I have a pyspark dataframe in which I need to add “translate” for a column.
I have the below code

I have a pyspark dataframe in which I need to add “translate” for a column.
I have the below code

I have a pyspark dataframe in which I need to add “translate” for a column.
I have the below code

I have a pyspark dataframe in which I need to add “translate” for a column.
I have the below code

I have a pyspark dataframe in which I need to add “translate” for a column.
I have the below code

I have a .zip file present on an ADLS path which contains multiple files of different formats. I want to get metadata of the files like file name, modification time present in it without unzipping it. I have a code which works for smaller zip but runs into memory issues for large zip files leading to job failures. Is there a way to handle this within PySpark itself?

I’m currently struggling with spark checkpoints and trying to understand what’s the difference between DataFrame and RDD checkpoints.

How can I read large file CSV file up 500 GB in Apache Spark and perform calculation and transformation on one of its Column. I have been given a large file to perform ETL and calculation on it. I am newbie in Python / Spark. Any help will be appreciated

I’m working with a pyspark dataframe in Azure Databricks and I’m trying to count how many unique (distinct) values a particular column has.

Yesterday, I ran a simple spark code on ingesting a large table. The code was simple in that it did a