Spark SQL MCQ Questions with Answers (Latest 2026)

Q1. Which option best describes Spark SQL?

A. A pure DB engine. B. A pure scheduler. C. A pure file format. D. Module for SQL/structured queries on Spark.

Select an answer to check.

Answer: Module for SQL/structured queries on Spark.

Here, Module for SQL/structured queries on Spark. is the right choice. Backed by Catalyst. It aligns directly with what the question asks about which option best describes spark sql. A quick elimination of partially true options helps confirm it.

Q2. What is the primary purpose of Spark SQL?

A. A pure file format. B. A pure DB engine. C. A pure scheduler. D. Module for SQL/structured queries on Spark.

Select an answer to check.

Answer: Module for SQL/structured queries on Spark.

In this case, Module for SQL/structured queries on Spark. is correct. Backed by Catalyst. It aligns directly with what the question asks about what is the primary purpose of spark sql. A quick elimination of partially true options helps confirm it.

Q3. Which statement about Spark SQL is most accurate?

A. A pure scheduler. B. A pure file format. C. A pure DB engine. D. Module for SQL/structured queries on Spark.

Select an answer to check.

Answer: Module for SQL/structured queries on Spark.

The best option here is Module for SQL/structured queries on Spark.. Backed by Catalyst. It aligns directly with what the question asks about which statement about spark sql is most accurate. A quick elimination of partially true options helps confirm it.

Q4. How is Spark SQL best characterized?

A. Module for SQL/structured queries on Spark. B. A pure file format. C. A pure DB engine. D. A pure scheduler.

Select an answer to check.

Answer: Module for SQL/structured queries on Spark.

For this question, Module for SQL/structured queries on Spark. is correct. Backed by Catalyst. It aligns directly with what the question asks about how is spark sql best characterized. A quick elimination of partially true options helps confirm it.

Q5. Which option best describes a temporary view?

A. A pure SQL alias. B. A persistent table. C. A pure RDD. D. Session-scoped view over a DataFrame.

Select an answer to check.

Answer: Session-scoped view over a DataFrame.

Session-scoped view over a DataFrame. is the correct answer here. CreateOrReplaceTempView(). It aligns directly with what the question asks about which option best describes a temporary view. A quick elimination of partially true options helps confirm it.

Q6. What is the primary purpose of a temporary view?

A. Session-scoped view over a DataFrame. B. A pure SQL alias. C. A persistent table. D. A pure RDD.

Select an answer to check.

Answer: Session-scoped view over a DataFrame.

Here, Session-scoped view over a DataFrame. is the right choice. CreateOrReplaceTempView(). This matches the core idea being tested around what is the primary purpose of a temporary. A quick elimination of partially true options helps confirm it.

Q7. Which statement about a temporary view is most accurate?

A. Session-scoped view over a DataFrame. B. A persistent table. C. A pure SQL alias. D. A pure RDD.

Select an answer to check.

Answer: Session-scoped view over a DataFrame.

In this case, Session-scoped view over a DataFrame. is correct. CreateOrReplaceTempView(). This matches the core idea being tested around which statement about a temporary view is most. A quick elimination of partially true options helps confirm it.

Q8. How is a temporary view best characterized?

A. A pure RDD. B. Session-scoped view over a DataFrame. C. A pure SQL alias. D. A persistent table.

Select an answer to check.

Answer: Session-scoped view over a DataFrame.

The best option here is Session-scoped view over a DataFrame.. CreateOrReplaceTempView(). This matches the core idea being tested around how is a temporary view best characterized. A quick elimination of partially true options helps confirm it.

Q9. Which option best describes a global temp view?

A. A pure log. B. A persistent table. C. View visible across sessions in same app. D. Per-session only.

Select an answer to check.

Answer: View visible across sessions in same app.

For this question, View visible across sessions in same app. is correct. Global_temp database. This matches the core idea being tested around which option best describes a global temp view. A quick elimination of partially true options helps confirm it.

Q10. What is the primary purpose of a global temp view?

A. Per-session only. B. View visible across sessions in same app. C. A persistent table. D. A pure log.

Select an answer to check.

Answer: View visible across sessions in same app.

View visible across sessions in same app. is the correct answer here. Global_temp database. This matches the core idea being tested around what is the primary purpose of a global. A quick elimination of partially true options helps confirm it.

Q11. Which statement about a global temp view is most accurate?

A. Per-session only. B. A persistent table. C. View visible across sessions in same app. D. A pure log.

Select an answer to check.

Answer: View visible across sessions in same app.

Here, View visible across sessions in same app. is the right choice. Global_temp database. That is exactly the concept behind which statement about a global temp view is in this context. A quick elimination of partially true options helps confirm it.

Q12. How is a global temp view best characterized?

A. A persistent table. B. Per-session only. C. A pure log. D. View visible across sessions in same app.

Select an answer to check.

Answer: View visible across sessions in same app.

In this case, View visible across sessions in same app. is correct. Global_temp database. That is exactly the concept behind how is a global temp view best characterized in this context. A quick elimination of partially true options helps confirm it.

Q13. Which option best describes a managed table?

A. Pure view. B. Spark/metastore manages metadata + data lifecycle. C. External table. D. Pure RDD.

Select an answer to check.

Answer: Spark/metastore manages metadata + data lifecycle.

The best option here is Spark/metastore manages metadata + data lifecycle.. DROP removes data. That is exactly the concept behind which option best describes a managed table in this context. A quick elimination of partially true options helps confirm it.

Q14. What is the primary purpose of a managed table?

A. External table. B. Pure RDD. C. Spark/metastore manages metadata + data lifecycle. D. Pure view.

Select an answer to check.

Answer: Spark/metastore manages metadata + data lifecycle.

For this question, Spark/metastore manages metadata + data lifecycle. is correct. DROP removes data. That is exactly the concept behind what is the primary purpose of a managed in this context. A quick elimination of partially true options helps confirm it.

Q15. Which statement about a managed table is most accurate?

A. Pure view. B. Spark/metastore manages metadata + data lifecycle. C. Pure RDD. D. External table.

Select an answer to check.

Answer: Spark/metastore manages metadata + data lifecycle.

Spark/metastore manages metadata + data lifecycle. is the correct answer here. DROP removes data. That is exactly the concept behind which statement about a managed table is most in this context. A quick elimination of partially true options helps confirm it.

Q16. How is a managed table best characterized?

A. Pure RDD. B. Spark/metastore manages metadata + data lifecycle. C. Pure view. D. External table.

Select an answer to check.

Answer: Spark/metastore manages metadata + data lifecycle.

Here, Spark/metastore manages metadata + data lifecycle. is the right choice. DROP removes data. It fits the requirement in the prompt about how is a managed table best characterized. A quick elimination of partially true options helps confirm it.

Q17. Which option best describes an external table?

A. Pure RDD. B. Spark manages metadata; data lives at given path. C. Pure view. D. Managed table.

Select an answer to check.

Answer: Spark manages metadata; data lives at given path.

In this case, Spark manages metadata; data lives at given path. is correct. DROP keeps data. It fits the requirement in the prompt about which option best describes an external table. A quick elimination of partially true options helps confirm it.

Q18. What is the primary purpose of an external table?

A. Pure RDD. B. Pure view. C. Managed table. D. Spark manages metadata; data lives at given path.

Select an answer to check.

Answer: Spark manages metadata; data lives at given path.

The best option here is Spark manages metadata; data lives at given path.. DROP keeps data. It fits the requirement in the prompt about what is the primary purpose of an external. A quick elimination of partially true options helps confirm it.

Q19. Which statement about an external table is most accurate?

A. Pure view. B. Managed table. C. Pure RDD. D. Spark manages metadata; data lives at given path.

Select an answer to check.

Answer: Spark manages metadata; data lives at given path.

For this question, Spark manages metadata; data lives at given path. is correct. DROP keeps data. It fits the requirement in the prompt about which statement about an external table is most. A quick elimination of partially true options helps confirm it.

Q20. How is an external table best characterized?

A. Pure RDD. B. Managed table. C. Spark manages metadata; data lives at given path. D. Pure view.

Select an answer to check.

Answer: Spark manages metadata; data lives at given path.

Spark manages metadata; data lives at given path. is the correct answer here. DROP keeps data. It fits the requirement in the prompt about how is an external table best characterized. A quick elimination of partially true options helps confirm it.

Q21. Which option best describes the metastore?

A. Pure file system. B. Stores table metadata (schemas, partitions). C. Pure cache. D. Pure scheduler.

Select an answer to check.

Answer: Stores table metadata (schemas, partitions).

Here, Stores table metadata (schemas, partitions). is the right choice. Hive metastore or Unity Catalog. This is the most accurate statement for which option best describes the metastore. A quick elimination of partially true options helps confirm it.

Q22. What is the primary purpose of the metastore?

A. Pure file system. B. Pure scheduler. C. Pure cache. D. Stores table metadata (schemas, partitions).

Select an answer to check.

Answer: Stores table metadata (schemas, partitions).

In this case, Stores table metadata (schemas, partitions). is correct. Hive metastore or Unity Catalog. This is the most accurate statement for what is the primary purpose of the metastore. A quick elimination of partially true options helps confirm it.

Q23. Which statement about the metastore is most accurate?

A. Pure scheduler. B. Stores table metadata (schemas, partitions). C. Pure file system. D. Pure cache.

Select an answer to check.

Answer: Stores table metadata (schemas, partitions).

The best option here is Stores table metadata (schemas, partitions).. Hive metastore or Unity Catalog. This is the most accurate statement for which statement about the metastore is most accurate. A quick elimination of partially true options helps confirm it.

Q24. How is the metastore best characterized?

A. Pure file system. B. Pure scheduler. C. Pure cache. D. Stores table metadata (schemas, partitions).

Select an answer to check.

Answer: Stores table metadata (schemas, partitions).

For this question, Stores table metadata (schemas, partitions). is correct. Hive metastore or Unity Catalog. This is the most accurate statement for how is the metastore best characterized. A quick elimination of partially true options helps confirm it.

Q25. Which option best describes Catalyst?

A. A pure cache. B. A pure shuffler. C. A pure scheduler. D. Optimizer for SQL/DF queries.

Select an answer to check.

Answer: Optimizer for SQL/DF queries.

Optimizer for SQL/DF queries. is the correct answer here. Logical/physical plan rewrites. This is the most accurate statement for which option best describes catalyst. A quick elimination of partially true options helps confirm it.

Q26. What is the primary purpose of Catalyst?

A. A pure shuffler. B. Optimizer for SQL/DF queries. C. A pure scheduler. D. A pure cache.

Select an answer to check.

Answer: Optimizer for SQL/DF queries.

Here, Optimizer for SQL/DF queries. is the right choice. Logical/physical plan rewrites. It aligns directly with what the question asks about what is the primary purpose of catalyst. The other options are either incomplete or contextually incorrect.

Q27. Which statement about Catalyst is most accurate?

A. A pure cache. B. A pure scheduler. C. A pure shuffler. D. Optimizer for SQL/DF queries.

Select an answer to check.

Answer: Optimizer for SQL/DF queries.

In this case, Optimizer for SQL/DF queries. is correct. Logical/physical plan rewrites. It aligns directly with what the question asks about which statement about catalyst is most accurate. The other options are either incomplete or contextually incorrect.

Q28. How is Catalyst best characterized?

A. A pure shuffler. B. Optimizer for SQL/DF queries. C. A pure cache. D. A pure scheduler.

Select an answer to check.

Answer: Optimizer for SQL/DF queries.

The best option here is Optimizer for SQL/DF queries.. Logical/physical plan rewrites. It aligns directly with what the question asks about how is catalyst best characterized. The other options are either incomplete or contextually incorrect.

Q29. Which option best describes predicate pushdown?

A. Pure post-scan filter. B. Pure shuffle. C. Pure broadcast. D. Filters pushed to source/scan level.

Select an answer to check.

Answer: Filters pushed to source/scan level.

For this question, Filters pushed to source/scan level. is correct. Reduces I/O. It aligns directly with what the question asks about which option best describes predicate pushdown. The other options are either incomplete or contextually incorrect.

Q30. What is the primary purpose of predicate pushdown?

A. Filters pushed to source/scan level. B. Pure post-scan filter. C. Pure broadcast. D. Pure shuffle.

Select an answer to check.

Answer: Filters pushed to source/scan level.

Filters pushed to source/scan level. is the correct answer here. Reduces I/O. It aligns directly with what the question asks about what is the primary purpose of predicate pushdown. The other options are either incomplete or contextually incorrect.

Q31. Which statement about predicate pushdown is most accurate?

A. Pure broadcast. B. Pure shuffle. C. Filters pushed to source/scan level. D. Pure post-scan filter.

Select an answer to check.

Answer: Filters pushed to source/scan level.

Here, Filters pushed to source/scan level. is the right choice. Reduces I/O. This matches the core idea being tested around which statement about predicate pushdown is most accurate. The other options are either incomplete or contextually incorrect.

Q32. How is predicate pushdown best characterized?

A. Pure shuffle. B. Filters pushed to source/scan level. C. Pure post-scan filter. D. Pure broadcast.

Select an answer to check.

Answer: Filters pushed to source/scan level.

In this case, Filters pushed to source/scan level. is correct. Reduces I/O. This matches the core idea being tested around how is predicate pushdown best characterized. The other options are either incomplete or contextually incorrect.

Q33. Which option best describes partition pruning?

A. Skip partitions not matching filter. B. Pure index seek. C. Always full scan. D. Pure broadcast.

Select an answer to check.

Answer: Skip partitions not matching filter.

The best option here is Skip partitions not matching filter.. Large I/O savings. This matches the core idea being tested around which option best describes partition pruning. The other options are either incomplete or contextually incorrect.

Q34. What is the primary purpose of partition pruning?

A. Skip partitions not matching filter. B. Pure broadcast. C. Pure index seek. D. Always full scan.

Select an answer to check.

Answer: Skip partitions not matching filter.

For this question, Skip partitions not matching filter. is correct. Large I/O savings. This matches the core idea being tested around what is the primary purpose of partition pruning. The other options are either incomplete or contextually incorrect.

Q35. Which statement about partition pruning is most accurate?

A. Pure index seek. B. Always full scan. C. Pure broadcast. D. Skip partitions not matching filter.

Select an answer to check.

Answer: Skip partitions not matching filter.

Skip partitions not matching filter. is the correct answer here. Large I/O savings. This matches the core idea being tested around which statement about partition pruning is most accurate. The other options are either incomplete or contextually incorrect.

Q36. How is partition pruning best characterized?

A. Always full scan. B. Pure broadcast. C. Skip partitions not matching filter. D. Pure index seek.

Select an answer to check.

Answer: Skip partitions not matching filter.

Here, Skip partitions not matching filter. is the right choice. Large I/O savings. That is exactly the concept behind how is partition pruning best characterized in this context. The other options are either incomplete or contextually incorrect.

Q37. Which option best describes CTAS?

A. Pure SELECT only. B. Pure CREATE only. C. Pure INSERT. D. CREATE TABLE AS SELECT.

Select an answer to check.

Answer: CREATE TABLE AS SELECT.

In this case, CREATE TABLE AS SELECT. is correct. Materialize query results as table. That is exactly the concept behind which option best describes ctas in this context. The other options are either incomplete or contextually incorrect.

Q38. What is the primary purpose of CTAS?

A. CREATE TABLE AS SELECT. B. Pure INSERT. C. Pure CREATE only. D. Pure SELECT only.

Select an answer to check.

Answer: CREATE TABLE AS SELECT.

The best option here is CREATE TABLE AS SELECT.. Materialize query results as table. That is exactly the concept behind what is the primary purpose of ctas in this context. The other options are either incomplete or contextually incorrect.

Q39. Which statement about CTAS is most accurate?

A. Pure INSERT. B. Pure SELECT only. C. CREATE TABLE AS SELECT. D. Pure CREATE only.

Select an answer to check.

Answer: CREATE TABLE AS SELECT.

For this question, CREATE TABLE AS SELECT. is correct. Materialize query results as table. That is exactly the concept behind which statement about ctas is most accurate in this context. The other options are either incomplete or contextually incorrect.

Q40. How is CTAS best characterized?

A. Pure CREATE only. B. Pure SELECT only. C. Pure INSERT. D. CREATE TABLE AS SELECT.

Select an answer to check.

Answer: CREATE TABLE AS SELECT.

CREATE TABLE AS SELECT. is the correct answer here. Materialize query results as table. That is exactly the concept behind how is ctas best characterized in this context. The other options are either incomplete or contextually incorrect.

Q41. Which option best describes CTE / WITH clauses?

A. Inline named subqueries. B. Pure subqueries only. C. Pure UDFs only. D. Pure views only.

Select an answer to check.

Answer: Inline named subqueries.

Here, Inline named subqueries. is the right choice. Improves readability. It fits the requirement in the prompt about which option best describes cte / with clauses. The other options are either incomplete or contextually incorrect.

Q42. What is the primary purpose of CTE / WITH clauses?

A. Pure subqueries only. B. Inline named subqueries. C. Pure UDFs only. D. Pure views only.

Select an answer to check.

Answer: Inline named subqueries.

In this case, Inline named subqueries. is correct. Improves readability. It fits the requirement in the prompt about what is the primary purpose of cte /. The other options are either incomplete or contextually incorrect.

Q43. Which statement about CTE / WITH clauses is most accurate?

A. Pure subqueries only. B. Pure UDFs only. C. Inline named subqueries. D. Pure views only.

Select an answer to check.

Answer: Inline named subqueries.

The best option here is Inline named subqueries.. Improves readability. It fits the requirement in the prompt about which statement about cte / with clauses is. The other options are either incomplete or contextually incorrect.

Q44. How is CTE / WITH clauses best characterized?

A. Pure subqueries only. B. Inline named subqueries. C. Pure UDFs only. D. Pure views only.

Select an answer to check.

Answer: Inline named subqueries.

For this question, Inline named subqueries. is correct. Improves readability. It fits the requirement in the prompt about how is cte / with clauses best characterized. The other options are either incomplete or contextually incorrect.

Q45. Which option best describes window functions?

A. Pure filters. B. Pure joins. C. Pure aggregates only. D. ROW_NUMBER, LAG, etc., over partitions.

Select an answer to check.

Answer: ROW_NUMBER, LAG, etc., over partitions.

ROW_NUMBER, LAG, etc., over partitions. is the correct answer here. Per-partition computations. It fits the requirement in the prompt about which option best describes window functions. The other options are either incomplete or contextually incorrect.

Q46. What is the primary purpose of window functions?

A. Pure joins. B. Pure aggregates only. C. ROW_NUMBER, LAG, etc., over partitions. D. Pure filters.

Select an answer to check.

Answer: ROW_NUMBER, LAG, etc., over partitions.

Here, ROW_NUMBER, LAG, etc., over partitions. is the right choice. Per-partition computations. This is the most accurate statement for what is the primary purpose of window functions. The other options are either incomplete or contextually incorrect.

Q47. Which statement about window functions is most accurate?

A. Pure aggregates only. B. Pure joins. C. ROW_NUMBER, LAG, etc., over partitions. D. Pure filters.

Select an answer to check.

Answer: ROW_NUMBER, LAG, etc., over partitions.

In this case, ROW_NUMBER, LAG, etc., over partitions. is correct. Per-partition computations. This is the most accurate statement for which statement about window functions is most accurate. The other options are either incomplete or contextually incorrect.

Q48. How is window functions best characterized?

A. Pure joins. B. ROW_NUMBER, LAG, etc., over partitions. C. Pure filters. D. Pure aggregates only.

Select an answer to check.

Answer: ROW_NUMBER, LAG, etc., over partitions.

The best option here is ROW_NUMBER, LAG, etc., over partitions.. Per-partition computations. This is the most accurate statement for how is window functions best characterized. The other options are either incomplete or contextually incorrect.

Q49. Which option best describes explain plans?

A. EXPLAIN to see physical/logical plans. B. Pure ANALYZE. C. Pure DESCRIBE only. D. Pure SHOW.

Select an answer to check.

Answer: EXPLAIN to see physical/logical plans.

For this question, EXPLAIN to see physical/logical plans. is correct. Debug performance. This is the most accurate statement for which option best describes explain plans. The other options are either incomplete or contextually incorrect.

Q50. What is the primary purpose of explain plans?

A. EXPLAIN to see physical/logical plans. B. Pure DESCRIBE only. C. Pure SHOW. D. Pure ANALYZE.

Select an answer to check.

Answer: EXPLAIN to see physical/logical plans.

EXPLAIN to see physical/logical plans. is the correct answer here. Debug performance. This is the most accurate statement for what is the primary purpose of explain plans. The other options are either incomplete or contextually incorrect.