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NEW QUESTION # 21
Which command can temporarily disable Multi-factor Authentication (MFA) for the Snowflake username user1 for 24 hours?
Answer: B
Explanation:
According to the Snowflake documentation1, the MINS_TO_BYPASS_MFA property specifies the number of minutes to temporarily disable MFA for a user so that they can log in without the temporary token generated by the Duo Mobile application. After the time passes, MFA is enforced and the user cannot log in without the token. Therefore, to disable MFA for 24 hours, the value of this property should be set to 1440 minutes (24 x 60). Option B is incorrect because the DISABLE_MFA property is a boolean value that permanently disables MFA for a user, not a numeric value that specifies the duration. Option C is incorrect because there is no such property as TEMPORARY_MFA_BYPASS in Snowflake. Option D is incorrect because there is no such property as HOURS_TO_BYPASS_MFA in Snowflake.
NEW QUESTION # 22
An Administrator receives data from a Snowflake partner. The partner is sharing a dataset that contains multiple secure views. The Administrator would like to configure the data so that only certain roles can see certain secure views.
How can this be accomplished?
Answer: A
Explanation:
According to the Snowflake documentation1, secure views are only exposed to authorized users who have been granted the role that owns the view. Therefore, applying RBAC directly onto the partner's shared secure views (option A) is not possible, as the administrator does not own those views. Individually granting imported privileges onto the schema in the share (option B) is also not feasible, as the privileges granted on the schema do not apply to existing secure views, only to future ones2. Cloning the data and inserting it into a company-owned share (option C) is not recommended, as it would create unnecessary duplication of data and increase storage costs. The best option is to create views over the incoming shared database and apply the desired RBAC onto these views (option D). This way, the administrator can control the access to the data based on the roles in their account, without modifying the original data or views from the partner.
NEW QUESTION # 23
A Snowflake Administrator has a multi-cluster virtual warehouse and is using the Snowflake Business Critical edition. The minimum number of clusters is set to 2 and the maximum number of clusters is set to 10. This configuration works well for the standard workload, rarely exceeding 5 running clusters. However, once a month the Administrator notes that there are a few complex long-running queries that are causing increased queue time and the warehouse reaches its maximum limit at 10 clusters.
Which solutions will address the issues happening once a month? (Select TWO).
Answer: C,E
Explanation:
Explanation
According to the Snowflake documentation1, a multi-cluster warehouse is a virtual warehouse that consists of multiple clusters of compute resources that can scale up or down automatically to handle the concurrency and performance needs of the queries submitted to the warehouse. A multi-cluster warehouse has a minimum and maximum number of clusters that can be specified by the administrator. Option A is a possible solution to address the issues happening once a month, as it allows the administrator to use a task to increase the cluster size for the time period that the more complex queries are running and another task to reduce the size of the cluster once the complex queries complete. This way, the warehouse can have more resources available to handle the complex queries without reaching the maximum limit of 10 clusters, and then return to the normal cluster size to save costs. Option B is another possible solution to address the issues happening once a month, as it allows the administrator to have the group running the complex monthly queries use a separate appropriately-sized warehouse to support their workload. This way, the warehouse can isolate the complex queries from the standard workload and avoid queue time and resource contention. Option C is not a recommended solution to address the issues happening once a month, as it would increase the costs and complexity of managing the multi-cluster warehouse, and may not solve the underlying problem of inefficient queries. Option D is a good practice to improve the performance of the queries, but it is not a direct solution to address the issues happening once a month, as it requires analyzing and optimizing the complex queries using clustering keys or materialized views, which may not be feasible or effective in all cases. Option E is not a recommended solution to address the issues happening once a month, as it would increase the costs and waste resources by starting more clusters than needed for the standard workload.
NEW QUESTION # 24
A Snowflake Administrator needs to retrieve the list of the schemas deleted within the last two days from the DB1 database.
Which of the following will achieve this?
Answer: B
Explanation:
To retrieve a list of schemas deleted within the last 2 days from the DB1 database, you need a metadata view that includes historical data, including dropped (deleted) objects.
Let's review the options:
✅ B. SNOWFLAKE.ACCOUNT_USAGE.SCHEMATA
This is the correct choice because:
It includes metadata for all schemas, even deleted ones, within the retention period.
It contains a DELETED column and a DELETED_ON timestamp column.
You can filter rows with:
sql
CopyEdit
SELECT *
FROM SNOWFLAKE.ACCOUNT_USAGE.SCHEMATA
WHERE DELETED IS TRUE
AND DELETED_ON >= DATEADD(DAY, -2, CURRENT_TIMESTAMP())
AND CATALOG_NAME = 'DB1';
❌ A. SHOW SCHEMAS IN DATABASE DB1;
Only shows current (active) schemas - does not include deleted schemas.
❌ C. DB1.INFORMATION_SCHEMA.SCHEMATA
Like option A, this view only includes active schemas in the current database.
No info on deleted schemas is retained.
❌ D. SNOWFLAKE.ACCOUNT_USAGE.DATABASES
This metadata view tracks databases, not individual schemas.
SnowPro Administrator Reference:
SNOWFLAKE.ACCOUNT_USAGE.SCHEMATA documentation
Metadata includes both active and deleted schemas (within retention window).
NEW QUESTION # 25
A Snowflake user runs a complex SQL query on a dedicated virtual warehouse that reads a large amount of data from micro-partitions. The same user wants to run another query that uses the same data set.
Which action would provide optimal performance for the second SQL query?
Answer: D
Explanation:
Explanation
According to the Using Persisted Query Results documentation, the RESULT_SCAN function allows you to query the result set of a previous command as if it were a table. This can improve the performance of the second query by avoiding reading the same data from micro-partitions again. The other actions do not provide optimal performance for the second query because:
*Assigning additional clusters to the virtual warehouse does not affect the data access speed, but only the query execution speed. It also increases the cost of the warehouse.
*Increasing the STATEMENT_TIMEOUT_IN_SECONDS parameter in the session does not improve the performance of the query, but only allows it to run longer before timing out. It also increases the risk of resource contention and deadlock.
*Preventing the virtual warehouse from suspending between the running of the first and second queries does not guarantee that the data will be cached in memory, as Snowflake uses a least recently used (LRU) cache eviction policy. It also increases the cost of the warehouse.
https://docs.snowflake.com/en/user-guide/querying-persisted-results
NEW QUESTION # 26
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