Performance issue while calling mlflow endpoint

[sanjay]

Hi,

I have pyspark dataframe and pyspark udf which calls mlflow model for each row but its performance is too slow.

Here is sample code

def myfunc(input_text):
   restult = mlflowmodel.predict(input_text)
   return result

myfuncUDF = udf(myfunc,StringType())

df = spark.sql("select * from test")
df=df.withColumn("test_result",myfuncUDF("input_text"))

Please suggest how to improve the performance.

Regards,
Sanjay

[sanjay]

Thank you Kaniz for the suggestions. This is really helpful. I even tried using applyInPandas. Not sure if this is better than spark UDF. If not can you help me in converting this function to pandas udf or any other optimized function.

def myfunc(input_text):

   restult = mlflowmodel.predict(input_text)

   return result

def myfuncUDF(pdf):

  pdf['test_result']=pdf["input_text"].apply(myfunc)

  return pdf

df = spark.sql("select * from test")

df = df.groupBy("id").applyInPandas(myfuncUDF)

Regards,

Sanjay

[sanjay]

Thank you @Retired_mod, its really helpful and did worked. Another quick question, I have to pass 2 parameters as input to myfunc. Please help how to pass multiple parameters. 

def myfunc(input_text, param2):
   # Assuming mlflowmodel is defined elsewhere
   result = mlflowmodel.predict(input_text, param2)
   return result

# Create a Pandas UDF
@pandas_udf(StringType())
def myfunc_udf(input_text_series: pd.Series, param2_series: pd.Series) -> pd.Series:
   return input_text_series.apply(myfunc) ??

[sanjay]

Hi Kaniz,

I started getting following error after using myfunc_udf with 2 parameters.

pythonException: 'ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

Regards,

Sanjay

[sanjay]

Hi @Retired_mod Appreciate if you can help in resolving this issue.

Regards,

Sanjay

[Isabeente]

I need to send two arguments to myfunc, thus I have another brief question. I need some guidance on how to pass in many parameters.

[BR_DatabricksAI]

Hello Sanjay, 

Could you please share your code snippet as per latest changes?

[sanjay]

Hi,

Here is code snippet as per latest changes.

def myfunc(t1,t2)

  return 'test'

@pandas_udf(psf.StringType())

def myfunc_udf(input_text_series: pd.Series, param2_series: pd.Series) -> pd.Series:

  def apply_myfunc(input_text, param2)

    return myfunc(input_text, param2)

  return input_text_series.apply(apply_myfunc, param2_series)

df.withColumn("result", myfunc_udf("input_text1", "input_text2"))

But I am getting error while running this

pythonException: 'ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

[BR_DatabricksAI]

Hello Sanjay,

The above code don't have the df defined. Can you share your df.show() output. 

[Isabeente]

So good