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Cloudera CDP Data Engineer - Certification Sample Questions:

1. How does Apache NiFi support schema inference during data flow management?

A) By manually specifying schemas for each data source
B) Utilizing external schema repositories exclusively for schema management
C) By enforcing static schemas for all data flows
D) Through processors that automatically detect data formats and schemas

2. For improving join performance, why is it recommended to filter data before joining tables in Apache Spark?

A) To prepare data for broadcast joins irrespective of size
B) To reduce the volume of data processed during the join
C) To enforce strict data typing across joined datasets
D) To increase the amount of data being shuffled

3. You're using Iceberg for streaming data ingestion. A critical use case requires exactly-once processing guarantees. Which considerations are most important for achieving this? (Choose two)

A) Using a data format like JSON, which is less prone to corruption than Parquet.
B) Leveraging a CDC (Change Data Captur tool integrated with Iceberg.
C) Disabling Iceberg's snapshot isolation feature.
D) Enabling Iceberg's transactional writes
E) Carefully configuring the streaming source to handle retries and failures

4. Explain the concept of lineage tracking in Spark and its benefits for fault tolerance and debugging.

A) Both A and B.
B) Lineage tracks the dependencies between data transformations, enabling efficient re-execution on failures.
C) Lineage allows for caching intermediate results, improving performance.
D) It creates a log of all operations performed on data, aiding in debugging issues.

5. After running a PySpark job, you want to analyze the performance and identify potential bottlenecks. Which tool should you use for this purpose?

A) PySpark SQL CLI.
B) Spark Web I-Jl.
C) Hadoop YARN ResourceManager.
D) PySpark DataFrame API.

Solutions: