AI Models and Data Engineering →hardMultiple ChoiceObjective-mapped

AI0-001 AI Models and Data Engineering Practice Question

Exhibit

Data Pipeline Architecture:
- Source: IoT devices -> Kafka Topic "sensor_data"
- Stream Processing: Apache Flink job that ingests from Kafka, cleanses data, and outputs to another Kafka Topic "cleaned_sensor_data"
- Batch Processing: Apache Spark job that reads from "cleaned_sensor_data" via Kafka batch integration, performs feature engineering, and writes to HDFS as Parquet
- Model Training: Python script reads from HDFS, trains an LSTM model, and saves to model registry
- Inference: REST API loads model from registry and serves predictions

Refer to the exhibit. A data engineer notices that the batch processing step is taking too long and causing delays. Which change would most likely reduce the latency?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Move feature engineering to the stream processing step in Flink

Moving feature engineering from the batch Spark job to the stream processing Flink job reduces the workload on the batch step, making it faster. Replacing Flink, increasing parallelism, or changing output format do not address the bottleneck as effectively.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Increase the parallelism of the Spark job
Why it's wrong here
Parallelism helps but the feature engineering workload remains in batch; moving it earlier is more effective.
✓
Move feature engineering to the stream processing step in Flink
Why this is correct
Performing feature engineering in stream reduces batch processing time and overall latency.
✗
Replace Apache Flink with Apache Storm for stream processing
Why it's wrong here
Changing stream processing engine does not reduce batch workload.
✗
Change the output format from Parquet to CSV
Why it's wrong here
CSV is not columnar and would be slower, increasing latency.

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This AI0-001 question is part of Courseiva's 754-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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