Optimizing PySpark Code: Avoiding For Loop and Reduce While Maintaining Functionality
from pyspark.sql import Window from pyspark.sql import functions as F import functools from datetime import datetime def generate_new_rating_data(w_df, count_a, distinct_a, flag_a, suffix): if flag_a: w_df = w_df.where( (w_df[f”NR_Count{suffix}”] > 0) & (w_df[f”NR_Count{suffix}”] == w_df[f”Rate_Count{suffix}”]) ) window_spec = Window.partitionBy(“ID”).orderBy(“rating_order”) return { w_df.where(F.col(f”Rating_Rank{suffix}”) >= 250) .withColumn(“rank”, F.row_number().over(window_spec)) .where(F.col(“rank”) == 1) .select( F.col(“ID”), F.col(“Source”).alias(f”Source{suffix}”), F.col(f”Rating_Rank{suffix}”), F.col(f”NormCode{suffix}”).alias(f”Rating{suffix}”) ) } […]
How to import in Python the library spark_session?
I am trying to run a ipynb where there are these libraries:
Collect values as dictionary in parent column using Pyspark
I have code and data like below:
pyspark Exception in collect and take, first actions
I’m new to pyspark, i’m taking a beginner friendly course in that the first step was to import data and split based on delimeter comma (“,”), after splitting the data when i try to execute collect or take actions its throwing an error, please assist.