Snowflake ARA-R01 Exam Practice Test Instant Access

Question 1

The data share exists between a data provider account and a data consumer account. Five tables from the provider account are being shared with the consumer account. The consumer role has been granted the imported privileges privilege.

What will happen to the consumer account if a new table (table_6) is added to the provider schema?

AThe consumer role will automatically see the new table and no additional grants are needed.

BThe consumer role will see the table only after this grant is given on the consumer side:
grant imported privileges on database PSHARE_EDW_4TEST_DB to DEV_ROLE;

CThe consumer role will see the table only after this grant is given on the provider side:
use role accountadmin;
Grant select on table EDW.ACCOUNTING.Table_6 to share PSHARE_EDW_4TEST;

DThe consumer role will see the table only after this grant is given on the provider side:
use role accountadmin;
grant usage on database EDW to share PSHARE_EDW_4TEST ;
grant usage on schema EDW.ACCOUNTING to share PSHARE_EDW_4TEST ;
Grant select on table EDW.ACCOUNTING.Table_6 to database PSHARE_EDW_4TEST_DB ;

Answer : D

When a new table (table_6) is added to a schema in the provider's account that is part of a data share, the consumer will not automatically see the new table. The consumer will only be able to access the new table once the appropriate privileges are granted by the provider. The correct process, as outlined in option D, involves using the provider's ACCOUNTADMIN role to grant USAGE privileges on the database and schema, followed by SELECT privileges on the new table, specifically to the share that includes the consumer's database. This ensures that the consumer account can access the new table under the established data sharing setup. Reference:

Snowflake Documentation on Managing Access Control

Snowflake Documentation on Data Sharing

Question 2

A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.

The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.

What step can be taken to improve the pruning of the reporting tables?

AEliminate the use of Snowpipe and load the files into internal stages using PUT commands.

BIncrease the size of the virtual warehouse to a size 5X-Large.

CUse an ORDER BY <cluster_key (s) > command to load the reporting tables.

DCreate larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.

Answer : C

Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.

Reference =

* Snowflake Documentation on micro-partitions and data clustering2

* Community article on recognizing unsatisfactory pruning and improving it1

Question 3

An Architect needs to design a data unloading strategy for Snowflake, that will be used with the COPY INTO command.

Which configuration is valid?

ALocation of files: Snowflake internal location
. File formats: CSV, XML
. File encoding: UTF-8
. Encryption: 128-bit

BLocation of files: Amazon S3
. File formats: CSV, JSON
. File encoding: Latin-1 (ISO-8859)
. Encryption: 128-bit

CLocation of files: Google Cloud Storage
. File formats: Parquet
. File encoding: UTF-8
* Compression: gzip

DLocation of files: Azure ADLS
. File formats: JSON, XML, Avro, Parquet, ORC
. Compression: bzip2
. Encryption: User-supplied key

Answer : C

For the configuration of data unloading in Snowflake, the valid option among the provided choices is 'C.' This is because Snowflake supports unloading data into Google Cloud Storage using the COPY INTO <location> command with specific configurations. The configurations listed in option C, such as Parquet file format with UTF-8 encoding and gzip compression, are all supported by Snowflake. Notably, Parquet is a columnar storage file format, which is optimal for high-performance data processing tasks in Snowflake. The UTF-8 file encoding and gzip compression are both standard and widely used settings that are compatible with Snowflake's capabilities for data unloading to cloud storage platforms. Reference:

Snowflake Documentation on COPY INTO command

Snowflake Documentation on Supported File Formats

Snowflake Documentation on Compression and Encoding Options

Question 4

Which command will create a schema without Fail-safe and will restrict object owners from passing on access to other users?

Acreate schema EDW.ACCOUNTING WITH MANAGED ACCESS;

Bcreate schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS - 7;

Ccreate TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 1;

Dcreate TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 7;

Answer : D

A transient schema in Snowflake is designed without a Fail-safe period, meaning it does not incur additional storage costs once it leaves Time Travel, and it is not protected by Fail-safe in the event of a data loss. The WITH MANAGED ACCESS option ensures that all privilege grants, including future grants on objects within the schema, are managed by the schema owner, thus restricting object owners from passing on access to other users1.

Reference =

* Snowflake Documentation on creating schemas1

* Snowflake Documentation on configuring access control2

* Snowflake Documentation on understanding and viewing Fail-safe3

Question 5

A table, EMP_ TBL has three records as shown:

The following variables are set for the session:

Which SELECT statements will retrieve all three records? (Select TWO).

ASelect * FROM Stbl_ref WHERE Scol_ref IN ('Name1','Nam2','Name3');

BSELECT * FROM EMP_TBL WHERE identifier(Scol_ref) IN ('Namel','Name2', 'Name3');

CSELECT * FROM identifier<Stbl_ref> WHERE NAME IN ($var1, $var2, $var3);

DSELECT * FROM identifier($tbl_ref) WHERE ID IN Cvarl','var2','var3');

ESELECT * FROM $tb1_ref WHERE $col_ref IN ($var1, Svar2, Svar3);

Answer : B, E

The correct answer is B and E because they use the correct syntax and values for the identifier function and the session variables.

The identifier function allows you to use a variable or expression as an identifier (such as a table name or column name) in a SQL statement. It takes a single argument and returns it as an identifier. For example, identifier($tbl_ref) returns EMP_TBL as an identifier.

The session variables are set using the SET command and can be referenced using the $ sign. For example, $var1 returns Name1 as a value.

Option A is incorrect because it uses Stbl_ref and Scol_ref, which are not valid session variables or identifiers. They should be $tbl_ref and $col_ref instead.

Option C is incorrect because it uses identifier<Stbl_ref>, which is not a valid syntax for the identifier function. It should be identifier($tbl_ref) instead.

Option D is incorrect because it uses Cvarl, var2, and var3, which are not valid session variables or values. They should be $var1, $var2, and $var3 instead.Reference:

Snowflake Documentation: Identifier Function

Snowflake Documentation: Session Variables

Snowflake Learning: SnowPro Advanced: Architect Exam Study Guide

Question 6

An Architect has designed a data pipeline that Is receiving small CSV files from multiple sources. All of the files are landing in one location. Specific files are filtered for loading into Snowflake tables using the copy command. The loading performance is poor.

What changes can be made to Improve the data loading performance?

AIncrease the size of the virtual warehouse.

BCreate a multi-cluster warehouse and merge smaller files to create bigger files.

CCreate a specific storage landing bucket to avoid file scanning.

DChange the file format from CSV to JSON.

Answer : B

According to the Snowflake documentation, the data loading performance can be improved by following some best practices and guidelines for preparing and staging the data files. One of the recommendations is to aim for data files that are roughly 100-250 MB (or larger) in size compressed, as this will optimize the number of parallel operations for a load. Smaller files should be aggregated and larger files should be split to achieve this size range. Another recommendation is to use a multi-cluster warehouse for loading, as this will allow for scaling up or out the compute resources depending on the load demand. A single-cluster warehouse may not be able to handle the load concurrency and throughput efficiently. Therefore, by creating a multi-cluster warehouse and merging smaller files to create bigger files, the data loading performance can be improved.Reference:

Data Loading Considerations

Preparing Your Data Files

Planning a Data Load

Question 7

A company wants to Integrate its main enterprise identity provider with federated authentication with Snowflake.

The authentication integration has been configured and roles have been created in Snowflake. However, the users are not automatically appearing in Snowflake when created and their group membership is not reflected in their assigned rotes.

How can the missing functionality be enabled with the LEAST amount of operational overhead?

AOAuth must be configured between the identity provider and Snowflake. Then the authorization server must be configured with the right mapping of users and roles.

BOAuth must be configured between the identity provider and Snowflake. Then the authorization server must be configured with the right mapping of users, and the resource server must be configured with the right mapping of role assignment.

CSCIM must be enabled between the identity provider and Snowflake. Once both are synchronized through SCIM, their groups will get created as group accounts in Snowflake and the proper roles can be granted.

DSCIM must be enabled between the identity provider and Snowflake. Once both are synchronized through SCIM. users will automatically get created and their group membership will be reflected as roles In Snowflake.

Answer : D

The best way to integrate an enterprise identity provider with federated authentication and enable automatic user creation and role assignment in Snowflake is to use SCIM (System for Cross-domain Identity Management). SCIM allows Snowflake to synchronize with the identity provider and create users and groups based on the information provided by the identity provider. The groups are mapped to roles in Snowflake, and the users are assigned the roles based on their group membership. This way, the identity provider remains the source of truth for user and group management, and Snowflake automatically reflects the changes without manual intervention. The other options are either incorrect or incomplete, as they involve using OAuth, which is a protocol for authorization, not authentication or user provisioning, and require additional configuration of authorization and resource servers.

Snowflake ARA-R01 SnowPro Advanced: Architect Recertification Exam Practice Test