COF-R02 SnowPro Core Recertification Exam Questions and Answers

1 second

60 seconds

5 minutes

60 minutes

Tri-Secret Secure

Time Travel

Fail-safe

Data encryption

External stages

The data provider in Azure Central Canada can create a direct share to AWS Asia Pacific, if they are both in the same organization.

The data consumer and data provider can form a Data Exchange within the same organization to create a share from Azure Central Canada to AWS Asia Pacific.

The data provider uses the GET DATA workflow in the Snowflake Data Marketplace to create a share between Azure Central Canada and AWS Asia Pacific.

The data provider must replicate the database to a secondary account in AWS Asia Pacific within the same organization then create a share to the data consumer ' s account.

Querying data-related objects that were created within the past 365 days

Restoring data-related objects that have been deleted within the past 90 days

Conducting point-in-time analysis for Bl reporting

Analyzing data usage/manipulation over all periods of time

SnowSQL

Snowflake classic web interface (Ul)

Snowsight

.NET driver

Database stage

External stage

Table stage

User stage

True

False

ROLES

POLICY_REFERENCES

QUERY_HISTORY

RESOURCE_MONIT ORS

ACCESS_HISTORY

The primary cluster in the virtual warehouse

The entire virtual warehouse

The database in which the virtual warehouse resides

The Queries currently being run on the virtual warehouse

Masking policy

Stored procedure

Task

External table

Snowflake parameters

Micro-partitions

Query history

Persisted query results

Standard and secure view results

True

False

UTF-8

UTF-16

ISO S859-1

ANSI_X3.A

True

False

True

False

They happen approximately weekly

They roll up and release approximately monthly, but customers can request early release application

During a release, new customer requests/queries/connections transparently move over to the newer

version

A customer is assigned a 30 minute window (that can be moved anytime within a week) during which the

system will be unavailable and customer is upgraded

True

False

True

False

Growth of storage and compute are tightly coupled together

Storage expands without the requirement to add more compute

Compute can be scaled up or down without the requirement to add more storage

Multiple compute clusters can access stored data without contention

True

False

Number of users

Warehouse size

Amount of data processed

# of clusters for the Warehouse

True

False

True

False

The Pipe load history is reset to empty

The REFRESH parameter is set to TRUE

Previously loaded files will be ignored

All of the above

JDBC

SnowSQL

Snowflake Web Interface (UI)

ODBC

Python

D18912E1457D5D1DDCBD40AB3BF70D5D

60 minutes

24 hours

14 days

30 days

1 year

The validation_mode option is used when creating an Internal Stage

validation_mode=return_all_errors is a parameter of the copy command

The validation_mode option will validate data to be loaded by the copy statement while completing the load and will return the rows that could not be loaded without error

The validation_mode option will validate data to be loaded by the copy statement without completing the load and will return possible errors

4

16

32

128

Configure the Maximum Clusters setting to “Auto-Scale”

Set the Warehouse type to “Auto”

Set the Minimum Clusters and Maximum Clusters settings to the same value

Set the Minimum Clusters and Maximum Clusters settings to the different values

True

False

True

False

To accommodate more queries

To accommodate more users

To accommodate fluctuations in workload

To accommodate a more complex workload

True

False

True

False

Temporary

Translent

Provisional

Permanent

Custom

Economy

Optimized

Standard

True

False

Per-second/per Warehouse size

Per-second/per-core granularity

Number of Pipes in account

Total storage bucket size

Data can be filtered by an optional where clause

Incoming data can be joined with other tables

Columns can be reordered

Columns can be omitted

Row level access can be defined

Okta Verify

Duo Mobile

Microsoft Authenticator

Google Authenticator

Pipes

Streams

Tasks

Procedures

Possibly, if the warehouse is resized to a smaller size and the cache no longer fits.

Yes. because the compute resource is replaced in its entirety with a new compute resource.

No. because the size of the cache is independent from the warehouse size

Yes. became the new compute resource will no longer have access to the cache encryption key

30 Days

60 Days

90 Days

365 Days

STRUCT

OBJECT

BINARY

ARRAY

CLOB

Query against the result set cache

Query against a virtual warehouse cache

Query against the most-recently created micro-partition

Query against the metadata excite

SCIM

Federated authentication

TLS 1.2

Key-pair authentication

OAuth

OCSP authentication

A single join node uses more than 50% of the query time

Partitions scanned is equal to partitions total

An AggregateOperacor node is present

The query is spilling to remote storage

Variant

Object

Geometry

Geography

Micro-partitions cannot overlap in their range of values

Micro-partitions are immutable objects that support the use of Time Travel.

Micro-partitions can reduce the amount of I/O from object storage to virtual warehouses

Rows are automatically stored in sorted order within micro-partitions

Micro-partitions can be defined on a schema-by-schema basis

True

False

Compute Credits = 50 Credits Cloud Services = 10

Compute Credits = 80 Credits Cloud Services = 5

Compute Credits = 10 Credits Cloud Services = 9

Compute Credits = 120 Credits Cloud Services = 10

Compute Credits = 200 Credits Cloud Services = 26

ORC

XML

Avro

Parquet

JSON

Users

Tables

Databases

Internal Stages

When increasing the size of an active warehouse the compute resource for all running and queued queries on the warehouse are affected

When reducing the size of a warehouse the compute resources are removed only when they are no longer being used to execute any current statements.

The warehouse will be suspended while the new compute resource is provisioned and will resume automatically once provisioning is complete.

Users who are trying to use the warehouse will receive an error message until the resizing is complete

SELECT LAST_SUCCESS_LOGIN, LOGIN_NAME

FROM ACCOUNT_USAGE.USERS;

SELECT EVENT_TIMESTAMP, USER_NAME

FROM table(information_schema.login_history_by_user())

SELECT EVENT_TIMESTAMP, USER_NAME

FROM ACCOUNT_USAGE.ACCESS_HISTORY;

SELECT EVENT_TIMESTAMP, USER_NAME

FROM ACCOUNT_USAGE.LOGIN_HISTORY;

LOAD

copy

GET

PUT

Data sharing within a specific region

Query result retrieval

Database replication

Loading data into Snowflake

Yes, because a table owner has full control and can unset masking policies.

Yes, because masking policies only apply to cloned tables.

No, because masking policies must always reference specific access roles.

No, because ownership of a table does not include the ability to change masking policies

ALLOW RESIZE ON WAREHOUSE MKTG__WH TO USER MKTG__LEAD;

GRANT MODIFY ON WAREHOUSE MKTG WH TO ROLE MARKETING;

GRANT MODIFY ON WAREHOUSE MKTG__WH TO USER MKTG__LEAD;

GRANT OPERATE ON WAREHOUSE MKTG WH TO ROLE MARKETING;

Compute

Data storage

Cloud services

Cloud provider

Configure the maximum clusters setting to " Maximum. "

Turn on the additional clusters manually after starting the warehouse.

Set the minimum Clusters and maximum Clusters settings to the same value.

Set the minimum clusters and maximum clusters settings to different values.

Use multi-clustered warehousing to scale out warehouse capacity.

Scale up the warehouse size to allow Queries to execute faster.

Stop and start the warehouse to clear the queued queries

Migrate some queries to a new warehouse to reduce load

Limit user access to the warehouse so fewer queries are run against it.

CSV

JSON

Parquet

XML

A compressed file size greater than 100 MB, and up to 250 MB

A compressed file size greater than 100 GB, and up to 250 GB

A compressed file size greater than 10 MB, and up to 100 MB

A compressed file size greater than 1 GB, and up to 2 GB

A task can be called using a CALL statement to run a set of predefined SQL commands.

A task allows a user to execute a single SQL statement/command using a predefined schedule.

A task allows a user to execute a set of SQL commands on a predefined schedule.

A task can be executed using a SELECT statement to run a predefined SQL command.

The USERS view in ACCOUNT_USAGE

The LOGIN_HISTORY view in ACCOUNT_USAGE

The ACCESS_HISTORY view in ACCOUNT_USAGE

The SESSIONS view in ACCOUNT_USAGE

Data expires from Time Travel

Data expires from Fail-safe

Data is deleted from a table

Data is truncated from a table

The database ACCOUNTADMIN must define the clustering methodology for each Snowflake table.

Clustering is the way data is grouped together and stored within Snowflake micro-partitions.

The clustering key must be included in the COPY command when loading data into Snowflake.

Clustering can be disabled within a Snowflake account.

INSERT

PUT

GET

COPY

10-50 MB

100-250 MB

300-500 MB

1000-1500 MB

Use Time Travel, as long as DATA_RETENTION_TIME_IN_DAYS was set to at least 3 days.

The transient table version cannot be retrieved after 24 hours.

Contact Snowflake Support to have the data retrieved from Fail-safe storage.

Use the FAIL_SAFE parameter for Time Travel to retrieve the data from Fail-safe storage.

SHOW STORAGE BY TABLE;

SHOW TABLES;

Information Schema - > TABLE_HISTORY

Information Schema - > TABLE_FUNCTION

Information Schema - > TABLE_STORAGE_METRICS

The cloned views and the stored procedures will reference the cloned tables in the cloned database.

An error will occur, as views with qualified references cannot be cloned.

An error will occur, as stored objects cannot be cloned.

The stored procedures and views will refer to tables in the source database.

Pre-signed URL

Scoped URL

Signed URL

File URL

Identifying queries that will likely run very slowly before executing them

Locating queries that consume a high amount of credits

Identifying logical issues with the queries

Identifying inefficient micro-partition pruning

Data spilling to a local or remote disk

Roles

Databases

Warehouses

Users

Accounts

Fail-safe makes data available up to 1 day, recoverable by user operations.

Fail-safe makes data available for 7 days, recoverable by user operations.

Fail-safe makes data available for 7 days, recoverable only by Snowflake Support.

Fail-safe makes data available up to 1 day, recoverable only by Snowflake Support.

There is no Fail-safe period for these tables.

1 day

7 days

31 days

90 days

4 minutes

10 minutes

14 minutes

24 minutes

Include the SQL statements in the body of the task CREATE TASK mytask .. AS INSERT INTO target1 SELECT .. FROM stream_s1 WHERE .. INSERT INTO target2 SELECT .. FROM stream_s1

WHERE ..

A stored procedure can have only one DML statement per stored procedure invocation and therefore the user should sequence stored procedure calls in the task definition CREATE TASK mytask .... AS

call stored_proc1(); call stored_proc2();

Use a stored procedure executing multiple SQL statements and invoke the stored procedure from the task. CREATE TASK mytask .... AS call stored_proc_multiple_statements_inside();

Create a task for each SQL statement (e.g. resulting in task1, task2, etc.) and string the series of SQL statements by having a control task calling task1, task2, etc. sequentially.

Query execution

Data loading

Time Travel data

Security

Authentication and access control

30 Days

60 Days

90 Days

365 Days.

The data is cloned into a historical object.

The data moves to Fail-safe

Time Travel on the historical data is dropped.

The object containing the historical data is dropped.

Database replication and failover

Automated index management

Customer managed keys (Tri-secret secure)

Extended time travel

Native support for geospatial data

When after 2-3 consecutive checks the system determines that the load on the most-loaded cluster could be redistributed.

When after 5-6 consecutive checks the system determines that the load on the most-loaded cluster could be redistributed.

When after 5-6 consecutive checks the system determines that the load on the least-loaded cluster could be redistributed.

When after 2-3 consecutive checks the system determines that the load on the least-loaded cluster could be redistributed.

Standard

Enterprise

Business Critical

Virtual Private Snowflake

External Tokenization

External Tables

Materialized Views

User-Defined Table Functions (UDTF)

Bytes sent over network

Percentage scanned from cache

Partitions total

Bytes spilled to local storage

Partitions scanned

The number of queries executed

The number of active users assigned to the warehouse

The size of the virtual warehouse

The length of time the warehouse is running

The duration of the queries that are executed

Tables

Named File Formats

Schemas

Shares

Databases

Users

True

False

A Schema may contain one or more Databases

A Database may contain one or more Schemas

A Schema is a logical grouping of Database Objects

Each Schema is contained within a Warehouse

Auto-suspend

Auto-resume

Local SSD size

User count

COPY INTO @stage

EXPORT TO @stage

INSERT INTO @stage

EXPORT_TO_STAGE(stage = > @Wage, select = > ' select * from t1);

True

False

True

False