COF-C02 Practice Questions

A.  

Bytes scanned

B.  

Partitions scanned

C.  

Bytes spilled to local storage

D.  

Bytes spilled to remote storage

E.  

Percentage scanned from cache

A.  

Manually re-cluster the table regularly.

B.  

Choose one high cardinality column as the clustering key.

C.  

Use the column that is most-frequently used in query select clauses as the clustering key.

D.  

Assess the average table depth to identify how clustering is impacting the query.

A.  

INSERT

B.  

JOIN

C.  

RENAME

D.  

ALTER

A.  

Standard Edition

B.  

Enterprise Edition

C.  

Business Critical Edition

D.  

Virtual Private Snowflake Edition

A.  

ARRAY

B.  

BLOB

C.  

CLOB

D.  

JSON

E.  

VARIANT

A.  

DATA_RETENTION_TIME_IN_DAYS

B.  

MAX_DATA_EXTENSION_TIME_IN_DAYS

C.  

MIN_DATA_RETENTION_TIME_IN_DAYS

D.  

MAX CONCURRENCY LEVEL

A.  

To profile how many times a particular query was executed and analyze its u^age statistics over time.

B.  

To profile a particular query to understand the mechanics of the query, its behavior, and performance.

C.  

To profile the user and/or executing role of a query and all privileges and policies applied on the objects within the query.

D.  

To profile which queries are running in each warehouse and identify proper warehouse utilization and sizing for better performance and cost balancing.

A.  

Operator tree

B.  

Table pruning

C.  

Most expensive nodes

D.  

Nodes by execution time

A.  

All child objects will retain data for the new retention period.

B.  

All child objects that do not have an explicit retention period will automatically inherit the new retention period.

C.  

All child objects with an explicit retention period will be overridden with the new retention period.

D.  

All explicit child object retention periods will remain unchanged.

A.  

OAuth

B.  

Network policies

C.  

Single Sign-On (SSO)

D.  

Multi-Factor Authentication (MFA)

A.  

Flatten the data and store it in structured data types in a flattened table. Query the table.

B.  

Store the data in a table with a variant data type. Query the table.

C.  

Store the data in a table with a vai : ant data type and include STRIP_NULL_VALUES while loading the table. Query the table.

D.  

Store the data in an external stage and create views on top of it. Query the views.

A.  

Temporary tables

B.  

Permanent tables

C.  

Transient tables

D.  

External tables

E.  

User-Defined Table Functions (UDTFs)

A.  

Views

B.  

Materialized views

C.  

Tables

D.  

External tables

E.  

Future grants

A.  

Network policy

B.  

End-to-end encryption

C.  

Multi-Factor Authentication (MFA)

D.  

Role-Based Access Control (RBAC)

A.  

RETURN_-1_R0WS

B.  

RETURN_n_ROWS

C.  

RETURN_ERRORS

D.  

RETURN ALL ERRORS

A.  

Load the data into a CSV file.

B.  

Load the data into a relational table.

C.  

Use the VALlDATlON_MODE - SQL statement.

D.  

Use the validation mode = return rows statement.

A.  

USAGE_VIEWER

B.  

GOVERNANCE_VIEWER

C.  

OBJECT_VIEWER

D.  

SECURITY_VIEWER

A.  

Casts the values of the flattened data

B.  

Extracts the path of the flattened data

C.  

Joins information outside the object with the flattened data

D.  

Retrieves a single instance of a repeating element in the flattened data

A.  

Use COPY INTO < external stage > followed by a GET command to download the file.

B.  

Use COPY INTO < internal stage > followed by a put command to download the file.

C.  

Use COPY INTO < internal stage > with SINGLE = TRUE followed by a GET command to download the file.

D.  

Use COPY INTO < external stage > with SINGLE = TRUE followed by a PUT command to download the file.

A.  

A Query Profile can help users right-size virtual warehouses.

B.  

A Query Profile defines the hardware specifications of the virtual warehouse.

C.  

A Query Profile can help determine the number of virtual warehouses available.

D.  

A Query Profile automatically scales the virtual warehouse based on the query complexity.