CreateDataFrame takes 2 arguments , an rdd and schema.
my schema is like this
val schemas= StructType(
Seq(
StructField("number",IntegerType,false),
StructField("notation", StringType,false)
)
)
in one case i am able to create dataframe from RDD like below:
`val data1=Seq(Row(1,"one"),Row(2,"two"))
val rdd=spark.sparkContext.parallelize(data1)
val final_df= spark.createDataFrame(rdd,schemas)`
In other case like below .. i am not able to
`val data2=Seq((1,"one"),(2,"two"))
val rdd=spark.sparkContext.parallelize(data2)
val final_df= spark.createDataFrame(rdd,schemas)`
Whats wrong with data2 for not able to become a valid rdd for Dataframe?
but we can able to create dataframe using toDF() with data2 but not CreateDataFrame.
val data2_DF=Seq((1,"one"),(2,"two")).toDF("number", "notation")
Please help me understand this behaviour.
Is Row mandatory while creating dataframe?
