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Home/Questions/Spark/Big Data/Write a PySpark script to filter out invalid records from a dataset and calculate the average for a specific column, ensuring the schema is strictly defined at runtime.

Write a PySpark script to filter out invalid records from a dataset and calculate the average for a specific column, ensuring the schema is strictly defined at runtime.

Spark/Big Datamedium0.7 min readPremium
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Asked at 1 company
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questions in Spark/Big Data
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Bristol Myers Squibb
Key Concepts Tested
partitionspark
Expert AnswerPremium
134 wordsInterview-ready
**Why It Matters (Architectural Logic)**: Strict schemas reject malformed data at read time—fail fast vs. silent corruption. FAILFAST mode prevents partial loads. Use a strictly defined schema via StructType to reject malformed records at read time. Define schema: `schema = StructType([StructField("id", LongType()), StructField("value", DoubleType())])`. Read with schema: `df = spark.read.schema(schema).csv(path)`....
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