Free Practice Questions for Snowflake ARA-C01 Exam

Zero-copy cloning is a Snowflake feature that can be used to save quarter-end financial results for the previous six years. Zero-copy cloning allows creating a copy of a database, schema, table, or view without duplicating the data or metadata. The clone shares the same data files as the original object, but tracks any changes made to the clone or the original separately. Zero-copy cloning can be used to create snapshots of data at different points in time, such as quarter-end financial results, and preserve them for future analysis or comparison. Zero-copy cloning is fast, efficient, and does not consume any additional storage space unless the data is modified1.

Zero-Copy Cloning | Snowflake Documentation

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.

References =

•Snowflake Documentation on micro-partitions and data clustering2

•Community article on recognizing unsatisfactory pruning and improving it1

The best design to store and analyze large amounts of structured and semi-structured data for different business units and departments is to use a centralized Snowflake database for core business data, and use separate databases for departmental or project-specific data. This design allows for scalability, security, and cost efficiency by leveraging Snowflake’s features such as:

Database cloning: Cloning a database creates a zero-copy clone that shares the same data files as the original database, but can be modified independently. This reduces storage costs and enables fast and consistent data replication for different purposes.

Database sharing: Sharing a database allows granting secure and governed access to a subset of data in a database to other Snowflake accounts or consumers. This enables data collaboration and monetization across different business units or external partners.

Warehouse scaling: Scaling a warehouse allows adjusting the size and concurrency of a warehouse to match the performance and cost requirements of different workloads. This enables optimal resource utilization and flexibility for different data analysis needs. References: Snowflake Documentation: Database Cloning, Snowflake Documentation: Database Sharing, [Snowflake Documentation: Warehouse Scaling]

 According to the SnowPro Advanced: Architect documents and learning resources, the minimum object privileges required for the Snowpipe user to execute Snowpipe are:

OWNERSHIP on the named pipe. This privilege allows the Snowpipe user to create, modify, and drop the pipe object that defines the COPY statement for loading data from the stage to the table1.

USAGE and READ on the named stage. These privileges allow the Snowpipe user to access and read the data files from the stage that are loaded by Snowpipe2.

USAGE on the target database and schema. These privileges allow the Snowpipe user to access the database and schema that contain the target table3.

INSERT and SELECT on the target table. These privileges allow the Snowpipe user to insert data into the table and select data from the table4.

The other options are incorrect because they do not specify the minimum object privileges required for the Snowpipe user to execute Snowpipe. Option A is incorrect because it does not include the READ privilege on the named stage, which is required for the Snowpipe user to read the data files from the stage. Option C is incorrect because it does not include the OWNERSHIP privilege on the named pipe, which is required for the Snowpipe user to create, modify, and drop the pipe object. Option D is incorrect because it does not include the OWNERSHIP privilege on the named pipe or the READ privilege on the named stage, which are both required for the Snowpipe user to execute Snowpipe. References: CREATE PIPE | Snowflake Documentation, CREATE STAGE | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation, CREATE TABLE | Snowflake Documentation

In Snowflake, the characteristics of result set caches include persistence of data results for 24 hours (B), each use of persisted results resets the 24-hour retention period (C), and result set caches are not shared between different warehouses (F). The result set cache is specifically designed to avoid repeated execution of the same query within this timeframe, reducing computational overhead and speeding up query responses. These caches do not contribute to storage costs, and their retention period cannot be extended beyond the default duration nor up to 31 days, as might be misconstrued.

Enabling the search optimization service on the table can improve the performance of queries that have selective filtering criteria, which seems to be the case here. This service optimizes the execution of queries by creating a persistent data structure called a search access path, which allows some micro-partitions to be skipped during the scanning process. This can significantly speed up query performance without increasing compute costs1.

References

•Snowflake Documentation on Search Optimization Service1.

According to the Snowflake documentation, tasks are objects that enable scheduling and execution of SQL statements or JavaScript user-defined functions (UDFs) in Snowflake. Tasks can be used to automate data loading, transformation, and maintenance operations. Snowflake scripting is a feature that allows writing procedural logic using SQL statements and JavaScript UDFs. Snowflake scripting can be used to create complex workflows and orchestrate tasks. Therefore, the best option to automate the daily import of two files from an external stage into Snowflake, join and aggregate the data, and produce a final result set is to create a task using Snowflake scripting that will import the files using the COPY INTO command, and then call a UDF to perform the join and aggregation logic. The UDF can return a table or a variant value as the final result set. References:

Tasks

Snowflake Scripting

User-Defined Functions

The requirements state that the data analysts need to be able to create and modify database objects and load data, but should not be able to manage access for users outside of their role.

Option C:By making each schema within the database a managed access schema and having them owned by SYSADMIN, the ability to grant privileges on the schema's objects is strictly controlled. Managed access schemas limit the granting of privileges to the role specified as the owner of the schema, in this case, SYSADMIN. The ANALYST_ROLE can be granted the privileges necessary to create and modify objects within these schemas, satisfying the requirement for the analysts to perform their tasks without being able to extend access beyond their role.

This is the correct command to create a clone of the table Data as it was 5 minutes ago using cloning and Time Travel. Cloning is a feature that allows creating a copy of a database, schema, table, or view without duplicating the data or metadata. Time Travel is a feature that enables accessing historical data (i.e. data that has been changed or deleted) at any point within a defined period. To create a clone of a table at a point in time in the past, the syntax is:

CREATE TABLE CLONE AT (OFFSET => );

The OFFSET parameter specifies the time difference in seconds from the present time. A negative value indicates a point in the past. For example, -60*5 means 5 minutes ago. Alternatively, the TIMESTAMP parameter can be used to specify an exact timestamp in the past. The clone will contain the data as it existed in the source table at the specified point in time12.

Snowflake Documentation: Cloning Objects

Snowflake Documentation: Cloning Objects at a Point in Time in the Past

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.

References =

•Snowflake Documentation on creating schemas1

•Snowflake Documentation on configuring access control2

•Snowflake Documentation on understanding and viewing Fail-safe3