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Snowflake ADA-C01 Exam Syllabus Topics:
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Snowflake SnowPro Advanced Administrator Sample Questions (Q31-Q36):
NEW QUESTION # 31
A Snowflake Administrator needs to persist all virtual warehouse configurations for auditing and backups. Given a table already exists with the following schema:
Table Name : VWH_META
Column 1 : SNAPSHOT_TIME TIMESTAMP_NTZ
Column 2 : CONFIG VARIANT
Which commands should be executed to persist the warehouse data at the time of execution in JSON format in the table VWH META?
Answer: D
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. The LAST_QUERY_ID function returns the query ID of the most recent statement executed in the current session. Therefore, the combination of these two functions can be used to access the output of the SHOW WAREHOUSES command, which returns the configurations of all the virtual warehouses in the account. However, to persist the warehouse data in JSON format in the table VWH_META, the OBJECT_CONSTRUCT function is needed to convert the output of the SHOW WAREHOUSES command into a VARIANT column. The OBJECT_CONSTRUCT function takes a list of key-value pairs and returns a single JSON object. Therefore, the correct commands to execute are:
1. SHOW WAREHOUSES;
2. INSERT INTO VWH_META SELECT CURRENT_TIMESTAMP (), OBJECT_CONSTRUCT (*) FROM TABLE (RESULT_SCAN (LAST_QUERY_ID ())); The other options are incorrect because:
* A) This option does not use the OBJECT_CONSTRUCT function, so it will not persist the warehouse data in JSON format. Also, it is missing the * symbol in the SELECT clause, so it will not select any columns from the result set of the SHOW WAREHOUSES command.
* B) This option does not use the OBJECT_CONSTRUCT function, so it will not persist the warehouse data in JSON format. It will also try to insert multiple columns into a single VARIANT column, which will cause a type mismatch error.
* D) This option does not use the OBJECT_CONSTRUCT function, so it will not persist the warehouse data in JSON format. It will also try to use the RESULT_SCAN function on a subquery, which is not supported. The RESULT_SCAN function can only be used on a query ID or a table name.
NEW QUESTION # 32
For Snowflake network policies, what will occur when the account_level and user_level network policies are both defined?
Answer: A
Explanation:
Explanation
According to the Network Policies documentation, a network policy can be applied to an account, a security integration, or a user. If there are network policies applied to more than one of these, the most specific network policy overrides more general network policies. The following summarizes the order of precedence:
*Account: Network policies applied to an account are the most general network policies. They are overridden by network policies applied to a security integration or user.
*Security Integration: Network policies applied to a security integration override network policies applied to the account, but are overridden by a network policy applied to a user.
*User: Network policies applied to a user are the most specific network policies. They override both accounts and security integrations.
Therefore, if both the account_level and user_level network policies are defined, the user_level policy will take effect and the account_level policy will be ignored. The other options are incorrect because:
*The account_level policy will not override the user_level policy, as explained above.
*The user_level network policies will be supported, as they are part of the network policyfeature.
*A network policy error will not be generated, as there is no conflict between the account_level and user_level network policies.
NEW QUESTION # 33
What are characteristics of Dynamic Data Masking? (Select TWO).
Answer: A,D
Explanation:
According to the Using Dynamic Data Masking documentation, Dynamic Data Masking is a feature that allows you to alter sections of data in table and view columns at query time using a predefined masking strategy. The following are some of the characteristics of Dynamic Data Masking:
* A single masking policy can be applied to columns in different tables. This means that you can write a policy once and have it apply to thousands of columns across databases and schemas.
* A single masking policy can be applied to columns with different data types. This means that you can use the same masking strategy for columns that store different kinds of data, such as strings, numbers, dates, etc.
* A masking policy that is currently set on a table can be dropped. This means that you can remove the masking policy from the table and restore the original data visibility.
* A masking policy can be applied to the VALUE column of an external table. This means that you can mask data that is stored in an external stage and queried through an external table.
* The role that creates the masking policy will always see unmasked data in query results. This is not true, as the masking policy can also apply to the creator role depending on the execution context conditions defined in the policy. For example, if the policy specifies that only users with a certain custom entitlement can see the unmasked data, then the creator role will also need to have that entitlement to see the unmasked data.
NEW QUESTION # 34
A Snowflake Administrator wants to create a virtual warehouse that supports several dashboards, issuing various queries on the same database.
For this warehouse, why should the Administrator consider setting AUTO_SUSPEND to 0 or NULL?
Answer: A
Explanation:
Explanation
According to the Snowflake documentation1, the AUTO_SUSPEND property specifies the number of seconds of inactivity after which a warehouse is automatically suspended. If the property is set to 0 or NULL, the warehouse never suspends automatically. For a warehouse that supports several dashboards, issuing various queries on the same database, setting AUTO_SUSPEND to 0 or NULL can help to keep the data cache warm, which means that the data used by the queries is already loaded into the warehouse memory and does not need to be fetched from the storage layer. This can improve the performance of similar queries that access the same data. Option A is incorrect because setting AUTO_SUSPEND to 0 or NULL does not save costs on warehouse shutdowns and startups, but rather increases the costs by keeping the warehouse running continuously. Option B is incorrect because setting AUTO_SUSPEND to 0 or NULL does not run the warehouse as little as possible, but rather runs the warehouse as much as possible. Option D is incorrect because setting AUTO_SUSPEND to 0 or NULL does not affect the query result cache, which is a separate cache that stores the results of previous queries for a period of time. The query result cache is not dependent on the warehouse state, but on the query criteria2.
NEW QUESTION # 35
When a role is dropped, which role inherits ownership of objects owned by the dropped role?
Answer: C
Explanation:
Explanation
According to the Snowflake documentation1, when a role is dropped, ownership of all objects owned by the dropped role is transferred to the role that is directly above the dropped role in the role hierarchy. This is to ensure that there is always a single owner for each object in the system.
1: Drop Role | Snowflake Documentation
NEW QUESTION # 36
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