SnowPro Advanced Workload Optimization

1. Which Snowflake edition supports multi-cluster warehouses?

Standard

Business Critical

Enterprise and above

All editions

2. Which Snowflake optimization technique involves pre-computing aggregations?

Materialized Views

Query Result Caching

Dynamic Sampling

Partition Elimination

3. How does Snowflake's data sharing feature optimize workload distribution?

By eliminating duplicate data copies across accounts

By automatically replicating data globally

By compressing shared datasets

By limiting concurrent access

4. What is the impact of setting a very small warehouse size on query performance?

Improved performance due to less overhead

Slower query execution due to limited compute resources

No impact on query speed

Automatic performance optimization

5. Which Snowflake feature allows you to monitor and control query execution in real-time?

Query Profiler

Resource Monitor

Warehouse Status Dashboard

Cost Analyzer

6. In Snowflake, what determines the size of micro-partitions?

User configuration

Approximately 16 MB of uncompressed data per partition

Warehouse size

Clustering key selection

7. What is the benefit of using Snowflake's result caching for repeated queries?

Eliminates need for clustering

Returns results instantly without recomputation

Increases warehouse capacity

Reduces table storage size

8. Which join strategy does Snowflake prefer for optimal performance?

Nested loop join

Hash join

Merge join

Index join

9. How can you identify queries consuming excessive credits in Snowflake?

Query History and Account Usage views

SHOW WAREHOUSES command only

Manual log file inspection

Warehouse monitoring alerts only

10. What is the primary purpose of Snowflake's dynamic data masking?

Encrypt data at rest

Hide sensitive data from unauthorized users

Compress sensitive columns

Archive old data

11. Which Snowflake feature automatically adjusts compute resources based on workload demand?

Warehouse Clustering

Auto-scaling

Query Result Caching

Materialized Views

12. In Snowflake, how does partition pruning differ from clustering?

Partition pruning is automatic; clustering is manual

Clustering organizes data; partition pruning filters micro-partitions

They are identical concepts

Partition pruning requires indexes

13. What does the SHOW QUERIES command display in Snowflake?

Predefined query templates

Current and recent query execution details

Stored procedure definitions

Database schema only

14. Which Snowflake resource consumes credits during idle time?

Storage

Compute warehouses

Query result caching

Data sharing

15. What is the maximum number of clustering keys recommended per table in Snowflake?

1

3

8

Unlimited

16. How does Snowflake's pruning mechanism optimize storage scans?

By removing duplicate rows

By skipping irrelevant micro-partitions based on filter conditions

By compressing all data uniformly

By limiting query concurrency

17. Which Snowflake feature caches query results to avoid redundant computations?

Result Set Cache

Metadata Cache

Local Disk Cache

Remote Data Cache

18. What does the EXPLAIN command in Snowflake help you identify?

Table statistics only

Query execution plan and performance bottlenecks

Warehouse configuration details

User permission levels

19. In Snowflake, which isolation level provides the strongest consistency guarantees?

Read Uncommitted

Read Committed

Serializable

Snapshot

20. What is the primary benefit of using clustering keys in Snowflake?

Reduces warehouse size

Improves query performance by organizing data physically

Eliminates the need for indexes

Automatically compresses data files

SnowPro Advanced Workload Optimization Quiz