PySpark IllegalArgumentException: Column Count Type Mismatch - How to Fix

This error occurs when you attempt to provide a column with an incorrect data type to a PySpark function. The error message signifies that the function expects a column of type 'array' or 'array', but you are supplying a column of type 'array<struct<_1:string,_2:string>>'.

To fix this issue, you need to transform your column from 'array<struct<_1:string,_2:string>>' to either 'array' or 'array', depending on the function's requirements. The explode() function is a useful tool for this.

Here's an example illustrating the solution:

from pyspark.sql import SparkSession
from pyspark.sql.functions import explode

spark = SparkSession.builder.getOrCreate()

# Assuming your DataFrame is named 'df' and the column needing conversion is 'col'
df = spark.createDataFrame([(1, [('a', 'b'), ('c', 'd')]), (2, [('e', 'f'), ('g', 'h')])], ['id', 'col'])

# Utilize explode() to convert the column to array<string>
df_exploded = df.withColumn('col_exploded', explode(df.col))
df_exploded.show()

# Now you can employ the exploded column in your function
# ...

Through the explode() function, each element within the array of structs is transformed into a separate row with two string columns. You can then utilize these columns in your desired function.