[Jun 25, 2024] Valid DEA-C01 Test Answers Full-length Practice Certification Exams [Q40-Q62]

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[Jun 25, 2024] Valid DEA-C01 Test Answers Full-length Practice Certification Exams

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QUESTION 40
Which methods will trigger an action that will evaluate a DataFrame? (Select TWO)

DataFrame.random_split ( )

DataFrame.collect ()

DateFrame.select ()

DataFrame.col ( )

DataFrame.show ()

QUESTION 41
Snowflake web interface can be used to create users with no passwords or remove passwords from existing users?

TRUE

FALSE

QUESTION 42
Which of the below concepts/functions helps while implementing advanced Column-level Security?

CURRENT_ROLE

INVOKER_ROLE

Role Hierarchy

CURRENT_CLIENT

QUESTION 43
A company is using Snowpipe to bring in millions of rows every day of Change Data Capture (CDC) into a Snowflake staging table on a real-time basis The CDC needs to get processedand combined with other data in Snowflake and land in a final table as part of the full data pipeline.
How can a Data engineer MOST efficiently process the incoming CDC on an ongoing basis?

Transform the data during the data load with Snowpipe by modifying the related copy into statement to include transformation steps such as case statements andJOIN’S.

Schedule a task that dynamically retrieves the last time the task was run from information_schema-rask_hiSwOry and use that timestamp to process the delta of the new rows since the last time the task was run.

Create a stream on the staging table and schedule a task that transforms data from the stream only when the stream has data.

Use a create ok replace table as statement that references the staging table and includes all the transformation SQL. Use a task to run the full create or replace table as statement on a scheduled basis

QUESTION 44
A Data Engineer is working on a Snowflake deployment in AWS eu-west-1 (Ireland). The Engineer is planning to load data from staged files into target tables using the copy into command Which sources are valid? (Select THREE)

Internal stage on GCP us-central1 (Iowa)

Internal stage on AWS eu-central-1 (Frankfurt)

External stage on GCP us-central1 (Iowa)

External stage in an Amazon S3 bucket on AWS eu-west-1 (Ireland)

External stage in an Amazon S3 bucket on AWS eu-central 1 (Frankfurt)

SSO attached to an Amazon EC2 instance on AWS eu-west-1 (Ireland)

QUESTION 45
You as Data engineer might want to consider disabling auto-suspend for a warehouse if?

You have a low, fluctuating workload for the warehouse.

You have a heavy, steady workload for the warehouse.

You require the warehouse to be available with delay.

You require the warehouse to be available with no delay or lag time.

QUESTION 46
To advance the offset of a stream to the current table version without consuming the change data in a DML operation, which of the following operations can be done by Data Engineer? [Select 2]

using the CREATE OR REPLACE STREAM syntax, Recreate the STREAM

Insert the current change data into a temporary table. In the INSERT statement, query the stream but include a WHERE clause that filters out all of the change data (e.g. WHERE 0 = 1).

A stream advances the offset only when it is used in a DML transaction, so none of the options works without consuming the change data of table.

Delete the offset using STREAM properties SYSTEM$RESET_OFFSET( <stream_id> )

Explanation
When created, a stream logically takes an initial snapshot of every row in the source object (e.g. ta-ble, external table, or the underlying tables for a view) by initializing a point in time (called an off-set) as the current transactional version of the object. The change tracking system utilized by the stream then records information about the DML changes after this snapshot was taken. Change rec-ords provide thestate of a row before and after the change. Change information mirrors the column structure of the tracked source object and includes additional metadata columns that describe each change event.
Note that a stream itself does not contain any table data. A stream only stores an offset for the source object and returns CDC records by leveraging the versioning history for the source object.
A new table version is created whenever a transaction that includes one or more DML statements is committed to the table.
In the transaction history for a table, a stream offset is located between two table versions. Query-ing a stream returns the changes caused by transactions committed after the offset and at or before the current time.
Multiple queries can independently consume the same change data from a stream without changing the offset.
A stream advances the offset only when it is used in a DML transaction. This behavior applies to both explicit and autocommit transactions. (By default, when a DML statement is execut-ed, an autocommit transaction is implicitly started and the transaction is committed at the comple-tion of the statement. This behavior is controlled with the AUTOCOMMIT parameter.) Querying a stream alone does not advance its offset, even within an explicit transaction; the stream contents must be consumed in a DML statement.
To advance the offset of a stream to the current table version without consuming the change data in a DML operation, complete either of the following actions:
Recreate the stream (using the CREATE OR REPLACE STREAM syntax).
Insert the current change data into a temporary table. In the INSERT statement, query the stream but include a WHERE clause that filters out all of the change data (e.g. WHERE 0 = 1).

QUESTION 47
Which Scenario Data engineer decide Materialized views are not useful. Select All that apply.

Query results contain a small number of rows and/or columns relative to the base table (the table on which the view is defined).

Query results contain results that require significant processing.

The query is on an external table (i.e. data sets stored in files in an external stage), which might have slower performance compared to querying native database tables.

The view’s base table change frequently.

QUESTION 48
Search optimization works best to improve the performance of a query when the following condi-tions are true:[Select All that apply]

The table is not clustered.

The table is frequently queried on columns other than the primary cluster key.

Search Query uses Equality predicates (for example, <column_name> = <constant>) OR Predicates that use IN.

Search Query uses Sort Operations.

QUESTION 49
A company is building a dashboard for thousands of Analysts. The dashboard presents the results of a few summary queries on tables that are regularly updated. The query conditions vary by tope according to what data each Analyst needs Responsiveness of the dashboard queries is a top priority, and the data cache should be preserved.
How should the Data Engineer configure the compute resources to support this dashboard?

Assign queries to a multi-cluster virtual warehouse with economy auto-scaling Allow the system to automatically start and stop clusters according to demand.

Assign all queries to a multi-cluster virtual warehouse set to maximized mode Monitor to determine the smallest suitable number of clusters.

Create a virtual warehouse for every 250 Analysts Monitor to determine how many of these virtual warehouses are being utilized at capacity.

Create a size XL virtual warehouse to support all the dashboard queries Monitor query runtimes to determine whether the virtual warehouse should be resized.

QUESTION 50
To support Time Travel, Which of the following SQL extensions/parameters/commands have been implemented?

AT | BEFORE clause which can be specified in the CREATE … CLONE commands.

ONSET (time difference in seconds from the present time)

OFFSET (time difference in seconds from the present time)

STATEMENT_ID (identifier for statement, e.g. query ID)

STATEMENT (identifier for statement, e.g. query ID)

UNDROP command for tables, schemas, and databases.

QUESTION 51
Which are supported Programming Languages for Creating UDTFs?

Python

Node.javascript

Javascript

Java

Perl

QUESTION 52
Which stages support external tables?

Internal stages only; within a single Snowflake account

internal stages only from any Snowflake account in the organization

External stages only from any region, and any cloud provider

External stages only, only on the same region and cloud provider as the Snowflake account

QUESTION 53
A Data Engineer is building a set of reporting tables to analyze consumer requests by region for each of the Data Exchange offerings annually, as well as click-through rates for each listing Which views are needed MINIMALLY as data sources?

SNOWFLAKE- DATA_SHARING_USAGE – LISTING_EVENTS_BAILY

SNOWFLAKE.DATA_SHARING_USAGE.LISTING_CONSOKE>TION_DAILY

SNOWFLAKE. DATA_SHARING_USAGE. LISTING_TELEMETRY_DAILy

SNOWFLAKE.ACCOUNT_USAGE.DATA _TRANSFER_HISTORY

QUESTION 54
Which Function would Data engineer used to recursively resume all tasks in Chain of Tasks rather than resuming each task individually (using ALTER TASK … RESUME)?

SYSTEM$TASK_DEPENDENTS

SYSTEM$TASK_DEPENDENTS_ENABLE

SYSTEM$TASK_DEPENDENTS_RESUME

SYSTEM$TASK_RECURSIVE_ENABLE

QUESTION 55
The smaller the average depth, the better clustered the table is with regards to the specified column?

TRUE

FALSE

QUESTION 56
Find out the odd one out:

1. Bulk Data Load: Loads are always performed in a single transaction.
2. SnowPipe: Loads are combined or split into a single or multiple transactions based on the number and size of the rows in each data file.

1. Bulk Data Load: Requires a user-specified warehouse to execute COPY statements.
2. SnowPipe: Uses Snowflake-supplied compute resources.

1. Bulk Data Load: Billed for the amount of time each virtual warehouse is active.
2. SnowPipe: Billed according to the compute resources used in the Snowpipe ware-house while loading the files.

1. Bulk Data Load: Load history Stored in the metadata of the target table for 365 days.
2. SnowPipe: Load history Stored in the metadata of the pipe for 64 days.

QUESTION 57
Which ones are the false statements about Materialized Views?

Snowflake does not allow standard DML (e.g. INSERT, UPDATE, DELETE) on ma-terialized views.

Snowflake does not allow users to truncate materialized views.

Materialized views are first-class account objects.

A materialized view can also be used as the data source for a subquery.

Materialized views can be secure views.

Clustering a subset of the materialized views on a table tends to be more cost-effective than clustering the table itself.

QUESTION 58
Which use case would be BEST suited for the search optimization service?

Analysts who need to perform aggregates over high cardinality columns

Business users who need fast response times using highly selective filters

Data Scientists who seek specific JOIN statements with large volumes of data

Data Engineers who create clustered tables with frequent reads against clustering keys

QUESTION 59
Which UDF programming language is not supported with Snowflake Secure Data Sharing feature?

SQL

JAVA

JAVASCRIPT

PYTHON

QUESTION 60
Which are the Cloud Platforms that Support Calling an External Function?

GCP

AWS & AZURE

AWS only

AWS,GCP,AZURE

QUESTION 61
A CSV file around 1 TB in size is generated daily on an on-premise server A corresponding table. Internal stage, and file format have already been created in Snowflake to facilitate the data loading process How can the process of bringing the CSV file into Snowflake be automated using the LEAST amount of operational overhead?

Create a task in Snowflake that executes once a day and runs a copy into statement that references the internal stage The internal stage will read the files directly from the on-premise server and copy the newest file into the table from the on-premise server to the Snowflake table

On the on-premise server schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage Create a task that executes once a day m Snowflake and runs a OOPY WTO statement that references the internal stage Schedule the task to start after the file lands in the internal stage

On the on-premise server schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage. Create a pipe that runs a copy into statement that references the internal stage Snowpipe auto-ingest will automatically load the file from the internal stage when the new file lands in the internal stage.

On the on premise server schedule a Python file that uses the Snowpark Python library. The Python script will read the CSV data into a DataFrame and generate an insert into statement that will directly load into the table The script will bypass the need to move a file into an internal stage

QUESTION 62
Select the incorrect statement while working with warehouses?

Compute resources waiting to shut down are considered to be in “quiesce” mode.

Resizing a warehouse to a larger size is useful while loading and unloading significant amounts of data.

Resizing a warehouse will have any immediate impact on statements that are currently being executed by the warehouse.

Resizing a suspended warehouse does not provision any new compute resources for the warehouse.

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