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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. You're building an Airflow DAG to extract data from a database table that is constantly updated. How can you implement incremental extraction to avoid processing the entire table each time the DAG runs?

A) Configure the database connection to only retrieve newly added data.
B) Implement a custom Python script to track the last processed record and use it to filter the data during subsequent runs.
C) Use the File sensor to check for the presence of a new data file and trigger the DAG only when the file appears.
D) Leverage the Previous execution operator to access the execution date of the previous DAG run and use it as a filter in the extraction query.

2. Which operator or feature in Apache Airflow can be used to dynamically adjust the schedule of data quality checks based on the volume of incoming data?

A) A custom PythonOperator that modifies the DAG's schedule interval
B) The BranchPythonOperator to choose between different scheduling paths
C) The ExternalTaskSensor to trigger data quality checks based on external events
D) The Scheduler component with dynamic DAG generation

3. What is the primary consideration when choosing the number of buckets in a Hive table?

A) The total storage capacity of the HDFS cluster
B) The number of nodes in the Hadoop cluster
C) The expected distribution of data across the bucketing column
D) The number of rows in each partition

4. Your team is using PySpark and wants to ensure task re-execution in case of a node failure. What mechanism in Spark ensures that tasks are retried on other nodes upon failure?

A) Master Node Redundancy
B) Data Replication
C) Task Re-execution
D) Checkpointing

5. For iterative machine learning algorithms in Spark, which caching level minimizes the trade-off between computation time and storage efficiency?

A) DISK ONLY
B) MEMORY ONLY SER
C) MEMORY AND DISK SER
D) MEMORY ONLY

Solutions: