On the public citation graph
Cracking Down MapReduce Failure Amplification through Analytics Logging and Migration
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1109/ccgrid.2010.112openalex-snapshot
An Analysis of Traces from a Production MapReduce Cluster
inferredcites →https://doi.org/10.1109/icde.2011.5767877openalex-snapshot
RAFTing MapReduce: Fast recovery on the RAFT
inferredcites →https://doi.org/10.1109/icpp.2006.26openalex-snapshot
Application-Transparent Checkpoint/Restart for MPI Programs over InfiniBand
inferredcites →https://doi.org/10.1109/ipdps.2013.13openalex-snapshot
JVM-Bypass for Efficient Hadoop Shuffling
inferredcites →https://doi.org/10.1109/ipdps.2014.87openalex-snapshot
Characterization and Optimization of Memory-Resident MapReduce on HPC Systems
inferredcites →https://doi.org/10.1109/msst.2010.5496972openalex-snapshot
The Hadoop Distributed File System
inferredcites →https://doi.org/10.1145/1807128.1807160openalex-snapshot
Making cloud intermediate data fault-tolerant
inferredcites →https://doi.org/10.1145/1807167.1807272openalex-snapshot
Integrating hadoop and parallel DBMs
inferredcites →https://doi.org/10.1145/1989323.1989426openalex-snapshot
A platform for scalable one-pass analytics using MapReduce
inferredcites →https://doi.org/10.1145/2063384.2063461openalex-snapshot
Hadoop acceleration through network levitated merge
inferredcites →https://doi.org/10.1145/2254756.2254761openalex-snapshot
Delay tails in MapReduce scheduling
inferredcites →https://doi.org/10.1145/2287076.2287108openalex-snapshot
Understanding the effects and implications of compute node related failures in hadoop
inferredcites →https://doi.org/10.21276/ijre.2018.5.5.4openalex-snapshot
MapReduce: Simplified Data Processing on Large Cluster
inferredcites →https://doi.org/10.5555/1855741.1855744openalex-snapshot
Improving MapReduce performance in heterogeneous environments
inferredcites →https://doi.org/10.5555/1924943.1924962openalex-snapshot
Reining in the outliers in map-reduce clusters using Mantri
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s11227-018-2716-8openalex-snapshot
Fast Recovery MapReduce (FAR-MR) to accelerate failure recovery in big data applications
inferred← citeshttps://doi.org/10.1016/j.parco.2016.10.004openalex-snapshot
FARMS: Efficient mapreduce speculation for failure recovery in short jobs
inferred← citeshttps://doi.org/10.1109/icccn.2017.8038373openalex-snapshot
LASER: A Deep Learning Approach for Speculative Execution and Replication of Deadline-Critical Jobs in Cloud
inferred← citeshttps://doi.org/10.1109/icdcs.2018.00075openalex-snapshot
Chronos: A Unifying Optimization Framework for Speculative Execution of Deadline-Critical MapReduce Jobs
inferred← citeshttps://doi.org/10.1109/ieee.edge.2017.23openalex-snapshot
TRCID: Optimized Task Recovery in MapReduce Based on Checkpointing Intermediate Data
inferred← citeshttps://doi.org/10.1109/innovate-data.2017.14openalex-snapshot
Bringing Big Data into the Car: Does it Scale?
inferred← citeshttps://doi.org/10.1109/mascots.2017.28openalex-snapshot
Lightweight Replication Through Remote Backup Memory Sharing for In-memory Key-Value Stores
inferred← citeshttps://doi.org/10.1109/tsc.2019.2904270openalex-snapshot
McTAR: A Multi-Trigger Checkpointing Tactic for Fast Task Recovery in MapReduce
inferred← citeshttps://doi.org/10.1145/2831244.2831245openalex-snapshot
A case study of MapReduce speculation for failure recovery
inferred← citeshttps://doi.org/10.48550/arxiv.1901.07715openalex-snapshot
Enhancing MapReduce Fault Recovery Through Binocular Speculation
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