spark 基本操作（二）

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1.dataframe 基本操作

 def main(args: Array[String]): Unit = {    val spark = SparkSession.builder()      .appName("test")      .master("local[*]")      .getOrCreate()    import spark.implicits._    val people = spark.read.format("json").load("people.json")    people.show()    /*    +----+-------+        | age|   name|        +----+-------+        |null|Michael|          |  30|   Andy|          |  19| Justin|          +----+-------+   */    people.printSchema()    /*root    |-- age: long (nullable = true)    |-- name: string (nullable = true)*/    people.select($"name").show()    /*    +-------+        |   name|        +-------+        |Michael|        |   Andy|        | Justin|        +-------+*/    people.select($"name", $"age".cast("string").as("age")).printSchema()    /*    root        |-- name: string (nullable = true)        |-- age: string (nullable = true)*/    people.select($"name", ($"age" + 1).as("age")).show()    /*    +-------+----+        |   name| age|        +-------+----+        |Michael|null|          |   Andy|  31|          | Justin|  20|          +-------+----+*/    people.filter($"age" > 21).show()    //    +---+----+    //    |age|name|    //    +---+----+    //    | 30|Andy|    //      +---+----+    people.groupBy("age").count().show()    //    +----+-----+    //    | age|count|    //    +----+-----+    //    |  19|    1|    //      |null|    1|    //      |  30|    1|    //      +----+-----+        spark.stop()  }

 

spark 基本操作（二）