package com.ws.sparksql
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.types._
import org.apache.spark.sql._
import org.apache.spark.{SparkConf, SparkContext}

/**
  * spark sql版本 2.x
  */
object SparkSql2Demo {

  def main(args: Array[String]): Unit = {
    //spark 2.X sql创建执行过程
    val session = SparkSession.builder().appName("SparkSql2Demo").master("local[*]").getOrCreate()

    val dataRdd: RDD[String] = session.sparkContext.textFile("hdfs://hadoop-01:9000/student")

    val studentRowRdd: RDD[Row] = dataRdd.map(line => {
      val fieldArr: Array[String] = line.split(",")
      val id = fieldArr(0).toLong
      val name = fieldArr(1)
      val age = fieldArr(2).toInt
      val score = fieldArr(3).toInt
      Row(id, name, age, score)
    })

    //创建结构化表
    val schema: StructType = StructType(List(
      StructField("id", LongType, true),
      StructField("name", StringType, true),
      StructField("age", IntegerType, true),
      StructField("score", IntegerType, true)
    ))

    val dataFrame: DataFrame = session.createDataFrame(studentRowRdd, schema)

    import session.implicits._
    val result: Dataset[Row] = dataFrame.where($"score" > 100).orderBy($"score" desc, $"age" asc)

    result.show()

    session.stop()
  }
}

结果 ：

+---+----+---+-----+
| id|name|age|score|
+---+----+---+-----+
|  1|  张三| 18|  150|
|  2|  李四| 19|  150|
+---+----+---+-----+