The steps are:
- Define python function
- Register function as UDF in spark
- Use the function, as we would use any other PySpark function.
Example Scenario
Filter rows with invalid mobile numbers in the data below. A mobile number is valid when.
- It has 10 digits
- It has only numbers
+-----+-------------+
| name|mobile_number|
+-----+-------------+
|Alice| 9876543210|
| Bob| 1234|
|Chris| abcd|
+-----+-------------+
Setup (Not required on databricks)
# NOT REQUIRED FOR DATABRICKS
# for jupyter notebook
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity='all'
# Create spark session (not required on databricks)
from pyspark.sql import SparkSession
spark = SparkSession.builder.master("local[*]").getOrCreate()
Define and use UDF
Perform imports
from pyspark.sql import types as T
from pyspark.sql import functions as F
Create sample dataframe
data = [
("Alice", "9876543210"),
("Bob", "1234"),
("Chris", "abcd"),
]
schema= ["name", "mobile_number"]
contact_df = spark.createDataFrame(data = data, schema = schema)
contact_df.show()
Define python function, and declare it as a UDF
# Create python function
def validate_mobile_number(mobile_number):
"""check if mobile number string is numeric, and has 10 digits"""
cleaned_mobile_number = str(mobile_number).strip()
if len(cleaned_mobile_number) == 10 and cleaned_mobile_number.isdigit():
return True
return False
# Register python function as UDF
validate_mobile_number_udf = F.udf(lambda n: validate_mobile_number(n),T.BooleanType())
Use UDF to create a new column
# Use UDF to create a new column
df = contact_df.withColumn("is_number_valid", validate_mobile_number_udf(F.col("mobile_number")))
df.show()
+-----+-------------+---------------+
| name|mobile_number|is_number_valid|
+-----+-------------+---------------+
|Alice| 9876543210| true|
| Bob| 1234| false|
|Chris| abcd| false|
+-----+-------------+---------------+
Example scenarios
UDFs are used to implement logic cannot be implemented using SQL or PySpark dataframe functions.
Some example scenarios are:
- Validate email addresses
- Validate IP addresses
That's all. Enjoy.