spark开窗函数
源文件内容示例：
http://bigdata.beiwang.cn/laoli http://bigdata.beiwang.cn/laoli http://bigdata.beiwang.cn/haiyuan http://bigdata.beiwang.cn/haiyuan
实现代码：
object SparkSqlDemo11 {
/**
* 使用开窗函数，计算TopN
* @param args
*/
def main(args: Array[String]): Unit = {
val session = SparkSession.builder()
.appName(this.getClass.getSimpleName)
.master("local")
.getOrCreate()
import session.implicits._
//原数据：http://bigdata.beiwang.cn/laoli
val sourceData = session.read.textFile("E:\\北网学习\\K_第十一个月_Spark 2（2019.8）\\8.5\\teacher.log")
val df = sourceData.map(line => {
val index = line.lastIndexOf("/")
val t_name = line.substring(index + 1)
val url = new URL(line.substring(0, index))
val subject = url.getHost.split("\\.")(0)
(subject, t_name)
}).toDF("subject", "t_name")
操作01：得到所有专业下所有老师的访问数：
df.createTempView("temp")
//获得所有学科下老师的访问量：
val middleData: DataFrame = session.sql("select subject,t_name,count(*) cnts from temp group by subject,t_name")
//middleData.show()
+-------+--------+----+ |subject| t_name|cnts| +-------+--------+----+ |bigdata| laoli| 2| |bigdata| haiyuan| 15| | javaee|chenchan| 6| | php| laoliu| 1| | php| laoli| 3| | javaee| laoshi| 9| |bigdata| lichen| 6| +-------+--------+----+
操作02：row_number() over()【按照老师的访问数，降序开窗】
//再将中间值middleData注册成一张表
middleData.createTempView("middleTemp")
//执行第二部查询，使用row_number()开窗函数，对所有的老师的访问数进行排序并添加编号
//开窗后生成的编号列 rn 是一个伪列，只能用于展示，不能用于查询
//row_number() over() 函数是按照某种规则对数据进行编号，需要我们在over()中指定一个排序规则，无规则将会报错
//此处是按照cnts列降序开窗
session.sql(
"""
|select subject,t_name,cnts,row_number() over(order by cnts desc) rn from middleTemp
""".stripMargin).show()
+-------+--------+----+---+ |subject| t_name|cnts| rn| +-------+--------+----+---+ |bigdata| haiyuan| 15| 1| | javaee| laoshi| 9| 2| | javaee|chenchan| 6| 3| |bigdata| lichen| 6| 4| | php| laoli| 3| 5| |bigdata| laoli| 2| 6| | php| laoliu| 1| 7| +-------+--------+----+---+
♈ 注意：over()内必须指定开窗规则，否则会抛出解析异常：
session.sql(
"""
|select subject,t_name,cnts,row_number() over() rn from middleTemp
""".stripMargin).show()
Exception in thread "main" org.apache.spark.sql.AnalysisException: Window function row_number() requires window to be ordered, please add ORDER BY clause. For example SELECT row_number()(value_expr) OVER (PARTITION BY window_partition ORDER BY window_ordering) from table; at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:39) at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:91) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveWindowOrder$$anonfun$apply$31$$anonfun$applyOrElse$12.applyOrElse(Analyzer.scala:2173) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveWindowOrder$$anonfun$apply$31$$anonfun$applyOrElse$12.applyOrElse(Analyzer.scala:2171)
操作03：row_number() over(partition by.. 【根据学科进行分区后为每个分区开窗】
//根据学科进行分区后为每个分区开窗
session.sql(
"""
|select subject,t_name,cnts,row_number() over(partition by subject order by cnts desc) rn from middleTemp
""".stripMargin).show()
+-------+--------+----+---+ |subject| t_name|cnts| rn| +-------+--------+----+---+ | javaee| laoshi| 9| 1| | javaee|chenchan| 6| 2| |bigdata| haiyuan| 15| 1| |bigdata| lichen| 6| 2| |bigdata| laoli| 2| 3| | php| laoli| 3| 1| | php| laoliu| 1| 2| +-------+--------+----+---+
♎ 注意：开窗生成的列是伪列，不能用于实际操作：
//开窗形成的列是伪列，不能用于实际操作
session.sql(
"""
|select subject,t_name,cnts,row_number() over(partition by subject order by cnts desc) rn from middleTemp
|where rn <=2
""".stripMargin).show()
操作04：伪列的使用：
由于开窗形成的伪列不能被直接用于查询，那么我们可以将整个开窗语句的操作作为一个子查询使用，那么开窗语句的结果集对于父查询来说就是一张完整的表，这时候伪列就是一个有效的列，可以用于查询：
//开窗生成的伪列不能用于直接查询，但是我们可以将开窗语句的结果集作为一张表或者说一个子查询，这时候伪列就是一个有效的列，可以进行再次嵌套查询,
session.sql(
"""
|select * from (
|select subject,t_name,cnts,row_number() over(partition by subject order by cnts desc) rn from middleTemp
|) where rn <= 2
""".stripMargin).show()
+-------+--------+----+---+ |subject| t_name|cnts| rn| +-------+--------+----+---+ | javaee| laoshi| 9| 1| | javaee|chenchan| 6| 2| |bigdata| haiyuan| 15| 1| |bigdata| lichen| 6| 2| | php| laoli| 3| 1| | php| laoliu| 1| 2| +-------+--------+----+---+
操作05：【开窗嵌套开窗】rank() over() 函数
在row_number() over() 分区+开窗的基础上，再次进行rank() over() 按照cnts进行全部数据的开窗
//开窗嵌套开窗：
//rank() over() 函数
session.sql(
"""
|select t.*,rank() over(order by cnts desc) rn1 from (
|select subject,t_name,cnts,row_number() over(partition by subject order by cnts desc) rn from middleTemp
|) t
|where rn <= 2
""".stripMargin).show()
+-------+--------+----+---+---+ |subject| t_name|cnts| rn|rn1| +-------+--------+----+---+---+ |bigdata| haiyuan| 15| 1| 1| | javaee| laoshi| 9| 1| 2| | javaee|chenchan| 6| 2| 3| |bigdata| lichen| 6| 2| 3| | php| laoli| 3| 1| 5| | php| laoliu| 1| 2| 6| +-------+--------+----+---+---+
操作06：dense_rank() over() 函数 【三个开窗函数的业务对比】：
//dense_rank() over() 函数
//三个开窗函数的业务对比：
session.sql(
"""
|select t.*,rank() over(order by cnts desc) rank,
|row_number() over(order by cnts desc) row_n,
|dense_rank() over(order by cnts desc) dense_n
|from (
|select subject,t_name,cnts,row_number() over(partition by subject order by cnts desc) row_n_par from middleTemp
|) t
|where row_n_par <= 2
""".stripMargin).show()
+-------+--------+----+---------+----+-----+-------+ |subject| t_name|cnts|row_n_par|rank|row_n|dense_n| +-------+--------+----+---------+----+-----+-------+ |bigdata| haiyuan| 15| 1| 1| 1| 1| | javaee| laoshi| 9| 1| 2| 2| 2| | javaee|chenchan| 6| 2| 3| 3| 3| |bigdata| lichen| 6| 2| 3| 4| 3| | php| laoli| 3| 1| 5| 5| 4| | php| laoliu| 1| 2| 6| 6| 5| +-------+--------+----+---------+----+-----+-------+
操作07：整合为一句SQL完成：
//合并两个SQL语句：
session.sql(
"""
|select t.*,rank() over(order by cnts desc) rank,
|row_number() over(order by cnts desc) row_n,
|dense_rank() over(order by cnts desc) dense_n
|from
|(select subject,t_name,cnts,row_number() over(partition by subject order by cnts desc) row_n_par from
|(select subject,t_name,count(*) cnts from temp group by subject,t_name)) t
|where row_n_par <= 2
""".stripMargin).show()
+-------+--------+----+---------+----+-----+-------+ |subject| t_name|cnts|row_n_par|rank|row_n|dense_n| +-------+--------+----+---------+----+-----+-------+ |bigdata| haiyuan| 15| 1| 1| 1| 1| | javaee| laoshi| 9| 1| 2| 2| 2| | javaee|chenchan| 6| 2| 3| 3| 3| |bigdata| lichen| 6| 2| 3| 4| 3| | php| laoli| 3| 1| 5| 5| 4| | php| laoliu| 1| 2| 6| 6| 5| +-------+--------+----+---------+----+-----+-------+
