ARA-R01 무료 덤프문제 온라인 액세스

A data platform team creates two multi-cluster virtual warehouses with the AUTO_SUSPEND value set to NULL on one. and '0' on the other. What would be the execution behavior of these virtual warehouses?

• A.Setting a '0' value means the warehouses will suspend immediately, and NULL means the warehouses will never suspend.
• B.Setting a '0' or NULL value means the warehouses will never suspend.
• C.Setting a '0' or NULL value means the warehouses will suspend after the default of 600 seconds.
• D.Setting a '0' or NULL value means the warehouses will suspend immediately.

An Architect has been asked to clone schema STAGING as it looked one week ago, Tuesday June 1st at 8:00 AM, to recover some objects.
The STAGING schema has 50 days of retention.
The Architect runs the following statement:
CREATE SCHEMA STAGING_CLONE CLONE STAGING at (timestamp => '2021-06-01 08:00:00'); The Architect receives the following error: Time travel data is not available for schema STAGING. The requested time is either beyond the allowed time travel period or before the object creation time.
The Architect then checks the schema history and sees the following:
CREATED_ON|NAME|DROPPED_ON
2021-06-02 23:00:00 | STAGING | NULL
2021-05-01 10:00:00 | STAGING | 2021-06-02 23:00:00
How can cloning the STAGING schema be achieved?

• A.Modify the statement: CREATE SCHEMA STAGING_CLONE CLONE STAGING at (timestamp =>
  '2021-05-01 10:00:00');
• B.Cloning cannot be accomplished because the STAGING schema version was not active during the proposed Time Travel time period.
• C.Undrop the STAGING schema and then rerun the CLONE statement.
• D.Rename the STAGING schema and perform an UNDROP to retrieve the previous STAGING schema version, then run the CLONE statement.

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?

• A.Divide 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.
• B.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.
• C.Divide 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.
• D.Add search optimization service on the variant column for longitude and latitude in order to query the information by using specific metadata.

Which of the below commands will use warehouse credits?

• A.SELECT MAX(FLAKE_ID) FROM SNOWFLAKE;
• B.SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID;
• C.SELECT COUNT(*) FROM SNOWFLAKE;
• D.SHOW TABLES LIKE 'SNOWFL%';

A company is using Snowflake in Azure in the Netherlands. The company analyst team also has data in JSON format that is stored in an Amazon S3 bucket in the AWS Singapore region that the team wants to analyze.
The Architect has been given the following requirements:
1. Provide access to frequently changing data
2. Keep egress costs to a minimum
3. Maintain low latency
How can these requirements be met with the LEAST amount of operational overhead?

• A.Copy the data between providers from S3 to Azure Blob storage to collocate, then use Snowpipe for data ingestion.
• B.Use a materialized view on top of an external table against the S3 bucket in AWS Singapore.
• C.Use an external table against the S3 bucket in AWS Singapore and copy the data into transient tables.
• D.Use AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then use an external table against the Blob storage.