在Spark 2.x当中，实际上SQLContext和HiveContext是过时的，相反是采用SparkSession对象的sql函数来操作SQL语句的。使用这个函数执行SQL语句前需要先调用DataFrame的createOrReplaceTempView注册一个临时表，所以关键是先要将RDD转换成DataFrame。实际上，在Spark中实际声明了
type DataFrame = Dataset[Row]
所以，DataFrame是Dataset[Row]的别名。RDD是提供面向低层次的API，而DataFrame/Dataset提供面向高层次的API（适合于SQL等面向结构化数据的场合）。
下面提供一些Spark SQL程序的例子。
例子一：SparkSQLExam.scala
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