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Databricks-Certified-Associate-Developer-for-Apache-Spark-3.5 Exam Dumps : Databricks Certified Associate Developer for Apache Spark 3.5 – Python

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Databricks Certified Associate Developer for Apache Spark 3.5 – Python Questions and Answers

Question 1

A data engineer is streaming data from Kafka and requires:

Minimal latency

Exactly-once processing guarantees

Which trigger mode should be used?

Options:

A.

.trigger(processingTime='1 second')

B.

.trigger(continuous=True)

C.

.trigger(continuous='1 second')

D.

.trigger(availableNow=True)

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Question 2

38 of 55.

A data engineer is working with Spark SQL and has a large JSON file stored at /data/input.json.

The file contains records with varying schemas, and the engineer wants to create an external table in Spark SQL that:

    Reads directly from /data/input.json.

    Infers the schema automatically.

    Merges differing schemas.

Which code snippet should the engineer use?

Options:

A.

CREATE EXTERNAL TABLE users

USING json

OPTIONS (path '/data/input.json', mergeSchema 'true');

B.

CREATE TABLE users

USING json

OPTIONS (path '/data/input.json');

C.

CREATE EXTERNAL TABLE users

USING json

OPTIONS (path '/data/input.json', inferSchema 'true');

D.

CREATE EXTERNAL TABLE users

USING json

OPTIONS (path '/data/input.json', mergeAll 'true');

Question 3

Given this code:

.withWatermark("event_time", "10 minutes")

.groupBy(window("event_time", "15 minutes"))

.count()

What happens to data that arrives after the watermark threshold?

Options:

Options:

A.

Records that arrive later than the watermark threshold (10 minutes) will automatically be included in the aggregation if they fall within the 15-minute window.

B.

Any data arriving more than 10 minutes after the watermark threshold will be ignored and not included in the aggregation.

C.

Data arriving more than 10 minutes after the latest watermark will still be included in the aggregation but will be placed into the next window.

D.

The watermark ensures that late data arriving within 10 minutes of the latest event_time will be processed and included in the windowed aggregation.