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Main Memory-Based Algorithms for Efficient Parallel Aggregation for Temporal Databases

Dengfeng Gao, Jose Alvin G. Gendrano, Bongki Moon, Richard T. Snodgrass, Minseok Park, Bruce C. Huang, Jim M. Rodrigue
2004 Distributed and parallel databases  
In this paper, we introduce a variety of parallel temporal aggregation algorithms for the shared-nothing architecture; these algorithms are based on the sequential Aggregation Tree algorithm.  ...  We are particularly interested in developing parallel algorithms that can maximally exploit available memory to quickly compute large-scale temporal aggregates without intermediate disk writes and reads  ...  We would like to thank the reviewers for their suggestions, which improved this paper.  ... 
doi:10.1023/b:dapd.0000028553.70337.e1 fatcat:6fkf7meuizfwzcvlsfokg7y57q

Efficient algorithms for large-scale temporal aggregation

Bongki Moon, I.F. Vega Lopez, V. Immanuel
2003 IEEE Transactions on Knowledge and Data Engineering  
Second, for large-scale aggregations, the proposed algorithms can deal with a database that is substantially larger than the size of available memory.  ...  Index Terms-Temporal databases, temporal aggregation, scalable query processing, data partitioning, balanced tree algorithm, merge-sort algorithm, temporal query processing, aggregate queries.  ...  The authors assume all responsibility for the contents of the paper. The authors would like to thank the anonymous reviewers for all the constructive comments and suggestions.  ... 
doi:10.1109/tkde.2003.1198403 fatcat:p56ex5sl2becxamjk7343uj6oy

ParTime

Markus Pilman, Martin Kaufmann, Florian Köhl, Donald Kossmann, Damien Profeta
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
This paper presents ParTime, a parallel algorithm for temporal aggregation. Temporal aggregation is one of the most important, yet most complex temporal query operators.  ...  on modern hardware (i.e., NUMA machines with large main memories).  ...  of ParTime into Crescando, a parallel, main-memory database system.  ... 
doi:10.1145/2882903.2903732 dblp:conf/sigmod/PilmanKKKP16 fatcat:eykmwvbldzfgzpmogmcrijcjiy

Storing and processing temporal data in a main memory column store

Martin Kaufmann, Donald Kossmann
2013 Proceedings of the VLDB Endowment  
We present a novel data structure called Timeline Index and algorithms based on this index, which have a very competitive performance for all temporal operators beating existing best-of-breed approaches  ...  Taking into account the underlying physical representation, different temporal operators such as temporal aggregation, time travel and temporal join have to be executed efficiently.  ...  THE SAP HANA DATABASE SYSTEM SAP HANA [3] is a commercial database system, which consists of a combination of a main memory column store and a main memory row store.  ... 
doi:10.14778/2536274.2536333 fatcat:22cf7q4usngp5ivv7g7eoi2tcu

Timeline index

Martin Kaufmann, Amin Amiri Manjili, Panagiotis Vagenas, Peter Michael Fischer, Donald Kossmann, Franz Färber, Norman May
2013 Proceedings of the 2013 international conference on Management of data - SIGMOD '13  
., it supports any kind of compression scheme, which is crucial for main memory column stores.  ...  In this paper, we develop the Timeline Index as a novel, unified data structure that efficiently supports temporal operators such as temporal aggregation, time travel, and temporal joins.  ...  Acknowledgments We thank our colleagues at SAP, Andreas Tonder, Ingo Müller and Jonathan Dees for their valuable feedback and comments on our work.  ... 
doi:10.1145/2463676.2465293 dblp:conf/sigmod/KaufmannMVFKFM13 fatcat:2t4f66oo3jbg5hq6hqfe5ioo5a

U2SOD-DB

Jianting Zhang, Camille Kamga, Hongmian Gong, Le Gruenwald
2012 Proceedings of the ACM SIGKDD International Workshop on Urban Computing - UrbComp '12  
Spatial and temporal aggregations on 150 million pickup locations and times in middle-town and downtown Manhattan areas in the New York City (NYC) can be completed in a fraction of a second.  ...  data efficiently.  ...  main memory for fast data accesses.  ... 
doi:10.1145/2346496.2346522 dblp:conf/kdd/ZhangKGG12 fatcat:aqxz5s23jjblziwllw6oc64eje

Parallel online spatial and temporal aggregations on multi-core CPUs and many-core GPUs

Jianting Zhang, Simin You, Le Gruenwald
2014 Information Systems  
to achieving even higher OLAP query efficiency for large-scale applications through integrating domain-specific data management platforms, novel parallel data structures and algorithm designs, and hardware  ...  Unfortunately, existing spatial, temporal and spatiotemporal OLAP techniques are mostly based on traditional computing frameworks, i.e., disk-resident systems on uniprocessors based on serial algorithms  ...  Camille Kamga at CUNY City College for providing the NYC taxi trip data and Dr. Hongmian Gong at CUNY Hunter College for insightful discussions on urban applications of GPS data.  ... 
doi:10.1016/j.is.2014.01.005 fatcat:y43k2qlcqrg6lnt5ryitfnpahy

Mining Massive-Scale Spatiotemporal Trajectories in Parallel: A Survey [chapter]

Pengtao Huang, Bo Yuan
2015 Lecture Notes in Computer Science  
For many trajectory mining problems, a number of computationally efficient approaches have been proposed.  ...  In this paper, we present a comprehensive survey of the state-of-the-art techniques for mining massive-scale spatiotemporal trajectory data based on parallel computing platforms such as Graphics Processing  ...  The main contribution of this paper is a novel and comprehensive survey of parallel trajectory mining algorithms based on GPU, MapReduce and FPGA.  ... 
doi:10.1007/978-3-319-25660-3_4 fatcat:qdkslwlgjzesdfnzvkbrpsgmti

Efficient and Scalable Aggregate Computation on Temporal Graphs

Vincent Le Claire
2020 Very Large Data Bases Conference  
Aggregations, which are very common for relational data, are just as insightful for temporal graph data, but need to be computed efficiently and scalable.  ...  Existing and ongoing work on temporal graphs has focused on path problems and graph databases in general.  ...  Secondly, because some aggregations can be composed into others, it is wise to study how this can be done efficiently. Thirdly, the time dimension and the graph structure give granularity.  ... 
dblp:conf/vldb/Claire20 fatcat:x5dlv6tlyjdu3o6lmvh4volyme

Parallel algorithms for computing temporal aggregates

J.A.G. Gendrano, B.C. Huang, J.M. Rodrigue, Bongki Moon, R.T. Snodgrass
1999 Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337)  
In this paper, we introduce a variety of parallel temporal aggregation algorithms for a sharednothing architecture based on the sequential Aggregation Tree algorithm.  ...  Furthermore, the rate of increase in database size and response time requirements has outpaced advancements in processor and mass storage technology, leading to the need for parallel temporal database  ...  Acknowledgement We would like to thank Minseok Park for his great work on generating performance numbers for this research effort.  ... 
doi:10.1109/icde.1999.754958 dblp:conf/icde/GendranoHRMS99 fatcat:rrpdss7sxjfqncjt2ibvelhqaa

Algorithms for Extracting Frequent Episodes in the Process of Temporal Data Mining

Alexandru PIRJAN
2010 Informatică economică  
Parallel pattern discovery algorithms offer better performance and scalability, so they are of a great interest for the data mining research community.  ...  Based on their high performance, low cost and the increasing number of features offered, GPU processors are viable solutions for an optimal implementation of frequent pattern mining algorithms  ...  The benefits of having a large quantity of aggregate memory and a storage space on parallel platforms are affected by database replication.  ... 
doaj:b4f9f47e312f4ac98df8108c47a94d9d fatcat:3xkkt7d7lbcezf7rggxwz5o6fa

Spatiotemporal aggregate computation: a survey

I.F.V. Lopez, R.T. Snodgrass, Bongki Moon
2005 IEEE Transactions on Knowledge and Data Engineering  
In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data.  ...  At the same time, it allows us to identify opportunities for research on types of aggregate queries that have not been studied.  ...  It was also supported in part by the Mexican Foundation for Science and Technology (CONACyT), scholarship 117476. The authors assume all responsibility for the contents of the paper.  ... 
doi:10.1109/tkde.2005.34 fatcat:j54z4j2chzgchnyqdwoilwnpjy

Distributed Database Management Techniques for Wireless Sensor Networks

Ousmane Diallo, Joel Jose P. C. Rodrigues, Mbaye Sene, Jaime Lloret
2015 IEEE Transactions on Parallel and Distributed Systems  
In this way, the distributed database approach for sensor networks is proved as one of the most energy-efficient data storage and query techniques.  ...  This paper surveys the state of the art of the techniques used to manage data and queries in wireless sensor networks based on the distributed paradigm.  ...  Algorithm for sensor networks), for processing in-network aggregation in WSNs.  ... 
doi:10.1109/tpds.2013.207 fatcat:jnuoflwt2zhntcylijjryh4v2m

A Flexible and Efficient Alert Correlation Platform for Distributed IDS

Sebastian Roschke, Feng Cheng, Christoph Meinel
2010 2010 Fourth International Conference on Network and System Security  
The utilization of the column-oriented database, an In-Memory Alert Storage, and memory-based index tables leads to significant improvements on the performance.  ...  We propose and implement the utilization of memory-supported algorithms and a column-oriented database for correlation and clustering in an extensible IDS correlation platform.  ...  By storing a database in the main memory, analytical operations can be processed in parallel by several CPUs with direct access to the main memory.  ... 
doi:10.1109/nss.2010.26 dblp:conf/nss/RoschkeCM10 fatcat:mi45poj3pfd7lpwxymhsidw3k4

TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs [article]

Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis
2022 arXiv   pre-print
TGL comprises five main components, a temporal sampler, a mailbox, a node memory module, a memory updater, and a message passing engine.  ...  We design a Temporal-CSR data structure and a parallel sampler to efficiently sample temporal neighbors to formtraining mini-batches.  ...  • TGAT [1] is a attention-based TGNN that gathers temporal information by the attention aggregator. • TGN [15] is a memory-based TGNN that applies the attention aggregator on the node memory updated  ... 
arXiv:2203.14883v2 fatcat:t2xd2nmrezejdamcdspt23q2bi
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