Practice Spark Performance Tuning MCQ questions with detailed explanations and clear answer validation. These MCQs help you revise core concepts, compare close options, and improve accuracy for interviews, certification exams, and technical screening rounds. Use this updated 2026 set to strengthen fundamentals and confidence.
Q51. Which statement about caching pitfalls is most accurate?
Select an answer to check.
Answer: Caching too much causes spill/eviction.
Here, Caching too much causes spill/eviction. is the right choice. Cache deliberately. It aligns directly with what the question asks about which statement about caching pitfalls is most accurate. Competing choices sound plausible, but they miss the key condition.
Q52. How is caching pitfalls best characterized?
Select an answer to check.
Answer: Caching too much causes spill/eviction.
In this case, Caching too much causes spill/eviction. is correct. Cache deliberately. It aligns directly with what the question asks about how is caching pitfalls best characterized. Competing choices sound plausible, but they miss the key condition.
Q53. Which option best describes spill?
Select an answer to check.
Answer: Memory overflow causes disk spill.
The best option here is Memory overflow causes disk spill.. Tune memory and partitions. It aligns directly with what the question asks about which option best describes spill. Competing choices sound plausible, but they miss the key condition.
Q54. What is the primary purpose of spill?
Select an answer to check.
Answer: Memory overflow causes disk spill.
For this question, Memory overflow causes disk spill. is correct. Tune memory and partitions. It aligns directly with what the question asks about what is the primary purpose of spill. Competing choices sound plausible, but they miss the key condition.
Q55. Which statement about spill is most accurate?
Select an answer to check.
Answer: Memory overflow causes disk spill.
Memory overflow causes disk spill. is the correct answer here. Tune memory and partitions. It aligns directly with what the question asks about which statement about spill is most accurate. Competing choices sound plausible, but they miss the key condition.
Q56. How is spill best characterized?
Select an answer to check.
Answer: Memory overflow causes disk spill.
Here, Memory overflow causes disk spill. is the right choice. Tune memory and partitions. This matches the core idea being tested around how is spill best characterized. Competing choices sound plausible, but they miss the key condition.
Q57. Which option best describes repartition vs coalesce?
In this case, Repartition shuffles; coalesce avoids shuffle. is correct. Pick based on need. This matches the core idea being tested around which option best describes repartition vs coalesce. Competing choices sound plausible, but they miss the key condition.
Q58. What is the primary purpose of repartition vs coalesce?
The best option here is Repartition shuffles; coalesce avoids shuffle.. Pick based on need. This matches the core idea being tested around what is the primary purpose of repartition vs. Competing choices sound plausible, but they miss the key condition.
Q59. Which statement about repartition vs coalesce is most accurate?
For this question, Repartition shuffles; coalesce avoids shuffle. is correct. Pick based on need. This matches the core idea being tested around which statement about repartition vs coalesce is most. Competing choices sound plausible, but they miss the key condition.
Q60. How is repartition vs coalesce best characterized?
Repartition shuffles; coalesce avoids shuffle. is the correct answer here. Pick based on need. This matches the core idea being tested around how is repartition vs coalesce best characterized. Competing choices sound plausible, but they miss the key condition.
Q61. Which option best describes avoid wide transformations when possible?
Select an answer to check.
Answer: Reduce shuffles.
Here, Reduce shuffles. is the right choice. Plan logic to minimize shuffles. That is exactly the concept behind which option best describes avoid wide transformations when in this context. Competing choices sound plausible, but they miss the key condition.
Q62. What is the primary purpose of avoid wide transformations when possible?
Select an answer to check.
Answer: Reduce shuffles.
In this case, Reduce shuffles. is correct. Plan logic to minimize shuffles. That is exactly the concept behind what is the primary purpose of avoid wide in this context. Competing choices sound plausible, but they miss the key condition.
Q63. Which statement about avoid wide transformations when possible is most accurate?
Select an answer to check.
Answer: Reduce shuffles.
The best option here is Reduce shuffles.. Plan logic to minimize shuffles. That is exactly the concept behind which statement about avoid wide transformations when possible in this context. Competing choices sound plausible, but they miss the key condition.
Q64. How is avoid wide transformations when possible best characterized?
Select an answer to check.
Answer: Reduce shuffles.
For this question, Reduce shuffles. is correct. Plan logic to minimize shuffles. That is exactly the concept behind how is avoid wide transformations when possible best in this context. Competing choices sound plausible, but they miss the key condition.
Q65. Which option best describes file format choice?
Select an answer to check.
Answer: Parquet > CSV/JSON for analytics.
Parquet > CSV/JSON for analytics. is the correct answer here. Columnar formats are best. That is exactly the concept behind which option best describes file format choice in this context. Competing choices sound plausible, but they miss the key condition.
Q66. What is the primary purpose of file format choice?
Select an answer to check.
Answer: Parquet > CSV/JSON for analytics.
Here, Parquet > CSV/JSON for analytics. is the right choice. Columnar formats are best. It fits the requirement in the prompt about what is the primary purpose of file format. Competing choices sound plausible, but they miss the key condition.
Q67. Which statement about file format choice is most accurate?
Select an answer to check.
Answer: Parquet > CSV/JSON for analytics.
In this case, Parquet > CSV/JSON for analytics. is correct. Columnar formats are best. It fits the requirement in the prompt about which statement about file format choice is most. Competing choices sound plausible, but they miss the key condition.
Q68. How is file format choice best characterized?
Select an answer to check.
Answer: Parquet > CSV/JSON for analytics.
The best option here is Parquet > CSV/JSON for analytics.. Columnar formats are best. It fits the requirement in the prompt about how is file format choice best characterized. Competing choices sound plausible, but they miss the key condition.
Q69. Which option best describes compression codec?
Select an answer to check.
Answer: Snappy/zstd balance speed and size.
For this question, Snappy/zstd balance speed and size. is correct. Default Snappy is fine. It fits the requirement in the prompt about which option best describes compression codec. Competing choices sound plausible, but they miss the key condition.
Q70. What is the primary purpose of compression codec?
Select an answer to check.
Answer: Snappy/zstd balance speed and size.
Snappy/zstd balance speed and size. is the correct answer here. Default Snappy is fine. It fits the requirement in the prompt about what is the primary purpose of compression codec. Competing choices sound plausible, but they miss the key condition.
Q71. Which statement about compression codec is most accurate?
Select an answer to check.
Answer: Snappy/zstd balance speed and size.
Here, Snappy/zstd balance speed and size. is the right choice. Default Snappy is fine. This is the most accurate statement for which statement about compression codec is most accurate. Competing choices sound plausible, but they miss the key condition.
Q72. How is compression codec best characterized?
Select an answer to check.
Answer: Snappy/zstd balance speed and size.
In this case, Snappy/zstd balance speed and size. is correct. Default Snappy is fine. This is the most accurate statement for how is compression codec best characterized. Competing choices sound plausible, but they miss the key condition.
Q73. Which option best describes vectorized readers?
Select an answer to check.
Answer: Default for Parquet; faster than row-based.
The best option here is Default for Parquet; faster than row-based.. Improves I/O. This is the most accurate statement for which option best describes vectorized readers. Competing choices sound plausible, but they miss the key condition.
Q74. What is the primary purpose of vectorized readers?
Select an answer to check.
Answer: Default for Parquet; faster than row-based.
For this question, Default for Parquet; faster than row-based. is correct. Improves I/O. This is the most accurate statement for what is the primary purpose of vectorized readers. Competing choices sound plausible, but they miss the key condition.
Q75. Which statement about vectorized readers is most accurate?
Select an answer to check.
Answer: Default for Parquet; faster than row-based.
Default for Parquet; faster than row-based. is the correct answer here. Improves I/O. This is the most accurate statement for which statement about vectorized readers is most accurate. Competing choices sound plausible, but they miss the key condition.
Q76. How is vectorized readers best characterized?
Select an answer to check.
Answer: Default for Parquet; faster than row-based.
Here, Default for Parquet; faster than row-based. is the right choice. Improves I/O. It aligns directly with what the question asks about how is vectorized readers best characterized. The remaining choices fail because they don’t satisfy the full definition.
In this case, executor.memory, memoryOverhead, fractions. is correct. Tune for workload. It aligns directly with what the question asks about which option best describes memory tuning. The remaining choices fail because they don’t satisfy the full definition.
Q78. What is the primary purpose of memory tuning?
The best option here is executor.memory, memoryOverhead, fractions.. Tune for workload. It aligns directly with what the question asks about what is the primary purpose of memory tuning. The remaining choices fail because they don’t satisfy the full definition.
Q79. Which statement about memory tuning is most accurate?
For this question, executor.memory, memoryOverhead, fractions. is correct. Tune for workload. It aligns directly with what the question asks about which statement about memory tuning is most accurate. The remaining choices fail because they don’t satisfy the full definition.
executor.memory, memoryOverhead, fractions. is the correct answer here. Tune for workload. It aligns directly with what the question asks about how is memory tuning best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q81. Which option best describes shuffle partitions?
Here, spark.sql.shuffle.partitions controls post-shuffle parallelism. is the right choice. Tune (often AQE handles). This matches the core idea being tested around which option best describes shuffle partitions. The remaining choices fail because they don’t satisfy the full definition.
Q82. What is the primary purpose of shuffle partitions?
In this case, spark.sql.shuffle.partitions controls post-shuffle parallelism. is correct. Tune (often AQE handles). This matches the core idea being tested around what is the primary purpose of shuffle partitions. The remaining choices fail because they don’t satisfy the full definition.
Q83. Which statement about shuffle partitions is most accurate?
The best option here is spark.sql.shuffle.partitions controls post-shuffle parallelism.. Tune (often AQE handles). This matches the core idea being tested around which statement about shuffle partitions is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q84. How is shuffle partitions best characterized?
For this question, spark.sql.shuffle.partitions controls post-shuffle parallelism. is correct. Tune (often AQE handles). This matches the core idea being tested around how is shuffle partitions best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q85. Which option best describes file compaction (lakehouse)?
Select an answer to check.
Answer: Merge small files via OPTIMIZE.
Merge small files via OPTIMIZE. is the correct answer here. Improves scan efficiency. This matches the core idea being tested around which option best describes file compaction (lakehouse). The remaining choices fail because they don’t satisfy the full definition.
Q86. What is the primary purpose of file compaction (lakehouse)?
Select an answer to check.
Answer: Merge small files via OPTIMIZE.
Here, Merge small files via OPTIMIZE. is the right choice. Improves scan efficiency. That is exactly the concept behind what is the primary purpose of file compaction in this context. The remaining choices fail because they don’t satisfy the full definition.
Q87. Which statement about file compaction (lakehouse) is most accurate?
Select an answer to check.
Answer: Merge small files via OPTIMIZE.
In this case, Merge small files via OPTIMIZE. is correct. Improves scan efficiency. That is exactly the concept behind which statement about file compaction (lakehouse) is most in this context. The remaining choices fail because they don’t satisfy the full definition.
Q88. How is file compaction (lakehouse) best characterized?
Select an answer to check.
Answer: Merge small files via OPTIMIZE.
The best option here is Merge small files via OPTIMIZE.. Improves scan efficiency. That is exactly the concept behind how is file compaction (lakehouse) best characterized in this context. The remaining choices fail because they don’t satisfy the full definition.
Q89. Which option best describes z-order / clustering?
Select an answer to check.
Answer: Co-locate related data in files.
For this question, Co-locate related data in files. is correct. Selective scans benefit. That is exactly the concept behind which option best describes z-order / clustering in this context. The remaining choices fail because they don’t satisfy the full definition.
Q90. What is the primary purpose of z-order / clustering?
Select an answer to check.
Answer: Co-locate related data in files.
Co-locate related data in files. is the correct answer here. Selective scans benefit. That is exactly the concept behind what is the primary purpose of z-order / in this context. The remaining choices fail because they don’t satisfy the full definition.
Q91. Which statement about z-order / clustering is most accurate?
Select an answer to check.
Answer: Co-locate related data in files.
Here, Co-locate related data in files. is the right choice. Selective scans benefit. It fits the requirement in the prompt about which statement about z-order / clustering is most. The remaining choices fail because they don’t satisfy the full definition.
Q92. How is z-order / clustering best characterized?
Select an answer to check.
Answer: Co-locate related data in files.
In this case, Co-locate related data in files. is correct. Selective scans benefit. It fits the requirement in the prompt about how is z-order / clustering best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q93. Which option best describes speculative execution?
Select an answer to check.
Answer: Run slow tasks on alternates.
The best option here is Run slow tasks on alternates.. Mitigates stragglers. It fits the requirement in the prompt about which option best describes speculative execution. The remaining choices fail because they don’t satisfy the full definition.
Q94. What is the primary purpose of speculative execution?
Select an answer to check.
Answer: Run slow tasks on alternates.
For this question, Run slow tasks on alternates. is correct. Mitigates stragglers. It fits the requirement in the prompt about what is the primary purpose of speculative execution. The remaining choices fail because they don’t satisfy the full definition.
Q95. Which statement about speculative execution is most accurate?
Select an answer to check.
Answer: Run slow tasks on alternates.
Run slow tasks on alternates. is the correct answer here. Mitigates stragglers. It fits the requirement in the prompt about which statement about speculative execution is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q96. How is speculative execution best characterized?
Select an answer to check.
Answer: Run slow tasks on alternates.
Here, Run slow tasks on alternates. is the right choice. Mitigates stragglers. This is the most accurate statement for how is speculative execution best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q97. Which option best describes metrics-driven tuning?
Select an answer to check.
Answer: Use Spark UI/metrics to find bottlenecks.
In this case, Use Spark UI/metrics to find bottlenecks. is correct. Stage time, shuffle, GC, spill. This is the most accurate statement for which option best describes metrics-driven tuning. The remaining choices fail because they don’t satisfy the full definition.
Q98. What is the primary purpose of metrics-driven tuning?
Select an answer to check.
Answer: Use Spark UI/metrics to find bottlenecks.
The best option here is Use Spark UI/metrics to find bottlenecks.. Stage time, shuffle, GC, spill. This is the most accurate statement for what is the primary purpose of metrics-driven tuning. The remaining choices fail because they don’t satisfy the full definition.
Q99. Which statement about metrics-driven tuning is most accurate?
Select an answer to check.
Answer: Use Spark UI/metrics to find bottlenecks.
For this question, Use Spark UI/metrics to find bottlenecks. is correct. Stage time, shuffle, GC, spill. This is the most accurate statement for which statement about metrics-driven tuning is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q100. How is metrics-driven tuning best characterized?
Select an answer to check.
Answer: Use Spark UI/metrics to find bottlenecks.
Use Spark UI/metrics to find bottlenecks. is the correct answer here. Stage time, shuffle, GC, spill. This is the most accurate statement for how is metrics-driven tuning best characterized. The remaining choices fail because they don’t satisfy the full definition.