Spark编程: Spark SQL基本操作 2020.11.01

{ "id":1 , "name":" Ella" , "age":36 } 
{ "id":2, "name":"Bob","age":29 } 
{ "id":3 , "name":"Jack","age":29 } 
{ "id":4 , "name":"Jim","age":28 }
{ "id":4 , "name":"Jim","age":28 } 
{ "id":5 , "name":"Damon" } 
{ "id":5 , "name":"Damon" }

为employee.json 创建DataFrame, 并写出Scala语句完成下列操作:

(1)查询所有数据;

import spark.implicits._
val df=spark.read.json("file:///home/beyond-dhl/Desktop/sparkSQL/employee.json")
df.show()

(2)查询所有数据,并去除重复的数据;

df.distinct().show()

(3)查询所有数据, 打印时去除id字段;

df.drop(df("id")).show()

(4)筛选出age>30 的记录;

df.filter(df("age")>30).show()

(5)将数据按age分组

df.groupBy(df("age")).count.show()

(6)将数据按neme升序排列

df.sort(df("name").asc).show()

(7)取出前3行数据

df.show(3)

(8)打印时修改name 的列名 为 username

df.select(df("name").as("username")).show()

(9)age 的平均值(agg是聚合操作)

df.agg("age"->"avg").show()

(10)age 的最小值

df.agg("age"->"min").show()