FreeQAs
 Request Exam  Contact
  • Home
  • View All Exams
  • New QA's
  • Upload
PRACTICE EXAMS:
  • Oracle
  • Fortinet
  • Juniper
  • Microsoft
  • Cisco
  • Citrix
  • CompTIA
  • VMware
  • ISC
  • SAP
  • EMC
  • PMI
  • HP
  • Salesforce
  • Other
  • Oracle
    Oracle
  • Fortinet
    Fortinet
  • Juniper
    Juniper
  • Microsoft
    Microsoft
  • Cisco
    Cisco
  • Citrix
    Citrix
  • CompTIA
    CompTIA
  • VMware
    VMware
  • ISC
    ISC
  • SAP
    SAP
  • EMC
    EMC
  • PMI
    PMI
  • HP
    HP
  • Salesforce
    Salesforce
  1. Home
  2. Snowflake Certification
  3. COF-C03 Exam
  4. Snowflake.COF-C03.v2026-06-01.q489 Dumps
  • ««
  • «
  • …
  • 47
  • 48
  • 49
  • 50
  • 51
  • 52
  • 53
  • 54
  • 55
  • 56
  • …
  • »
  • »»
Download Now

Question 251

While clustering a table, columns with which data types can be used as clustering keys? (Select TWO).

Correct Answer: A,C
A clustering key can be defined when a table is created by appending a CLUSTER Where each clustering key consists of one or more table columns/expressions, which can be of any data type, except GEOGRAPHY, VARIANT, OBJECT, or ARRAY https://docs.snowflake.com/en/user-guide/tables-clustering-keys
insert code

Question 252

When is a DataFrame processed in Snowpark?

Correct Answer: B
The correct answer is B. When a collect() action is triggered .
Snowpark DataFrames are evaluated lazily. Creating a DataFrame or applying transformations does not immediately execute the query in Snowflake. Execution happens only when an action is called.
Why B is correct:
collect() is an action. When it is called, Snowpark sends the accumulated DataFrame logic to Snowflake for execution and returns the results to the client.
Example:
df = session.table( " CUSTOMERS " )
filtered_df = df.filter(df[ " REGION " ] == " WEST " )
# Query is processed when this action runs:
rows = filtered_df.collect()
Why the other options are incorrect:
A). Creating a DataFrame builds a logical plan but does not process the data.
C). Warehouse memory availability is not what triggers DataFrame execution.
D). Applying a transformation adds to the logical plan, but it does not execute the plan.
Official Snowflake documentation reference:
Snowflake documentation describes Snowpark DataFrames as lazily evaluated. Transformations are not executed until an action, such as collect(), is called.
Reference: Snowflake Documentation - Snowpark DataFrames; Snowflake Documentation - Snowpark actions and transformations; SnowPro Core Study Guide - SQL and Snowflake Objects.
insert code

Question 253

A Snowflake Practitioner manages a database called SALES_DB. This database has a PUBLIC schema and an ORDERS table that is updated frequently. The database has a data retention period of 7 days. On November 16, 2025, at 3:00 PM, the Practitioner accidentally ran a DELETE command that removed all records from the ORDERS table. Which statement will recover all deleted records?

Correct Answer: B
To recover data deleted at 3:00 PM, the clone should be created from a point immediately before the delete statement. BEFORE (TIMESTAMP = > ' 2025-11-16 15:00:00 ' ) returns the table state before that timestamp.
Why B is correct:
Snowflake Time Travel supports cloning a table at or before a specific timestamp within the retention period.
Reference: Snowflake Documentation - Time Travel; CREATE TABLE ... CLONE; AT | BEFORE.
==
insert code

Question 254

Which command will consume credits from a virtual warehouse?

Correct Answer: A,B,D
The correct answers are A, B, and D , assuming SNOWFLAKE is a table or queryable object.
Important exam-note correction:
This question is written as a single-answer question, but more than one listed command can consume virtual warehouse credits. Any SELECT query that scans or processes table data generally requires a running virtual warehouse and can consume warehouse credits.
Why A, B, and D are correct:
These are SELECT statements against a table-like object. Query execution that scans or aggregates data uses compute resources from a virtual warehouse.
Examples:
SELECT MAX(UUID) FROM SNOWFLAKE;
SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY UUID;
SELECT COUNT(*) FROM SNOWFLAKE;
These involve SQL query processing and therefore require warehouse compute unless the result is fully served from cache.
Why C is incorrect:
SHOW commands are metadata commands handled by Snowflake's cloud services layer. They do not require an active virtual warehouse in the same way table-scanning SELECT queries do.
Official Snowflake documentation reference:
Snowflake documentation explains that virtual warehouses provide the compute resources required to execute SQL queries and DML operations. Metadata commands such as SHOW are handled by the cloud services layer.
Reference: Snowflake Documentation - Virtual warehouses; Snowflake Documentation - SHOW commands; SnowPro Core Study Guide - Snowflake Architecture and Resource Management.
insert code

Question 255

A user is preparing to load data from an external stage
Which practice will provide the MOST efficient loading performance?

Correct Answer: A
Organizing files into logical paths can significantly improve the efficiency of data loading from an external stage.This practice helps in managing and locating files easily, which can be particularly beneficial when dealing with large datasets or complex directory structures1.
insert code
  • ««
  • «
  • …
  • 47
  • 48
  • 49
  • 50
  • 51
  • 52
  • 53
  • 54
  • 55
  • 56
  • …
  • »
  • »»
[×]

Download PDF File

Enter your email address to download Snowflake.COF-C03.v2026-06-01.q489 Dumps

Email:

FreeQAs

Our website provides the Largest and the most Latest vendors Certification Exam materials around the world.

Using dumps we provide to Pass the Exam, we has the Valid Dumps with passing guranteed just which you need.

  • DMCA
  • About
  • Contact Us
  • Privacy Policy
  • Terms & Conditions
©2026 FreeQAs

www.freeqas.com materials do not contain actual questions and answers from Cisco's certification exams.