spark: RDD与DataFrame之间的相互转换方法

# -*- coding: utf-8 -*-
from __future__ import print_function
from pyspark.sql import SparkSession
from pyspark.sql import Row

if __name__ == "__main__":
 # 初始化SparkSession
 spark = SparkSession \
 .builder \
 .appName("RDD_and_DataFrame") \
 .config("spark.some.config.option", "some-value") \
 .getOrCreate()

 sc = spark.sparkContext

 lines = sc.textFile("employee.txt")
 parts = lines.map(lambda l: l.split(","))
 employee = parts.map(lambda p: Row(name=p[0], salary=int(p[1])))

 #RDD转换成DataFrame
 employee_temp = spark.createDataFrame(employee)

 #显示DataFrame数据
 employee_temp.show()

 #创建视图
 employee_temp.createOrReplaceTempView("employee")
 #过滤数据
 employee_result = spark.sql("SELECT name,salary FROM employee WHERE salary >= 14000 AND salary <= 20000")

 # DataFrame转换成RDD
 result = employee_result.rdd.map(lambda p: "name: " + p.name + " salary: " + str(p.salary)).collect()

 #打印RDD数据
 for n in result:
 print(n)