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Snowflake ADA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Given a scenario, configure access controls Set up and manage security administration and authorization
Topic 2	Manage and implement data sharing Given a set of business requirements, establish access control architecture
Topic 3	Given a scenario, manage databases, tables, and views Manage organizations and access control
Topic 4	Given a scenario, create and manage access control Given a scenario, implement resource monitors
Topic 5	Interpret and make recommendations for data clustering Manage DML locking and concurrency in Snowflake
Topic 6	Set up and manage network and private connectivity Given a scenario, manage Snowflake Time Travel and Fail-safe

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Snowflake - ADA-C01 - Accurate SnowPro Advanced Administrator Reliable Test Syllabus

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Snowflake SnowPro Advanced Administrator Sample Questions (Q63-Q68):

NEW QUESTION # 63
An Administrator needs to create a sample of the table LINEITEM. The sample should not be repeatable and the sampling function should take the data by blocks of rows.
What select command will generate a sample of 20% of the table?

A. select * from LINEITEM tablesample system (20) seed (1);
B. select * from LINEITEM tablesample block (20 rows);
C. select * from LINEITEM sample bernoulli (20);
D. select * from LINEITEM sample system (20);

Answer: D

Explanation:
Explanation
This command will generate a sample of 20% of the table by using the SYSTEM (or BLOCK) sampling method, which selects each block of rows with a probability of 20/100. This method is suitable for taking data by blocks of rows, as the question requires. According to the Snowflake documentation, "SYSTEM (or BLOCK): Includes each block of rows with a probability of p/100. Similar to flipping a weighted coin for each block of rows. This method does not support fixed-size sampling." The other options are either incorrect or do not meet the requirements of the question. Option A uses the BERNOULLI (or ROW) sampling method, which selects each row with a probability of 20/100, but does not take data by blocks of rows. Option C uses the BLOCK sampling method, but specifies a fixed number of rows (20) instead of a percentage (20%).
Option D uses the SYSTEM sampling method, but specifies a seed value (1), which makes the sampling repeatable, contrary to the question.

NEW QUESTION # 64
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).

A. Increase the multi-cluster maximum to 20 or more clusters.
B. Increase the minimum number of clusters started in the multi-cluster configuration to 5.
C. Examine the complex queries and determine if they can be made more efficient using clustering keys or materialized views.
D. Have the group running the complex monthly queries use a separate appropriately-sized warehouse to support their workload.
E. 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.

Answer: D,E

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 # 65
What are benefits of creating and maintaining resource monitors in Snowflake? (Select THREE).

A. Multiple triggers can be configured across various virtual warehouse thresholds.
B. The cost of running a resource monitor is only 10% of a credit, per day of operation.
C. Resource monitor governance is tightly controlled and monitors can only be created by the ACCOUNTADMIN role or users with the CREATE MONITOR privilege.
D. Resource monitors add no additional load to virtual warehouse compute.
E. Multiple resource monitors can be applied to a single virtual warehouse.
F. Resource monitors can be applied to more than one virtual warehouse.

Answer: A,D,F

Explanation:
According to the Snowflake documentation1, resource monitors are a feature that helps you manage and control Snowflake costs by monitoring and setting limits on your compute resources. Resource monitors do not consume any credits or add any load to the virtual warehouses they monitor1. Resource monitors can also have multiple triggers that specify different actions (such as suspending or notifying) when certain percentages of the credit quota are reached2. Resource monitors can be applied to either the entire account or a specific set of individual warehouses1. The other options are not benefits of resource monitors. The cost of running a resource monitor is negligible, not 10% of a credit3. Multiple resource monitors cannot be applied to a single virtual warehouse; only one resource monitor can be assigned to a warehouse at a time2. Resource monitor governance is not tightly controlled; account administrators can enable users with other roles to view and modify resource monitors using SQL2.

NEW QUESTION # 66
A team is provisioning new lower environments from the production database using cloning. All production objects and references reside in the database, and do not have external references.
What set of object references needs to be re-pointed before granting access for usage?

A. Sequences, views, secure views, and materialized views
B. Sequences, views, and secure views
C. There are no object references that need to be re-pointed
D. Sequences, storage integrations, views, secure views, and materialized views

Answer: D

Explanation:
According to the Snowflake documentation1, when an object in a schema is cloned, any future grants defined for this object type in the schema are applied to the cloned object unless the COPY GRANTS option is specified in the CREATE statement for the clone operation. However, some objects may still reference the source object or external objects after cloning, which may cause issues with access or functionality. These objects include:
* Sequences: If a table column references a sequence that generates default values, the cloned table may reference the source or cloned sequence, depending on where the sequence is defined. To avoid conflicts, the sequence reference should be re-pointed to the desired sequence using the ALTER TABLE command2.
* Storage integrations: If a stage or a table references a storage integration, the cloned object may still reference the source storage integration, which may not be accessible or valid in the new environment. To avoid errors, the storage integration reference should be re-pointed to the desired storage integration using the ALTER STAGE or ALTER TABLE command34.
* Views, secure views, and materialized views: If a view references another view or table, the cloned view may still reference the source object, which may not be accessible or valid in the new environment. To avoid errors, the view reference should be re-pointed to the desired object using the CREATE OR REPLACE VIEW command5.
1: Cloning Considerations | Snowflake Documentation 2: [ALTER TABLE | Snowflake Documentation] 3: [ALTER STAGE | Snowflake Documentation] 4: [ALTER TABLE | Snowflake Documentation] 5: [CREATE VIEW | Snowflake Documentation]

NEW QUESTION # 67
MY_TABLE is a table that has not been updated or modified for several days. On 01 January 2021 at 07:01, a user executed a query to update this table. The query ID is
'8e5d0ca9-005e-44e6-b858-a8f5b37c5726'. It is now 07:30 on the same day.
Which queries will allow the user to view the historical data that was in the table before this query was executed? (Select THREE).

A. SELECT * FROM my table PRIOR TO STATEMENT '8e5d0ca9-005e-44e6-b858-a8f5b37c5726';
B. SELECT * FROM TIME_TRAVEL ('MY_TABLE', 2021-01-01 07:00:00);
C. SELECT * FROM my table WITH TIME_TRAVEL (OFFSET => -60*30);
D. SELECT * FROM my_table AT (OFFSET => -60*30);
E. SELECT * FROM my_table AT (TIMESTAMP => '2021-01-01 07:00:00' :: timestamp);
F. SELECT * FROM my_table BEFORE (STATEMENT => '8e5d0ca9-005e-44e6-b858-a8f5b37c5726');

Answer: A,E,F

Explanation:
Explanation
According to the AT | BEFORE documentation, the AT or BEFORE clause is used for Snowflake Time Travel, which allows you to query historical data from a table based on a specific point in the past. The clause can use one of the following parameters to pinpoint the exact historical data you wish to access:
*TIMESTAMP: Specifies an exact date and time to use for Time Travel.
*OFFSET: Specifies the difference in seconds from the current time to use for Time Travel.
*STATEMENT: Specifies the query ID of a statement to use as the reference point for Time Travel.
Therefore, the queries that will allow the user to view the historical data that was in the table before the query was executed are:
*B. SELECT * FROM my_table AT (TIMESTAMP => '2021-01-01 07:00:00' :: timestamp); This query uses the TIMESTAMP parameter to specify a point in time that is before the query execution time of 07:01.
*D. SELECT * FROM my table PRIOR TO STATEMENT '8e5d0ca9-005e-44e6-b858-a8f5b37c5726'; This query uses the PRIOR TO STATEMENT keyword and the STATEMENT parameter to specify a point in time that is immediately preceding the query execution time of 07:01.
*F. SELECT * FROM my_table BEFORE (STATEMENT => '8e5d0ca9-005e-44e6-b858-a8f5b37c5726'); This query uses the BEFORE keyword and the STATEMENT parameter to specify a point in time that is immediately preceding the query execution time of 07:01.
The other queries are incorrect because:
*A. SELECT * FROM my table WITH TIME_TRAVEL (OFFSET => -60*30); This query uses the OFFSET parameter to specify a point in time that is 30 minutes before the current time, which is 07:30. This is after the query execution time of 07:01, so it will not show the historical data before the query was executed.
*C. SELECT * FROM TIME_TRAVEL ('MY_TABLE', 2021-01-01 07:00:00); This query is not valid syntax for Time Travel. The TIME_TRAVEL function does not exist in Snowflake. The correct syntax is to use the AT or BEFORE clause after the table name in the FROM clause.
*E. SELECT * FROM my_table AT (OFFSET => -60*30); This query uses the AT keyword and the OFFSET parameter to specify a point in time that is 30 minutes before the current time, which is 07:30. This is equal to the query execution time of 07:01, so it will not show the historical data before the query was executed. The AT keyword specifies that the request is inclusive of any changes made by a statement or transaction with timestamp equal to the specified parameter. To exclude the changes made by the query, the BEFORE keyword should be used instead.

NEW QUESTION # 68
......

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