I am trying to convert a data frame to RDD, then perform some operations below to return tuples:
df.rdd.map { t=>
(t._2 + "_" + t._3 , t)
}.take(5)
Then I got the error below. Anyone have any ideas? Thanks!
<console>:37: error: value _2 is not a member of org.apache.spark.sql.Row
(t._2 + "_" + t._3 , t)
^
When you convert a DataFrame to RDD, you get an RDD[Row]
, so when you use map
, your function receives a Row
as parameter. Therefore, you must use the Row
methods to access its members (note that the index starts from 0):
df.rdd.map {
row: Row => (row.getString(1) + "_" + row.getString(2), row)
}.take(5)
You can view more examples and check all methods available for Row
objects in the Spark scaladoc.
Edit: I don't know the reason why you are doing this operation, but for concatenating String columns of a DataFrame you may consider the following option:
import org.apache.spark.sql.functions._
val newDF = df.withColumn("concat", concat(df("col2"), lit("_"), df("col3")))
You can access every element of a Row like if it was a List
or Array
, it means using (index)
, however you can use the method get
also.
For example:
df.rdd.map {t =>
(t(2).toString + "_" + t(3).toString, t)
}.take(5)