We can use the following function to covert a single integer value.
val x=100
Integer.toString(x, 16).toUpperCase
But how to apply it to a integer column to generate a new column with hex string? thanks!
The below method does not work.
testDF = testDF.withColumn("data_hex_string", Integer.toString(testDF("data"), 16).toUpperCase)
AFAIK, there isn't a spark native function, so make a udf function to do that.
import org.apache.spark.sql.functions.udf
def toHex = udf((int: Int) => java.lang.Integer.toString(int, 16).toUpperCase)
df.withColumn("hex", toHex($"int")).show()
+---+---+---+
| id|int|hex|
+---+---+---+
| 1| 1| 1|
| 2| 11| B|
| 3| 23| 17|
+---+---+---+
As @jxc already mentioned in a comment, use the conv function:
import org.apache.spark.sql.functions.{conv, lower}
df.withColumn("hex", conv($"int_col",10,16)).show
For those who want lowercase, wrap it with lower:
df.withColumn("hex", lower(conv($"int_col",10,16))).show
