Free Access to Snowflake.ARA-C01.v2026-04-11.q236 with Valid Practice Test (Page 11)

Question 46

How do Snowflake databases that are created from shares differ from standard databases that are not created from shares? (Choose three.)

A.Shared databases are read-only.
B.Shared databases must be refreshed in order for new data to be visible.
C.Shared databases cannot be cloned.
D.Shared databases are not supported by Time Travel.
E.Shared databases will have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share.
F.Shared databases can also be created as transient databases.

Correct Answer: A,C,D

According to the SnowPro Advanced: Architect documents and learning resources, the ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares are:
* Shared databases are read-only. This means that the data consumers who access the shared databases cannot modify or delete the data or the objects in the databases. The data providers who share the databases have full control over the data and the objects, and can grant or revoke privileges on them1.
* Shared databases cannot be cloned. This means that the data consumers who access the shared databases cannot create a copy of the databases or the objects in the databases. The data providers who share the databases can clone the databases or the objects, but the clones are not automatically shared2.
* Shared databases are not supported by Time Travel. This means that the data consumers who access the shared databases cannot use the AS OF clause to query historical data or restore deleted data. The data providers who share the databases can use Time Travel on the databases or the objects, but the historical data is not visible to the data consumers3.
The other options are incorrect because they are not ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares. Option B is incorrect because shared databases do not need to be refreshed in order for new data to be visible. The data consumers who access the shared databases can see the latest data as soon as the data providers update the data1. Option E is incorrect because shared databases will not have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share. The data consumers who access the shared databases can only see the objects that the data providers grant to the share, and the PUBLIC and INFORMATION_SCHEMA schemas are not granted by default4. Option F is incorrect because shared databases cannot be created as transient databases. Transient databases are databases that do not support Time Travel or Fail-safe, and can be dropped without affecting the retention period of the data. Shared databases are always created as permanent databases, regardless of the type of the source database5. References: Introduction to Secure Data Sharing | Snowflake Documentation, Cloning Objects | Snowflake Documentation, Time Travel | Snowflake Documentation, Working with Shares | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation

Question 47

A company is storing large numbers of small JSON files (ranging from 1-4 bytes) that are received from IoT devices and sent to a cloud provider. In any given hour, 100,000 files are added to the cloud provider.
What is the MOST cost-effective way to bring this data into a Snowflake table?

A.An external table
B.A pipe
C.A stream
D.A copy command at regular intervals

Correct Answer: B

Explanation
* A pipe is a Snowflake object that continuously loads data from files in a stage (internal or external) into a table. A pipe can be configured to use auto-ingest, which means that Snowflake automatically detects new or modified files in the stage and loads them into the table without any manual intervention1.
* A pipe is the most cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it minimizes the number of COPY commands executed and the number of micro-partitions created. A pipe can use file aggregation, which means that it can combine multiple small files into a single larger file before loading them into the table. This reduces the load time and the storage cost of the data2.
* An external table is a Snowflake object that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table does not store the data in Snowflake, but only provides a view of the data for querying. An external table is not a cost-effective way to bring data into a Snowflake table, because it does not support file aggregation, and it requires additional network bandwidth and compute resources to query the external data3.
* A stream is a Snowflake object that records the history of changes (inserts, updates, and deletes) made to a table. A stream can be used to consume the changes from a table and apply them to another table or a task. A stream is not a way to bring data into a Snowflake table, but a way to process the data after it is loaded into a table4.
* A copy command is a Snowflake command that loads data from files in a stage into a table. A copy command can be executed manually or scheduled using a task. A copy command is not a cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it does not support file aggregation, and it may create many micro-partitions that increase the storage cost of the data5.
References: : Pipes : Loading Data Using Snowpipe : External Tables : Streams : COPY INTO <table>

Question 48

An Architect plans to stream data using the Snowflake Connector for Kafka in Snowpipe.
What setting will optimize costs?

A.Set buffer.flush.time = 1.
B.Set buffer.count.records = 1.
C.Set buffer.size.bytes = 10 MB.
D.Maximize the number of micro-partitions.

Question 49

An Architect is troubleshooting a query with poor performance using the QUERY_HIST0RY function. The Architect observes that the COMPILATIONJHME is greater than the EXECUTIONJTIME.
What is the reason for this?

A.The query is processing a very large dataset.
B.The query has overly complex logic.
C.The query is queued for execution.
D.The query is reading from remote storage.

Question 50

SNOWPIPE_AUTO_INGEST is supported for external stages only

A.FALSE
B.TRUE

Question 46

Question 47

Question 48

Question 49

Question 50

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