A Study on Join Operations in MongoDB Preserving Collections Data Models for Future Internet Applications

被引:12
作者
Celesti, Antonio [1 ,2 ]
Fazio, Maria [1 ,3 ]
Villari, Massimo [1 ,3 ]
机构
[1] Univ Messina, Dept MIFT, I-98166 Messina, Italy
[2] BIG DATA Lab CINI, Via Volturno,58, I-00185 Rome, Italy
[3] IRCCS Ctr Neurolesi Bonino Pulejo, Contrada Casazza,SS113, I-98124 Messina, Italy
来源
FUTURE INTERNET | 2019年 / 11卷 / 04期
关键词
future internet; big data; NoSQL; MongoDB; join; SYSTEM;
D O I
10.3390/fi11040083
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Presently, we are observing an explosion of data that need to be stored and processed over the Internet, and characterized by large volume, velocity and variety. For this reason, software developers have begun to look at NoSQL solutions for data storage. However, operations that are trivial in traditional Relational DataBase Management Systems (DBMSs) can become very complex in NoSQL DBMSs. This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases. As a consequence, the data model has to be changed or a set of operations have to be performed to address particular queries on data. Thus, open questions are: how do NoSQL solutions work when they have to perform join operations on data that are not natively supported? What is the quality of NoSQL solutions in such cases? In this paper, we deal with such issues specifically considering one of the major NoSQL document oriented DB available on the market: MongoDB. In particular, we discuss an approach to perform join operations at application layer in MongoDB that allows us to preserve data models. We analyse performance of the proposes approach discussing the introduced overhead in comparison with SQL-like DBs.
引用
收藏
页数:17
相关论文
共 25 条
  • [1] [Anonymous], 2016, FED CONF COMPUT SCI, DOI DOI 10.15439/2016F45
  • [2] Brewer Eric A, 2000, PODC, V7
  • [3] Toward Improving Robotic-Assisted Gait Training: Can Big Data Analysis Help Us?
    Carnevale, Lorenzo
    Calabro, Rocco Salvatore
    Celesti, Antonio
    Leo, Antonino
    Fazio, Maria
    Bramanti, Placido
    Villari, Massimo
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (02) : 1419 - 1426
  • [4] How to Conceive Future Mobility Services in Smart Cities according to the FIWARE frontierCities Experience
    Carnevale, Lorenzo
    Celesti, Antonio
    Di Pietro, Maria
    Galletta, Antonino
    [J]. IEEE CLOUD COMPUTING, 2018, 5 (05): : 25 - 36
  • [5] Celesti A., 2016, P 39 INT CONV INF CO
  • [6] An IoT Cloud System for Traffic Monitoring and Vehicular Accidents Prevention Based on Mobile Sensor Data Processing
    Celesti, Antonio
    Galletta, Antonino
    Carnevale, Lorenzo
    Fazio, Maria
    Lay-Ekuakille, Aime
    Villari, Massimo
    [J]. IEEE SENSORS JOURNAL, 2018, 18 (12) : 4795 - 4802
  • [7] An OAIS-Based Hospital Information System on the Cloud: Analysis of a NoSQL Column-Oriented Approach
    Celesti, Antonio
    Fazio, Maria
    Romano, Agata
    Bramanti, Alessia
    Bramanti, Placido
    Villari, Massimo
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2018, 22 (03) : 912 - 918
  • [8] Are Next-Generation Sequencing Tools Ready for the Cloud?
    Celesti, Antonio
    Celesti, Fabrizio
    Fazio, Maria
    Bramanti, Placido
    Villari, Massimo
    [J]. TRENDS IN BIOTECHNOLOGY, 2017, 35 (06) : 486 - 489
  • [9] Why Deep Learning Is Changing the Way to Approach NGS Data Processing: A Review
    Celesti F.
    Celesti A.
    Wan J.
    Villari M.
    [J]. IEEE Reviews in Biomedical Engineering, 2018, 11 : 68 - 76
  • [10] A Cloud-Based System for Improving Retention Marketing Loyalty Programs in Industry 4.0: A Study on Big Data Storage Implications
    Galletta, Antonino
    Carnevale, Lorenzo
    Celesti, Antonio
    Fazio, Maria
    Villari, Massimo
    [J]. IEEE ACCESS, 2018, 6 : 5485 - 5492