Lifetime-Based Memory Management for Distributed Data Processing Systems
Lifetime-Based Memory Management for Distributed Data Processing Systems （Deca：Decompose and Analyze） 一、分佈式數據處理系統像Spark、FLink中的優缺點： 1、優點： in-memory中可以通過緩存中間數據以及在shuffle buffer中組合和聚合數據最小化重複
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相關文章
- 1. In-Memory Database Management Systems
- 2. Big Data Systems - Batch Processing
- 3. Redis vs. Memcached: In-Memory Data Storage Systems
- 4. Chubby - lock service for loosely-coupled distributed systems
- 5. Video processing systems and methods
- 6. Memory Management in C++
- 7. Scalable Web Architecture and Distributed Systems
- 8. Collaborative Memory Network for Recommendation Systems
- 9. Akka - Basis for Distributed Computing
- 10. Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (I - III)