Create Top-3-movies.py

 Add Top-3-movies.py for PySpark and update contributors list

This pull request adds the Top-3-movies.py script for PySpark functionality and includes myself (divith raju) in the contributors list.

Author: divithraju

Top-3-movies.py

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+#find top 3 movie based on the rating
+
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import avg
+
+# Initialize Spark Session
+#spark = SparkSession.builder.appName("TopMovies").getOrCreate()
+
+# Sample DataFrames
+data_movies = [(1, "Movie A"), (2, "Movie B"), (3, "Movie C"), (4, "Movie D"), (5, "Movie E")]
+
+data_ratings = [(1, 101, 4.5), (1, 102, 4.0), (2, 103, 5.0), 
+                (2, 104, 3.5), (3, 105, 4.0), (3, 106, 4.0), 
+                (4, 107, 3.0), (5, 108, 2.5), (5, 109, 3.0)]
+
+columns_movies = ["MovieID", "MovieName"]
+columns_ratings = ["MovieID", "UserID", "Rating"]
+
+# Creating DataFrames
+df_movies = spark.createDataFrame(data_movies, columns_movies)
+df_ratings = spark.createDataFrame(data_ratings, columns_ratings)
+
+# Calculating average ratings
+avg_ratings = df_ratings.groupBy('MovieID').agg(avg('Rating').alias('AvgRating'))
+
+# Joining with df_movies to get movie names
+top_movies = avg_ratings.join(df_movies, 'MovieID').orderBy('AvgRating', ascending=False).limit(3)
+
+# Showing the top 3 movies
+top_movies.show()