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How would you fetch data from an API and load it into a DataFrame?

Spark/Big Datahard0.5 min readPremium
Frequency
Low
Asked at 1 company
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
Warner Bros Discovery
Key Concepts Tested
optimizationpartitionspark
Expert AnswerPremium
98 wordsInterview-ready
**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams. Fetch API → DataFrame: Use `requests` or `urllib` to call API, parse JSON, create RDD/DataFrame. Example: `import requests; r = requests.get(url); data = r.json(); df = spark.createDataFrame(data['results'])`. For pagination: loop with `next_page`; collect pages; concatenate. For large APIs: use async, batch, or streaming....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Warner Bros Discovery. The answer also includes follow-up discussion points that interviewers commonly explore.

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