COF-R02 Questions and Answers

Load files that are approximately 25 MB or smaller.

Remove all dates and timestamps.

Load files that are approximately 100-250 MB (or larger)

Avoid using embedded characters such as commas for numeric data types

Remove semi-structured data types

Compute layer

Storage layer

Cloud infrastructure layer

Cloud services layer

Data is hashed by the cluster key to facilitate fast searches for common data values

Larger micro-partitions are created for common data values to reduce the number of partitions that must be scanned

Smaller micro-partitions are created for common data values to allow for more parallelism

Data may be colocated by the cluster key within the micro-partitions to improve pruning performance

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.

Credits are billed per-minute with a 60-minute minimum

Credits are used to pay for cloud data storage usage

Credits are consumed based on the number of credits billed for each hour that a warehouse runs

Credits are consumed based on the warehouse size and the time the warehouse is running

Automatically creates a File Format object

Automatically uses the last Stage created

Automatically compresses files using Gzip

Automatically encrypts files

True

False

Schema

View

Internal stage

Table

User

Role

Custom Edition

Virtual Private Snowflake

Business Critical Edition

Standard Edition

Enterprise Edition

Modify the columns in the underlying table

Use the ALTER VIEW command to update the view

Recreate the view with the required changes

Materialize the view to perform the changes

VIEWS_HISTORY

OBJECT_HISTORY

ACCESS_HISTORY

LOGIN_HISTORY

In the metadata of the target table for 14 days

In the metadata of the pipe for 14 days

In the metadata of the target table for 64 days

In the metadata of the pipe for 64 days

True

False

Columnar shared nothing

Shared disk

Multi-cluster, shared data

Cloud-native shared memory

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

The complexity of each query

The CONCURRENT_QUERY_UMIT parameter set on the Snowflake account

The size of the data required for each query

The tool that s executing the query

On-premise availability

Simplicity

Open source based

Concurrency

Performance

UPSERT

MERGE

UPDATE

TRUNCATE TABLE

True

False

Tables

Schemas

Databases

Stages

Columns can be aggregated

Columns can be joined with an existing table

Columns can be reordered

Columns can be omitted

Data can be loaded without the need to spin up a virtual warehouse

ORC

XML

Avro

Parquet

JSON

Standard

Premium

Enterprise

Business Critical

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

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;

A read-only copy of the cloned tables is stored.

The replication will not be successful.

The physical data is replicated

Additional costs for storage are charged to a secondary account

Metadata pointers to cloned tables are replicated

Pre-signed URL

Scoped URL

Signed URL

File URL

select src:dealership from car_sales;

select src.dealership from car_sales;

select src:Dealership from car_sales;

select dealership from car_sales;

Aim to produce data files that are between 100 MB and 250 MB in size, compressed.

Load data from files in a cloud storage service in a different region or cloud platform from the service or region containing the Snowflake account, to save on cost.

Enclose fields that contain delimiter characters in single or double quotes.

Split large files into a greater number of smaller files to distribute the load among the compute resources in an active warehouse.

When planning which warehouse(s) to use for data loading, start with the largest warehouse possible.

Partition the staged data into large folders with random paths, allowing Snowflake to determine the best way to load each file.

GeoJSON

Array

XML

Object

BLOB

Organize files into logical paths

Store the files on the external stage to ensure caching is maintained

Use pattern matching for regular expression execution

Load the data in one large file

Reader

Consumer

Vendor

Standard

Personalized

C:\Users\Admin\Desktop\Data\Odt data\Untitled.jpg

C:\Users\Admin\Desktop\Data\Odt data\Untitled.jpg

C:\Users\Admin\Desktop\Data\Odt data\Untitled.jpg

C:\Users\Admin\Desktop\Data\Odt data\Untitled.jpg

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.

Custom

Economy

Optimized

Standard

Role

Schema

User

Database

Account

Tables

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.

When dropping an external stage, the files are not removed and only the stage is dropped

When dropping an external stage, both the stage and the files within the stage are removed

When dropping an internal stage, the files are deleted with the stage and the files are recoverable

When dropping an internal stage, the files are deleted with the stage and the files are not recoverable

When dropping an internal stage, only selected files are deleted with the stage and are not recoverable

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

Micro-partitions

Clustering keys

Key partitions

Clustered partitions

The user has the appropriate privileges on the objects associated with the query

Micro-partitions have been reclustered since the query was last run

The new query is run using the same virtual warehouse as the previous query

The query includes a User Defined Function (UDF)

The query has been run within 24 hours of the previously-run query