UDFs with modular code - INVALID_ARGUMENT

Zeruno — Fri, 09 Aug 2024 15:42:27 GMT

I am migrating a massive codebase to Pyspark on Azure Databricks,using DLT Pipelines. It is very important that code will be modular, that is I am looking to make use of UDFs for the timebeing that use modules and classes.

I am receiving the following error:

org.apache.spark.SparkRuntimeException: [UDF_ERROR.PAYLOAD] Execution of function <lambda>(MYCOLUMN_NAME1531) 
2) failed - failed to set payload
== Error ==
INVALID_ARGUMENT: No module named 'mymodule'
== Stacktrace ==

With the following code (anonymized to create a minimum working example):

# demo.py
from pyspark.sql.functions import col
import dlt 
import mymodule

demodata = mymodule.DemoData("EX")
helper = mymodule.Helper(demodata)

@dlt.table(name="DEMO")
def table():
    return (
spark.readStream.format("cloudFiles")
.option("cloudFiles.Format", "PARQUET")
.load("abfss://...")
.withColumn("DEMO", helper.transform(col("MYCOLUMN_NAME")))
)


# mymodule.py
from pyspark.sql.typos import StringType
from pyspark.sql.functions import udf

class DemoData:
    def __init__(self, suffix)
        self.suffix = suffix

class Helper:
    def __init__(self, demoData):
        _suffix = demoData.suffix
        self.transform = udf(lambda _string: self.helper(_string, _suffix), StringType())

    @staticmethod
    def helper(string, suffix):
        return string + suffix

#dlt

Can someone help me understand what is happening? I am thinking that the Spark Worker cannot see my module. Is this correct? How would I use UDFs with modular code? I understand that this might not be ideal, but I want to understand this technicality.

Re: UDFs with modular code - INVALID_ARGUMENT

briceg — Wed, 14 May 2025 23:12:04 GMT

Hi @Zeruno. What you can do is to package up your code and pip install in your pipeline. I had the same situation where I developed some code which ran fine in a notebook, but when used in a DLT pipeline, the deps were not found. Packaging them up and then installing them via pip in the beginning of my notebook allowed me to pull in my code and custom udfs.

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UDFs with modular code - INVALID_ARGUMENT

Re: UDFs with modular code - INVALID_ARGUMENT