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COF-C02
SnowPro Core Certification Exam Questions and Answers

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Viewing questions 261-280 out of questions

Questions # 261:

Which columns are part of the result set of the Snowflake LATERAL FLATTEN command? (Choose two.)

Options:

CONTENT

PATH

BYTE_SIZE

INDEX

DATATYPE

Answer

B, D

Explanation

The LATERAL FLATTEN command in Snowflake produces a result set that includes several columns, among which PATH and INDEX are includedPATH indicates the path to the element within a data structure that needs to be flattened, and INDEX represents the index of the element if it is an array2.

Questions # 262:

When loading data into Snowflake via Snowpipe what is the compressed file size recommendation?

Options:

10-50 MB

100-250 MB

300-500 MB

1000-1500 MB

Answer

Explanation

For loading data into Snowflake via Snowpipe, the recommended compressed file size is between 100-250 MB. This size range is optimal for balancing the performance of parallel processing and minimizing the overhead associated with handling many small files2.

Questions # 263:

How are serverless features billed?

Options:

Per second multiplied by an automatic sizing for the job

Per minute multiplied by an automatic sizing for the job, with a minimum of one minute

Per second multiplied by the size, as determined by the SERVERLESS_FEATURES_SIZE account parameter

Serverless features are not billed, unless the total cost for the month exceeds 10% of the warehouse credits, on the account

Answer

Explanation

Serverless features in Snowflake are billed based on the time they are used, measured in minutes. The cost is calculated by multiplying the duration of the job by an automatic sizing determined by Snowflake, with a minimum billing increment of one minute. This means that even if a serverless feature is used for less than a minute, it will still be billed for the full minute.

Questions # 264:

Why does Snowflake recommend file sizes of 100-250 MB compressed when loading data?

Options:

Optimizes the virtual warehouse size and multi-cluster setting to economy mode

Allows a user to import the files in a sequential order

Increases the latency staging and accuracy when loading the data

Allows optimization of parallel operations

Answer

Explanation

Snowflake recommends file sizes between 100-250 MB compressed when loading data to optimize parallel processing. Smaller, compressed files can be loaded in parallel, which maximizes the efficiency of the virtual warehouses and speeds up the data loading process

Questions # 265:

A single user of a virtual warehouse has set the warehouse to auto-resume and auto-suspend after 10 minutes. The warehouse is currently suspended and the user performs the following actions:

1. Runs a query that takes 3 minutes to complete

2. Leaves for 15 minutes

3. Returns and runs a query that takes 10 seconds to complete

4. Manually suspends the warehouse as soon as the last query was completed

When the user returns, how much billable compute time will have been consumed?

Options:

4 minutes

10 minutes

14 minutes

24 minutes

Answer

Explanation

The billable compute time includes the time the warehouse is running queries plus the auto-suspend time after the last query if the warehouse is not manually suspended. In this scenario, the warehouse runs for 3 minutes, suspends after 10 minutes of inactivity, resumes for a 10-second query, and then is manually suspended. The total billable time is the sum of the initial 3 minutes, the 10 minutes of auto-suspend time, and the brief period for the 10-second query, which is rounded up to the next full minute due to Snowflake’s billing practices. References: [COF-C02] SnowPro Core Certification Exam Study Guide

Questions # 266:

Which Snowflake layer is always leveraged when accessing a query from the result cache?

Options:

Metadata

Data Storage

Compute

Cloud Services

Answer

Explanation

The Cloud Services layer in Snowflake is responsible for managing the result cache. When a query is executed, the results are stored in this cache, and subsequent identical queries can leverage these cached results without re-executing the entire query1.

Questions # 267:

Which Snowflake function will interpret an input string as a JSON document, and produce a VARIANT value?

Options:

parse_json()

json_extract_path_text()

object_construct()

flatten

Answer

Explanation

The parse_json() function in Snowflake interprets an input string as a JSON document and produces a VARIANT value containing the JSON document. This function is specifically designed for parsing strings that contain valid JSON information3.

Questions # 268:

What COPY INTO SQL command should be used to unload data into multiple files?

Options:

SINGLE=TRUE

MULTIPLE=TRUE

MULTIPLE=FALSE

SINGLE=FALSE

Answer

Explanation

The COPY INTO SQL command with the option SINGLE=FALSE is used to unload data into multiple files. This option allows the data to be split into multiple files during the unload process. References: SnowPro Core Certification COPY INTO SQLcommand unload multiple files

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