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Cloudera CDP-3002 Exam Syllabus Topics:

Section	Objectives
Data Storage and Modeling	- Data lake architecture 1. Partitioning and file formats (Parquet, ORC) 2. HDFS / cloud object storage concepts - Data modeling 1. Dimensional modeling concepts 2. Schema design for analytics
Data Governance and Security	- Data governance 1. Metadata management 2. Data lineage and auditing - Security frameworks 1. Authentication and authorization in CDP 2. Ranger / Sentry policies
Data Ingestion and Integration	- Data movement and pipelines 1. ETL/ELT workflows 2. Data flow orchestration - Batch and streaming ingestion 1. Apache NiFi / Kafka ingestion concepts 2. Data ingestion patterns in CDP
Data Processing and Transformation	- SQL analytics engines 1. Hive / Impala query optimization 2. Data transformation best practices - Spark processing 1. Distributed processing concepts 2. Spark SQL and DataFrames
Platform Operations	- Cluster and workload management 1. Resource management and scheduling 2. Monitoring and troubleshooting

Cloudera CDP Data Engineer - Certification Sample Questions:

1. You have an Airflow DAG that extracts data from a CSV file. How can you ensure that the DAG doesn't attempt to process the same file multiple times in case of retries or task failures?

A) Modify the extraction task to skip processing existing files based on a timestamp or marker within the file.
B) Use the File lock operator before the extraction task to prevent other tasks from accessing the file while it's being processed.
C) Configure the DAG to run only once and manually trigger subsequent runs when needed.
D) Implement a custom mechanism to rename the processed file after each successful run.

2. You encounter an error message stating "Failed to find persisted data for RDD" in your Spark application. What are the potential causes and how can you troubleshoot them?

A) The data might have been corrupted or deleted from the storage location
B) The RDD was never persisted, or the storage level was set incorrectly
C) All of the above
D) Spark encountered a network issue and couldn't access the persisted data

3. You are setting up a high-availability Spark cluster and need to configure the master node for recovery using ZooKeeper.
Which configuration should be added to the 'spark-defaults.conf' file?

A)

B)

C)

D)

4. Your Spark application encounters frequent failures during the execution of a specific stage. How can you utilize Spark's persistence mechanisms to improve the application's fault tolerance?

A) Increase the number of Spark executors to handle potential resource limitations
B) Leverage Spark's checkpointing functionality to save application state periodically
C) Persist the RDDs used in the failing stage with MEMORY_ONLY storage level
D) Implement custom retry logic within the failing stage

5. You're deploying a Spark application in a Kubernetes cluster. Which YAML specification would correctly define a SparkApplication in cluster mode using Scala and the Spark Pi example?