Compare Spark RDDs, DataFrames, and Spark SQL Benefits

Q: How do I practice SQL interview questions?

PracHub provides an interactive SQL console where you can write and test queries against real database schemas. Get instant feedback and compare your solution with the expected output.

Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at Experian.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Experian during technical interviews.

Question

spark_jobs

+---------+---------------------+-------+-----------+---------+
| job_id | submit_time          | user  | memory_gb | status  |
+---------+---------------------+-------+-----------+---------+
| 101     | 2023-10-20 10:35:00 | alice | 8         | success |
| 102     | 2023-10-20 11:10:00 | bob   | 16        | running |
| 103     | 2023-10-20 12:40:00 | carol | 32        | failed  |
+---------+---------------------+-------+-----------+---------+

##### Scenario

Big-data discussion on Spark and cloud pipelines

##### Question

Compare Spark RDDs, DataFrames and Spark SQL and state their advantages.

What benefits does Spark offer versus classic MapReduce?

Explain Spark’s lazy evaluation and how it optimizes execution.

Describe how you would submit and monitor jobs on AWS EMR or a similar managed cluster.

##### Hints

Mention in-memory processing, Catalyst and Tungsten optimizers, DAG scheduling, cost/scalability on the cloud.

PracHub · Accepted Answer

This question evaluates understanding of Apache Spark core abstractions (RDDs, DataFrames, Spark SQL), execution model concepts such as lazy evaluation and optimizer-driven execution, and operational competency with managed cloud cluster job submission and monitoring, categorized under Data Manipulation (SQL/Python) for a Data Scientist role.

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