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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Li, Jingbo Gai, Rongli Dalian University School of Information Engineering Dalian China

ISBN: (纸本)9781665494571

Non relational database is a very popular and popular database technology. It has the characteristics of large amount of data, high concurrency, strong reading and writing ability, flexible use, simple data structure and good scalability. Non relational database can solve the problem of data cache and reduce the connection of tables. Based on the analysis of the performance of non relational database, this paper compares the performance of several non relational databases. Firstly, this paper introduces the concept of non relational database and the classification of non relational database. Then the read and write performance of commonly used non-relational databases MongDB and Redis are compared in detail. Finally, the performance of four non-relational databases in different usage scenarios is compared. © 2021 IEEE.

关键词： Concurrent computing databases nosql databases Scalability Writing Data structures

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A Framework for Data Migration between Different Datastore of nosql Database

A Framework for Data Migration between Different Datastore o...

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2018 International Conference on ICT for Smart Society, ICISS 2018

作者： Wijaya, Yansyah Saputra Akhmadarman, Arry School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781538665893

Since its origin, the nosql database has achieved widespread use, but nosql (Not Only SQL) still a new concept in database technology that has much lack, especially the standard in terms of data migration from the nosql database to nosql database. This deficiency causes needs for a general migration framework that includes all stages of data migration. Many frameworks have developed to solve the data migration problem with a different solution, characteristics, and properties. This paper combines all the framework by comparing the existing framework, isolate an important variable to create a general framework. The proposed framework provides algorithm migration, model migration, and migration schemes, which will help in the data migration process. After testing and evaluation, the proposed framework is able to migrate data in the actual operating environment. However, this Framework still needs to be tested in other cases or using different data and other operating environments. The results of this research will help organizations or developers who need guidance on data migration by providing a general data migration framework. © 2018 IEEE.

关键词： nosql databases Data models Testing Data mining Diversity reception Standards

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Performance Scaling of Cassandra on High-Thread Count Servers 19

Performance Scaling of Cassandra on High-Thread Count Server...

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10th ACM/SPEC International Conference on Performance Engineering (ICPE)

作者： Talreja, Disha Lahiri, Kanishka Kalambur, Subramaniam Raghavendra, Prakash Adv Micro Devices Inc Santa Clara CA 95054 USA PES Univ Dept Comp Sci Bengaluru Karnataka India

ISBN: (纸本)9781450362399

nosql databases are commonly used today in cloud deployments due to their ability to "scale-out" and effectively use distributed computing resources in a data center. At the same time, cloud servers are also witnessing rapid growth in CPU core counts, memory bandwidth, and memory capacity. Hence, apart from scaling out effectively, it's important to consider how such workloads "scale-up" within a single system, so that they can make the best use of available resources. In this paper, we describe our experiences studying the performance scaling characteristics of Cassandra, a popular open-source, column-oriented database, on a single high-thread count dual socket server. We demonstrate that using commonly used benchmarking practices, Cassandra does not scale well on such systems. Next, we show how by taking into account specific knowledge of the underlying topology of the server architecture, we can achieve substantial improvements in performance scalability. We report on how, during the course of our work, we uncovered an area for performance improvement in the official open-source implementation of the Java platform with respect to NUMA awareness. We show how optimizing this resulted in 27% throughput gain for Cassandra under studied configurations. As a result of these optimizations, using standard workload generators, we obtained up to 1.44x and 2.55x improvements in Cassandra throughput over baseline single and dual-socket performance measurements respectively. On wider testing across a variety of workloads, we achieved excellent performance scaling, averaging 98% efficiency within a socket and 90% efficiency at the system-level.

关键词： Performance benchmarking Cassandra nosql databases Performance scalability

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Podpora MongoDB pro UnifiedPush Server

Podpora MongoDB pro UnifiedPush Server

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作者： Pecsérke, Róbert Brno University of Technology

Tato diplomová práce se zabývá návrhem a implementací rozšíření pro UnifiedPush Server, které serveru umožní přistupovat k nerelační databázi MongoDB a využ&... 详细信息

Tato diplomová práce se zabývá návrhem a implementací rozšíření pro UnifiedPush Server, které serveru umožní přistupovat k nerelační databázi MongoDB a využívá potenciál horiznotální škálovatelnosti neralačních databází. Součástí práce je i návrh výkonnostních testů a porovnání výkonu při behu na jednom a vícero uzlích, návrh migračního scénáře z MySQL na MongoDB, identifikace úzkých míst. Aplikace je implementována v jazyce Java a využívá Java Persistence API pro přístup k databázím. Pro přístup k nerelačním databázím používá implementaci standardu JPA Hibernate OGM.

关键词： nosql databáze MongoDB Aerogear UnifiedPush Server Java Persistence API horizontální škálovatelnost nosql databases MongoDB Aerogear UnifiedPush Server Java Persistence API horizontal scalability Text

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Discovering User Behavioral Features to Enhance Information Search on Big Data

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ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS 2017年第2期7卷 7-7页

作者： Cassavia, Nunziato Masciari, Elio Pulice, Chiara Sacca, Domenico ICAR CNR Arcavacata Di Rende CS Italy DIMES UNICAL Arcavacata Di Rende CS Italy Via P Bucci 41C I-87036 Arcavacata Di Rende CS Italy UMIACS Univ Maryland College Pk MD USA

Due to the emerging Big Data paradigm, driven by the increasing availability of intelligent services easily accessible by a large number of users (e.g., social networks), traditional data management techniques are inadequate in many real-life scenarios. In particular, the availability of huge amounts of data pertaining to user social interactions, user preferences, and opinions calls for advanced analysis strategies to understand potentially interesting social dynamics. Furthermore, heterogeneity and high speed of user-generated data require suitable data storage and management tools to be designed fromscratch. This article presents a framework tailored for analyzing user interactions with intelligent systems while seeking some domain-specific information (e.g., choosing a good restaurant in a visited area). The framework enhances a user's quest for information by exploiting previous knowledge about their social environment, the extent of influence the users are potentially subject to, and the influence they may exert on other users. User influence spread across the network is dynamically computed as well to improve user search strategy by providing specific suggestions, represented as tailored faceted features. Such features are the result of data exchange activity (called data posting) that enriches information sources with additional background information and knowledge derived from experiences and behavioral properties of domain experts and users. The approach is tested in an important application scenario such as tourist recommendation, but it can be profitably exploited in several other contexts, for example, viral marketing and food education.

关键词： nosql databases information extraction intelligent recommendation personal big data user behavior

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Optimization of Processing of Data Files in System DIRAC

Optimization of Processing of Data Files in System DIRAC

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作者： Adam, Martin Charles University of Prague

DIRAC is a software framework for distributed computing providing a complete solution to one (or more) user community requiring access to distributed resources. In this thesis the DIRAC File Catalog (DFC) is extended by adding a DatasetManager module, thus adding support for datasets based on metadata queries. To improve the metaquery handling in the code, a new class MetaQuery was implemented that bundles the handling methods and adds normalization and optimization of the user input. The metaquery language was extended enabling logical operators and parenthesis. In the second part of the thesis the hypothesis that connecting the metadata part of the DIRAC File Catalog to a nosql database could improve metaquery performance is evaluated. Several databases are tested and the best performing one is then connected via an interface module to the DFC. Powered by TCPDF (***)

关键词： System DIRAC nosql databases efficient processing of data files metadata querying

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Enabling schema-independent data retrieval queries in MongoDB

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INFORMATION SYSTEMS 2023年 114卷

作者： Cabral, Joao Vitor Lopes Noguera, Viviana Elizabeth Romero Ciferri, Ricardo Rodrigues Lucredio, Daniel UFSCar Fed Univ Sao Carlos Rodovia Washington LuisKm 235 BR-13565905 Sao Carlos SP Brazil Univ Sao Paulo ICMC Inst Math & Comp Sci Ave Trabalhador Sao Carlense 400 BR-13566590 Sao Carlos SP Brazil

nosql databases are designed to allow data to be stored without a fixed schema. In this scenario, writing data access code (queries and associated code) is challenging for two main reasons: (i) the query developer needs to know all details regarding the logical/physical schema;(ii) whenever the schema needs to change, all queries need to be rewritten. The literature presents some solutions to mitigate these challenges by making queries independent from the schema, but they are either restricted to simple queries or depend on a prescribed schema. In this paper, we propose a solution based on conceptual data modeling and code generation to enable the writing of complex data retrieval queries in a document-oriented database, independent from the logical/physical schema. We created a language for a classic ER algebra, with a concrete syntax and generative operational semantics targeting MongoDB. Based on the ideas of model management, the generative semantics uses a model that establishes the mapping between entities, relationships and document collections. From a single ER-based data retrieval query, native query code is automatically generated for any logical/physical schema. Additionally, the resulting data structure produced by the generated code is always the same. Tests show that our implementation produces consistent results. Also, we show that our solution is able to obtain up to 500% gains in throughput and response time by simply changing the schema, without modifying the queries. Our solution requires a little extra effort from the database designer, to create the mapping, but makes the job of the query developer easier. It also results in more flexibility. Whenever the schema changes, only the mapping needs to be updated, not the queries.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： nosql databases Model management Code generation Query rewriting Entity -Relationship algebra

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Data in the time of COVID-19: a general methodology to select and secure a nosql DBMS for medical data

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PEERJ COMPUTER SCIENCE 2020年 6卷 e297页

作者： ElDahshan, Kamal A. AlHabshy, AbdAllah A. Abutaleb, Gaber E. Al Azhar Univ Fac Sci Math Dept Cairo Egypt

Background. As the COVID-19 crisis endures and the virus continues to spread globally, the need for collecting epidemiological data and patient information also grows exponentially. The race against the clock to find a cure and a vaccine to the disease means researchers require storage of increasingly large and diverse types of information;for doctors following patients, recording symptoms and reactions to treatments, the need for storage flexibility is only surpassed by the necessity of storage security. The volume, variety, and variability of COVID-19 patient data requires storage in nosql database management systems (DBMSs). But with a multitude of existing nosql DBMSs, there is no straightforward way for institutions to select the most appropriate. And more importantly, they suffer from security flaws that would render them inappropriate for the storage of confidential patient data. Motivation. This paper develops an innovative solution to remedy the aforementioned shortcomings. COVID-19 patients, as well as medical professionals, could be subjected to privacy-related risks, from abuse of their data to community bullying regarding their medical condition. Thus, in addition to being appropriately stored and analyzed, their data must imperatively be highly protected against misuse. Methods. This paper begins by explaining the five most popular categories of nosql databases. It also introduces the most popular nosql DBMS types related to each one of them. Moreover, this paper presents a comparative study of the different types of nosql DBMS, according to their strengths and weaknesses. This paper then introduces an algorithm that would assist hospitals, and medical and scientific authorities to choose the most appropriate type for storing patients' information. This paper subsequently presents a set of functions, based on web services, offering a set of endpoints that include authentication, authorization, auditing, and encryption of information. These functions ar

关键词： nosql databases Database security Key-value stores nosql systems Document-based stores nosql systems Column-based stores nosql systems Graph stores nosql systems Object Store nosql systems COVID-19 patients' data

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Design a Data Warehouse Schema from Document-Oriented database

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Procedia Computer Science 2019年 159卷 221-230页

作者： Senda Bouaziz Ahlem Nabli Faiez Gargouri MIRACL Laboratory Faculty of Economics and Management Sfax BP 3018 Tunisia MIRACL Laboratory Faculty of Computer Sciences and Information Technologies Al-Baha University KSA MIRACL Laboratory Institute of Computer Science and Multimedia Sfax BP 3021 Tunisia

Traditional data warehouses are unable to meet the growing needs of the modern enterprise to integrate and analyze a wide variety of data generated by social, mobile and sensor sources. What is remarkable is that many companies have changed their data storage in nosql databases. Given the important role played by this type of databases, it is necessary to study nosql databases as a data source for the modeling and the implementation of data warehouses. This paper proposes a method to design the data warehouse schema from schema free databases known as nosql databases. Our proposal starts with the extraction of schemes from document-oriented databases as an example of nosql database. This extraction is performed based on the MapReduce paradigm. Then, it defines the structure identification graph from the extracted schemes. This graph will help the designer to identify the multidimensional concepts for each schema extracted in order to design the global data warehouse schema.

关键词： nosql databases Map-Reduce Data Warehouse Schema Design Document-oriented database Extraction

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CryptDICE: Distributed data protection system for secure cloud data storage and computation

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INFORMATION SYSTEMS 2021年 96卷 101671-101671页

作者： Rafique, Ansar Van Landuyt, Dimitri Beni, Emad Heydari Lagaisse, Bert Joosen, Wouter Katholieke Univ Leuven Imec DistriNet B-3001 Leuven Belgium

Cloud storage allows organizations to store data at remote sites of service providers. Although cloud storage services offer numerous benefits, they also involve new risks and challenges with respect to data security and privacy aspects. To preserve confidentiality, data must be encrypted before outsourcing to the cloud. Although this approach protects the security and privacy aspects of data, it also impedes regular functionality such as executing queries and performing analytical computations. To address this concern, specific data encryption schemes (e.g., deterministic, random, homomorphic, order-preserving, etc.) can be adopted that still support the execution of different types of queries (e.g., equality search, full-text search, etc.) over encrypted data. However, these specialized data encryption schemes have to be implemented and integrated in the application and their adoption introduces an extra layer of complexity in the application code. Moreover, as these schemes imply trade-offs between performance and security, storage efficiency, etc, making the appropriate trade-off is a challenging and non-trivial task. In addition, to support aggregate queries, User Defined Functions (UDF) have to be implemented directly in the database engine and these implementations are specific to each underlying data storage technology, which demands expert knowledge and in turn increases management complexity. In this paper, we introduce CryptDICE, a distributed data protection system that (i) provides builtin support for a number of different data encryption schemes, made accessible via annotations that represent application-specific (search) requirements;(ii) supports making appropriate trade-offs and execution of these encryption decisions at diverse levels of data granularity;and (iii) integrates a lightweight service that performs dynamic deployment of User Defined Functions (UDF) -without performing any alteration directly in the database engine- for heterogeneous NoS

关键词： Data security and privacy nosql databases Search over encrypted data Database-as-a-Service Data encryption Cloud computing Query processing Computation over encrypted data

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