Snowflake Updated ARA-C01 Exam Questions and Answers by bowie

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.

CREATE DATABASE | Snowflake Documentation

Importing Data from a Share | Snowflake Documentation

Importing a Share | Snowflake Documentation

CREATE SHARE | Snowflake Documentation

Warehouse credits are used to pay for the processing time used by each virtual warehouse in Snowflake. A virtual warehouse is a cluster of compute resources that enables executing queries, loading data, and performing other DML operations. Warehouse credits are charged based on the number of virtual warehouses you use, how long they run, and their size1.

Among the commands listed in the question, the following ones will use warehouse credits:

SELECT MAX(FLAKE_ID) FROM SNOWFLAKE: This command will use warehouse credits because it is a query that requires a virtual warehouse to execute. The query will scan the SNOWFLAKE table and return the maximum value of the FLAKE_ID column2. Therefore, option B is correct.

SELECT COUNT(*) FROM SNOWFLAKE: This command will also use warehouse credits because it is a query that requires a virtual warehouse to execute. The query will scan the SNOWFLAKE table and return the number of rows in the table3. Therefore, option C is correct.

SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID: This command will also use warehouse credits because it is a query that requires a virtual warehouse to execute. The query will scan the SNOWFLAKE table and return the number of rows for each distinct value of the FLAKE_ID column4. Therefore, option D is correct.

The command that will not use warehouse credits is:

SHOW TABLES LIKE ‘SNOWFL%’: This command will not use warehouse credits because it is a metadata operation that does not require a virtual warehouse to execute. The command will return the names of the tables that match the pattern ‘SNOWFL%’ in the current database and schema5. Therefore, option A is incorrect.

 Understanding Compute Cost : MAX Function : COUNT Function : GROUP BY Clause : SHOW TABLES

An external table schema defines the columns and data types of the data stored in an external stage. All external tables include the following columns by default:

VALUE: A VARIANT type column that represents a single row in the external file.

METADATA$FILENAME: A pseudocolumn that identifies the name of each staged data file included in the external table, including its path in the stage.

METADATA$FILE_ROW_NUMBER: A pseudocolumn that shows the row number for each record in a staged data file.

You can also create additional virtual columns as expressions using the VALUE column and/or the pseudocolumns. However, the following columns are not valid for external tables and cannot be included in the schema:

METADATASROW_ID: This column is only available for internal tables and shows the unique identifier for each row in the table.

METADATASISUPDATE: This column is only available for internal tables and shows whether the row was inserted or updated by a merge operation.

METADATASEXTERNAL TABLE PARTITION: This column is not a valid column name and does not exist in Snowflake.

 Introduction to External Tables, CREATE EXTERNAL TABLE

According to the SnowPro Advanced: Architect documents and learning resources, column masking policies are applied at query time based on the privileges of the user who runs the query. Therefore, if a user has the privilege to see unmasked data in a column, they will see the original data when they query that column. If they load this column data into another column that does not have a masking policy, the unmasked data will be loaded in the new column, and any user who can query the new column will see the unmasked data as well. The masking policy does not affect the underlying data in the column, only the query results.

Snowflake Documentation: Column Masking

Snowflake Learning: Column Masking