Improving Cache Management with Redundant RDDs Eviction in Spark
Source abstract
Abstract
Efficient cache management plays a vital role in in-memory data-parallel systems, such as Spark, Tez, Storm and HANA. Recent research, notably research on the Least Reference Count (LRC) and Most Reference Distance (MRD) poli... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Caching and Content Delivery · Advanced Data Storage Technologies · IoT and Edge/Fog Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (23)
Show source-provided references
1. Spark: Cluster computing with working sets
2. Apache tez: A unifying framework for modeling and building data processing applications
3. Apache storm, a hands on tutorial
4. Pacman: Coordinated memory caching for parallel jobs
5. Elastic memory management for cloud data analytics
6. Transparent in-memory cache management in apache spark based on post-mortem analysis
7. Brief talk about big data graph analysis and visualization10.32604/jbd.2019.05800 ↗
8. OpuS: Fair and efficient cache sharing for in-memory data analytics
9. A cache replacement policy based on multi-factors for named data networking10.32604/cmc.2020.010831 ↗
10. An optimal data placement strategy in hadoop for data intensive applications based on cohesion relation10.32604/csse.2019.34.047 ↗
11. Adaptive scheduling of parallel jobs in spark streaming
12. An improved memory cache management study based on spark
13. LRC: Dependency-aware cache management for data analytics clusters
14. LCRC: A dependency-aware cache management policy for spark
15. Reference-distance eviction and prefetching for cache management in spark
16. Evaluation techniques for storage hierarchies10.1147/sj.92.0078 ↗
17. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing
18. Resource-aware cache management for in-memory data analytics frameworks
19. The classified and active caching strategy for iterative application in spark
20. A dynamic memory allocation optimization mechanism based on spark10.32604/cmc.2019.06097 ↗
21. Sparkbench: A comprehensive benchmarking suite for in memory data analytic platform spark
22. Workload allocation based on user mobility in mobile edge computing10.32604/jbd.2020.010958 ↗
23. An optimization scheme for task offloading and resource allocation in vehicle edge networks10.32604/jiot.2020.011792 ↗