TOO MANY ARGUMENTS FOR METHOD MAP SPARK CODE

That registered function calls another function toInt (), which we donвЂ™t need to register. First, we create a function colsInt and register it. Yields below output after applying map() operation. df spark.createDataFrame(data,schemaschema) Now we do two things. Spark provides 2 map transformations signatures on DataFrame one takes.

As you can see, the method takes the Map and the target file size.

Val df3Map = df3.toDF('fullName','id','salary') In this map () example, we are adding a new element with value 1 for each element, the result of the RDD is PairRDDFunctions which contains key-value pairs, word of type String as Key and 1 of type Int as value. This is where we find the group of smaller files that could be merged. (fullName, row.getString(3),row.getInt(5))

TOO MANY ARGUMENTS FOR METHOD MAP SPARK CODE

Val fullName = row.getString(0) +row.getString(1) +row.getString(2) The code looks like it might be off in other areas, but without the rest I can't be sure, so at minimum this should get you moving you need either a semicolon after your split or to put the two separate statements on separate lines. One key point to remember is these both transformations returns the DatasetВ but not the DataFrameВ (In Spark 2.0, DataFrame = Dataset). 2.1 Dataframe map() syntaxДЎ) map(func : scala.Function1)(implicit evidence$6 : .Encoder)Дў) map(func : ., encoder : .Encoder)

If you want a DataFrame as output then you need to convert the Dataset to DataFrame using toDF()В function. if you notice below signatures, both these functions returns Dataset but not DataFrame (DataFrame=Dataset). Spark provides 2 map transformations signatures on DataFrame one takesВ scala.function1В as an argument and the other takes Spark MapFunction.

Too many arguments for method map spark