Application of Heterogeneous Network Oriented to NoSQL Database in Optimal Postevaluation Indexes of Construction Projects

With the advent of the Internet Web 2.0 era, storage devices used to store website data are developing at an ever-increasing high-growth rate and a diversified trend. The focus on the structured data storage model has reduced the responsiveness of traditional relational databases to data changes. NoSQL database is scalable, has a powerful and flexible data model and a large amount of data, and has an increasing application potential in the memory field. Heterogeneous networks are composed of third-party computers, network equipment, and systems. Network types are usually used for other protocols to support other functions and applications. The research on heterogeneous networks can be traced back to the BARWAN project that started in 1995 at the University of California, Berkeley. The project leader RHKatz merged multiple types of nested networks for the first time to form heterogeneous network requirements for various future terminal services. Construction engineering refers to an engineering entity formed by installing pipelines and equipment that support the construction of various houses and ancillary facilities. “House construction” refers to projects with roofs, beams, columns, walls, and foundations that can form internal spaces to meet people’s needs in production, living, learning, and public activities. Among them, the engineering evaluation index is a statistical index used to evaluate and compare the quality and effects of social and economic activities through the use of equipment, such as capital turnover rate and employee labor efficiency. It is the exchange of corporate performance evaluation content and the expression of corporate performance evaluation content.

A Comparative study of SQL Databases and NoSQL Databases for E-Commerce

With the advent of E-Commerce, businesses persistently examine various ways to improvise and accomplish their demands with web engineering that provide notable resolution. The progress in economic status demands colossal databases that store the data efficiently. The databases currently used are relational or non-relational. Both these types have their benefits and limitations that influence the overall processing of data. Non-relational databases are referred to as NoSQL-not only SQL, and Relational databases are known as SQL-Structured Query Language. It has been suggested in many studies that NoSQL databases surpass SQL databases. Our paper aims to evaluate these claims by analyzing the CRUD [Create, Read, Update, Delete] operations executed by both database types. Keywords: NoSQL, SQL, Non-relational Databases, MySQL, E-Commerce, MongoDb , Relational Databases

Comparative analysis of connection performance with databases via JDBC interface and ORM programming frameworks

The research subject of this paper was the comparative analysis of efficiency of connections with databases using different communication methods based on Java programming language. The tools investigated included JDBC drivers and Object-relational mapping (ORM) frameworks. A survey based on 8 different criteria was conducted to determine the most effective method and tool for working with relational databases when developing Java applications. The weights of the criteria were determined through a survey of Java programmers and computer science students.

Experience in developing a web application for relational databases modeling with a forward engineering function for training students of technical specialties

The article actualizes the need to develop software for modeling relational databases for use in the process of teaching students of technical specialties in disciplines related to databases.The problem is considered from the point of view of assessing modern software used in the process of teaching students database design skills. Based on the shortcomings identified during the software review, a number of requirements for the actual software were determined. Formed key requirements are mobility, accessibility, versatility and openness of the development platform.The article describes the process of solving key problems that arose during the implementation of a project to develop a web application for modeling relational databases in accordance with the generated requirements. The practical implementation of the following functions is sequentially considered: creation of a logical relational data model, creation of a physical data model, direct engineering into relational database software. The main technological solutions used in the development of a web application to ensure the qualities specified in the condition are described.The result of the work is the successful testing of the development results in the process of creating a real web application, both within the framework of laboratory and practical work in the disciplines “Design and administration of databases” and “Data management”, and at the stage of writing graduate works for technical directions of training.

Storage organization for "open" sets of entity attributes in relational databases

Relations are practically implemented by database management systems in the form of two-dimensional tables. In this regard, certain difficulties arise in the development of relational database schemas, in which it is necessary to represent objects with an alterable (open) set of attributes. The article proposes a solution to this problem by including special relations in the scheme - relations of properties directory. Properties directory allow replenishing the sets of object attributes without changing the structure of the database. Examples of the practical use of properties directory in the development of database schemas of two information systems are presented.

A Natural Language Interface to Relational Databases Using an Online Analytic Processing Hypercube

Structured Query Language (SQL) is commonly used in Relational Database Management Systems (RDBMS) and is currently one of the most popular data definition and manipulation languages. Its core functionality is implemented, with only some minor variations, throughout all RDBMS products. It is an effective tool in the process of managing and querying data in relational databases. This paper describes a method to effectively automate the conversion of a data query from a Natural Language Query (NLQ) to Structured Query Language (SQL) with Online Analytical Processing (OLAP) cube data warehouse objects. To obtain or manipulate the data from relational databases, the user must be familiar with SQL and must also write an appropriate and valid SQL statement. However, users who are not familiar with SQL are unable to obtain relevant data through relational databases. To address this, we propose a Natural Language Processing (NLP) model to convert an NLQ into an SQL query. This allows novice users to obtain the required data without having to know any complicated SQL details. The model is also capable of handling complex queries using the OLAP cube technique, which allows data to be pre-calculated and stored in a multi-dimensional and ready-to-use format. A multi-dimensional cube (hypercube) is used to connect with the NLP interface, thereby eliminating long-running data queries and enabling self-service business intelligence. The study demonstrated how the use of hypercube technology helps to increase the system response speed and the ability to process very complex query sentences. The system achieved impressive performance in terms of NLP and the accuracy of generating different query sentences. Using OLAP hypercube technology, the study achieved distinguished results compared to previous studies in terms of the speed of the response of the model to NLQ analysis, the generation of complex SQL statements, and the dynamic display of the results. As a plan for future work, it is recommended to use infinite-dimension (n-D) cubes instead of 4-D cubes to enable ingesting as much data as possible in a single object and to facilitate the execution of query statements that may be too complex in query interfaces running in a data warehouse. The study demonstrated how the use of hypercube technology helps to increase system response speed and process very complex query sentences.

Noise Resistant Multidimensional Data Fusion via Quasi-Cliques on Hypergraphs

Cross-matching data stored on separate files is an everyday activity in the scientific domain. However sometimes the relation between attributes may not be obvious. The discovery of foreign keys on relational databases is a similar problem. Thus techniques devised for this problem can be adapted. Nonetheless, given the different nature of the data, which can be subject to uncertainty, this adaptation is not trivial.<br>This paper firstly introduces the concept of Equally-Distributed Dependencies, which is similar to the Inclusion Dependencies from the relational domain. We describe a correspondence in order to bridge existing ideas. We then propose PresQ: a new algorithm based on the search of maximal quasi-cliques on hyper-graphs to make it more robust to the nature of uncertain numerical data. This algorithm has been tested on three public datasets, showing promising results both in its capacity to find multidimensional equally-distributed sets of attributes and in run-time.

Noise Resistant Multidimensional Data Fusion via Quasi-Cliques on Hypergraphs

Cross-matching data stored on separate files is an everyday activity in the scientific domain. However sometimes the relation between attributes may not be obvious. The discovery of foreign keys on relational databases is a similar problem. Thus techniques devised for this problem can be adapted. Nonetheless, given the different nature of the data, which can be subject to uncertainty, this adaptation is not trivial.<br>This paper firstly introduces the concept of Equally-Distributed Dependencies, which is similar to the Inclusion Dependencies from the relational domain. We describe a correspondence in order to bridge existing ideas. We then propose PresQ: a new algorithm based on the search of maximal quasi-cliques on hyper-graphs to make it more robust to the nature of uncertain numerical data. This algorithm has been tested on three public datasets, showing promising results both in its capacity to find multidimensional equally-distributed sets of attributes and in run-time.

An Analysis of the Performance and Configuration Features of MySQL Document Store and Elasticsearch as an Alternative Backend in a Data Replication Solution

In recent years, with the increase in the volume and complexity of data, choosing a suitable database for storing huge amounts of data is not easy, because it must consider aspects such as manageability, scalability, and extensibility. Nowadays, the NoSQL databases have gained immense popularity for their efficiency in managing such datasets compared to relational databases. However, relational databases also exhibit some advantages in certain circumstances, therefore many applications use a combined approach: relational and non-relational. This paper performs a comparative evaluation of two popular open-source DBMSs: MySQL Document Store and Elasticsearch as non-relational DBMSs; this comparison is based on a detailed analysis of CRUD operations for different amounts of data showing how the databases could be modeled and used in an application. A case-study application was developed for this purpose in Java programming language and Spring framework using for data storage both relational MySQL and non-relational Elasticsearch and MySQL Document Store. To model the real situation encountered in several developed applications that use both relational and non-relational databases, a data replication solution that imports data from the primary relational MySQL database into Elasticsearch and MySQL Document Store as possible alternatives for more efficient data search was proposed and implemented.