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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitoring, Troubleshooting & Workload Management | 10% | - Cluster resource allocation - Performance monitoring and logging - Bottleneck identification and resolution |
| Topic 2: Streaming & IoT Data Processing | 15% | - Real-time ingestion frameworks - Pravega, Kafka, NiFi usage - Stream processing optimization |
| Topic 3: Data Processing Frameworks | 22% | - Apache Spark optimization - Batch and real-time processing optimization - Hadoop ecosystem tuning |
| Topic 4: Storage & Data Management | 18% | - Distributed storage system optimization - Data formats, partitioning, and indexing - SQL/NoSQL performance tuning |
| Topic 5: Governance, Security & Compliance | 15% | - Regulatory compliance - Data governance policies - Security and privacy protection |
| Topic 6: Data Pipeline Optimization | 20% | - Reduce latency and improve throughput - Design scalable and efficient data pipelines - ETL/ELT workflow optimization |
1. What step in a query plan determines the best execution path for the provided query?
A) Execution
B) Optimizer
C) Parser
D) Algebrizer
2. With Apache Kafka, what is an advantage of implementing the Publish/Subscribe messaging system over Point-to-Point messaging system?
A) Any message published to a topic is received only by a few subscribers to that topic
B) Messages stored are deduplicated automatically to increase the overall storage capacity of a topic
C) Any message published to a topic is immediately received by all the subscribers to that topic
D) Messages can be dynamically moved between topics to improve the overall throughput of the system
3. An organization has decided to structure their governance model to allow either a single individual or a team to control and maintain the master data.
Which governance model is being implemented?
A) Hybrid
B) Distributed
C) Federated
D) Centralized
4. What is the primary focus of the EdgeX Foundry architecture?
A) Cloud computing
B) Edge computing and IoT devices
C) Quantum computing
D) Big data analytics
5. How is replication implemented in Redis?
A) Data is shared among many computers to enable fault tolerance and data accessibility
B) Meta information is generated based on the client-server communication protocol
C) The developer copies and pastes the data in multiple databases
D) Client-server communication protocol is used, whereby every client replicates data from the server
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: A |
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