1.需求：
在IDEA中编写代码，创建DataFrame 执行sql命令：
2.数据源：
student.txt
1 tom 15
2 lucy 20
3 mike 18
3.编写代码：
(1)添加依赖：
pom.xml
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>2.1.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>2.1.0</version>
</dependency>
(2)Demo1.scala
package day1209
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.types.StructType
import org.apache.spark.sql.types.StructField
import org.apache.spark.sql.types.IntegerType
import org.apache.spark.sql.types.StringType
import org.apache.spark.sql.Row
/**
* 创建DataFrame 执行sql
*/
object Demo1 {
def main(args: Array[String]): Unit = {
//创建Spark Session对象
val spark = SparkSession.builder().master("local").appName("UnderstandSparkSession").getOrCreate()
//从指定地址读取文件 创建RDD
val personRDD = spark.sparkContext.textFile("/users/macbook/TestInfo/student.txt").map(_.split("\t"))
//指定schema
val schema = StructType(
List(
StructField("id", IntegerType),
StructField("name", StringType),
StructField("age", IntegerType)))
//将RDD转换为 rowRDD
val rowRDD = personRDD.map(p => Row(p(0).toInt, p(1).trim(), p(2).toInt))
//创建DataFrame 将schema与row对应
val personDataFrame = spark.createDataFrame(rowRDD, schema)
//注册视图
personDataFrame.createOrReplaceTempView("t_person")
//执行SQL
val df = spark.sql("select * from t_person order by age desc")
//显示结果
df.show()
//停止Spark
spark.stop()
}
}
4.运行结果：
