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Selection and replacement algorithms for memory performance improvement in Spark
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.3083openalex-snapshot
SaC‐FRAPP: a scalable and cost‐effective framework for privacy preservation over big data on cloud
inferredcites →https://doi.org/10.1109/icbnmt.2013.6823956openalex-snapshot
Log analysis in cloud computing environment with Hadoop and Spark
inferredcites →https://doi.org/10.1109/tc.2001.970573openalex-snapshot
LRFU: a spectrum of policies that subsumes the least recently used and least frequently used policies
inferredcites →https://doi.org/10.1109/tc.2010.225openalex-snapshot
RT-PLRU: A New Paging Scheme for Real--Time Execution of Program Codes on NAND Flash Memory for Portable Media Players
inferredcites →https://doi.org/10.1109/tcc.2014.2314655openalex-snapshot
Deadline Based Resource Provisioningand Scheduling Algorithm for Scientific Workflows on Clouds
inferredcites →https://doi.org/10.1145/301453.301487openalex-snapshot
On the existence of a spectrum of policies that subsumes the least recently used (LRU) and least frequently used (LFU) policies
inferredcites →https://doi.org/10.1145/98457.98523openalex-snapshot
Data cache management using frequency-based replacement
inferredcites →https://doi.org/10.1145/98460.98523openalex-snapshot
Data cache management using frequency-based replacement
inferredcites →https://doi.org/10.48550/arxiv.1107.4851openalex-snapshot
AWRP: Adaptive Weight Ranking Policy for Improving Cache Performance
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Parallel and distributed computing for Big Data applications
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Performance enhancement for iterative data computing with in‐memory concurrent processing
inferred← citeshttps://doi.org/10.1007/978-3-030-58669-0_36openalex-snapshot
Memory Management Approaches in Apache Spark: A Review
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Flow data processing paradigm and its application in smart city using a cluster analysis approach
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Efficient and privacy-preserving location-based services over the cloud
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Dynamic data replacement and adaptive scheduling policies in spark
inferred← citeshttps://doi.org/10.1007/s10766-018-0612-8openalex-snapshot
A Dependency-Aware Storage Schema Selection Mechanism for In-Memory Big Data Computing Frameworks
inferred← citeshttps://doi.org/10.1007/s10766-020-00662-2openalex-snapshot
A Task-Aware Fine-Grained Storage Selection Mechanism for In-Memory Big Data Computing Frameworks
inferred← citeshttps://doi.org/10.1007/s11227-022-04663-5openalex-snapshot
Memory management optimization strategy in Spark framework based on less contention
inferred← citeshttps://doi.org/10.1007/s42514-025-00218-1openalex-snapshot
An optimized hierarchical MapReduce framework in supercomputing Internet environment
inferred← citeshttps://doi.org/10.1016/j.future.2018.11.010openalex-snapshot
Profile-based power-aware workflow scheduling framework for energy-efficient data centers
inferred← citeshttps://doi.org/10.1016/j.jpdc.2022.01.020openalex-snapshot
Intermediate data placement and cache replacement strategy under Spark platform
inferred← citeshttps://doi.org/10.1109/bdcloud.2018.00140openalex-snapshot
LCRC: A Dependency-Aware Cache Management Policy for Spark
inferred← citeshttps://doi.org/10.1109/bigcom61073.2023.00032openalex-snapshot
SAC: Dynamic Caching upon Sketch for In-Memory Big Data Analytics
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8258209openalex-snapshot
Understanding and improving disk-based intermediate data caching in Spark
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8258264openalex-snapshot
Finding the best box-cox transformation from massive datasets on spark
inferred← citeshttps://doi.org/10.1109/bigdata47090.2019.9006590openalex-snapshot
Transparent In-memory Cache Management in Apache Spark based on Post-Mortem Analysis
inferred← citeshttps://doi.org/10.1109/ccgrid.2017.21openalex-snapshot
Efficient Cache Update for In-Memory Cluster Computing with Spark
inferred← citeshttps://doi.org/10.1109/cloud.2018.00042openalex-snapshot
Intermediate Data Caching Optimization for Multi-Stage and Parallel Big Data Frameworks
inferred← citeshttps://doi.org/10.1109/iccae55086.2022.9762451openalex-snapshot
Cache Replacement Strategy Based on User Behaviour Analysis for a Massive Small File Storage System
inferred← citeshttps://doi.org/10.1109/icccn.2018.8487381openalex-snapshot
The Classified and Active Caching Strategy for Iterative Application in Spark
inferred← citeshttps://doi.org/10.1109/icma.2016.7558977openalex-snapshot
An overview on cloud computing platform spark for Human Genome mining
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A Fast Large-Scale Path Planning Method on Lunar DEM Using Distributed Tile Pyramid Strategy
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Dynamic Caching for Multi-Job and Real-Time IoT Data Analytics
inferred← citeshttps://doi.org/10.1109/tcc.2019.2947674openalex-snapshot
Optimizing Speculative Execution in Spark Heterogeneous Environments
inferred← citeshttps://doi.org/10.1109/tcomm.2020.3022692openalex-snapshot
Virtual Service Placement for Edge Computing Under Finite Memory and Bandwidth
inferred← citeshttps://doi.org/10.1109/w-ficloud.2018.00016openalex-snapshot
Adaptive Control of Apache Spark's Data Caching Mechanism Based on Workload Characteristics
inferred← citeshttps://doi.org/10.1145/3180270.3180276openalex-snapshot
Transparent Avoidance of Redundant Data Transfer on GPU-enabled Apache Spark
inferred← citeshttps://doi.org/10.2991/icmmct-17.2017.96openalex-snapshot
Research on Serialization Storage Strategy Based on Spark Cluster
inferred← citeshttps://doi.org/10.31871/ijntr.5.9.10openalex-snapshot
Research Cache Replacement Strategy in Memory Optimization of Spark
inferred← citeshttps://doi.org/10.32604/cmc.2024.046807openalex-snapshot
Research on Performance Optimization of Spark Distributed Computing Platform
inferred← citeshttps://doi.org/10.3390/app122211491openalex-snapshot
RCM: A Remote Cache Management Framework for Spark
inferred← citeshttps://doi.org/10.5753/sbesc_estendido.2021.18491openalex-snapshot
Gerenciamento Dinâmico de Memória em Aplicações com Reutilização de RDDs no Spark
inferred← citeshttps://doi.org/10.7717/peerj-cs.2460openalex-snapshot
Adaptive memory reservation strategy for heavy workloads in the Spark environment
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