Passing two columns to a udf in scala?

Question

I have a dataframe containing two columns,one is data and the other column is character count in that data field.

Data    Count
Hello   5
How     3
World   5

I want to change value of column data based on the value in count column. How can this be achieved? I tried this using an udf :

invalidrecords.withColumn("value",appendDelimiterError(invalidrecords("value"),invalidrecords("a_cnt")))

This seems to fail, is this the correct way to do it?

Answer 1

Here's an easy way of doing it

first you create a dataframe

import sqlContext.implicits._
val invalidrecords = Seq(
  ("Hello", 5),
  ("How", 3),
  ("World", 5)
).toDF("Data", "Count")

you should have

+-----+-----+
|Data |Count|
+-----+-----+
|Hello|5    |
|How  |3    |
|World|5    |
+-----+-----+

Then you define udf function as

import org.apache.spark.sql.functions._
def appendDelimiterError = udf((data: String, count: Int) => "value with error" )

And you call using withColumn as

invalidrecords.withColumn("value",appendDelimiterError(invalidrecords("Data"),invalidrecords("Count"))).show(false)

You should have output as

+-----+-----+----------------+
|Data |Count|value           |
+-----+-----+----------------+
|Hello|5    |value with error|
|How  |3    |value with error|
|World|5    |value with error|
+-----+-----+----------------+

You can write your logic instead of returning a string from udf function

Edited

Answering your requirements in the comment below would require you to change the udf function and withColumn as below

def appendDelimiterError = udf((data: String, count: Int) => {
  if(count < 5) s"convert value to ${data} - error"
  else data
} )

invalidrecords.withColumn("Data",appendDelimiterError(invalidrecords("Data"),invalidrecords("Count"))).show(false)

you should have output as

+----------------------------+-----+
|Data                        |Count|
+----------------------------+-----+
|Hello                       |5    |
|convert value to How - error|3    |
|World                       |5    |
+----------------------------+-----+