Spark Performance Tuning MCQ Questions with Answers (Latest 2026)

Q1. Which option best describes partition sizing?

A. Pure tiny partitions. B. Right-sized partitions (~100-300MB) for parallelism. C. Single huge partition. D. Pure rows only.

Select an answer to check.

Answer: Right-sized partitions (~100-300MB) for parallelism.

Here, Right-sized partitions (~100-300MB) for parallelism. is the right choice. Avoid skew and small files. It aligns directly with what the question asks about which option best describes partition sizing. A quick elimination of partially true options helps confirm it.

Q2. What is the primary purpose of partition sizing?

A. Pure tiny partitions. B. Right-sized partitions (~100-300MB) for parallelism. C. Single huge partition. D. Pure rows only.

Select an answer to check.

Answer: Right-sized partitions (~100-300MB) for parallelism.

In this case, Right-sized partitions (~100-300MB) for parallelism. is correct. Avoid skew and small files. It aligns directly with what the question asks about what is the primary purpose of partition sizing. A quick elimination of partially true options helps confirm it.

Q3. Which statement about partition sizing is most accurate?

A. Right-sized partitions (~100-300MB) for parallelism. B. Pure tiny partitions. C. Pure rows only. D. Single huge partition.

Select an answer to check.

Answer: Right-sized partitions (~100-300MB) for parallelism.

The best option here is Right-sized partitions (~100-300MB) for parallelism.. Avoid skew and small files. It aligns directly with what the question asks about which statement about partition sizing is most accurate. A quick elimination of partially true options helps confirm it.

Q4. How is partition sizing best characterized?

A. Right-sized partitions (~100-300MB) for parallelism. B. Pure rows only. C. Pure tiny partitions. D. Single huge partition.

Select an answer to check.

Answer: Right-sized partitions (~100-300MB) for parallelism.

For this question, Right-sized partitions (~100-300MB) for parallelism. is correct. Avoid skew and small files. It aligns directly with what the question asks about how is partition sizing best characterized. A quick elimination of partially true options helps confirm it.

Q5. Which option best describes avoiding small files?

A. Pure log. B. Compact small files for fewer tasks. C. Always many tiny files. D. Pure single file always.

Select an answer to check.

Answer: Compact small files for fewer tasks.

Compact small files for fewer tasks. is the correct answer here. Reduces metadata overhead. It aligns directly with what the question asks about which option best describes avoiding small files. A quick elimination of partially true options helps confirm it.

Q6. What is the primary purpose of avoiding small files?

A. Pure single file always. B. Always many tiny files. C. Compact small files for fewer tasks. D. Pure log.

Select an answer to check.

Answer: Compact small files for fewer tasks.

Here, Compact small files for fewer tasks. is the right choice. Reduces metadata overhead. This matches the core idea being tested around what is the primary purpose of avoiding small. A quick elimination of partially true options helps confirm it.

Q7. Which statement about avoiding small files is most accurate?

A. Compact small files for fewer tasks. B. Pure log. C. Pure single file always. D. Always many tiny files.

Select an answer to check.

Answer: Compact small files for fewer tasks.

In this case, Compact small files for fewer tasks. is correct. Reduces metadata overhead. This matches the core idea being tested around which statement about avoiding small files is most. A quick elimination of partially true options helps confirm it.

Q8. How is avoiding small files best characterized?

A. Always many tiny files. B. Pure log. C. Pure single file always. D. Compact small files for fewer tasks.

Select an answer to check.

Answer: Compact small files for fewer tasks.

The best option here is Compact small files for fewer tasks.. Reduces metadata overhead. This matches the core idea being tested around how is avoiding small files best characterized. A quick elimination of partially true options helps confirm it.

Q9. Which option best describes predicate/projection pushdown?

A. Post-scan only. B. Pure broadcast. C. Filter and project at source. D. Pure shuffle.

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Answer: Filter and project at source.

For this question, Filter and project at source. is correct. Reduces I/O dramatically. This matches the core idea being tested around which option best describes predicate/projection pushdown. A quick elimination of partially true options helps confirm it.

Q10. What is the primary purpose of predicate/projection pushdown?

A. Filter and project at source. B. Pure shuffle. C. Pure broadcast. D. Post-scan only.

Select an answer to check.

Answer: Filter and project at source.

Filter and project at source. is the correct answer here. Reduces I/O dramatically. This matches the core idea being tested around what is the primary purpose of predicate/projection pushdown. A quick elimination of partially true options helps confirm it.

Q11. Which statement about predicate/projection pushdown is most accurate?

A. Pure shuffle. B. Filter and project at source. C. Post-scan only. D. Pure broadcast.

Select an answer to check.

Answer: Filter and project at source.

Here, Filter and project at source. is the right choice. Reduces I/O dramatically. That is exactly the concept behind which statement about predicate/projection pushdown is most accurate in this context. A quick elimination of partially true options helps confirm it.

Q12. How is predicate/projection pushdown best characterized?

A. Pure shuffle. B. Filter and project at source. C. Post-scan only. D. Pure broadcast.

Select an answer to check.

Answer: Filter and project at source.

In this case, Filter and project at source. is correct. Reduces I/O dramatically. That is exactly the concept behind how is predicate/projection pushdown best characterized in this context. A quick elimination of partially true options helps confirm it.

Q13. Which option best describes partition pruning?

A. Pure index seek. B. Always full scan. C. Skip partitions outside filter range. D. Pure broadcast.

Select an answer to check.

Answer: Skip partitions outside filter range.

The best option here is Skip partitions outside filter range.. Big I/O savings. That is exactly the concept behind which option best describes partition pruning in this context. A quick elimination of partially true options helps confirm it.

Q14. What is the primary purpose of partition pruning?

A. Skip partitions outside filter range. B. Pure index seek. C. Pure broadcast. D. Always full scan.

Select an answer to check.

Answer: Skip partitions outside filter range.

For this question, Skip partitions outside filter range. is correct. Big I/O savings. That is exactly the concept behind what is the primary purpose of partition pruning in this context. A quick elimination of partially true options helps confirm it.

Q15. Which statement about partition pruning is most accurate?

A. Pure index seek. B. Skip partitions outside filter range. C. Always full scan. D. Pure broadcast.

Select an answer to check.

Answer: Skip partitions outside filter range.

Skip partitions outside filter range. is the correct answer here. Big I/O savings. That is exactly the concept behind which statement about partition pruning is most accurate in this context. A quick elimination of partially true options helps confirm it.

Q16. How is partition pruning best characterized?

A. Skip partitions outside filter range. B. Always full scan. C. Pure index seek. D. Pure broadcast.

Select an answer to check.

Answer: Skip partitions outside filter range.

Here, Skip partitions outside filter range. is the right choice. Big I/O savings. It fits the requirement in the prompt about how is partition pruning best characterized. A quick elimination of partially true options helps confirm it.

Q17. Which option best describes DPP?

A. Pure static pruning. B. Pure broadcast. C. Pure cache. D. Dynamic Partition Pruning at runtime.

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Answer: Dynamic Partition Pruning at runtime.

In this case, Dynamic Partition Pruning at runtime. is correct. Spark 3 with AQE. It fits the requirement in the prompt about which option best describes dpp. A quick elimination of partially true options helps confirm it.

Q18. What is the primary purpose of DPP?

A. Pure broadcast. B. Pure cache. C. Pure static pruning. D. Dynamic Partition Pruning at runtime.

Select an answer to check.

Answer: Dynamic Partition Pruning at runtime.

The best option here is Dynamic Partition Pruning at runtime.. Spark 3 with AQE. It fits the requirement in the prompt about what is the primary purpose of dpp. A quick elimination of partially true options helps confirm it.

Q19. Which statement about DPP is most accurate?

A. Dynamic Partition Pruning at runtime. B. Pure cache. C. Pure static pruning. D. Pure broadcast.

Select an answer to check.

Answer: Dynamic Partition Pruning at runtime.

For this question, Dynamic Partition Pruning at runtime. is correct. Spark 3 with AQE. It fits the requirement in the prompt about which statement about dpp is most accurate. A quick elimination of partially true options helps confirm it.

Q20. How is DPP best characterized?

A. Dynamic Partition Pruning at runtime. B. Pure broadcast. C. Pure static pruning. D. Pure cache.

Select an answer to check.

Answer: Dynamic Partition Pruning at runtime.

Dynamic Partition Pruning at runtime. is the correct answer here. Spark 3 with AQE. It fits the requirement in the prompt about how is dpp best characterized. A quick elimination of partially true options helps confirm it.

Q21. Which option best describes AQE?

A. Pure CBO once. B. Adaptive Query Execution. C. Pure static plan. D. Pure scheduler.

Select an answer to check.

Answer: Adaptive Query Execution.

Here, Adaptive Query Execution. is the right choice. Skew, joins, partitions. This is the most accurate statement for which option best describes aqe. A quick elimination of partially true options helps confirm it.

Q22. What is the primary purpose of AQE?

A. Pure scheduler. B. Pure CBO once. C. Adaptive Query Execution. D. Pure static plan.

Select an answer to check.

Answer: Adaptive Query Execution.

In this case, Adaptive Query Execution. is correct. Skew, joins, partitions. This is the most accurate statement for what is the primary purpose of aqe. A quick elimination of partially true options helps confirm it.

Q23. Which statement about AQE is most accurate?

A. Pure scheduler. B. Pure CBO once. C. Pure static plan. D. Adaptive Query Execution.

Select an answer to check.

Answer: Adaptive Query Execution.

The best option here is Adaptive Query Execution.. Skew, joins, partitions. This is the most accurate statement for which statement about aqe is most accurate. A quick elimination of partially true options helps confirm it.

Q24. How is AQE best characterized?

A. Adaptive Query Execution. B. Pure static plan. C. Pure CBO once. D. Pure scheduler.

Select an answer to check.

Answer: Adaptive Query Execution.

For this question, Adaptive Query Execution. is correct. Skew, joins, partitions. This is the most accurate statement for how is aqe best characterized. A quick elimination of partially true options helps confirm it.

Q25. Which option best describes broadcast joins?

A. Pure sort-merge. B. Pure RDD. C. Pure cross. D. Small side broadcast to executors.

Select an answer to check.

Answer: Small side broadcast to executors.

Small side broadcast to executors. is the correct answer here. Best for small/large joins. This is the most accurate statement for which option best describes broadcast joins. A quick elimination of partially true options helps confirm it.

Q26. What is the primary purpose of broadcast joins?

A. Pure RDD. B. Pure cross. C. Small side broadcast to executors. D. Pure sort-merge.

Select an answer to check.

Answer: Small side broadcast to executors.

Here, Small side broadcast to executors. is the right choice. Best for small/large joins. It aligns directly with what the question asks about what is the primary purpose of broadcast joins. The other options are either incomplete or contextually incorrect.

Q27. Which statement about broadcast joins is most accurate?

A. Pure cross. B. Pure RDD. C. Small side broadcast to executors. D. Pure sort-merge.

Select an answer to check.

Answer: Small side broadcast to executors.

In this case, Small side broadcast to executors. is correct. Best for small/large joins. It aligns directly with what the question asks about which statement about broadcast joins is most accurate. The other options are either incomplete or contextually incorrect.

Q28. How is broadcast joins best characterized?

A. Pure sort-merge. B. Pure RDD. C. Pure cross. D. Small side broadcast to executors.

Select an answer to check.

Answer: Small side broadcast to executors.

The best option here is Small side broadcast to executors.. Best for small/large joins. It aligns directly with what the question asks about how is broadcast joins best characterized. The other options are either incomplete or contextually incorrect.

Q29. Which option best describes broadcast threshold?

A. Never broadcast. B. Pure log. C. spark.sql.autoBroadcastJoinThreshold. D. Always broadcast.

Select an answer to check.

Answer: spark.sql.autoBroadcastJoinThreshold.

For this question, spark.sql.autoBroadcastJoinThreshold. is correct. Tunable size threshold. It aligns directly with what the question asks about which option best describes broadcast threshold. The other options are either incomplete or contextually incorrect.

Q30. What is the primary purpose of broadcast threshold?

A. Always broadcast. B. spark.sql.autoBroadcastJoinThreshold. C. Never broadcast. D. Pure log.

Select an answer to check.

Answer: spark.sql.autoBroadcastJoinThreshold.

spark.sql.autoBroadcastJoinThreshold. is the correct answer here. Tunable size threshold. It aligns directly with what the question asks about what is the primary purpose of broadcast threshold. The other options are either incomplete or contextually incorrect.

Q31. Which statement about broadcast threshold is most accurate?

A. spark.sql.autoBroadcastJoinThreshold. B. Pure log. C. Always broadcast. D. Never broadcast.

Select an answer to check.

Answer: spark.sql.autoBroadcastJoinThreshold.

Here, spark.sql.autoBroadcastJoinThreshold. is the right choice. Tunable size threshold. This matches the core idea being tested around which statement about broadcast threshold is most accurate. The other options are either incomplete or contextually incorrect.

Q32. How is broadcast threshold best characterized?

A. Never broadcast. B. Pure log. C. Always broadcast. D. spark.sql.autoBroadcastJoinThreshold.

Select an answer to check.

Answer: spark.sql.autoBroadcastJoinThreshold.

In this case, spark.sql.autoBroadcastJoinThreshold. is correct. Tunable size threshold. This matches the core idea being tested around how is broadcast threshold best characterized. The other options are either incomplete or contextually incorrect.

Q33. Which option best describes salting?

A. Pure log. B. Add salt to skewed keys to spread tasks. C. Pure broadcast only. D. Pure cache.

Select an answer to check.

Answer: Add salt to skewed keys to spread tasks.

The best option here is Add salt to skewed keys to spread tasks.. Combine with AQE skew handling. This matches the core idea being tested around which option best describes salting. The other options are either incomplete or contextually incorrect.

Q34. What is the primary purpose of salting?

A. Pure cache. B. Add salt to skewed keys to spread tasks. C. Pure broadcast only. D. Pure log.

Select an answer to check.

Answer: Add salt to skewed keys to spread tasks.

For this question, Add salt to skewed keys to spread tasks. is correct. Combine with AQE skew handling. This matches the core idea being tested around what is the primary purpose of salting. The other options are either incomplete or contextually incorrect.

Q35. Which statement about salting is most accurate?

A. Add salt to skewed keys to spread tasks. B. Pure log. C. Pure cache. D. Pure broadcast only.

Select an answer to check.

Answer: Add salt to skewed keys to spread tasks.

Add salt to skewed keys to spread tasks. is the correct answer here. Combine with AQE skew handling. This matches the core idea being tested around which statement about salting is most accurate. The other options are either incomplete or contextually incorrect.

Q36. How is salting best characterized?

A. Pure log. B. Add salt to skewed keys to spread tasks. C. Pure broadcast only. D. Pure cache.

Select an answer to check.

Answer: Add salt to skewed keys to spread tasks.

Here, Add salt to skewed keys to spread tasks. is the right choice. Combine with AQE skew handling. That is exactly the concept behind how is salting best characterized in this context. The other options are either incomplete or contextually incorrect.

Q37. Which option best describes avoid groupByKey on RDD?

A. Always groupByKey. B. Prefer reduceByKey for map-side combine. C. Pure flatMap. D. Pure shuffle.

Select an answer to check.

Answer: Prefer reduceByKey for map-side combine.

In this case, Prefer reduceByKey for map-side combine. is correct. Less shuffle traffic. That is exactly the concept behind which option best describes avoid groupbykey on rdd in this context. The other options are either incomplete or contextually incorrect.

Q38. What is the primary purpose of avoid groupByKey on RDD?

A. Pure shuffle. B. Always groupByKey. C. Prefer reduceByKey for map-side combine. D. Pure flatMap.

Select an answer to check.

Answer: Prefer reduceByKey for map-side combine.

The best option here is Prefer reduceByKey for map-side combine.. Less shuffle traffic. That is exactly the concept behind what is the primary purpose of avoid groupbykey in this context. The other options are either incomplete or contextually incorrect.

Q39. Which statement about avoid groupByKey on RDD is most accurate?

A. Pure shuffle. B. Always groupByKey. C. Prefer reduceByKey for map-side combine. D. Pure flatMap.

Select an answer to check.

Answer: Prefer reduceByKey for map-side combine.

For this question, Prefer reduceByKey for map-side combine. is correct. Less shuffle traffic. That is exactly the concept behind which statement about avoid groupbykey on rdd is in this context. The other options are either incomplete or contextually incorrect.

Q40. How is avoid groupByKey on RDD best characterized?

A. Always groupByKey. B. Pure shuffle. C. Prefer reduceByKey for map-side combine. D. Pure flatMap.

Select an answer to check.

Answer: Prefer reduceByKey for map-side combine.

Prefer reduceByKey for map-side combine. is the correct answer here. Less shuffle traffic. That is exactly the concept behind how is avoid groupbykey on rdd best characterized in this context. The other options are either incomplete or contextually incorrect.

Q41. Which option best describes avoid Python UDFs?

A. Always Python UDFs. B. Prefer SQL/Pandas UDFs for performance. C. Pure RDDs. D. Pure broadcast.

Select an answer to check.

Answer: Prefer SQL/Pandas UDFs for performance.

Here, Prefer SQL/Pandas UDFs for performance. is the right choice. SerDe overhead is real. It fits the requirement in the prompt about which option best describes avoid python udfs. The other options are either incomplete or contextually incorrect.

Q42. What is the primary purpose of avoid Python UDFs?

A. Pure broadcast. B. Always Python UDFs. C. Pure RDDs. D. Prefer SQL/Pandas UDFs for performance.

Select an answer to check.

Answer: Prefer SQL/Pandas UDFs for performance.

In this case, Prefer SQL/Pandas UDFs for performance. is correct. SerDe overhead is real. It fits the requirement in the prompt about what is the primary purpose of avoid python. The other options are either incomplete or contextually incorrect.

Q43. Which statement about avoid Python UDFs is most accurate?

A. Pure broadcast. B. Prefer SQL/Pandas UDFs for performance. C. Always Python UDFs. D. Pure RDDs.

Select an answer to check.

Answer: Prefer SQL/Pandas UDFs for performance.

The best option here is Prefer SQL/Pandas UDFs for performance.. SerDe overhead is real. It fits the requirement in the prompt about which statement about avoid python udfs is most. The other options are either incomplete or contextually incorrect.

Q44. How is avoid Python UDFs best characterized?

A. Pure RDDs. B. Always Python UDFs. C. Pure broadcast. D. Prefer SQL/Pandas UDFs for performance.

Select an answer to check.

Answer: Prefer SQL/Pandas UDFs for performance.

For this question, Prefer SQL/Pandas UDFs for performance. is correct. SerDe overhead is real. It fits the requirement in the prompt about how is avoid python udfs best characterized. The other options are either incomplete or contextually incorrect.

Q45. Which option best describes caching reused DFs?

A. Cache DFs reused multiple times. B. Pure logs. C. Pure broadcast. D. Always recompute.

Select an answer to check.

Answer: Cache DFs reused multiple times.

Cache DFs reused multiple times. is the correct answer here. Use appropriate storage level. It fits the requirement in the prompt about which option best describes caching reused dfs. The other options are either incomplete or contextually incorrect.

Q46. What is the primary purpose of caching reused DFs?

A. Pure broadcast. B. Pure logs. C. Cache DFs reused multiple times. D. Always recompute.

Select an answer to check.

Answer: Cache DFs reused multiple times.

Here, Cache DFs reused multiple times. is the right choice. Use appropriate storage level. This is the most accurate statement for what is the primary purpose of caching reused. The other options are either incomplete or contextually incorrect.

Q47. Which statement about caching reused DFs is most accurate?

A. Cache DFs reused multiple times. B. Always recompute. C. Pure broadcast. D. Pure logs.

Select an answer to check.

Answer: Cache DFs reused multiple times.

In this case, Cache DFs reused multiple times. is correct. Use appropriate storage level. This is the most accurate statement for which statement about caching reused dfs is most. The other options are either incomplete or contextually incorrect.

Q48. How is caching reused DFs best characterized?

A. Pure broadcast. B. Pure logs. C. Cache DFs reused multiple times. D. Always recompute.

Select an answer to check.

Answer: Cache DFs reused multiple times.

The best option here is Cache DFs reused multiple times.. Use appropriate storage level. This is the most accurate statement for how is caching reused dfs best characterized. The other options are either incomplete or contextually incorrect.

Q49. Which option best describes caching pitfalls?

A. Pure log. B. Never cache. C. Caching too much causes spill/eviction. D. Always cache everything.

Select an answer to check.

Answer: Caching too much causes spill/eviction.

For this question, Caching too much causes spill/eviction. is correct. Cache deliberately. This is the most accurate statement for which option best describes caching pitfalls. The other options are either incomplete or contextually incorrect.

Q50. What is the primary purpose of caching pitfalls?

A. Always cache everything. B. Never cache. C. Pure log. D. Caching too much causes spill/eviction.

Select an answer to check.

Answer: Caching too much causes spill/eviction.

Caching too much causes spill/eviction. is the correct answer here. Cache deliberately. This is the most accurate statement for what is the primary purpose of caching pitfalls. The other options are either incomplete or contextually incorrect.