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Free Snowflake ARA-R01 Exam Actual Questions

The questions for ARA-R01 were last updated On Jun 12, 2025

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Question No. 1

An Architect is implementing a CI/CD process. When attempting to clone a table from a production to a development environment, the cloning operation fails.

What could be causing this to happen?

AThe table is transient.

BThe table has a masking policy.

CThe retention time for the table is set to zero.

DTables cannot be cloned from a higher environment to a lower environment.

Show Answer

Correct Answer: B

Cloning a table with a masking policy can cause the cloning operation to fail because the masking policy is not automatically cloned with the table. This is due to the fact that the masking policy is considered a separate object with its own set of privileges1.

Reference

Snowflake Documentation on Cloning Considerations1.

Question No. 2

A company is designing its serving layer for data that is in cloud storage. Multiple terabytes of the data will be used for reporting. Some data does not have a clear use case but could be useful for experimental analysis. This experimentation data changes frequently and is sometimes wiped out and replaced completely in a few days.

The company wants to centralize access control, provide a single point of connection for the end-users, and maintain data governance.

What solution meets these requirements while MINIMIZING costs, administrative effort, and development overhead?

AImport the data used for reporting into a Snowflake schema with native tables. Then create external tables pointing to the cloud storage folders used for the experimentation data. Then create two different roles with grants to the different datasets to match the different user personas, and grant these roles to the corresponding users.

BImport all the data in cloud storage to be used for reporting into a Snowflake schema with native tables. Then create a role that has access to this schema and manage access to the data through that role.

CImport all the data in cloud storage to be used for reporting into a Snowflake schema with native tables. Then create two different roles with grants to the different datasets to match the different user personas, and grant these roles to the corresponding users.

DImport the data used for reporting into a Snowflake schema with native tables. Then create views that have SELECT commands pointing to the cloud storage files for the experimentation data. Then create two different roles to match the different user personas, and grant these roles to the corresponding users.

Show Answer

Correct Answer: A

The most cost-effective and administratively efficient solution is to use a combination of native and external tables. Native tables for reporting data ensure performance and governance, while external tables allow for flexibility with frequently changing experimental data. Creating roles with specific grants to datasets aligns with the principle of least privilege, centralizing access control and simplifying user management12.

Reference

* Snowflake Documentation on Optimizing Cost1.

* Snowflake Documentation on Controlling Cost2.

Question No. 3

An Architect needs to meet a company requirement to ingest files from the company's AWS storage accounts into the company's Snowflake Google Cloud Platform (GCP) account. How can the ingestion of these files into the company's Snowflake account be initiated? (Select TWO).

AConfigure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage.

BConfigure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 Glacier storage.

CCreate an AWS Lambda function to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage.

DConfigure AWS Simple Notification Service (SNS) to notify Snowpipe when new files have arrived in Amazon S3 storage.

EConfigure the client application to issue a COPY INTO <TABLE> command to Snowflake when new files have arrived in Amazon S3 Glacier storage.

Show Answer

Correct Answer: A, C

Snowpipe is a feature that enables continuous, near-real-time data ingestion from external sources into Snowflake tables. Snowpipe can ingest files from Amazon S3, Google Cloud Storage, or Azure Blob Storage into Snowflake tables on any cloud platform.Snowpipe can be triggered in two ways: by using the Snowpipe REST API or by using cloud notifications2

To ingest files from the company's AWS storage accounts into the company's Snowflake GCP account, the Architect can use either of these methods:

Configure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage. This method requires the client application to monitor the S3 buckets for new files and send a request to the Snowpipe REST API with the list of files to ingest.The client application must also handle authentication, error handling, and retry logic3

Create an AWS Lambda function to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage. This method leverages the AWS Lambda service to execute a function that calls the Snowpipe REST API whenever an S3 event notification is received.The AWS Lambda function must be configured with the appropriate permissions, triggers, and code to invoke the Snowpipe REST API4

The other options are not valid methods for triggering Snowpipe:

Configure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 Glacier storage. This option is not feasible because Snowpipe does not support ingesting files from Amazon S3 Glacier storage, which is a long-term archival storage service.Snowpipe only supports ingesting files from Amazon S3 standard storage classes5

Configure AWS Simple Notification Service (SNS) to notify Snowpipe when new files have arrived in Amazon S3 storage. This option is not applicable because Snowpipe does not support cloud notifications from AWS SNS.Snowpipe only supports cloud notifications from AWS SQS, Google Cloud Pub/Sub, or Azure Event Grid6

Configure the client application to issue a COPY INTO <TABLE> command to Snowflake when new files have arrived in Amazon S3 Glacier storage. This option is not relevant because it does not use Snowpipe, but rather the standard COPY command, which is a batch loading method.Moreover, the COPY command also does not support ingesting files from Amazon S3 Glacier storage7Reference:

1: SnowPro Advanced: Architect | Study Guide8

2: Snowflake Documentation | Snowpipe Overview9

3: Snowflake Documentation | Using the Snowpipe REST API10

4: Snowflake Documentation | Loading Data Using Snowpipe and AWS Lambda11

5: Snowflake Documentation | Supported File Formats and Compression for Staged Data Files12

6: Snowflake Documentation | Using Cloud Notifications to Trigger Snowpipe13

7: Snowflake Documentation | Loading Data Using COPY into a Table

:SnowPro Advanced: Architect | Study Guide

:Snowpipe Overview

:Using the Snowpipe REST API

:Loading Data Using Snowpipe and AWS Lambda

:Supported File Formats and Compression for Staged Data Files

:Using Cloud Notifications to Trigger Snowpipe

:Loading Data Using COPY into a Table

Question No. 4

A Developer is having a performance issue with a Snowflake query. The query receives up to 10 different values for one parameter and then performs an aggregation over the majority of a fact table. It then

joins against a smaller dimension table. This parameter value is selected by the different query users when they execute it during business hours. Both the fact and dimension tables are loaded with new data in an overnight import process.

On a Small or Medium-sized virtual warehouse, the query performs slowly. Performance is acceptable on a size Large or bigger warehouse. However, there is no budget to increase costs. The Developer

needs a recommendation that does not increase compute costs to run this query.

What should the Architect recommend?

ACreate a task that will run the 10 different variations of the query corresponding to the 10 different parameters before the users come in to work. The query results will then be cached and ready to respond quickly when the users re-issue the query.

BCreate a task that will run the 10 different variations of the query corresponding to the 10 different parameters before the users come in to work. The task will be scheduled to align with the users' working hours in order to allow the warehouse cache to be used.

CEnable the search optimization service on the table. When the users execute the query, the search optimization service will automatically adjust the query execution plan based on the frequently-used parameters.

DCreate a dedicated size Large warehouse for this particular set of queries. Create a new role that has USAGE permission on this warehouse and has the appropriate read permissions over the fact and dimension tables. Have users switch to this role and use this warehouse when they want to access this data.

Show Answer

Correct Answer: C

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.

Reference

* Snowflake Documentation on Search Optimization Service1.

Question No. 5

The Business Intelligence team reports that when some team members run queries for their dashboards in parallel with others, the query response time is getting significantly slower What can a Snowflake Architect do to identify what is occurring and troubleshoot this issue?

AOption A

BOption B

COption C

DOption D

Show Answer

Correct Answer: A

The image shows a SQL query that can be used to identify which queries are spilled to remote storage and suggests changing the warehouse parameters to address this issue. Spilling to remote storage occurs when the memory allocated to a warehouse is insufficient to process a query, and Snowflake uses disk or cloud storage as a temporary cache. This can significantly slow down the query performance and increase the cost. To troubleshoot this issue, a Snowflake Architect can run the query shown in the image to find out which queries are spilling, how much data they are spilling, and which warehouses they are using.Then, the architect can adjust the warehouse size, type, or scaling policy to provide enough memory for the queries and avoid spilling12.Reference:

Recognizing Disk Spilling

Managing the Kafka Connector