Modeling and querying data in NoSQL databases

Kaur, Karamjit; Rani, Rinkle

doi:10.1109/bigdata.2013.6691765

Cited by 99 publications

(68 citation statements)

References 5 publications

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“…The pyramid provides the rules of image cutting, and hash indexing gives a solution to store and search these tiles in a highly effective manner. NoSQL is one of the key technologies for large-capacity storage and fast retrieval oriented toward the continuous growth of datasets [33][34][35][36]. The main features of NoSQL databases are as follows [7,37] The most popular categories of NoSQL databases include key-value databases and document databases.…”

Section: Methodsmentioning

confidence: 99%

An On-Demand Retrieval Method Based on Hybrid NoSQL for Multi-Layer Image Tiles in Disaster Reduction Visualization

Qiu

Zhu

et al. 2017

IJGI

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Monitoring, response, mitigation and damage assessment of disasters places a wide variety of demands on the spatial and temporal resolutions of remote sensing images. Images are divided into tile pyramids by data sources or resolutions and published as independent image services for visualization. A disaster-affected area is commonly covered by multiple image layers to express hierarchical surface information, which generates a large amount of namesake tiles from different layers that overlay the same location. The traditional tile retrieval method for visualization cannot distinguish between distinct layers and traverses all image datasets for each tile query. This process produces redundant queries and invalid access that can seriously affect the visualization performance of clients, servers and network transmission. This paper proposes an on-demand retrieval method for multi-layer images and defines semantic annotations to enrich the description of each dataset. By matching visualization demands with the semantic information of datasets, this method automatically filters inappropriate layers and finds the most suitable layer for the final tile query. The design and implementation are based on a two-layer NoSQL database architecture that provides scheduling optimization and concurrent processing capability. The experimental results reflect the effectiveness and stability of the approach for multi-layer retrieval in disaster reduction visualization.

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Section: Methodsmentioning

confidence: 99%

An On-Demand Retrieval Method Based on Hybrid NoSQL for Multi-Layer Image Tiles in Disaster Reduction Visualization

Qiu

Zhu

et al. 2017

IJGI

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“…NoSQL databases: NoSQL [28] databases have been rapidly emerged, becoming a popular alternative to the existing relational databases that can better store, process and analyse large-volume data.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Relational and NoSQL Approaches for Cohort Identification from Heterogeneous Data Sources in the National Sleep Research Resource

Zeng¹,

Zhang²,

Li³

et al. 2017

J Health Med Inform

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Patient cohort identification across heterogeneous data sources is a challenging task, which may involve a complicated process of data loading, harmonization and querying. Most existing cohort identification tools use a relational database model implemented in SQL for storing patient data. However, SQL databases have restrictions on the maximum number of columns in a table, which necessitates the breaking down of high dimensional data into multiple tables and as a consequence affects query performance. In this paper, we developed two NoSQL-based patient cohort query systems based on an existing SQL-based system for the cross-cohort query in the National Sleep Resource Research (NSRR). We used eight NSRR datasets in our experiment to evaluate the performance of the NoSQLbased and SQL-based systems in data loading, harmonization and query. Our experiment showed that NoSQL-based approaches outperformed the SQL-based and are rather promising for developing patient cohort query systems across heterogeneous data sources.

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“…The figure [6] describes how the data flow occur in the map reduce framework through different stages. It is an example of map reduce word count programme.…”

Section: A Hadoop Ecosystemmentioning

confidence: 99%

“…NOSQL is a term basically refered to define a class of non-relational databases that can scale horizontally to very large data sets but never give ACID guarantees [6], [7]. Nosql data keeps data vary widely in their offerings and have some definite features of its own.…”

Section: B Nosqlmentioning

confidence: 99%

A Survey Work on Optimization Techniques Utilizing Map Reduce Framework in Hadoop Cluster

Jena¹,

Gourisaria²,

Rautaray³

et al. 2017

IJISA

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Modeling and querying data in NoSQL databases

Cited by 99 publications

References 5 publications

An On-Demand Retrieval Method Based on Hybrid NoSQL for Multi-Layer Image Tiles in Disaster Reduction Visualization

An On-Demand Retrieval Method Based on Hybrid NoSQL for Multi-Layer Image Tiles in Disaster Reduction Visualization

Evaluation of Relational and NoSQL Approaches for Cohort Identification from Heterogeneous Data Sources in the National Sleep Research Resource

A Survey Work on Optimization Techniques Utilizing Map Reduce Framework in Hadoop Cluster

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