Free Online Snowflake ARA-R01 Practice Test

Prepare Your Snowflake ARA-R01 Exam Questions with Free online ARA-R01 Practice Test. Get Brilliant SnowPro Advanced: Architect Recertification Exam Results with Valid ARA R01 Exam Dumps.

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Total 166 Questions | Updated On: May 14, 2024

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Question 1

Which of the below commands will use warehouse credits?

A : SHOW TABLES LIKE 'SNOWFL%';

B : SELECT MAX(FLAKE_ID) FROM SNOWFLAKE;

C : SELECT COUNT(*) FROM SNOWFLAKE;

D : SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID;

Answer: B,C,D

Question 2

An Architect is designing a pipeline to stream event data into Snowflake using the Snowflake Kafka connector. The Architect’s highest priority is to configure the connector to stream data in the MOST cost-effective manner. Which of the following is recommended for optimizing the cost associated with the Snowflake Kafka connector?

A : Utilize a higher Buffer.flush.time in the connector configuration.

B : Utilize a higher Buffer.size.bytes in the connector configuration.

C : Utilize a lower Buffer.size.bytes in the connector configuration.

D : Utilize a lower Buffer.count.records in the connector configuration.

Answer: A

Question 3

When using the copy into < table > command with the CSV file format, how does the match_by_column_name parameter behave?

A : It expects a header to be present in the CSV file, which is matched to a case-sensitive table column name.

B : The parameter will be ignored.

C : The command will return an error.

D : The command will return a warning stating that the file has unmatched columns.

Answer: B

Question 4

Which SQL alter command will MAXIMIZE memory and compute resources for a Snowpark stored procedure when executed on the snowpark_opt_wh warehouse?

A :

B :

C :

D :

Answer: A

Question 5

A retail company has over 3000 stores all using the same Point of Sale (POS) system. The company wants to

deliver near real-time sales results to category managers. The stores operate in a variety of time zones and

exhibit a dynamic range of transactions each minute, with some stores having higher sales volumes than

others.

Sales results are provided in a uniform fashion using data engineered fields that will be calculated in a

complex data pipeline. Calculations include exceptions, aggregations, and scoring using external functions

interfaced to scoring algorithms. The source data for aggregations has over 100M rows.

Every minute, the POS sends all sales transactions files to a cloud storage location with a naming convention

that includes store numbers and timestamps to identify the set of transactions contained in the files. The files

are typically less than 10MB in size.

How can the near real-time results be provided to the category managers? (Select TWO).

A : All files should be concatenated before ingestion into Snowflake to avoid micro-ingestion.

B : A Snowpipe should be created and configured with AUTO_INGEST = true. A stream should be created to process INSERTS into a single target table using the stream metadata to inform the store number and timestamps.

C : A stream should be created to accumulate the near real-time data and a task should be created that runs at a frequency that matches the real-time analytics needs.

D : An external scheduler should examine the contents of the cloud storage location and issue SnowSQL commands to process the data at a frequency that matches the real-time analytics needs

E : The copy into command with a task scheduled to run every second should be used to achieve the near-real time requirement.

Answer: B,C

Page: 1 / 34

Total 166 Questions | Updated On: May 14, 2024

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