QUIZ SNOWFLAKE - ARA-C01 - SNOWPRO ADVANCED ARCHITECT CERTIFICATION USEFUL TEST TESTKING

Quiz Snowflake - ARA-C01 - SnowPro Advanced Architect Certification Useful Test Testking

Quiz Snowflake - ARA-C01 - SnowPro Advanced Architect Certification Useful Test Testking

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For exam applicants TestsDumps offers real Snowflake ARA-C01 exam questions. There are three formats of the SnowPro Advanced Architect Certification (ARA-C01) practice material. These formats are PDF, desktop practice exam software, and web-based SnowPro Advanced Architect Certification (ARA-C01) practice exam. With these questions, you can crack the Snowflake ARA-C01 certification exam and save your time and money.

To qualify for the Snowflake ARA-C01 Exam, candidates must first obtain the SnowPro Advanced Architect certification. SnowPro Advanced Architect Certification certification requires passing the SnowPro Core exam, as well as demonstrating proficiency in data modeling and performance tuning. Once candidates have achieved this certification, they can then take the ARA-C01 exam to further validate their expertise.

The SnowPro Advanced Architect Certification is a comprehensive exam that tests the candidate's knowledge of Snowflake's advanced features, including Snowflake data sharing, multi-cluster and multi-region data replication, and advanced security features. It tests the candidate's ability to design and implement Snowflake environments that are highly scalable, performant, and secure. SnowPro Advanced Architect Certification certification also validates the candidate's ability to troubleshoot complex Snowflake environments and resolve performance issues.

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q132-Q137):

NEW QUESTION # 132
Which query will identify the specific days and virtual warehouses that would benefit from a multi-cluster warehouse to improve the performance of a particular workload?

  • A. A close up of a message Description automatically generated
  • B. A white background with black text Description automatically generated
  • C. A white background with black text Description automatically generated
  • D. A screen shot of a computer Description automatically generated

Answer: C

Explanation:
A multi-cluster warehouse is a virtual warehouse that can scale compute resources by adding or removing clusters based on the workload demand. A multi-cluster warehouse can improve the performance of a particular workload by reducing the query queue time and the data spillage to local storage. To identify the specific days and virtual warehouses that would benefit from a multi-cluster warehouse, you need to analyze the query history and look for the following indicators:
* High average queued load: This metric shows the average number of queries waiting in the queue for each warehouse cluster. A high value indicates that the warehouse is overloaded and cannot handle the concurrency demand.
* High bytes spilled to local storage: This metric shows the amount of data that was spilled from memory to local disk during query processing. A high value indicates that the warehouse size is too small and cannot fit the data in memory.
* High variation in workload: This metric shows the fluctuation in the number of queries submitted to the warehouse over time. A high variation indicates that the workload is unpredictable and dynamic, and requires a flexible scaling policy.
The query in option C is the best one to identify these indicators, as it selects the date, warehouse name, bytes spilled to local storage, and sum of average queued load from the query history table, and filters the results where bytes spilled to local storage is greater than zero. This query will show the days and warehouses that experienced data spillage and high queue time, and could benefit from a multi-cluster warehouse with auto-scale mode.
The query in option A is not correct, as it only selects the date and warehouse name, and does not include any metrics to measure the performance of the workload. The query in option B is not correct, as it selects the date, warehouse name, and average execution time, which is not a good indicator of the need for a multi-cluster warehouse. The query in option D is not correct, as it selects the date, warehouse name, and average credits used, which is not a good indicator of the need for a multi-cluster warehouse either.
References: Multi-cluster Warehouses, Query History View, Reducing Queues


NEW QUESTION # 133
Which of the following are characteristics of Snowflake's parameter hierarchy?

  • A. Virtual warehouse parameters override user parameters.
  • B. Schema parameters override account parameters.
  • C. Session parameters override virtual warehouse parameters.
  • D. Table parameters override virtual warehouse parameters.

Answer: C


NEW QUESTION # 134
An Architect needs to allow a user to create a database from an inbound share.
To meet this requirement, the user's role must have which privileges? (Choose two.)

  • A. CREATE SHARE;
  • B. IMPORT SHARE;
  • C. IMPORT DATABASE;
  • D. IMPORT PRIVILEGES;
  • E. CREATE DATABASE;

Answer: C,E

Explanation:
According to the Snowflake documentation, to create a database from an inbound share, the user's role must have the following privileges:
The CREATE DATABASE privilege on the current account. This privilege allows the user to create a new database in the account1.
The IMPORT DATABASE privilege on the share. This privilege allows the user to import a database from the share into the account2. The other privileges listed are not relevant for this requirement. The IMPORT SHARE privilege is used to import a share into the account, not a database3. The IMPORT PRIVILEGES privilege is used to import the privileges granted on the shared objects, not the objects themselves2. The CREATE SHARE privilege is used to create a share to provide data to other accounts, not to consume data from other accounts4.
Reference:
CREATE DATABASE | Snowflake Documentation
Importing Data from a Share | Snowflake Documentation
Importing a Share | Snowflake Documentation
CREATE SHARE | Snowflake Documentation


NEW QUESTION # 135
The Business Intelligence team reports that when some team members run queries for their dashboards in parallel with others, the query response time is getting significantly slower What can a Snowflake Architect do to identify what is occurring and troubleshoot this issue?

  • A.
  • B.
  • C.
  • D.

Answer: D

Explanation:
The image shows a SQL query that can be used to identify which queries are spilled to remote storage and suggests changing the warehouse parameters to address this issue. Spilling to remote storage occurs when the memory allocated to a warehouse is insufficient to process a query, and Snowflake uses disk or cloud storage as a temporary cache. This can significantly slow down the query performance and increase the cost. To troubleshoot this issue, a Snowflake Architect can run the query shown in the image to find out which queries are spilling, how much data they are spilling, and which warehouses they are using. Then, the architect can adjust the warehouse size, type, or scaling policy to provide enough memory for the queries and avoid spilling12. References:
* Recognizing Disk Spilling
* Managing the Kafka Connector


NEW QUESTION # 136
At which object type level can the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges be granted?

  • A. Global
  • B. Database
  • C. Schema
  • D. Table

Answer: A

Explanation:
The object type level at which the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges can be granted is global. These are account-level privileges that control who can apply or unset these policies on objects such as columns, tables, views, accounts, or users.
These privileges are granted to the ACCOUNTADMIN role by default, and can be granted to other roles as needed. The other options are incorrect because they are not the object type level at which these privileges can be granted. Database, schema, and table are lower-level object types that do not support these privileges. References: Access Control Privileges | Snowflake Documentation, Using Dynamic Data Masking
| Snowflake Documentation, Using Row Access Policies | Snowflake Documentation, Using Session Policies | Snowflake Documentation


NEW QUESTION # 137
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