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Lazy Analytics: Let Other Queries Do the Work For You

William Jannen, Michael A. Bender, Martin Farach-Colton, Rob Johnson, Bradley C. Kuszmaul, Donald E. Porter
2016 USENIX Workshop on Hot Topics in Storage and File Systems  
Derange queries defer work until it is either convenient or necessary, and, as a result, can reduce total I/O costs of the system.  ...  They are most useful for performing calculations where the results are not needed until some future deadline. When necessary, derange queries can also execute immediately.  ...  Acknowledgments We thank the anonymous reviewers and our shepherd, Cindy Rubio Gonzalez, for their insightful comments on earlier drafts of the work.  ... 
dblp:conf/hotstorage/JannenBFJKP16 fatcat:jzcq4naenbaxznsc3zq74y2zxm

MonetDBLite: An Embedded Analytical Database [article]

Mark Raasveldt, Hannes Mühleisen
2018 arXiv   pre-print
These alternatives, however, lack features that are standard for RDBMSes, e.g. out-of-core query execution. In this paper, we introduce the embedded analytical database MonetDBLite.  ...  It is designed for OLAP scenarios, and offers near-instantaneous data transfer between the database and analytical tools, all the while maintaining the transactional guarantees and ACID properties of a  ...  We also thank Pedro Ferreira for his work integrating MonetDBLite into the JVM.  ... 
arXiv:1805.08520v1 fatcat:y7eqirodufdyngj32uuwwnbnki

Big data analytics on Apache Spark

Salman Salloum, Ruslan Dautov, Xiaojun Chen, Patrick Xiaogang Peng, Joshua Zhexue Huang
2016 International Journal of Data Science and Analytics  
Apache Spark has emerged as the de facto framework for big data analytics with its advanced in-memory programming model and upper-level libraries for scalable machine learning, graph analysis, streaming  ...  In addition, we highlight some research and development directions on Apache Spark for big data analytics.  ...  On the other hand, an unreliable receiver does not send acknowledgment to a source. However, unreliable receivers can be used for sources that do not support acknowledgment or for those which do.  ... 
doi:10.1007/s41060-016-0027-9 dblp:journals/ijdsa/SalloumD0PH16 fatcat:gtzw3aqupnhxvcjbefovrnfhne

An Introduction to Sensor Data Analytics [chapter]

Charu C. Aggarwal
2012 Managing and Mining Sensor Data  
The chapter describes the above different techniques and concludes with a brief review of other troubleshooting work, not inspired by data mining literature.  ...  For example, if we are considering the L ∞ norm, then each sensor value of the data stream is approximated within an error bound . Let us assume that we have K segments of a data stream.  ...  The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.  ... 
doi:10.1007/978-1-4614-6309-2_1 fatcat:pfbx566yfzgqpnjcuzonmxr23q

Big Data Analytics with Datalog Queries on Spark

Alexander Shkapsky, Mohan Yang, Matteo Interlandi, Hsuan Chiu, Tyson Condie, Carlo Zaniolo
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics.  ...  We perform an experimental comparison with other state-ofthe-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics.  ...  We thank Jingjing Wang and Jiwon Seo for their assistance with the experimental comparison.  ... 
doi:10.1145/2882903.2915229 pmid:28626296 pmcid:PMC5470845 dblp:conf/sigmod/ShkapskyYICCZ16 fatcat:fw2fje66wfaipfvhax5bi4mim4

Distributed temporal graph analytics with GRADOOP

Christopher Rost, Kevin Gomez, Matthias Täschner, Philip Fritzsche, Lucas Schons, Lukas Christ, Timo Adameit, Martin Junghanns, Erhard Rahm
2021 The VLDB journal  
We give a complete overview of Gradoop, a graph dataflow system for scalable, distributed analytics of temporal property graphs which has been continuously developed since 2005.  ...  We evaluate the performance and scalability of selected operators and a composed workflow for synthetic and real-world temporal graphs with up to 283 M vertices and 1.8 B edges, and a graph lifetime of  ...  The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.  ... 
doi:10.1007/s00778-021-00667-4 fatcat:3rbroxyhpzc5hlxkrasqicqbre

Scaling-up reasoning and advanced analytics on BigData

2018 Theory and Practice of Logic Programming  
Looking back, we see how this realizes the ambitious goal pursued by deductive database researchers beginning 40 years ago: this is the goal of combining the rigor and power of logic in expressing queries  ...  This paper is under consideration for acceptance in Theory and Practice of Logic Programming.  ...  Acknowledgements We would like to thank the reviewers for the comments and suggested improvements.  ... 
doi:10.1017/s1471068418000418 fatcat:xvfcjy4fi5ctvpesstdhqrhsvq

Epistemology, pedagogy, assessment and learning analytics

Simon Knight, Simon Buckingham Shum, Karen Littleton
2013 Proceedings of the Third International Conference on Learning Analytics and Knowledge - LAK '13  
for bounding this middle space.  ...  As a detailed worked example of how one might design analytics to scaffold a specific form of higher order learning, we focus on the construct of epistemic beliefs: beliefs about the nature of knowledge  ...  Acknowledgements: We are grateful to Cindy Kerawalla and 3 anonymous reviewers for helpful comments on an earlier version of this paper presented at the LAK13 conference, and to Dan Suthers and the LAK13  ... 
doi:10.1145/2460296.2460312 dblp:conf/lak/KnightSL13 fatcat:sfqbgk7bijawldlbymqx5xqlnm

Epistemology, Assessment, Pedagogy: Where Learning Meets Analytics in the Middle Space

Simon Knight, Simon Buckingham Shum, Karen Littleton
2014 Journal of Learning Analytics  
for bounding this middle space.  ...  As a detailed worked example of how one might design analytics to scaffold a specific form of higher order learning, we focus on the construct of epistemic beliefs: beliefs about the nature of knowledge  ...  ACKNOWLEDGEMENTS We are grateful to Cindy Kerawalla and three anonymous reviewers for helpful comments on an earlier version of this paper presented at the LAK13 conference, and to Dan Suthers and the  ... 
doi:10.18608/jla.2014.12.3 fatcat:gfw2hqs5qzgmtbpa7wqcmsxtzu

A Comparative Study on Big Data Analytics Frameworks, Data Resources and Challenges

Flasteen Abuqabita, Razan Al-Omoush, Jaber Alwidian
2019 Modern Applied Science  
In this study we categorized the existing frameworks which is used for processing the big data into three groups, namely as, Batch processing, Stream analytics and Interactive analytics, we discussed each  ...  In order to extract the value from this data and make sense of it, a lot of frameworks and tools are needed to be developed for analyzing it.  ...  and k-mean algorithm for clustering (Tsai et al..,2015) , but this image works also if we consider the output data as a row one other area.  ... 
doi:10.5539/mas.v13n7p1 fatcat:74icluidsnbd7koqximzjxzfii


Natalya Alekseevna Mulina, Moscow International University, Moscow, Russia, Vladimir Alekseevich Chvyakin, Moscow Polytechnic University, Moscow, Russia
Unlike the other two types of DBMS, relational data models do not need to look at all the pointers, which makes it easier to perform queries for fetching information compared to network and hierarchical  ...  .), but this is nothing more than a deception of the user. All these elements do not work, and when you try to click on any of them, the user simply gets to the advertiser's site.  ...  to which he makes a choice of this product from many others.  ... 
doi:10.46916/16022021-978-5-00174-130-5 fatcat:fiqvnwcrwfe6lhfcxreey4wczm

D3.2 Bigdataocean Harmonisation, Knowledge Extraction, Business Intelligence And Usage Analytics Services

Project Consortium Members
2017 Zenodo  
In the context of this deliverable, the first version of the various BigDataOcean services related to harmonisation, knowledge extraction, business intelligence and usage analytics service is reported.  ...  When you do stats, your sample size must be optimal -not too large or too small.  ...  analytics tools Analyses data Data volume that was used for all analyses performed from a particular dataset Analytics Queried data Data volume that was returned by queries from a particular  ... 
doi:10.5281/zenodo.1249381 fatcat:5utn7auknfe6zpfhg6sx6neh7q

High performance frequent subgraph mining on transaction datasets: A survey and performance comparison

Bismita S. Jena, Cynthia Khan, Rajshekhar Sunderraman
2019 Big Data Mining and Analytics  
Hendricus van der Holst for giving their precious time and serving as the review committee members.  ...  I thank the entire computer science department faculties and staffs who have educated me and made me eligible to reach this level.  ...  Graph 2 contains the subgraph E-D-C twice. Do note that although we count it as one instance of the subgraph, we do not discard the other instance before pruning.  ... 
doi:10.26599/bdma.2019.9020006 dblp:journals/bigdatama/JenaKS19 fatcat:lkmaerj3yvdkrkodrt6jwn7asm

Social Influence and Radicalization: A Social Data Analytics Study [article]

Vahid Moraveji Hashemi
2019 arXiv   pre-print
To address this challenge, we study and analyze the recent work done in influence maximization and social data analytics from effectiveness, efficiency and scalability viewpoints.  ...  We introduce a social data analytics pipeline, namely iRadical, to enable analysts engage with social data to explore the potential for online radicalization.  ...  position x i (0)∀i ∈ 1 : N ; of population gets generated depending on RHD, refer to algorithm 3 for more detail; 2.for n=1 to (xyz/2) do for m=1 to k do If rand(1) > 0.5 x i gets substituted with a  ... 
arXiv:1910.01212v1 fatcat:iskswunaxfcubalskz4fl4nvre


Mohammad Al Ojail, Surbhi Bhatia
2020 IEEE Access  
This research work will present a detailed analysis in user behavioral to use for business or Online Behavioral advertising and provide the framework of how Enterprise Resource Planning systems track the  ...  This is where an Enterprise Resource Planning driven data will give rise to behavioral analytics.  ...  Analytical Model The analytics model used in the paper (referred to as "M" from now on for brevity), will work on the data that is being streamed from the ERP database.  ... 
doi:10.1109/access.2020.3016419 fatcat:7wn6nijdh5exlb5bonaruj4bxu
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