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Implement a Spark job to find the top 10 most frequent words in a large text file.

Spark/Big Datahard0.6 min readPremium
Frequency
Low
Asked at 2 companies
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
CapcoPubmatic
Key Concepts Tested
partitionsparksqlwindow
Expert AnswerPremium
126 wordsInterview-ready
Core logic: read text → split → explode → filter empty → groupBy → count → orderBy desc → limit 10. Code: from pyspark.sql import functions as F; df = spark.read.text("path/to/file.txt"); words = df.select(F.explode(F.split(F.col("value"), "\\s+")).alias("word")); top10 = words.filter(F.length(F.col("word")) > 0).groupBy("word").count().orderBy(F.desc("count")).limit(10). **Why \\s+**: Handles multiple spaces/tabs; more robust than single space....
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