Pre-Summer Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

ARA-R01 Exam Dumps : SnowPro Advanced: Architect Recertification Exam

PDF
ARA-R01 pdf
 Real Exam Questions and Answer
 Last Update: Apr 20, 2026
 Question and Answers: 162 With Explanation
 Compatible with all Devices
 Printable Format
 100% Pass Guaranteed
$25.5  $84.99
ARA-R01 exam
PDF + Testing Engine
ARA-R01 PDF + engine
 Both PDF & Practice Software
 Last Update: Apr 20, 2026
 Question and Answers: 162
 Discount Offer
 Download Free Demo
 24/7 Customer Support
$40.5  $134.99
Testing Engine
ARA-R01 Engine
 Desktop Based Application
 Last Update: Apr 20, 2026
 Question and Answers: 162
 Create Multiple Test Sets
 Questions Regularly Updated
  90 Days Free Updates
  Windows and Mac Compatible
$30  $99.99

Verified By IT Certified Experts

CertsTopics.com Certified Safe Files

Up-To-Date Exam Study Material

99.5% High Success Pass Rate

100% Accurate Answers

Instant Downloads

Exam Questions And Answers PDF

Try Demo Before You Buy

Certification Exams with Helpful Questions And Answers

SnowPro Advanced: Architect Recertification Exam Questions and Answers

Question 1

A company has a source system that provides JSON records for various loT operations. The JSON Is loading directly into a persistent table with a variant field. The data Is quickly growing to 100s of millions of records and performance to becoming an issue. There is a generic access pattern that Is used to filter on the create_date key within the variant field.

What can be done to improve performance?

Options:

A.

Alter the target table to Include additional fields pulled from the JSON records. This would Include a create_date field with a datatype of time stamp. When this field Is used in the filter, partition pruning will occur.

B.

Alter the target table to include additional fields pulled from the JSON records. This would include a create_date field with a datatype of varchar. When this field is used in the filter, partition pruning will occur.

C.

Validate the size of the warehouse being used. If the record count is approaching 100s of millions, size XL will be the minimum size required to process this amount of data.

D.

Incorporate the use of multiple tables partitioned by date ranges. When a user or process needs to query a particular date range, ensure the appropriate base table Is used.

Buy Now
Question 2

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

Options:

A.

Global

B.

Database

C.

Schema

D.

Table

Question 3

A Developer is having a performance issue with a Snowflake query. The query receives up to 10 different values for one parameter and then performs an aggregation over the majority of a fact table. It then

joins against a smaller dimension table. This parameter value is selected by the different query users when they execute it during business hours. Both the fact and dimension tables are loaded with new data in an overnight import process.

On a Small or Medium-sized virtual warehouse, the query performs slowly. Performance is acceptable on a size Large or bigger warehouse. However, there is no budget to increase costs. The Developer

needs a recommendation that does not increase compute costs to run this query.

What should the Architect recommend?

Options:

A.

Create a task that will run the 10 different variations of the query corresponding to the 10 different parameters before the users come in to work. The query results will then be cached and ready to respond quickly when the users re-issue the query.

B.

Create a task that will run the 10 different variations of the query corresponding to the 10 different parameters before the users come in to work. The task will be scheduled to align with the users' working hours in order to allow the warehouse cache to be used.

C.

Enable the search optimization service on the table. When the users execute the query, the search optimization service will automatically adjust the query execution plan based on the frequently-used parameters.

D.

Create a dedicated size Large warehouse for this particular set of queries. Create a new role that has USAGE permission on this warehouse and has the appropriate read permissions over the fact and dimension tables. Have users switch to this role and use this warehouse when they want to access this data.