Leaky Buffer: A Novel Abstraction for Relieving Memory Pressure from Cluster Data Processing Frameworks
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[1] Daoyuan Wang,et al. Tuning Java Garbage Collection for Spark Applications , 2015 .
[2] Beng Chin Ooi,et al. Llama: leveraging columnar storage for scalable join processing in the MapReduce framework , 2011, SIGMOD '11.
[3] David Cunningham,et al. M3R: Increased performance for in-memory Hadoop jobs , 2012, Proc. VLDB Endow..
[4] Scott Shenker,et al. Shark: SQL and rich analytics at scale , 2012, SIGMOD '13.
[5] Shrinivas Joshi. Java Garbage Collection Characteristics and Tuning Guidelines for Apache Hadoop TeraSort Workload , 2010 .
[6] Roy H. Campbell,et al. ARIA: automatic resource inference and allocation for mapreduce environments , 2011, ICAC '11.
[7] Evangelos P. Markatos,et al. Implementation of a Reliable Remote Memory Pager , 1996, USENIX Annual Technical Conference.
[8] John Kubiatowicz,et al. Trash Day: Coordinating Garbage Collection in Distributed Systems , 2015, HotOS.
[9] Michael Dahlin,et al. Cooperative caching: using remote client memory to improve file system performance , 1994, OSDI '94.
[10] Michael Stonebraker,et al. C-Store: A Column-oriented DBMS , 2005, VLDB.
[11] Jie Huang,et al. The HiBench benchmark suite: Characterization of the MapReduce-based data analysis , 2010, 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010).
[12] Randy H. Katz,et al. Topology-aware resource allocation for data-intensive workloads , 2011, Comput. Commun. Rev..
[13] Carlo Curino,et al. Apache Tez: A Unifying Framework for Modeling and Building Data Processing Applications , 2015, SIGMOD Conference.
[14] L.Bharathi G.Sireesha,et al. Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud , 2011, IEEE Transactions on Parallel and Distributed Systems.
[15] Odej Kao,et al. Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud , 2011, IEEE Transactions on Parallel and Distributed Systems.
[16] Randy H. Katz,et al. Topology-aware resource allocation for data-intensive workloads , 2010, APSys '10.
[17] Parag Agrawal,et al. The case for RAMClouds: scalable high-performance storage entirely in DRAM , 2010, OPSR.
[18] Michael Stonebraker,et al. A comparison of approaches to large-scale data analysis , 2009, SIGMOD Conference.
[19] Sanjay Ghemawat,et al. MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.
[20] Christopher Olston,et al. SpongeFiles: mitigating data skew in mapreduce using distributed memory , 2014, SIGMOD Conference.
[21] Scott Shenker,et al. Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks , 2014, SoCC.
[22] Matei Zaharia,et al. Resilient Distributed Datasets , 2016 .
[23] Michael J. Franklin,et al. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing , 2012, NSDI.
[24] Benjamin Hindman,et al. Dominant Resource Fairness: Fair Allocation of Multiple Resource Types , 2011, NSDI.