如何自动创建StructType以将RDD传递给DataFrame

Question

我想将RDD保存为parquet文件。为此，我将RDD传递给DataFrame，然后使用结构将DataFrame保存为parquet文件:

    val aStruct = new StructType(Array(StructField("id",StringType,nullable = true),
                                       StructField("role",StringType,nullable = true)))
    val newDF = sqlContext.createDataFrame(filtered, aStruct)

问题是如何为所有列自动创建aStruct假设它们都是StringType ?另外，nullable = true的含义是什么?这是否意味着所有的空值都将被Null代替?

Answer 1

为什么不使用内置的toDF呢?

scala> val myRDD = sc.parallelize(Seq(("1", "roleA"), ("2", "roleB"), ("3", "roleC")))
myRDD: org.apache.spark.rdd.RDD[(String, String)] = ParallelCollectionRDD[60] at parallelize at <console>:27
scala> val colNames = List("id", "role")
colNames: List[String] = List(id, role)
scala> val myDF = myRDD.toDF(colNames: _*)
myDF: org.apache.spark.sql.DataFrame = [id: string, role: string]
scala> myDF.show
+---+-----+
| id| role|
+---+-----+
|  1|roleA|
|  2|roleB|
|  3|roleC|
+---+-----+
scala> myDF.printSchema
root
 |-- id: string (nullable = true)
 |-- role: string (nullable = true)
scala> myDF.write.save("myDF.parquet")

nullable=true仅仅意味着指定的列可以包含null值(这对于通常没有null值的int列尤其有用——Int没有NA或null)。