I came across- the below lambda code line in PySpark while browsing a long python Jupyter notebook, I am trying to understand this piece of line. Can you explain what it does in a best possible way? Answer udf in PySpark assigns a Python function which is run for every row of Spark df. Creates a user defined function (UDF).
Tag: user-defined-functions
Python function make parameter mandatory if another parameter is passed
I have a function in Python as Is there a way to ensure that if the user passes the value of the parameter b it is necessary to pass the parameter c to myfunc? Answer You can write a simple if condition in your function. See the code below:
Why do we use pyspark UDF when python functions are faster than them? (Note. Not worrying about spark SQL commands)
I have a dataframe: Output: Now, a simple – Add 1 to ‘v’ can be done via SQL functions and UDF. If we ignore the SQL (best performant) We can create a UDF as: and call it: Time: 16.5sec But here is my question: if I DO NOT use udf and directly write: Time Taken – 352ms In a nutshell,
PySpark udf returns null when function works in Pandas dataframe
I’m trying to create a user-defined function that takes a cumulative sum of an array and compares the value to another column. Here is a reproducible example: In Pandas, this is the output: In Spark using temp_sdf.withColumn(‘len’, test_function_udf(‘x_ary’, ‘y’)), all of len ends up being null. Would anyone know why this is the case? Also, replacing cumsum_array = np.cumsum(np.flip(x_ary)) fails
Printing lines in a text file given line numbers
I am having trouble with a while loop statement for the question below. This is for a txt.file. ‘Write a program that allows the user to navigate through the lines of text in any text file. The program prompts the user for a filename and copies the lines of text from the file into a list. The program then prints