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The CloudMdsQL Multistore System

Published: 26 June 2016 Publication History

Abstract

The blooming of different cloud data management infrastructures has turned multistore systems to a major topic in the nowadays cloud landscape. In this demonstration, we present a Cloud Multidatastore Query Language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized. Within our demonstration, we focus on two use cases each involving four diverse data stores (graph, document, relational, and key-value) with its corresponding CloudMdsQL queries. The query execution flows are visualized by an embedded real-time monitoring subsystem. The users can also try out different ad-hoc queries, not necessarily in the context of the use cases.

References

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Bondiombouy, C., Kolev, B., Levchenko, O., Valduriez, P. 2015. Integrating Big Data and Relational Data with a Functional SQL-like Query Language. DEXA, 170--185.
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DeWitt, D., Halverson, A., Nehme, R., Shankar, S., Aguilar-Saborit J., Avanes, A., Flasza, M., Gramling, J. 2013. Split Query Processing in Polybase. In ACM SIGMOD (2013), 1255--1266.
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Duggan, J., Elmore, A. J., Stonebraker, M., Balazinska, M., Howe, B., Kepner, J., Madden, S., Maier, D., Mattson, T., Zdonik, S. 2015. The BigDAWG Polystore System. SIGMOD Rec. 44, 2 (August 2015), 11--16. DOI=http://dx.doi.org/10.1145/2814710.2814713
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Guimarães, P., Pereira, J. 2015. X-Ray: Monitoring and Analysis of Distributed Database Queries, In 15th IFIP WG 6.1 International Conference, DAIS, 80--93.
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Kolev, B., Valduriez, P., Bondiombouy, C., Jiménez-Peris, R., Pau, R., Pereira, J. 2015. CloudMdsQL: Querying Heterogeneous Cloud Data Stores with a Common Language. Distributed and Parallel Databases, pp 1--41, http://hal-lirmm.ccsd.cnrs.fr/lirmm-01184016.
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LeFevre, J., Sankaranarayanan, J., Hacıgümüs, H., Tatemura, J., Polyzotis, N., Carey, M. 2014. MISO: Souping Up Big Data Query Processing with a Multistore System. In ACM SIGMOD (2014), 1591--1602.
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Özsu, T., Valduriez, P. 2011. Principles of Distributed Database Systems -- Third Edition. Springer, 850 pages.

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cover image ACM Conferences
SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data
June 2016
2300 pages
ISBN:9781450335317
DOI:10.1145/2882903
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 June 2016

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Author Tags

  1. SQL and noSQL integration
  2. cloud
  3. heterogeneous data stores
  4. multistore system

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  • Research-article

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SIGMOD/PODS'16
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SIGMOD/PODS'16: International Conference on Management of Data
June 26 - July 1, 2016
California, San Francisco, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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  • (2024)ECQL: Towards Succinct and Extensible Modeling of Multi-model Query ResultsConceptual Modeling10.1007/978-3-031-75872-0_7(112-130)Online publication date: 21-Oct-2024
  • (2023)SQL and NoSQL Database Software Architecture Performance Analysis and Assessments—A Systematic Literature ReviewBig Data and Cognitive Computing10.3390/bdcc70200977:2(97)Online publication date: 12-May-2023
  • (2023)60 Years of Databases (final part)PROBLEMS IN PROGRAMMING10.15407/pp2023.01.066(66-103)Online publication date: Jan-2023
  • (2023)In-Situ Cross-Database Query Processing2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00214(2794-2807)Online publication date: Apr-2023
  • (2023)Extracting Graphs Properties with Semantic Joins2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00175(2262-2275)Online publication date: Apr-2023
  • (2023)Empowering Data Federation Security in Polystore Systems2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA59173.2023.10479321(1-8)Online publication date: 4-Dec-2023
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  • (2022)Big graphsProceedings of the VLDB Endowment10.14778/3554821.355489915:12(3782-3797)Online publication date: 1-Aug-2022
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