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On the Expressiveness and Trade-Offs of Large Scale Tuple Stores [chapter]

Ricardo Vilaça, Francisco Cruz, Rui Oliveira
2010 Lecture Notes in Computer Science  
In this paper we introduce DataDroplets, a novel tuple store that shifts the current trade-off towards the needs of common business users, providing additional consistency guarantees and higher level data  ...  By doing so, these services focus on a specific narrow trade-off between consistency, availability, performance, scale, and migration cost, that is much less attractive to common business needs.  ...  Trade-offs of current tuple stores The data model type of a tuple store, in addition to determine its expressiveness, also impacts the way of storing data.  ... 
doi:10.1007/978-3-642-16949-6_5 fatcat:ppzhaemf7bblpngo32omsa54te

Clouder: a flexible large scale decentralized object store

Ricardo Vilaça, Rui Oliveira
2009 Proceedings of the Third Workshop on Dependable Distributed Data Management - WDDM '09  
The devised mechanisms should not hinder the scalability and dependability of large scale data stores.  ...  With a number of alternatives now available and mature, there is an increasing willingness to use them in a wider and more diverse spectrum of applications, by skewing the current trade-off towards the  ...  On the expressiveness and trade-offs of large scale tuple stores.  ... 
doi:10.1145/1518691.1518699 fatcat:bmegtojlkngnrecectx3o5d5zm

Adaptive RDF Query Processing Based on Provenance [chapter]

Marcin Wylot, Philippe Cudré-Mauroux, Paul Groth
2015 Lecture Notes in Computer Science  
An interesting area of work would be to study the trade off between runtime query adaptation based on provenance and post hoc provenance queries.  ...  A key focus of TripleProv is the efficient implementation of provenance-enabled queries over large scale RDF datasets.  ...  This work was funded in part by the Swiss National Science Foundation under grant number PP00P2 128459 and by the Data2Semantics project in the Dutch national program COMMIT.  ... 
doi:10.1007/978-3-319-16462-5_29 fatcat:wdavr5zhijev3au5tp6akz5zoa

DiSC: Benchmarking Secure Chip DBMS

N. Anciaux, L. Bouganim, P. Pucheral, P. Valduriez
2008 IEEE Transactions on Knowledge and Data Engineering  
The main problem faced by secure chip DBMS designers is to be able to assess various design choices and trade-offs for different applications.  ...  Our solution is to use a benchmark for secure chip DBMS in order to 1) compare different database techniques, 2) predict the limits of on-chip applications, and 3) provide codesign hints.  ...  DiSC metrics allow comparing different techniques and trade-offs on the processor cache, the RAM, and the stable storage competing on the same silicon die.  ... 
doi:10.1109/tkde.2008.67 fatcat:n4bgg5ozqbfgvmxvaasd4zwqsq

MOOLAP: Towards Multi-Objective OLAP

Shyam Antony, Ping Wu, Divyakant Agrawal, Amr El Abbadi
2008 2008 IEEE 24th International Conference on Data Engineering  
users do not need to specify a ranking function and (ii) the result is independent of the dimension scales.  ...  When more than one aggregation function is involved and the notion of interest is not clearly defined, skyline queries provide a robust mechanism to capture the potentially interesting points where (i)  ...  Instead, a number of alternative solutions may coexist involving various trade-offs in different objectives.  ... 
doi:10.1109/icde.2008.4497567 dblp:conf/icde/AntonyWAA08 fatcat:7quevfkaynhariurycw2orziq4

How to Win a Hot Dog Eating Contest

Milos Nikolic, Mohammad Dashti, Christoph Koch
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
We show how to derive incremental programs optimized for running on large-scale processing platforms.  ...  Batch updates are essential for enabling distributed incremental view maintenance and amortizing the cost of network communication and synchronization.  ...  We study the trade-offs between tuple-at-a-time and batched recursive incremental view maintenance in local settings.  ... 
doi:10.1145/2882903.2915246 dblp:conf/sigmod/NikolicD016 fatcat:bnqsj45fh5fkzldf3rf6gx43ta

Integrating scale out and fault tolerance in stream processing using operator state management

Raul Castro Fernandez, Matteo Migliavacca, Evangelia Kalyvianaki, Peter Pietzuch
2013 Proceedings of the 2013 international conference on Management of data - SIGMOD '13  
Based on them, we describe an integrated approach for dynamic scale out and recovery of stateful operators.  ...  At any point, failed operators are recovered by restoring checkpointed state on a new VM and replaying unprocessed tuples.  ...  This work was supported by a PhD CASE Award funded by the Engineering and Physical Sciences Research Council (EPSRC) and BAE Systems.  ... 
doi:10.1145/2463676.2465282 dblp:conf/sigmod/FernandezMKP13 fatcat:cni5omzumjhnbmkvumsbjmghia


Marco Serafini, Rebecca Taft, Aaron J. Elmore, Andrew Pavlo, Ashraf Aboulnaga, Michael Stonebraker
2016 Proceedings of the VLDB Endowment  
Clay dynamically creates blocks of tuples to migrate among servers during repartitioning, placing no constraints on the schema but taking care to balance load and reduce the amount of data migrated.  ...  Clay achieves this goal by including in each block a set of hot tuples and other tuples co-accessed with these hot tuples.  ...  For example, the trading volume on the NYSE is an order of magnitude higher at the beginning and end of the trading day, and transaction volume spikes when there is relevant breaking news.  ... 
doi:10.14778/3025111.3025125 fatcat:avvjkvbxhbcx3go7mr3gl4cgdy

Materialization Strategies in a Column-Oriented DBMS

Daniel J. Abadi, Daniel S. Myers, David J. DeWitt, Samuel R. Madden
2007 2007 IEEE 23rd International Conference on Data Engineering  
This paper describes a variety of strategies for tuple construction and intermediate result representations and provides a systematic evaluation of these strategies.  ...  Thus, the input columns stored on disk must be converted to rows at some point in the query plan, but the optimal point at which to do the conversion is not obvious.  ...  Acknowledgements We would like to thank the C-Store team for their helpful feedback and ideas.  ... 
doi:10.1109/icde.2007.367892 dblp:conf/icde/AbadiMDM07 fatcat:hdcnbavj7zdstcikppdwbrozma

Lookup Tables: Fine-Grained Partitioning for Distributed Databases

Aubrey L. Tatarowicz, Carlo Curino, Evan P.C. Jones, Sam Madden
2012 2012 IEEE 28th International Conference on Data Engineering  
Ideally, this results in each query/transaction being executed at just one node, to avoid the overhead of distribution and allow the system to scale by adding nodes.  ...  We present a design that efficiently stores very large tables and maintains them as the database is modified.  ...  ACKNOWLEDGEMENTS This work was supported by Quanta Computer as a part of the T-Party Project, and by NSF IIS-III Grant 1065219.  ... 
doi:10.1109/icde.2012.26 dblp:conf/icde/TatarowiczCJM12 fatcat:hkvyk54vsjderkzshurn6sqy4y

Speed-Ups and Time–Memory Trade-Offs for Tuple Lattice Sieving [chapter]

Gottfried Herold, Elena Kirshanova, Thijs Laarhoven
2018 Lecture Notes in Computer Science  
In this work we study speed-ups and time-space trade-offs for solving the shortest vector problem (SVP) on Euclidean lattices based on tuple lattice sieving.  ...  The trade-offs we obtain stem from the generalization and combination of two algorithmic techniques: the configuration framework introduced by Herold-Kirshanova, and the spherical locality-sensitive filters  ...  We thank the anonymous reviewers of PKC 2018 for careful proof-reading and finding an error in one of our tables.  ... 
doi:10.1007/978-3-319-76578-5_14 fatcat:47z37awwdvdszjqt4qbfbirjzq

Scalable Multi-Query Execution using Reinforcement Learning

Panagiotis Sioulas, Anastasia Ailamaki
2021 Proceedings of the 2021 International Conference on Management of Data  
Both strategies fail to minimize the cost of processing for large and ad-hoc workloads.  ...  strategy scales poorly to large query counts, as it requires expensive sharing-aware optimization, whereas the latter detects only a subset of the opportunities.  ...  The experiments show that RouLette scales to hundreds of complex queries, unlike offline sharing, and improves throughput compared to query-at-a-time and online sharing systems.  ... 
doi:10.1145/3448016.3452799 fatcat:sjt5akmfufc37honzmywh7e5jq

Scalable package queries in relational database systems

Matteo Brucato, Juan Felipe Beltran, Azza Abouzied, Alexandra Meliou
2016 Proceedings of the VLDB Endowment  
This model is computationally efficient, as the database system can evaluate the query conditions on each tuple individually.  ...  We prove that PaQL is at least as expressive as integer linear programming, and therefore, evaluation of package queries is in general NP-hard.  ...  This material is based upon work supported by the National Science Foundation under grants IIS-1420941, IIS-1421322, and IIS-1453543.  ... 
doi:10.14778/2904483.2904489 fatcat:ac65v4b2h5a6zexjwkcsfdbbze


Louis Woods, Zsolt István, Gustavo Alonso
2014 Proceedings of the VLDB Endowment  
Ibex is a hybrid engine, with dedicated hardware that evaluates SQL expressions at line-rate and a software fallback for tasks that the hardware engine cannot handle.  ...  In this paper, we present Ibex , a prototype of an intelligent storage engine that supports off-loading of complex query operators.  ...  This work was supported by the Enterprise Computing Center (ECC) of ETH Zurich (  ... 
doi:10.14778/2732967.2732972 fatcat:f6f4rtrd3ffinecxzwq6k3gpm4

Deductive Optimization of Relational Data Storage [article]

John K. Feser, Samuel Madden, Nan Tang, Armando Solar-Lezama
2020 arXiv   pre-print
In this paper, we propose a language that can express a wide range of physical database layouts, going well beyond the row- and column-based methods that are widely used in database management systems.  ...  Optimizing the physical data storage and retrieval of data are two key database management problems.  ...  Optimization Trade-offs The nested call query is interesting because the data in question is fairly large-hundreds of thousands of rows-and keeping it fully in memory, or even better in cache, is a significant  ... 
arXiv:1903.03229v3 fatcat:3lmmfmgjubgybhoes43prvfik4
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