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18th International Conference on Hybrid Artificial Intelligence Systems

作者： Matias, Rosa Piedade, Maria Beatriz Polytech Leiria Sch Technol & Management P-2411901 Leiria Portugal Polytech Leiria Sch Technol & Management Comp Sci & Commun Res Ctr CIIC P-2411901 Leiria Portugal

ISBN: (纸本)9783031407246;9783031407253

For decades the multidimensional model has been applied to development data warehouses. It usually consists of a fact table surrounded by dimensional tables. It aims to enhance the exploration of historical data and is supported mostly by relational databases. Meanwhile the evolution to Big Data is responsible for the proliferation of other types of databases namely document-oriented databases. They store the data in collections of documents such as JSON documents. In this context some efforts have been made to adapt the multidimensional model to document-oriented databases to take advantages of the exploration capabilities provided by it. The model adaptation efforts suggest: (i) a collection of documents only with fields representing both measures and dimensions;(ii) a collection of documents with fields representing measures and with subdocuments representing dimensions;(iii) collections for facts and collections for dimensions. In this work it is presented a study about the mentioned approaches. Three document-oriented data warehouses are developed using the same scenario. Nevertheless, each uses a different approach. Later, the same group of analytical queries is applied to them to identify the commands complexity and gather execution times. The results show that the first and second approaches outperforms the third. The second approach has a richer organization and requires less storage space regarding the first. A schema for a metamodel is presented to couple the multidimensional model to document data warehouses to eliminate the gap between them.

关键词： Decision Support Systems Multidimensional Model nosql databases

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Graph databases Assessment: JanusGraph, Neo4j, and TigerGraph

Graph Databases Assessment: JanusGraph, Neo4j, and TigerGrap...

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International Conference on Information Technology and Education (ICITED)

作者： Monteiro, Jessica Sa, Filipe Bernardino, Jorge Polytech Coimbra ISEC Rua Pedro Nunes P-3030199 Coimbra Portugal

ISBN: (纸本)9789811965876;9789811965852;9789811965845

Over time, data growth across technology platforms has become a challenge for relational databases. Therefore, it becomes difficult to store and process massive volumes of data and data where the schema is represented by graphs, such as social networking sites. Graph databases emerged as the solution, wherein entities from the domain of interest are represented by nodes and relationships between them by edges. The main objective of this paper is to find out which of the top three open source graph databases are the most complete and efficient. According to DB-Engines Ranking, the top three graph databases are: JanusGraph, Neo4j, and TigerGraph. We apply the OSSpal methodology, which consists of an evaluation based on qualitative and quantitative measures to these databases. The evaluation categories of the OSSpal methodology are focused on software functionalities, attributes and features, available documentation, support and service, user community, and graph database development.

关键词： Graph databases nosql databases OSSpal methodology Open source tools JanusGraph Neo4j TigerGraph

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Towards Leveraging Artificial Intelligence for nosql Data Modeling, Querying and Quality Characterization

Towards Leveraging Artificial Intelligence for NoSQL Data Mo...

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ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS)

作者： Asaad, Chaimae Mohammed V Univ Rabat Int Univ Rabat Rabat IT CtrTicLab AlqualsadiENSIASFac Engn & Architecture Rabat Morocco

ISBN: (纸本)9798350324983

In the last two decades, nosql databases emerged and formed an umbrella category grouping well over a hundred databases of different characteristics, and providing a new take on scalability, availability, consistency and data modeling, with the aim of conquering the classic one-size-fits-all solution represented in traditional databases. nosql databases' heterogeneity, flexibility and high performance allowed them to encompass the volume, velocity and variety challenges brought by the Big Data era and to fulfill the complex requirements of real-time applications. These advantages have given them a competitive edge in the database market. However, despite these added bonuses, a wider adoption of nosql has been hindered by a few challenges. The "schema-less" nature of nosql databases allowing data to be directly ingested, without defining a schema a priori, can be a deterrent for many users given its potential impact on data management and integrity, application complexity and system integration. Additionally, the heterogeneous nature of nosql databases creates a complex and diverse landscape of query languages and interfaces requiring extensive and wideranging expertise. In an effort to breach the standardization and democratization of nosql databases, I propose an approach integrating artificial intelligence techniques in nosql life cycles, namely: data modeling, querying and quality assessment. This approach offers multi-faceted contributions to the literature and the industry, including: a uniform design methodology for nosql databases, an intelligent bi-directional mapping between higher and lower level nosql schema representations, the generation of logical and physical nosql data models from requirements specified in natural language, intelligent and bi-directional generation of a nosql query from a prompt expressed in natural language, and a multi-stakeholder nosql database-agnostic quality characterization framework. With this approach, I aim to pave the way

关键词： nosql databases Database Design Query Languages Natural Language Querying Data Model Quality Assesment Artificial Intelligence

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A Semantic Space-Time Event Representation Model in Production Equipment Monitoring of Technical State and Utilization Condition 8

A Semantic Space-Time Event Representation Model in Producti...

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8th International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Petrina, Oksana Marchenkov, Sergei Korzun, Dmitry Petrozavodsk State Univ Inst Math & Informat Technol Dept Comp Sci Lenin Ave 33 Petrozavodsk 185910 Republic Of Kar Russia

ISBN: (纸本)9781665496070

Production equipment monitoring is implemented in emerging applications of Industrial Internet of Things (IIoT). The goal of monitoring is detection of technical state and utilization condition. The collected data form the basis of so called "digital twin". In this paper, we introduce a semantic space-time event representation model, which is used for data fusion of multiple events on technical state and utilization condition of production equipment. The model describes monitoring objects and their surrounding context. The model considers a hierarchy of production equipment nodes and implements rules for identifying and composing events in the production process. The model is oriented to a graph database for collecting and linking the evens in space and time dimensions. As a result, efficient search queries can be used to construct diagnostic and predictive services on top of the database.

关键词： databases nosql databases Semantics Production equipment Prototypes Data models Sensors

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Apache ShardingSphere: A Holistic and Pluggable Platform for Data Sharding 38

Apache ShardingSphere: A Holistic and Pluggable Platform for...

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38th IEEE International Conference on Data Engineering (ICDE)

作者： Li, Ruiyuan Zhang, Liang Pan, Juan Liu, Junwen Wang, Peng Sun, Nianjun Wang, Shanmin Chen, Chao Gu, Fuqiang Guo, Songtao Chongqing Univ Coll Comp Sci Chongqing Peoples R China SphereEx Lab Beijing Peoples R China JD Technol JD iCity Beijing Peoples R China

ISBN: (数字)9781665408837

ISBN: (纸本)9781665408837

Traditional relational databases are nowadays overwhelmed by the increasing data volume and concurrent access. nosql databases can manage large-scale data, but most of them do not support complete transactions and standard SQL languages. NewSQL is proposed for both high scalability and transactional properties with SQL languages support. One type of NewSQL builds distributed systems from scratch, which is too radical for some critical applications. The other type of NewSQL, i.e., data sharding among relational databases, is a better option for these scenarios. This paper presents Apache ShardingSphere, the first toplevel open-source platform for data sharding in Apache, which enables developers to use sharded databases like one database. Specifically, Apache ShardingSphere integrates six databases, and designs and implements a complete SQL engine to route requests correctly and intelligently. Additionally, it encapsulates three types of distributed transactions, and provides two adaptors for different scenarios. Moreover, it proposes a novel AutoTable strategy and a query language, i.e., DistSQL, allowing database maintainers to easily configure the sharded databases. Furthermore, it provides many other pluggable features to better shard data. Extensive experiments are conducted using two famous benchmarking tools, proving that Apache ShardingSphere is more efficient than eight state-of-the-art systems in our settings. All experimental source codes are publicly released. More than 170 companies are currently using Apache ShardingSphere.

关键词： Structured Query Language Scalability nosql databases Conferences Relational databases Companies Data engineering

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HyDRa: A Framework for Modeling, Manipulating and Evolving Hybrid Polystores 29

HyDRa: A Framework for Modeling, Manipulating and Evolving H...

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29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Gobert, Maxime Meurice, Loup Cleve, Anthony Univ Namur PReCISE Res Ctr Namur Digital Inst Namur Belgium

ISBN: (纸本)9781665437868

Data-intensive system evolution is a complex and error-prone process, as most evolution scenarios impact several interdependent artefacts such as the application code, the data structures or data instances. This process is becoming even more challenging with the emergence of heterogeneous database architectures, commonly called hybrid polystores, that rely on a combination of several, possibly overlapping relational and nosql databases. This paper presents HyDRa, a framework aiming to facilitate the evolution of polystores thanks to automatically generated data access APIs. For a given polystore, a conceptual API can be derived from the conceptual schema of the polystore and its correspondences with the physical schemas of the underlying databases. Applications built on top of the generated API are then protected from future schema and data reconfiguration changes applied to the polystore. Furthermore, HyDRa automatically enforces cross-database data integrity constraints and does not require developers to master multiple data models and query languages. This paper presents HyDRa and demonstrates its main features based on open-source datasets and realistic use cases.

关键词： Analytical models Codes databases nosql databases Data integrity Conferences Data structures

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FacetsBase: A Key-Value Store Optimized for Querying on Scholarly Data

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2021年第1期9卷 302-315页

作者： Song, Jie Bi, Yuanguo Han, Guangjie Li, Tiantian Northeastern Univ Software Coll Shenyang 110006 Peoples R China Northeastern Univ Sch Comp Sci & Engn Shenyang 110006 Peoples R China Dalian Univ Technol Sch Software Technol Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116023 Peoples R China

As an emerging topic, scholarly big data is the vast quantity of research output that requires sophisticated platforms and tools for creating applications that can benefit the research community. This paper addresses the applied research in storing, indexing, and querying scholarly big data. The relational databases, which employ a pre-defined and well-partitioned data model are not flexible, while the nosql databases lack sophisticated index and partition mechanisms. The proposed FacetsBase, which is a Hadoop-based key-value data store, combines the performance advantages of a relational database, the flexibility of a nosql database and the parallelism of a distributed file system. It partitions and indexes the publication information using the concept of facets, it stores facetsin a multi-dimensional logical data model and lower-cost file format, and it provides the attribute-specified query and attribute-unspecific query. In experiments, FacetsBase was compared with Hive, HBase, MongoDB, and Cassandra in terms of query performance. The results indicate that FacetsBase performs 1.4x, 3.8x, 1.4x, and 2.9x faster on average, respectively.

关键词： Big Data Metadata Indexing Relational databases nosql databases Scholarly big data facet key-value stores optimization query storage

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Key-Value vs Graph-based data lakes for realizing Digital Twin systems (Poster) 10

Key-Value vs Graph-based data lakes for realizing Digital Tw...

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STAF 2022 Workshop: 10th International Workshop on Bidirectional Transformations, BX 2022, 2nd International Workshop on Foundations and Practice of Visual Modeling, FPVM 2022 and 2nd International Workshop on MDE for Smart IoT Systems, MeSS 2022

作者： Pérez-Porras, Daniel Muñoz, Paula Troya, Javier Vallecillo, Antonio University of Málaga Itis Software Spain

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OLAP and nosql: Happily Ever After 26th

OLAP and NoSQL: Happily Ever After

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26th European Conference on Advances in databases and Information Systems (ADBIS)

作者： Rizzi, Stefano Univ Bologna DISI Viale Risorgimento 2 I-40136 Bologna Italy

ISBN: (纸本)9783031157400;9783031157394

nosql databases are preferred to relational ones for storing heterogeneous data with variable schema and structure. However, their schemaless nature adds complexity to analytical applications, in which a single OLAP analysis often involves large sets of data with different schemas. In this tutorial we describe the main approaches to enable OLAP on nosql data. We start from schema-on-read approaches, where data are left unchanged in their structure until they are accessed by the user, so they are put into multidimensional form at query time. Specifically, we show how this enables a form of approximated OLAP that embraces the inherent variety of schemaless data. Then we move to schema-on-write approaches, where a fixed multidimensional structure is forced onto data, which are loaded into a data warehouse to be then queried. In particular, we introduce multi-model data warehouses as a way to store data in multidimensional form and, at the same time, let each piece of data be natively represented through the most appropriate nosql model.

关键词： nosql databases OLAP Multi-model databases

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Low Latency and High Throughput Write-Ahead Logging Using CAPI-Flash

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2021年第3期9卷 1129-1142页

作者： Sendir, Bedri Govindaraju, Madhusudhan Odaira, Rei Hofstee, Peter SUNY Binghamton Binghamton NY 13902 USA IBM Res Austin TX USA Delft Univ Technol NL-2628 Delft Netherlands

High-velocity data imposes high durability overheads on Big Data technology components such as nosql data stores. In Apache Cassandra and MongoDB, widely used nosql solutions with high scalability and availability, write-ahead logging is used to provide durability. However, current write-ahead logging techniques are limited by the excessive overhead in the I/O subsystem. To address this performance gap, we have designed a novel CAPI-Flash based high performance durable logging mechanism for Apache Cassandra and MongoDB. We take advantage of the high throughput, low latency path to flash storage provided by the Coherent Accelerator Processor Interface (CAPI) on IBM POWER8 Systems. Our experimental results show that for insert-only workloads, CAPI-Flash logging provides up to 70 and 514 percent improvement in throughput compared to Cassandra and MongoDB's durable alternatives, respectively. It also provides average of 45 percent increase in throughput with Cassandra and average of 115 percent increase in throughput with MongoDB for update-mostly and update-only workloads.

关键词： Big data nosql databases MongoDB apache cassandra write-ahead-logging flash storage CAPI-flash durability coherent accelerator processor interface

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