How to Dynamically Parse and Handle Various Date Formats in Spark DataFrames?
I’m working on a Spark job where I need to process a large dataset that contains date strings in various formats. The date formats might include:
Spark SQL : Order of placing the select column changes the resultant dataframe when count is used
I have a dataframe, where I want to get the count of distinct calltypes ((column name).