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ARA-C01 Exam Dumps : SnowPro Advanced: Architect Certification Exam

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SnowPro Advanced: Architect Certification Exam Questions and Answers

Question 1

An Architect is designing a pipeline to stream event data into Snowflake using the Snowflake Kafka connector. The Architect’s highest priority is to configure the connector to stream data in the MOST cost-effective manner.

Which of the following is recommended for optimizing the cost associated with the Snowflake Kafka connector?

Options:

A.

Utilize a higher Buffer.flush.time in the connector configuration.

B.

Utilize a higher Buffer.size.bytes in the connector configuration.

C.

Utilize a lower Buffer.size.bytes in the connector configuration.

D.

Utilize a lower Buffer.count.records in the connector configuration.

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Question 2

An Architect has a table called leader_follower that contains a single column named JSON. The table has one row with the following structure:

{

"activities": [

{ "activityNumber": 1, "winner": 5 },

{ "activityNumber": 2, "winner": 4 }

],

"follower": {

"name": { "default": "Matt" },

"number": 4

},

"leader": {

"name": { "default": "Adam" },

"number": 5

}

}

Which query will produce the following results?

ACTIVITY_NUMBER

WINNER_NAME

1

Adam

2

Matt

Options:

A.

SELECT lf.json:activities.activityNumber AS activity_number,

IFF(

lf.json:activities.activityNumber = lf.json:leader.number,

lf.json:leader.name.default,

lf.json:follower.name.default

)::VARCHAR

FROM leader_follower lf;

B.

SELECT

C.

value:activityNumber AS activity_number,

IFF(

D.

value:winner = lf.json:leader.number,

lf.json:leader.name.default,

lf.json:follower.name.default

)::VARCHAR AS winner_name

FROM leader_follower lf,

LATERAL FLATTEN(input => json:activities) p;

E.

SELECT

F.

value:activityNumber AS activity_number,

IFF(

G.

value:winner = lf.json:leader.number,

lf.json:leader,

lf.json:follower

)::VARCHAR AS winner_name

FROM leader_follower lf,

LATERAL FLATTEN(input => json:activities) p;

Question 3

An Architect is designing Snowflake architecture to support fast Data Analyst reporting. To optimize costs, the virtual warehouse is configured to auto-suspend after 2 minutes of idle time. Queries are run once in the morning after refresh, but later queries run slowly.

Why is this occurring?

Options:

A.

The warehouse is not large enough.

B.

The warehouse was not configured as a multi-cluster warehouse.

C.

The warehouse was not created with USE_CACHE = TRUE.

D.

When the warehouse was suspended, the cache was dropped.