【大数据】0001---使用SparkSQL关联两个表求和取前几行

场景：

有两个表，表可以是文本或Json数据，结构化后分别是Table1(A，B，C）和Table2（C、D、E），两个表通过C关联，要求求出D+E之和，并以（A、B、D+E）三列返回

解答：

思路：SparkSQL支持读取Json创建表，同时创建的表可以做联合查询，类似传统Sql语句进行关联查询和统计分析

代码：

package study

import org.apache.spark.SparkContext
import org.apache.spark.sql.SparkSession

object TestDataFrame2{
  def main(args:Array[String]):Unit={
    import org.apache.spark.sql.SparkSession

    val spark = SparkSession
      .builder()
      .master("local[*]")
      .appName("Spark SQL basic example")
      .config("spark.some.config.option", "some-value")
      .getOrCreate()

    spark.sql("""create table table1 using org.apache.spark.sql.json options(path "F://0002_BigData//Soft//comoceanspark//src//resources//Table1.json")""")

    spark.sql("""create table table2 using org.apache.spark.sql.json options(path "F://0002_BigData//Soft//comoceanspark//src//resources//Table2.json")""")

    spark.sql("show tables").show()

    spark.sql("select A,B,(D+E) as DE from table1 inner join table2 on table1.C = table2.C order by DE desc limit 5").show()

  }
}

Table1.json：

{"A":"A1", "B":30, "C":1}
{"A":"A2", "B":31, "C":2}
{"A":"A3", "B":32, "C":3}
{"A":"A4", "B":33, "C":4}
{"A":"A5", "B":34, "C":5}
{"A":"A6", "B":35, "C":6}
{"A":"A7", "B":36, "C":7}
{"A":"A8", "B":37, "C":8}
{"A":"A9", "B":38, "C":9}

Table2.json：

{"C":1, "D":1, "E":1}
{"C":2, "D":2, "E":2}
{"C":3, "D":3, "E":3}
{"C":4, "D":4, "E":4}
{"C":5, "D":5, "E":5}
{"C":6, "D":6, "E":6}
{"C":7, "D":7, "E":7}
{"C":8, "D":8, "E":8}
{"C":9, "D":9, "E":9}

结果：

表显示

计算结果显示：