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IEEE International Conference on Smart City

作者： Wenduo Feng Ping Gu Chao Zhang Kai Zhou School of Computer Electronics and Information Guangxi University

ISBN: (纸本)9781509018949

The coming of big data era seriously challenges many traditional database techniques and it also explains the popularity of nosql databases, Cassandra, for example. Storing data in these nosql databases is a prerequisite for applying some popular large-scale data processing frameworks such as Hadoop or Spark. In this paper, we propose a model transformation approach that transforms class diagrams into Cassandra database schemata, which make it possible to obtain larger storage capacity and large-scale data processing ability without painful database schema redesigning. To achieve this goal, meta-models of the source model and target model are built by simplifying the definition of the UML class diagram and studying the Cassandra data model respectively. An annotation system is designed to improve the transformation, i.e., a more appropriate schema for Cassandra and expected runtime performance are achieved by adding extra information about query patterns to the transformation phase. This transformation is implemented with the ATL Transformation Language (ATL).

关键词： Model transformation Class diagram Cassandra nosql database Model driven architecture

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High dimensional biological data retrieval optimization with nosql technology

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BMC GENOMICS 2014年第Sup8期15卷 S3-S3页

作者： Wang, Shicai Pandis, Ioannis Wu, Chao He, Sijin Johnson, David Emam, Ibrahim Guitton, Florian Guo, Yike Univ London Imperial Coll Sci Technol & Med Dept Comp Discovery Sci Grp London SW7 2AZ England

Background: High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in nosql databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results: In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions: The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that nosql technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new dat

关键词： Virtual Machine Relational Model Query Performance Hadoop Distribute File System nosql database

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Research and Application of Machine Learning on Geographic Information System

Research and Application of Machine Learning on Geographic I...

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作者： Zhenjiang Dong Peng Yang Zhicheng Ma Yongbiao Chen Shanghai Jiao Tong University Gansu State Grid Information & Telecommunication Co. Ltd.

In the big data era, an information system that is able to flexibly scale out, store mass data and quickly response to concurrent requests is particularly important. Despite the mature mining technologies on structured data, the utilization of unstructured data is still inadequate which results in the waste of data sources. Under this circumstance, this paper adopts machine-learning technologies to build a salable information system by analyzing Geographical landform data.

关键词： Machine Learning nosql database Neural Network Recommender System Collaborative Filtering

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Managing High-Density Genotyping Data with Gigwa

Managing High-Density Genotyping Data with Gigwa

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作者： Guilhem Sempéré Pierre Larmande Mathieu Rouard

Next generation sequencing technologies enabled high-density genotyping for large numbers of samples. Nowadays SNP calling pipelines produce up to millions of such markers, but which need to be filtered in various ways according to the type of analyses. One of the main challenges still lies in the management of an increasing volume of genotyping files that are difficult to handle for many applications. Here, we provide a practical guide for efficiently managing large genomic variation data using Gigwa, a user-friendly, scalable and versatile application that may be deployed either remotely on web servers or on a local machine. less

关键词： Genotyping Next Generation Sequencing SNP Calling Genome Visualization Genomics Genome Assembly Web tool VCF Interoperability SNP markers nosql database INDELs

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Heterogeneous database System for Faster Data Querying using Elasticsearch

Heterogeneous Database System for Faster Data Querying using...

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International Conference on Computing Communication Control and Automation

作者： Umesh Taware Nuzhat Shaikh Department of computer Engineering MES College of Engineering Pune India

ISBN: (纸本)9781538652589;9781538652572

Nowadays data is increasing at such high rate there is need of tool which can analyze this data in equally efficient matter, as this data analysis contributes to crucial decision making while dealing with day to day business scenarios. It is quite impractical to analyze this data with traditional relational database tools. There has been new growth in technologies which increases our ability to process to this data, Hadoop and nosql databases are some of the names that are very popular these for the same reason. In particular, Elasticsearch is most preferred tool now a days, it is text-based search engine developed by Apache Foundation. It is near real time, highly scalable and distributed tool to search, analyze and store your data. Hybrid database system proposes a solution to most common problem of increased data retrieval time as the size of data increases.

关键词： Elasticsearch Full-text search nosql database Search engine

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A Secure Threshold Secret Sharing Framework for database Outsourcing

A Secure Threshold Secret Sharing Framework for Database Out...

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International Conference on Advanced Communication Control and Computing Technologies

作者： Ajeet Ram Pathak B. Padmavathi Department of Computer Engineering G. H. Raisoni College of Engineering and ManagementPune 412207 India

ISBN: (纸本)9781479939152

Due to advancement in cloud computing technology and significant growth in database technology, database as a Service (DBaaS) has become the breakaway technology of the recent era. It is the paramount solution for managing and administering the outsourced databases. Though the users are availed through the database services, the security of databases being outsourced is not guaranteed as the database service provider can be deceitful. Therefore, implementing the security in outsourced databases is a grand challenge. In this paper, we have proposed a secure framework for achieving the confidentiality, integrity in outsourced databases using the customized secret sharing approach and polynomial interpolation. The completeness and correctness dimensions are considered for achieving the integrity. To the best of our findings, our framework is the first which provides security solutions to alphanumeric data, string, special symbols and any kind of database including nosql databases which support hash index. The multiple indexing in our research allows the user to search and process the query efficiently based on multiple searchable attributes.

关键词： Confidentiality Completeness Correctness DBaaS Integrity nosql database

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A Literature Review on Schema Evolution in databases

Computing Open

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Computing Open 2024年第2期computing-open卷

作者： Zouhaier Brahmia Fabio Grandi Barbara Oliboni Department of Computer Science Faculty of Economics and Management University of Sfax Road of the Aerodrome Km 4.5 P.O. Box 1088 3018 Sfax Tunisia Dipartimento di Informatica – Scienza e Ingegneria Alma Mater Studiorum – Università di Bologna Viale Risorgimento 2 I-40136 Bologna Italy Department of Computer Science University of Verona Ca' Vignal 2 Strada Le Grazie 15 I-37134 Verona Italy

Changing a database schema is a fact of life in information systems, as a response to changes inside the enterprise (e.g., new users’ requirements, correction of errors in the current database schema) or outside it (e.g., new regulations, new partners’ requirements). In the database research field, a well-known technique has been proposed for managing schema changes, called schema evolution . It allows the database to survive schema changes by adapting existing data to conform to the new schema. A lot of research efforts addressed the topic of schema evolution, in both conventional (i.e., relational) and advanced (e.g., XML, stream, nosql) databases, providing a plethora of heterogeneous approaches and solutions making up a quite large literature. Since there is no research work that extensively deals with different proposals and compares them, the purpose of this paper is to fill this gap by reviewing the available schema evolution literature. For that, first we collected and summarized the contributions of research papers dealing with database schema evolution. Then we organized their presentation in a chronological order, also giving a historical perspective on the topic development. Finally, we defined a list of six comparison criteria (database model, implementation, schema change semantics, schema change propagation, integrity constraints, and software evolution) that have helped us to categorize and compare the different database schema evolution proposals. In sum, our paper (i) provides an overview of the state-of-the-art research approaches on database schema evolution, with tables that compare such approaches based on some proposed criteria, (ii) studies the support of schema evolution in commercial database Management Systems (DBMSs), and (iii) points out some possible future research directions in this area.

关键词： database schema schema change schema change semantics schema change propagation schema evolution database evolution relational database object-oriented database XML database nosql database multi-model database

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Electrical production data of a domestic grid-connected rooftop PV plant in normal and shading faults conditions associated with solar and meteorological data in a tropical climate

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DATA IN BRIEF 2023年 46卷 108723页

作者： Graillet, Alexandre Lebreton, Carole Tang, Chao Kbidi, Fabrice Jegado, Tifenn Damour, Cedric Benne, Michel Univ Reun ENERGY Lab 15 Ave Rene Cassin CS 92003 F-97744 St Senis 9 France

The proposed measured data combines PV plant electrical data with associated solar and meteorological data during normal and faulty conditions. Data are collected regarding a domestic rooftop PV plant of 4 kW, located in the La Reu-nion Island, in the South-West of Indian Ocean. The present dataset includes healthy behavior and different types of shading faults, identified and labelled by means of a numeric variable. The electrical data (voltage, current and power at AC and DC side as well as produced energy and grid fre-quency) are collected thanks to PV inverters. Global and diffuse irradiance, PV temperature and ambient temperature are acquired thanks to additional sensors. Electrical and mete-orological data sampling frequencies are set to 0.2 Hz and 1 Hz respectively. At present, 12 months of data are avail-able and the database is still being updated. The data streams from each connected device require proper techniques to ensure their persistence. To be able to provide both efficient ingestion and retrieval of these time series collections, the nosql database management system InfluxDB has been im-plemented. The whole dataset is available on Zenodo repository, and can be used, for instance, for PV modeling, PV plant behavior analysis, PV production forecasting and PV Fault Detection and Diagnosis (FDD) tool development.(c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Photovoltaic system Shading faults Electrical production Temperature Solar irradiance nosql database

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Schema Versioning in databases: A Literature Review

Computing Open

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Computing Open 2024年第2期computing-open卷

作者： Zouhaier Brahmia Fabio Grandi Barbara Oliboni Department of Computer Science Faculty of Economics and Management University of Sfax Road of the Aerodrome Km 4.5 P.O. Box 1088 3018 Sfax Tunisia Dipartimento di Informatica – Scienza e Ingegneria Alma Mater Studiorum – Università di Bologna Viale Risorgimento 2 I-40136 Bologna Italy Department of Computer Science University of Verona Ca’ Vignal 2 Strada Le Grazie 15 I-37134 Verona Italy

Changes involving the database schema are unavoidable events that sometimes occur in data-centric systems, due to many reasons like evolution of user requirements, corrective maintenance, improvement of the current schema with the addition of new integrity constraints, implementation of new business rules, or compliance to new regulations. In order to manage schema changes, researchers have proposed a technique named “schema versioning”, in which all versions of the database schema are kept along with their underlying data, preventing loss of information and obsolescence of legacy applications. This technique has been widely studied in both conventional and emerging databases. Despite lot of interesting research efforts that have dealt with database schema versioning and the importance of this technique for database maintenance, current database Management Systems (DBMSs) do not provide sufficient support for its implementation. This paper (i) gives an overview of state-of-the-art research approaches to schema versioning in databases, based on the study of more than 270 papers and providing a historical perspective on the development of the topic, (ii) illustrates the support of schema versioning in commercial DBMSs, and (iii) points out some possible future research directions in this area.

关键词： database schema schema changes schema change semantics schema change propagation schema versioning database conversion relational database object-oriented database XML database nosql database Data Warehouse

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