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Snowflake Certification
COF-C03 Exam
Snowflake.COF-C03.v2026-06-01.q489 Dumps

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Question 286

When resizing a currently running virtual warehouse, what happens to in-progress queries?

A.In-progress queries will be cancelled.
B.Queries will continue running, using the new warehouse size.
C.Queries will continue running, using the current warehouse size.
D.Queries will be paused and automatically reprocessed using the new warehouse size.

Correct Answer: C

The correct answer is C. Queries will continue running, using the current warehouse size .
When a virtual warehouse is resized while it is running, the resize does not affect queries that are already in progress. Running queries continue using the warehouse resources that were available when they started. The new warehouse size applies to queries that start after the resize operation.
Why C is correct:
Snowflake does not cancel or restart existing queries when a warehouse is resized. In-progress queries continue executing with the current warehouse size.
Why the other options are incorrect:
A). Resizing a warehouse does not automatically cancel in-progress queries.
B). In-progress queries do not switch to the new warehouse size.
D). Queries are not paused and reprocessed after resizing.
Official Snowflake documentation reference:
Snowflake documentation explains that resizing a running warehouse affects only new queries and queued queries. Currently running queries continue to use the warehouse size that was in effect when they started.
Reference: Snowflake Documentation - Resizing a warehouse; Snowflake Documentation - Virtual warehouses; SnowPro Core Study Guide - Snowflake Account and Resource Management.

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Question 287

Queries are frequently run on very large tables and return only a few rows.
Use of which feature or service will optimize the query performance?

A.Automatic Clustering
B.The Search Optimization Service
C.The Query Acceleration Service
D.A Materialized View

Correct Answer: B

Search Optimization Service enhances performance for selective queries that return a small number of rows from large datasets. It avoids full table scans.
Reference:
Snowflake Docs: Search Optimization Service

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Question 288

Which virtual warehouse consideration can help lower compute resource credit consumption?

A.Setting up a multi-cluster virtual warehouse
B.Resizing the virtual warehouse to a larger size
C.Automating the virtual warehouse suspension and resumption settings
D.Increasing the maximum cluster count parameter for a multi-cluster virtual warehouse

Correct Answer: C

One key strategy to lower compute resource credit consumption in Snowflake is by automating the suspension and resumption of virtual warehouses. Virtual warehouses consume credits when they are running, and managing their operational times effectively can lead to significant cost savings.
A . Setting up a multi-cluster virtual warehouse increases parallelism and throughput but does not directly lower credit consumption. It is more about performance scaling than cost efficiency.
B . Resizing the virtual warehouse to a larger size increases the compute resources available for processing queries, which increases the credit consumption rate. This option does not help in lowering costs.
C . Automating the virtual warehouse suspension and resumption settings: This is a direct method to manage credit consumption efficiently. By automatically suspending a warehouse when it is not in use and resuming it when needed, you can avoid consuming credits during periods of inactivity. Snowflake allows warehouses to be configured to automatically suspend after a specified period of inactivity and to automatically resume when a query is submitted that requires the warehouse.
D . Increasing the maximum cluster count parameter for a multi-cluster virtual warehouse would potentially increase credit consumption by allowing more clusters to run simultaneously. It is used to scale up resources for performance, not to reduce costs.
Automating the operational times of virtual warehouses ensures that you only consume compute credits when the warehouse is actively being used for queries, thereby optimizing your Snowflake credit usage.

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Question 289

If a table was dropped and the DATA_RETENTION_TIME_IN_DAYS was set to 0, how can the data from the table be recovered?

A.By creating a failover group
B.By creating a Snowflake Support ticket
C.By running the UNDROP TABLE command
D.By running the CLONE ... BEFORE command

Correct Answer: B

The correct answer is B. By creating a Snowflake Support ticket .
If DATA_RETENTION_TIME_IN_DAYS = 0, Time Travel retention is disabled for the table. This means the table cannot be recovered using normal Time Travel operations such as UNDROP TABLE or CLONE ...
BEFORE.
Why B is correct:
After Time Travel retention is unavailable, recovery may only be possible through Snowflake Fail-safe for permanent tables. Fail-safe is not directly accessible by users. Recovery from Fail-safe requires contacting Snowflake Support.
Important qualification:
This assumes the dropped table is a permanent table and the data is still within Fail-safe. Temporary and transient tables do not have Fail-safe, so they cannot be recovered this way.
Why the other options are incorrect:
A). A failover group is used for replication and disaster recovery across accounts or regions. It does not recover a dropped table with no Time Travel retention.
C). UNDROP TABLE relies on Time Travel retention. With retention set to 0, this is not available.
D). CLONE ... BEFORE also relies on Time Travel. It cannot recover data when no retention period exists.
Official Snowflake documentation reference:
Snowflake documentation explains that Time Travel enables users to restore dropped objects within the retention period. Fail-safe is a separate recovery mechanism for permanent tables and is only available through Snowflake Support.
Reference: Snowflake Documentation - Time Travel; Fail-safe; UNDROP TABLE; SnowPro Core Study Guide - Data Protection and Governance.
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Question 290

What does the TableScan operator represent in the Query Profile?

A.The access to a single table
B.The access to data stored in stage objects
C.The list of values provided with the VALUES clause
D.The records generated using the TABLE (GENERATOR (...)) construct

Correct Answer: A

In the Query Profile of Snowflake, the TableScan operator represents the access to a single table. This operator indicates that the query execution involved reading data from a table stored in Snowflake. TableScan is a fundamental operation in query execution plans, showing how the database engine retrieves data directly from tables as part of processing a query.
References:
Snowflake Documentation: Understanding the Query Profile

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