Snowflake Exam ARA-R01 Topic 3 Question 22 Discussion

Actual exam question for Snowflake's ARA-R01 exam

Question #: 22
Topic #: 3

An Architect for a multi-national transportation company has a system that is used to check the weather conditions along vehicle routes. The data is provided to drivers.

The weather information is delivered regularly by a third-party company and this information is generated as JSON structure. Then the data is loaded into Snowflake in a column with a VARIANT data type. This

table is directly queried to deliver the statistics to the drivers with minimum time lapse.

A single entry includes (but is not limited to):

- Weather condition; cloudy, sunny, rainy, etc.

- Degree

- Longitude and latitude

- Timeframe

- Location address

- Wind

The table holds more than 10 years' worth of data in order to deliver the statistics from different years and locations. The amount of data on the table increases every day.

The drivers report that they are not receiving the weather statistics for their locations in time.

What can the Architect do to deliver the statistics to the drivers faster?

ACreate an additional table in the schema for longitude and latitude. Determine a regular task to fill this information by extracting it from the JSON dataset.

BAdd search optimization service on the variant column for longitude and latitude in order to query the information by using specific metadata.

CDivide the table into several tables for each year by using the timeframe information from the JSON dataset in order to process the queries in parallel.

DDivide the table into several tables for each location by using the location address information from the JSON dataset in order to process the queries in parallel.

Show Suggested Answer

Suggested Answer: B

To improve the performance of queries on semi-structured data, such as JSON stored in a VARIANT column, Snowflake's search optimization service can be utilized. By adding search optimization specifically for the longitude and latitude fields within the VARIANT column, the system can perform point lookups and substring queries more efficiently. This will allow for faster retrieval of weather statistics, which is critical for the drivers to receive timely updates.

by Tamala at Sep 15, 2024, 04:56 AM

Limited Time Offer

25%

Off

Get Premium ARA-R01 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Nan

12 days ago

I'd go with option C. Parallelizing the queries is the way to go, and using the timeframe info to split the table is a smart move.

upvoted 0 times

...

Cherelle

15 days ago

Wait, they've been storing 10 years' worth of data? Somebody call the weather forecast police, that's a serious data hoarding issue!

upvoted 0 times

...

Ariel

17 days ago

Dividing the table by location address might work, but then you'd have to manage a lot of smaller tables. Sounds like a lot of extra work to me.

upvoted 0 times

Laquanda

5 days ago

B: Add search optimization service on the variant column for longitude and latitude in order to query the information by using specific metadata.

upvoted 0 times

...

Paola

7 days ago

A: Create an additional table in the schema for longitude and latitude. Determine a regular task to fill this information by extracting it from the JSON dataset.

upvoted 0 times

...

Marsha

22 days ago

I think adding a search optimization service on the variant column is a good idea. It will make the queries more efficient, especially with the massive amount of data.

upvoted 0 times

...

1 months ago

I think option A could help speed up the delivery of weather statistics to the drivers.

upvoted 0 times

...