Ngân hàng câu hỏi

Discuss vertex-centric computation, message passing between nodes, and optimizations for large-scale processing.

Focus on CDN usage, adaptive bitrate streaming, content caching strategies, and handling peak traffic loads.

Use NLP for parsing resumes, implement ranking algorithms, and optimize for search and matching efficiency.

Consider consistency, data partitioning, eviction policies, and fault tolerance in distributed caching.

Address latency, data loss, and bandwidth issues; optimize for long-distance and high-latency networks.

Implement algorithms considering real-time obstacle avoidance, dynamic path adjustments, and efficient routing.

Utilize message queues (like Kafka, RabbitMQ), ensure fault tolerance, and implement load balancing.

Use NLP techniques like tokenization, parsing, and deep learning models for understanding and generating responses.

Implement statistical models or machine learning algorithms to detect unusual patterns indicative of anomalies.

Focus on handling large-scale data influx, real-time processing, data storage, and analytics.