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Cloudera CDP Data Engineer - Certification Sample Questions:

1. How can you utilize Spark SQL for complex data analysis involving joins and aggregations on large datasets?

A) By directly writing SQL queries against distributed data in Spark.
B) Both A and B.
C) By implementing custom logic in RDDs for data manipulation.
D) By using Spark ML libraries for machine learning tasks on data.

2. 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) Enabling Iceberg's transactional writes
C) Leveraging a CDC (Change Data Captur tool integrated with Iceberg.
D) Disabling Iceberg's snapshot isolation feature.
E) Carefully configuring the streaming source to handle retries and failures

3. You encounter an error message stating "Schema mismatch" when joining two DataFrames in Spark. What could be the potential causes and how can you resolve them?

A) All of the above
B) The DataFrames have the same column names but different data types
C) The DataFrames have different column names but the same data types
D) The join condition references non-existent columns in one of the DataFrames

4. Your ETL pipeline processes sensitive dat
a. How can you ensure data security within Airflow?

A) Grant everyone access to the Airflow web UI to monitor and manage the pipeline.
B) Store passwords and other sensitive data directly within your Airflow code.
C) Implement encryption for sensitive data at rest and in transit.
D) Use environment variables to store sensitive credentials for accessing data sources.

5. In the context of Hive, what mechanism ensures that data is evenly distributed across buckets?

A) External data balancing tools
B) Manual data insertion scripts
C) A hash function applied to the bucketing column
D) Natural key distribution

Solutions: