SQL Query Optimization in Distributed NoSQL Databases for Cloud-Based Applications

Karras, Aristeidis; Karras, Christos; Pervanas, Antonios; Sioutas, Spyros; Zaroliagis, Christos

doi:10.1007/978-3-031-33437-5_2

Cited by 2 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simplest ETL functionalities are directly included into the data lake API. If higher performances are required for ETL and data aggregation, we also include a big data analytics framework to speed up the most complex requests to the database [58], and ETL functions [49] are also available. For this purpose, we adopt Apache Spark and SparkSQL [59], which is integrated within MongoDB using the Spark MongoDB connector and a specifically developed Scala code.…”

Section: Methodsmentioning

confidence: 99%

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

Silvestri,

Tricomi,

Bassolillo

et al. 2024

Sensors

View full text Add to dashboard Cite

This paper describes a novel architecture that aims to create a template for the implementation of an IT platform, supporting the deployment and integration of the different digital twin subsystems that compose a complex urban intelligence system. In more detail, the proposed Smart City IT architecture has the following main purposes: (i) facilitating the deployment of the subsystems in a cloud environment; (ii) effectively storing, integrating, managing, and sharing the huge amount of heterogeneous data acquired and produced by each subsystem, using a data lake; (iii) supporting data exchange and sharing; (iv) managing and executing workflows, to automatically coordinate and run processes; and (v) to provide and visualize the required information. A prototype of the proposed IT solution was implemented leveraging open-source frameworks and technologies, to test its functionalities and performance. The results of the tests performed in real-world settings confirmed that the proposed architecture could efficiently and easily support the deployment and integration of heterogeneous subsystems, allowing them to share and integrate their data and to select, extract, and visualize the information required by a user, as well as promoting the integration with other external systems, and defining and executing workflows to orchestrate the various subsystems involved in complex analyses and processes.

show abstract

Section: Methodsmentioning

confidence: 99%

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

Silvestri,

Tricomi,

Bassolillo

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

Efficient Algorithms for Range Mode Queries in the Big Data Era

Karras,

Theodorakopoulos,

Karras

et al. 2024

Information

View full text Add to dashboard Cite

The mode is a fundamental descriptive statistic in data analysis, signifying the most frequent element within a dataset. The range mode query (RMQ) problem expands upon this concept by preprocessing an array A containing n natural numbers. This allows for the swift determination of the mode within any subarray A[a..b], thus optimizing the computation of the mode for a multitude of range queries. The efficacy of this process bears considerable importance in data analytics and retrieval across diverse platforms, including but not limited to online shopping experiences and financial auditing systems. This study is dedicated to exploring and benchmarking different algorithms and data structures designed to tackle the RMQ problem. The goal is to not only address the theoretical aspects of RMQ but also to provide practical solutions that can be applied in real-world scenarios, such as the optimization of an online shopping platform’s understanding of customer preferences, enhancing the efficiency and effectiveness of data retrieval in large datasets.

show abstract

SQL Query Optimization in Distributed NoSQL Databases for Cloud-Based Applications

Cited by 2 publications

References 27 publications

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

Efficient Algorithms for Range Mode Queries in the Big Data Era

Contact Info

Product

Resources

About