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A Snowflake account is configured with SCIM provisioning for user accounts and has bi-directional synchronization for user identities. An Administrator with access to SECURITYADMIN uses the Snowflake UI to create a user by issuing the following commands:
use role USERADMIN;
create or replace role DEVELOPER_ROLE;
create user PTORRES PASSWORD = 'hello world!' MUST_CHANGE_PASSWORD = FALSE
default_role = DEVELOPER_ROLE;
The new user named PTORRES successfully logs in, but sees a default role of PUBLIC in the web UI. When attempted, the following command fails:
use DEVELOPER_ROLE;
Why does this command fail?
According to the Snowflake documentation1, creating a user with a default role does not automatically grant that role to the user. The user must be explicitly granted the role by the role owner or a higher-level role. Therefore, the USERADMIN role, which created the DEVELOPER_ROLE, needs to explicitly grant the DEVELOPER_ROLE to the new user PTORRES using the GRANT ROLE command. Otherwise, the user PTORRES will not be able to use the DEVELOPER_ROLE and will see the default role of PUBLIC in the web UI. Option A is incorrect because the DEVELOPER_ROLE does not need to be granted to SYSADMIN before user PTORRES can use the role. Option B is incorrect because the new role can take effect immediately after it is created and granted to the user, and does not depend on the USERADMIN role logging out. Option D is incorrect because the new role will not be affected by the identity provider synchronization, as it is created and managed in Snowflake.
Review the output of the SHOW statement below which displays the current grants on the table DB1. S1. T1:
This statement is executed:
USE ROLE ACCOUNTADMIN;
DROP ROLE A;
What will occur?
An Administrator has been asked to support the company's application team need to build a loyalty program for its customers. The customer table contains Personal
Identifiable Information (PII), and the application team's role is DEVELOPER.
CREATE TABLE customer_data (
customer_first_name string,
customer_last_name string,
customer_address string,
customer_email string,
... some other columns,
);
The application team would like to access the customer data, but the email field must be obfuscated.
How can the Administrator protect the sensitive information, while maintaining the usability of the data?
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?
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
When does auto-suspend occur for a multi-cluster virtual warehouse?
According to the Multi-cluster Warehouses documentation, auto-suspend is a feature that allows a warehouse to automatically suspend itself after a specified period of inactivity. For a multi-cluster warehouse, auto-suspend applies to the entire warehouse, not to individual clusters. Therefore, auto-suspend occurs when the minimum number of clusters is running and there is no activity for the specified period of time. The other options are incorrect because:
* A. Auto-suspend does not occur when there has been no activity on any cluster for the specified period of time. This would imply that each cluster has its own auto-suspend timer, which is not the case. The warehouse has a single auto-suspend timer that is reset by any activity on any cluster.
* B. Auto-suspend does not occur after a specified period of time when an additional cluster has started on the maximum number of clusters specified for a warehouse. This would imply that the auto-suspend timer is affected by the number of clusters running, which is not the case. The auto-suspend timer is only affected by the activity on the warehouse, regardless of the number of clusters running.
* D. Auto-suspend does apply for multi-cluster warehouses, as explained above. It is a feature that can be enabled or disabled for any warehouse, regardless of the number of clusters.