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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q41-Q46):

NEW QUESTION # 41
Which system functions does Snowflake provide to monitor clustering information within a table (Choose two.)

A. SYSTEM$CLUSTERING_USAGE
B. SYSTEM$CLUSTERING_KEYS
C. SYSTEM$CLUSTERING_PERCENT
D. SYSTEM$CLUSTERING_DEPTH
E. SYSTEM$CLUSTERING_INFORMATION

Answer: D,E

Explanation:
Explanation
According to the Snowflake documentation, these two system functions are provided by Snowflake to monitor clustering information within a table. A system function is a type of function that allows executing actions or returning information about the system. A clustering key is a feature that allows organizing data across micro-partitions based on one or more columns in the table. Clustering can improve query performance by reducing the number of files to scan.
* SYSTEM$CLUSTERING_INFORMATION is a system function that returns clustering information, including average clustering depth, for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns a JSON string with the clustering information. The clustering information includes the cluster by keys, the total partition count, the total constant partition count, the average overlaps, and the average depth1.
* SYSTEM$CLUSTERING_DEPTH is a system function that returns the clustering depth for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns an integer value with the clustering depth. The clustering depth is the maximum number of overlapping micro-partitions for any micro-partition in the table. A lower clustering depth indicates a better clustering2.
References:
* SYSTEM$CLUSTERING_INFORMATION | Snowflake Documentation
* SYSTEM$CLUSTERING_DEPTH | Snowflake Documentation

NEW QUESTION # 42
Which system functions does Snowflake provide to monitor clustering information within a table (Choose two.)

A. SYSTEM$CLUSTERING_USAGE
B. SYSTEM$CLUSTERING_KEYS
C. SYSTEM$CLUSTERING_PERCENT
D. SYSTEM$CLUSTERING_DEPTH
E. SYSTEM$CLUSTERING_INFORMATION

Answer: D,E

NEW QUESTION # 43
An Architect clones a database and all of its objects, including tasks. After the cloning, the tasks stop running.
Why is this occurring?

A. The Architect has insufficient privileges to alter tasks on the cloned database.
B. The objects that the tasks reference are not fully qualified.
C. Cloned tasks are suspended by default and must be manually resumed.
D. Tasks cannot be cloned.

Answer: C

Explanation:
When a database is cloned, all of its objects, including tasks, are also cloned. However, cloned tasks are suspended by default and must be manually resumed by using the ALTER TASK command. This is to prevent the cloned tasks from running unexpectedly or interfering with the original tasks. Therefore, the reason why the tasks stop running after the cloning is because they are suspended by default (Option C). Options A, B, and D are not correct because tasks can be cloned, the objects that the tasks reference are also cloned and do not need to be fully qualified, and the Architect does not need to alter the tasks on the cloned database, only resume them. References: The answer can be verified from Snowflake's official documentation on cloning and tasks available on their website. Here are some relevant links:
* Cloning Objects | Snowflake Documentation
* Tasks | Snowflake Documentation
* ALTER TASK | Snowflake Documentation

NEW QUESTION # 44
What are some of the characteristics of result set caches? (Choose three.)

A. The result set cache is not shared between warehouses.
B. Snowflake persists the data results for 24 hours.
C. Time Travel queries can be executed against the result set cache.
D. The data stored in the result cache will contribute to storage costs.
E. The retention period can be reset for a maximum of 31 days.
F. Each time persisted results for a query are used, a 24-hour retention period is reset.

Answer: B,E,F

Explanation:
Comprehensive and Detailed According to the SnowPro Advanced: Architect documents and learning resources, some of the characteristics of result set caches are:
Snowflake persists the data results for 24 hours. This means that the result set cache holds the results of every query executed in the past 24 hours, and can be reused if the same query is submitted again and the underlying data has not changed1.
Each time persisted results for a query are used, a 24-hour retention period is reset. This means that the result set cache extends the lifetime of the results every time they are reused, up to a maximum of 31 days from the date and time that the query was first executed1.
The retention period can be reset for a maximum of 31 days. This means that the result set cache will purge the results after 31 days, regardless of whether they are reused or not. After 31 days, the next time the query is submitted, a new result is generated and persisted1.
The other options are incorrect because they are not characteristics of result set caches. Option A is incorrect because Time Travel queries cannot be executed against the result set cache. Time Travel queries use the AS OF clause to access historical data that is stored in the storage layer, not the result set cache2. Option D is incorrect because the data stored in the result set cache does not contribute to storage costs. The result set cache is maintained by the service layer, and does not incur any additional charges1. Option F is incorrect because the result set cache is shared between warehouses. The result set cache is available across virtual warehouses, so query results returned to one user are available to any other user on the system who executes the same query, provided the underlying data has not changed1. Reference: Using Persisted Query Results | Snowflake Documentation, Time Travel | Snowflake Documentation

NEW QUESTION # 45
Which of the below commands will use warehouse credits?

A. SELECT MAX(FLAKE_ID) FROM SNOWFLAKE;
B. SHOW TABLES LIKE 'SNOWFL%';
C. SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID;
D. SELECT COUNT(*) FROM SNOWFLAKE;

Answer: C

NEW QUESTION # 46
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