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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. In a Kubernetes environment, how does Kubernetes ensure fault tolerance when a pod running a Spark task fails?

A) By using a Standby Master setup
B) Using a load balancer for master components
C) By checkpointing RDDs
D) Through Pod Replication with ReplicaSets

2. You want to schedule your Airflow DAG to run every hour, starting at midnight (00:00). How can you achieve this scheduling configuration?

A) Use the cron expression "@hourly".
B) Utilize Airflow triggers to initiate the DAG execution at midnight.
C) Set the schedule_interval parameter to "0 0 ".
D) Define a custom Python function to schedule the DAG at the desired time.

3. For scripting and automation purposes, how can Cloudera's CLI tools be integrated into administrative workflows?

A) CLI tools cannot be integrated into administrative workflows; they are only for interactive use.
B) Using exclusively manual CLI commands for each task without automation.
C) By creating custom plugins for web browsers to manage Cloudera services.
D) Incorporating CLI commands into shell scripts or automation tools like Ansible, Chef, or Puppet.

4. In the context of Spark SQL, what does the Catalyst optimizer use to optimize queries?

A) Machine learning algorithms to predict the fastest query execution plan
B) A cost-based optimization model that considers the size of intermediate data
C) A rule-based optimization model that applies predefined rules to simplify queries

5. In an Airflow DAG, you have tasks A, B, C, and D. Task A must complete before B and C can start, but B and C can run in parallel. Task D should only run once both B and C have completed. How do you set up these dependencies?

A) [A ]] B, A]] C] and [B, C] ]] D
B) A.set_downstream([B, C]) and set_upstream([B, C])
C) A]] B, C]] D
D) A]] B ]] C]] D

Solutions: