This might not be the easiest way, but it's pretty easy: you can use
Row(field_1, ..., field_n) as a pattern in a case match. So if you have a data
frame with foo as an int column and bar as a String columns and you want to
construct instances of a case class that wraps these up, you can do something
like this:
// assuming Record is declared as case class Record(foo: Int, bar: String)
// and df is a data frame
df.map {
case Row(foo: Int, bar: String) => Record(foo, bar)
}
best,
wb
----- Original Message -----
> From: "Alexander Ulanov" <alexander.ula...@hp.com>
> To: dev@spark.apache.org
> Sent: Friday, May 8, 2015 11:50:53 AM
> Subject: Easy way to convert Row back to case class
>
> Hi,
>
> I created a dataset RDD[MyCaseClass], converted it to DataFrame and saved to
> Parquet file, following
> https://spark.apache.org/docs/latest/sql-programming-guide.html#interoperating-with-rdds
>
> When I load this dataset with sqlContext.parquetFile, I get DataFrame with
> column names as in initial case class. I want to convert this DataFrame to
> RDD to perform RDD operations. However, when I convert it I get RDD[Row] and
> all information about row names gets lost. Could you suggest an easy way to
> convert DataFrame to RDD[MyCaseClass]?
>
> Best regards, Alexander
>
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