How to do Luhn check in df column in spark scala - scala

Question

df has one string column like "100256437". I want to add one more column to check whether it pass Luhn. If pass, lit(true), else lit(false)
def Mod10(c: Column): Column = {
var (odd, sum) = (true, 0)
for (int <- c.reverse.map { _.toString.toShort }) {
println(int)
if (odd) sum += int
else sum += (int * 2 % 10) + (int / 5)
odd = !odd
}
lit(sum % 10 === 0)
}
Error:
error: value reverse is not a member of org.apache.spark.sql.Column
for (int <- c.reverse.map { _.toString.toShort }) {
^
error: value === is not a member of Int
lit(sum % 10 === 0)
^

Answer 1

Looks like, you are dealing with Spark Dataframes.
Lets say you have this dataframe
val df = List("100256437", "79927398713").toDF()
df.show()
+-----------+
| value|
+-----------+
| 100256437|
|79927398713|
+-----------+
Now, you can implement this Luhn test as an UDF,
val isValidLuhn = udf { (s: String) =>
val array = s.toCharArray.map(_.toString.toInt)
val len = array.length
var i = 1
while (i < len) {
if (i % 2 == 0) {
var updated = array(len - i) * 2
while (updated > 9) {
updated = updated.toString.toCharArray.map(_.toString.toInt).sum
}
array(len - i) = updated
}
i = i + 1
}
val sum = array.sum
println(array.toList)
(sum % 10) == 0
}
Which can be used as,
val dfWithLuhnCheck = df.withColumn("isValidLuhn", isValidLuhn(col("value")))
dfWithLuhnCheck.show()
+-----------+-----------+
| value|isValidLuhn|
+-----------+-----------+
| 100256437| true|
|79927398713| true|
+-----------+-----------+