Improving the energy efficiency of relational and NoSQL databases via query optimizations

Mahajan, Divya; Blakeney, Cody; Zong, Ziliang

doi:10.1016/j.suscom.2019.01.017

Cited by 25 publications

(21 citation statements)

References 3 publications

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“…The diseases are not coded according to different conditions. This is consistent with the results of Mahajan et al [ 22 ]. The diseases are not coded according to different sites and different onset times.…”

Section: Discussionsupporting

confidence: 94%

Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management

Wang

Yao

Chen³

et al. 2021

Journal of Healthcare Engineering

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The study aims to explore the application of international classification of diseases (ICD) coding technology and embedded electronic medical record (EMR) system. The study established an EMR information knowledge system and collected the data of patient medical records and disease diagnostic codes on the front pages of 8 clinical departments of endocrinology, oncology, obstetrics and gynecology, ophthalmology, orthopedics, neurosurgery, and cardiovascular medicine for statistical analysis. Natural language processing-bidirectional recurrent neural network (NLP-BIRNN) algorithm was used to optimize medical records. The results showed that the coder was not clear about the basic rules of main diagnosis selection and the classification of disease coding and did not code according to the main diagnosis principles. The disease was not coded according to different conditions or specific classification, the code of postoperative complications was inaccurate, the disease diagnosis was incomplete, and the code selection was too general. The solutions adopted were as follows: communication and knowledge training should be strengthened for coders and medical personnel. BIRNN was compared with the convolutional neural network (CNN) and recurrent neural network (RNN) in accuracy, symptom accuracy, and symptom recall, and it suggested that the proposed BIRNN has higher value. Pathological language reading under artificial intelligence algorithm provides some convenience for disease diagnosis and treatment.

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Section: Discussionsupporting

confidence: 94%

Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management

Wang

Yao

Chen³

et al. 2021

Journal of Healthcare Engineering

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“…Database configuration refers to the fine-tuning of a certain set of operations to improve the performance. This includes the configuration of the database parameters ( Zhu et al, 2017a ; Van Aken et al, 2017 ; Zhang et al, 2019 ; Li et al, 2019 ), but also the index selection ( Valentin et al, 2000 ; Schnaitter et al, 2007 ; Pedrozo, Nievola & Ribeiro, 2018 ) and view advisor ( Zilio et al, 2004 ; Jindal et al, 2018 ; Yuan et al, 2020 ) that optimize the performance when accessing the data, and the query rewriting that manipulates the queries provided by the user in order to make them more efficient ( Mahajan, Blakeney & Zong, 2019 ; Chavan et al, 2011 ; Baik, Jagadish & Li, 2019 ).…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Automatic configuration of the Cassandra database using irace

Silva-Muñoz¹,

Franzin²,

Bersini³

2021

PeerJ Computer Science

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Database systems play a central role in modern data-centered applications. Their performance is thus a key factor in the efficiency of data processing pipelines. Modern database systems expose several parameters that users and database administrators can configure to tailor the database settings to the specific application considered. While this task has traditionally been performed manually, in the last years several methods have been proposed to automatically find the best parameter configuration for a database. Many of these methods, however, use statistical models that require high amounts of data and fail to represent all the factors that impact the performance of a database, or implement complex algorithmic solutions. In this work we study the potential of a simple model-free general-purpose configuration tool to automatically find the best parameter configuration of a database. We use the irace configurator to automatically find the best parameter configuration for the Cassandra NoSQL database using the YCBS benchmark under different scenarios. We establish a reliable experimental setup and obtain speedups of up to 30% over the default configuration in terms of throughput, and we provide an analysis of the configurations obtained.

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“…Relational database management systems (RDBMSs) use the relational model, which relates the database's tables to each other by referential keys and indexes, making the data storage and retrieval faster than in the old navigational models [10]. SQL is a data query language originally developed by IBM in 1970 to help define and manipulate data.…”

Section: -Characteristics Of Sql Databasesmentioning

confidence: 99%

“…Whenever ACID becomes not the major concern, NoSQL is the optimal solution and BASE ensures eventual consistency [16]. The major uses of NoSQL databases are: (1) Embedded IR, (2) Parallel processing of data over distributed systems, (3) Explorative analytics on unstructured semistructured data, (4) large-scale data storage( structured, semi-structured, unstructured) [13], (5) Social Networks, (6) Search Engines, (7) Geospatial analysis, (8) Nuclear modeling, (9) Data warehouses, (10) Caching [17].…”

Section: -Characteristics Of Nosql Databasesmentioning

confidence: 99%

“…For every key (document ID) in the document-based databases, a record can be stored as a value to form the document with its own internal structure [14]. The documents can be inserted and exchanged in standard formats like Java Script Option Nations (JSON), extensible markup language (XML) [13], binary JSON (BSON) [10], or Yet Another Markup Language (YAML) [24]. In the document-based stores, a collection of data contains a set of separated documents.…”

Section: Document-based Nosql Storesmentioning

confidence: 99%

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A COMPARATIVE STUDY AMONG THE MAIN CATEGORIES OF NoSQL DATABASES

2020

Al-Azhar Bulletin of Science

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Relational databases are usually used for data storage and retrieval. They are suitable for limited data volume. But when it comes to Bigdata, we need to use more flexible databases that satisfy the need to handle semi-structured and unstructured data. These databases are called NoSQL (Not only SQL) databases. This type of database was developed to interact with data of large volumes. NoSQL databases provide many features such as scalability, availability, replication models, file sharing, and schema-free. This paper's main purpose is to present a comparative study of the five main categories of NoSQL databases; key-value stores, document stores, column family stores, graph stores databases, and object store NoSQL systems. Also, it discusses the famous database management systems for each one of these five categories. The comparison criteria used are performance, scalability, flexibility, complexity, and functionality. Moreover, this paper presents an overview of big data concepts. It briefly discusses the SQL databases versus NoSQL databases in terms of their high-level characteristics. Furthermore, this paper emphasizes the advantages and disadvantages of NoSQL databases. It illustrates the query languages in both SQL and NoSQL databases and represents the most common uses for each category to help users choose the most convenient DBMS for their organization.

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Improving the energy efficiency of relational and NoSQL databases via query optimizations

Cited by 25 publications

References 3 publications

Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management

Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management

Automatic configuration of the Cassandra database using irace

A COMPARATIVE STUDY AMONG THE MAIN CATEGORIES OF NoSQL DATABASES

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