.     val source: BufferedSource = Source.fromFile("D:\\develop\\ideaWorkSpace\\myself\\study\\scalaDemo\\data\\pvuv.txt")
13.     val list: List[String] = source.getLines().toList
15.     //过滤一些脏数据
16.     val filtered: List[String] = list.filter(line => {
17.       val arr: Array[String] = line.split(",",-1)
18.       arr.length >= 0 && !arr.exists(_.isEmpty)
19.     })
21.     val events: List[(String, String, String)] = filtered.map(line => {
22.       val arr: Array[String] = line.split(",")
23.       val date: String = arr(2).substring(0, 10)
24.       //site1,user1,2018-03-01 02:12:22
25.       (arr(0), arr(1),date)
26.     })
28.     //pv：该页面被浏览了多少次
29.     val tuples: List[((String, String), String)] = events.map(tp => {
30.       ((tp._3, tp._1), tp._2)
31.     })
33.     val pv: Map[(String, String), Int] = tuples.groupBy(_._1).map(tp => (tp._1, tp._2.size))
34.     val uv: Map[(String, String), Int] = tuples.groupBy(_._1).map(tp => (tp._1, tp._2.distinct.size))
35.     println("============pv================")
36.     pv.foreach(println)
37.     println("============uv================")
38.     uv.foreach(println)
39.   }
40. }

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