Index

Big Data Systems
​MapReduce: Simplified Data Processing on Large Clusters - Dean et al., OSDI '04 [Summary]
​Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks - Isard et al., EuroSys '07 [Summary]
​MapReduce Online - Condie et al., NSDI '10 [Summary]
​Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing(Spark) - Zaharia et al., NSDI '12 [Summary]
​Naiad: A Timely Dataflow System - Murray et al., SOSP '13 [Summary]
​Discretized Streams: Fault-Tolerant Streaming Computation at Scale - Zaharia et al., SOSP '13 [Summary]
​The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale  - Akidau et al., VLDB '15 [Summary]
​Resource Management ​
​Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center - Hindman et al., NSDI '11 [Summary]
​Dominant Resource Fairness  - Ghodsi et al., NSDI '11[Summary]
​PACMan: Coordinated Memory Caching for Parallel Jobs - Ananthanarayanan et al., NSDI '12 [Summary]
​Apache Hadoop YARN: Yet Another Resource Negotiator - Vavilapallih et al., SoCC '13 [Summary]
​Making Sense of Performance in Data Analytics Framework - Ousterhout et al., SOSP '15 [Summary]
​Large-scale cluster management at Google with Borg - Verma et al., EuroSys '15 [Summary]
​Efficient Queue Management for Cluster Scheduling - Rasley et al., EuroSys '16 [Summary]
​Morpheus: Towards Automated SLOs for Enterprise Clusters -Jyothi et al., OSDI '16
​Borg, Omega, and Kubernetes - Burns et al., ACM Queue '16
​Learning Scheduling Algorithms for Data Processing Clusters - Hongzi et al., SIGCOMM '19 
Scheduling 
​Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling - Zaharia et al., EuroSys '10 [Summary] 
​Sparrow: Distributed, Low Latency Scheduling - Ousterhout et al., SOSP '13 [Summary]
​Multi-Resource Packing for Cluster Schedulers - Grandl et al., SIGCOMM '14 [Summary]
​CLARINET: WAN-Aware Optimization for Analytics Queries - Viswanathan et al., OSDI '16 [Summary]
​Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks  - Ousterhout et al., SOSP '17 [Summary]
​Drizzle: Fast and Adaptable Stream Processing at Scale  - Venkataraman et al., SOSP '17 [Summary]
Storage
​Flat Datacenter Storage - Nightingale et al., OSDI '12 [Summary]
​Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks - Li et al., SoCC '14 [Summary]
​EC-Cache: Load-balanced, Low-latency Cluster Caching with Online Erasure Coding - Rashmi et al., OSDI '16
Fault Tolerance 
​Improving MapReduce Performance in Heterogeneous Environments - Zaharia et al., OSDI '08 [Summary]
​Reining in the Outliers in Map-Reduce Clusters using Mantri - Ananthanarayanan et al., OSDI '10 [Summary]
​Effective Straggler Mitigation: Attack of the Clones  - Ananthanarayanan et al., NSDI '13 [Summary]
​Interruptible Tasks: Treating Memory Pressure AsInterrupts for Highly Scalable Data-Parallel Program - Fang et al., SOSP '15 [Summary]
​Lineage Stash: Fault Tolerance Off the Critical Path - Wang et al., SOSP '19 [Summary] 
Misc.
​ApproxHadoop: Bringing Approximations to MapReduce Frameworks - Goiri et al., ASPLOS '15
​Yak: A High-Performance Big-Data-Friendly Garbage Collector - Nguyen et al., OSDI '16
​

Short Summaries

Improving MapReduce Performance in Heterogeneous Environments

Last modified 1yr ago

Index

Big Data Systems

​Resource Management ​

Scheduling

Storage

Fault Tolerance

Misc.

Resource Management