175 resultados para SQL


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L’obiettivo di questa tesi è quello di progettare un sistema gestionale che risponda alle esigenze organizzative delle palestre. In particolar modo verrà implementato un software per piattaforma Windows dedicato ai personal trainer. Questa applicazione dovrà essere in grado di registrare e gestire i clienti del centro sportivo, e permettere la creazione degli allenamenti a loro dedicati (con l’utilizzo quindi di schede, esercizi, serie, ripetizioni, ...). Tutti i dati andranno memorizzati su un server SQL centralizzato, accessibile anche da Internet. Successivamente questi allenamenti potranno esser scaricati e visualizzati dai clienti tramite i propri Smartphone Android.

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Esplicazione documentata del processo di progettazione e sviluppo di una libreria in grado di comunicare in maniera standard con 8 diversi database, sia a livello di query SQL che a livello di ORM transazionale, con opportuni richiami di ingegneria del software

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Obiettivo della tesi è la progettazione e lo sviluppo di un sistema di BI e di relativa reportistica per un'azienda di servizi. Il tutto realizzato mediante la suite Microsoft Business Intelligence.

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Negli ultimi anni i dati, la loro gestione e gli strumenti per la loro analisi hanno subito una trasformazione. Si è visto un notevole aumento dei dati raccolti dagli utenti, che si aggira tra il 40 e il 60 percento annuo, grazie ad applicazioni web, sensori, ecc.. Ciò ha fatto nascere il termine Big Data, con il quale ci si riferisce a dataset talmente grandi che non sono gestibili da sistemi tradizionali, come DBMS relazionali in esecuzione su una singola macchina. Infatti, quando la dimensione di un dataset supera pochi terabyte, si è obbligati ad utilizzare un sistema distribuito, in cui i dati sono partizionati su più macchine. Per gestire i Big Data sono state create tecnologie che riescono ad usare la potenza computazionale e la capacità di memorizzazione di un cluster, con un incremento prestazionale proporzionale al numero di macchine presenti sullo stesso. Il più utilizzato di questi sistemi è Hadoop, che offre un sistema per la memorizzazione e l’analisi distribuita dei dati. Grazie alla ridondanza dei dati ed a sofisticati algoritmi, Hadoop riesce a funzionare anche in caso di fallimento di uno o più macchine del cluster, in modo trasparente all’utente. Su Hadoop si possono eseguire diverse applicazioni, tra cui MapReduce, Hive e Apache Spark. É su quest’ultima applicazione, nata per il data processing, che è maggiormente incentrato il progetto di tesi. Un modulo di Spark, chiamato Spark SQL, verrà posto in confronto ad Hive nella velocità e nella flessibilità nell’eseguire interrogazioni su database memorizzati sul filesystem distribuito di Hadoop.

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I dispositivi mobili, dagli smartphone ai tablet, sono entrati a far parte della nostra quotidianità. Controllando l’infrastruttura delle comunicazioni, rispetto a qualsiasi altro settore, si ha un maggiore accesso a informazioni relative alla geo-localizzazione degli utenti e alle loro interazioni. Questa grande mole di informazioni può aiutare a costruire città intelligenti e sostenibili, che significa modernizzare ed innovare le infrastrutture, migliorare la qualità della vita e soddisfare le esigenze di cittadini, imprese e istituzioni. Vodafone offre soluzioni concrete nel campo dell’info-mobilità consentendo la trasformazione delle nostre città in Smart City. Obiettivo della tesi e del progetto Proactive è cercare di sviluppare strumenti che, a partire da dati provenienti dalla rete mobile Vodafone, consentano di ricavare e di rappresentare su cartografia dati indicanti la presenza dei cittadini in determinati punti d’interesse, il profilo di traffico di determinati segmenti viari e le matrici origine/destinazione. Per fare questo verranno prima raccolti e filtrati i dati della città di Milano e della regione Lombardia provenienti dalla rete mobile Vodafone per poi, in un secondo momento, sviluppare degli algoritmi e delle procedure in PL/SQL che siano in grado di ricevere questo tipo di dato, di analizzarlo ed elaborarlo restituendo i risultati prestabiliti. Questi risultati saranno poi rappresentati su cartografia grazie a QGis e grazie ad una Dashboard aziendale interna di Vodafone. Lo sviluppo delle procedure e la rappresentazione cartografica dei risultati verranno eseguite in ambiente di Test e se i risultati soddisferanno i requisiti di progetto verrà effettuato il porting in ambiente di produzione. Grazie a questo tipo di soluzioni, che forniscono dati in modalità anonima e aggregata in ottemperanza alle normative di privacy, le aziende di trasporto pubblico, ad esempio, potranno essere in grado di gestire il traffico in modo più efficiente.

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Progetto di un sistema software - integrato in un apparato di supervisione industriale - dedicato alla personalizzazione e alla generazione automatica di file di definizione di report basati su database SQL.

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Enterprise Applications are complex software systems that manipulate much persistent data and interact with the user through a vast and complex user interface. In particular applications written for the Java 2 Platform, Enterprise Edition (J2EE) are composed using various technologies such as Enterprise Java Beans (EJB) or Java Server Pages (JSP) that in turn rely on languages other than Java, such as XML or SQL. In this heterogeneous context applying existing reverse engineering and quality assurance techniques developed for object-oriented systems is not enough. Because those techniques have been created to measure quality or provide information about one aspect of J2EE applications, they cannot properly measure the quality of the entire system. We intend to devise techniques and metrics to measure quality in J2EE applications considering all their aspects and to aid their evolution. Using software visualization we also intend to inspect to structure of J2EE applications and all other aspects that can be investigate through this technique. In order to do that we also need to create a unified meta-model including all elements composing a J2EE application.

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Java Enterprise Applications (JEAs) are complex systems composed using various technologies that in turn rely on languages other than Java, such as XML or SQL. Given the complexity of these applications, the need to reverse engineer them in order to support further development becomes critical. In this paper we show how it is possible to split a system into layers and how is possible to interpret the distance between application elements in order to support the refactoring of JEAs. The purpose of this paper is to explore ways to provide suggestions about the refactoring operations to perform on the code by evaluating the distance between layers and elements belonging those layers. We split JEAs into layers by considering the kinds and the purposes of the elements composing the application. We measure distance between elements by using the notion of the shortest path in a graph. Also we present how to enrich the interpretation of the distance value with enterprise pattern detection in order to refine the suggestion about modifications to perform on the code.

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RDB2RDF systems generate RDF from relational databases, operating in two dierent manners: materializing the database content into RDF or acting as virtual RDF datastores that transform SPARQL queries into SQL. In the former, inferences on the RDF data (taking into account the ontologies that they are related to) are normally done by the RDF triple store where the RDF data is materialised and hence the results of the query answering process depend on the store. In the latter, existing RDB2RDF systems do not normally perform such inferences at query time. This paper shows how the algorithm used in the REQUIEM system, focused on handling run-time inferences for query answering, can be adapted to handle such inferences for query answering in combination with RDB2RDF systems.

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RDB2RDF systems generate RDF from relational databases, operating in two di�erent manners: materializing the database content into RDF or acting as virtual RDF datastores that transform SPARQL queries into SQL. In the former, inferences on the RDF data (taking into account the ontologies that they are related to) are normally done by the RDF triple store where the RDF data is materialised and hence the results of the query answering process depend on the store. In the latter, existing RDB2RDF systems do not normally perform such inferences at query time. This paper shows how the algorithm used in the REQUIEM system, focused on handling run-time inferences for query answering, can be adapted to handle such inferences for query answering in combination with RDB2RDF systems.

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Current development platforms for designing spoken dialog services feature different kinds of strategies to help designers build, test, and deploy their applications. In general, these platforms are made up of several assistants that handle the different design stages (e.g. definition of the dialog flow, prompt and grammar definition, database connection, or to debug and test the running of the application). In spite of all the advances in this area, in general the process of designing spoken-based dialog services is a time consuming task that needs to be accelerated. In this paper we describe a complete development platform that reduces the design time by using different types of acceleration strategies based on using information from the data model structure and database contents, as well as cumulative information obtained throughout the successive steps in the design. Thanks to these accelerations, the interaction with the platform is simplified and the design is reduced, in most cases, to simple confirmations to the “proposals” that the platform automatically provides at each stage. Different kinds of proposals are available to complete the application flow such as the possibility of selecting which information slots should be requested to the user together, predefined templates for common dialogs, the most probable actions that make up each state defined in the flow, different solutions to solve specific speech-modality problems such as the presentation of the lists of retrieved results after querying the backend database. The platform also includes accelerations for creating speech grammars and prompts, and the SQL queries for accessing the database at runtime. Finally, we will describe the setup and results obtained in a simultaneous summative, subjective and objective evaluations with different designers used to test the usability of the proposed accelerations as well as their contribution to reducing the design time and interaction.

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La computación distribuida ha estado presente desde hace unos cuantos años, pero es quizás en la actualidad cuando está contando con una mayor repercusión. En los últimos años el modelo de computación en la nube (Cloud computing) ha ganado mucha popularidad, prueba de ello es la cantidad de productos existentes. Todo sistema informático requiere ser controlado a través de sistemas de monitorización que permiten conocer el estado del mismo, de tal manera que pueda ser gestionado fácilmente. Hoy en día la mayoría de los productos de monitorización existentes limitan a la hora de visualizar una representación real de la arquitectura de los sistemas a monitorizar, lo que puede dificultar la tarea de los administradores. Es decir, la visualización que proporcionan de la arquitectura del sistema, en muchos casos se ve influenciada por el diseño del sistema de visualización, lo que impide ver los niveles de la arquitectura y las relaciones entre estos. En este trabajo se presenta un sistema de monitorización para sistemas distribuidos o Cloud, que pretende dar solución a esta problemática, no limitando la representación de la arquitectura del sistema a monitorizar. El sistema está formado por: agentes, que se encargan de la tarea de recolección de las métricas del sistema monitorizado; un servidor, al que los agentes le envían las métricas para que las almacenen en una base de datos; y una aplicación web, a través de la que se visualiza toda la información. El sistema ha sido probado satisfactoriamente con la monitorización de CumuloNimbo, una plataforma como servicio (PaaS), que ofrece interfaz SQL y procesamiento transaccional altamente escalable sobre almacenes clave valor. Este trabajo describe la arquitectura del sistema de monitorización, y en concreto, el desarrollo de la principal contribución al sistema, la aplicación web. ---ABSTRACT---Distributed computing has been around for quite a long time, but now it is becoming more and more important. In the last few years, cloud computing, a branch of distributed computing has become very popular, as its different products in the market can prove. Every computing system requires to be controlled through monitoring systems to keep them functioning correctly. Currently, most of the monitoring systems in the market only provide a view of the architectures of the systems monitored, which in most cases do not permit having a real view of the system. This lack of vision can make administrators’ tasks really difficult. If they do not know the architecture perfectly, controlling the system based on the view that the monitoring system provides is extremely complicated. The project introduces a new monitoring system for distributed or Cloud systems, which shows the real architecture of the system. This new system is composed of several elements: agents, which collect the metrics of the monitored system; a server, which receives the metrics from the agents and saves them in a database; and a web application, which shows all the data collected in an easy way. The monitoring system has been tested successfully with Cumulonimbo. CumuloNimbo is a platform as a service (PaaS) which offers an SQL interface and a high-scalable transactional process. This platform works over key-value storage. This project describes the architecture of the monitoring system, especially, the development of the web application, which is the main contribution to the system.

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This document is the result of a process of web development to create a tool that will allow to Cracow University of Technology consult, create and manage timetables. The technologies chosen for this purpose are Apache Tomcat Server, My SQL Community Server, JDBC driver, Java Servlets and JSPs for the server side. The client part counts on Javascript, jQuery, AJAX and CSS technologies to perform the dynamism. The document will justify the choice of these technologies and will explain some development tools that help in the integration and development of all this elements: specifically, NetBeans IDE and MySQL workbench have been used as helpful tools. After explaining all the elements involved in the development of the web application, the architecture and the code developed are explained through UML diagrams. Some implementation details related to security are also deeper explained through sequence diagrams. As the source code of the application is provided, an installation manual has been developed to run the project. In addition, as the platform is intended to be a beta that will be grown, some unimplemented ideas for future development are also exposed. Finally, some annexes with important files and scripts related to the initiation of the platform are attached. This project started through an existing tool that needed to be expanded. The main purpose of the project along its development has focused on setting the roots for a whole new platform that will replace the existing one. For this goal, it has been needed to make a deep inspection on the existing web technologies: a web server and a SQL database had to be chosen. Although the alternatives were a lot, Java technology for the server was finally selected because of the big community backwards, the easiness of modelling the language through UML diagrams and the fact of being free license software. Apache Tomcat is the open source server that can use Java Servlet and JSP technology. Related to the SQL database, MySQL Community Server is the most popular open-source SQL Server, with a big community after and quite a lot of tools to manage the server. JDBC is the driver needed to put in contact Java and MySQL. Once we chose the technologies that would be part of the platform, the development process started. After a detailed explanation of the development environment installation, we used UML use case diagrams to set the main tasks of the platform; UML class diagrams served to establish the existing relations between the classes generated; the architecture of the platform was represented through UML deployment diagrams; and Enhanced entity–relationship (EER) model were used to define the tables of the database and their relationships. Apart from the previous diagrams, some implementation issues were explained to make a better understanding of the developed code - UML sequence diagrams helped to explain this. Once the whole platform was properly defined and developed, the performance of the application has been shown: it has been proved that with the current state of the code, the platform covers the use cases that were set as the main target. Nevertheless, some requisites needed for the proper working of the platform have been specified. As the project is aimed to be grown, some ideas that could not be added to this beta have been explained in order not to be missed for future development. Finally, some annexes containing important configuration issues for the platform have been added after proper explanation, as well as an installation guide that will let a new developer get the project ready. In addition to this document some other files related to the project are provided: - Javadoc. The Javadoc containing the information of every Java class created is necessary for a better understanding of the source code. - database_model.mwb. This file contains the model of the database for MySQL Workbench. This model allows, among other things, generate the MySQL script for the creation of the tables. - ScheduleManager.war. The WAR file that will allow loading the developed application into Tomcat Server without using NetBeans. - ScheduleManager.zip. The source code exported from NetBeans project containing all Java packages, JSPs, Javascript files and CSS files that are part of the platform. - config.properties. The configuration file to properly get the names and credentials to use the database, also explained in Annex II. Example of config.properties file. - db_init_script.sql. The SQL query to initiate the database explained in Annex III. SQL statements for MySQL initialization. RESUMEN. Este proyecto tiene como punto de partida la necesidad de evolución de una herramienta web existente. El propósito principal del proyecto durante su desarrollo se ha centrado en establecer las bases de una completamente nueva plataforma que reemplazará a la existente. Para lograr esto, ha sido necesario realizar una profunda inspección en las tecnologías web existentes: un servidor web y una base de datos SQL debían ser elegidos. Aunque existen muchas alternativas, la tecnología Java ha resultado ser elegida debido a la gran comunidad de desarrolladores que tiene detrás, además de la facilidad que proporciona este lenguaje a la hora de modelarlo usando diagramas UML. Tampoco hay que olvidar que es una tecnología de uso libre de licencia. Apache Tomcat es el servidor de código libre que permite emplear Java Servlets y JSPs para hacer uso de la tecnología de Java. Respecto a la base de datos SQL, el servidor más popular de código libre es MySQL, y cuenta también con una gran comunidad detrás y buenas herramientas de modelado, creación y gestión de la bases de datos. JDBC es el driver que va a permitir comunicar las aplicaciones Java con MySQL. Tras elegir las tecnologías que formarían parte de esta nueva plataforma, el proceso de desarrollo tiene comienzo. Tras una extensa explicación de la instalación del entorno de desarrollo, se han usado diagramas de caso de UML para establecer cuáles son los objetivos principales de la plataforma; los diagramas de clases nos permiten realizar una organización del código java desarrollado de modo que sean fácilmente entendibles las relaciones entre las diferentes clases. La arquitectura de la plataforma queda definida a través de diagramas de despliegue. Por último, diagramas EER van a definir las relaciones entre las tablas creadas en la base de datos. Aparte de estos diagramas, algunos detalles de implementación se van a justificar para tener una mejor comprensión del código desarrollado. Diagramas de secuencia ayudarán en estas explicaciones. Una vez que toda la plataforma haya quedad debidamente definida y desarrollada, se va a realizar una demostración de la misma: se demostrará cómo los objetivos generales han sido alcanzados con el desarrollo actual del proyecto. No obstante, algunos requisitos han sido aclarados para que la plataforma trabaje adecuadamente. Como la intención del proyecto es crecer (no es una versión final), algunas ideas que se han podido llevar acabo han quedado descritas de manera que no se pierdan. Por último, algunos anexos que contienen información importante acerca de la plataforma se han añadido tras la correspondiente explicación de su utilidad, así como una guía de instalación que va a permitir a un nuevo desarrollador tener el proyecto preparado. Junto a este documento, ficheros conteniendo el proyecto desarrollado quedan adjuntos. Estos ficheros son: - Documentación Javadoc. Contiene la información de las clases Java que han sido creadas. - database_model.mwb. Este fichero contiene el modelo de la base de datos para MySQL Workbench. Esto permite, entre otras cosas, generar el script de iniciación de la base de datos para la creación de las tablas. - ScheduleManager.war. El fichero WAR que permite desplegar la plataforma en un servidor Apache Tomcat. - ScheduleManager.zip. El código fuente exportado directamente del proyecto de Netbeans. Contiene todos los paquetes de Java generados, ficheros JSPs, Javascript y CSS que forman parte de la plataforma. - config.properties. Ejemplo del fichero de configuración que permite obtener los nombres de la base de datos - db_init_script.sql. Las consultas SQL necesarias para la creación de la base de datos.

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En España, los datos catastrales de acceso público, obtenidos a través de la Sede Electrónica del Catastro (SEC), no incluyen información sobre la genealogía o las relaciones de linaje existente entre las parcelas, de forma que la gestión de la información histórica es muy limitada. Este artículo presenta un método para obtener las relaciones de linaje más frecuentes entre las parcelas (agregación y segregación) y propone un prototipo de estructura relacional para el almacenamiento y la gestión histórica de los datos catastrales de acceso público. El proceso de análisis para deducir el linaje se basa en superposiciones espacio-temporales junto con secuencias de sentencias SQL. El método proporciona un 70% de relaciones de agregación y segregación correctas; el resto presentan errores debidos, en general, a anomalías presentes en los propios datos catastrales.

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La gestión del conocimiento (KM) es el proceso de recolectar datos en bruto para su análisis y filtrado, con la finalidad de obtener conocimiento útil a partir de dichos datos. En este proyecto se pretende hacer un estudio sobre la gestión de la información en las redes de sensores inalámbricos como inicio para sentar las bases para la gestión del conocimiento en las mismas. Las redes de sensores inalámbricos (WSN) son redes compuestas por sensores (también conocidos como motas) distribuidos sobre un área, cuya misión es monitorizar una o varias condiciones físicas del entorno. Las redes de sensores inalámbricos se caracterizan por tener restricciones de consumo para los sensores que utilizan baterías, por su capacidad para adaptarse a cambios y ser escalables, y también por su habilidad para hacer frente a fallos en los sensores. En este proyecto se hace un estudio sobre la gestión de la información en redes de sensores inalámbricos. Se comienza introduciendo algunos conceptos básicos: arquitectura, pila de protocolos, topologías de red, etc.… Después de esto, se ha enfocado el estudio hacia TinyDB, el cual puede ser considerado como parte de las tecnologías más avanzadas en el estado del arte de la gestión de la información en redes de sensores inalámbricos. TinyDB es un sistema de procesamiento de consultas para extraer información de una red de sensores. Proporciona una interfaz similar a SQL y permite trabajar con consultas contra la red de sensores inalámbricos como si se tratara de una base de datos tradicional. Además, TinyDB implementa varias optimizaciones para manejar los datos eficientemente. En este proyecto se describe también la implementación de una sencilla aplicación basada en redes de sensores inalámbricos. Las motas en la aplicación son capaces de medir la corriente a través de un cable. El objetivo de esta aplicación es monitorizar el consumo de energía en diferentes zonas de un área industrial o doméstico, utilizando redes de sensores inalámbricas. Además, se han implementado las optimizaciones más importantes que se han aprendido en el análisis de la plataforma TinyDB. Para desarrollar esta aplicación se ha utilizado como sensores la plataforma open-source de creación de prototipos electrónicos Arduino, y el ordenador de placa reducida Raspberry Pi como coordinador. ABSTRACT. Knowledge management (KM) is the process of collecting raw data for analysis and filtering, to get a useful knowledge from this data. In this project the information management in wireless sensor networks is studied as starting point before knowledge management. Wireless sensor networks (WSN) are networks which consists of sensors (also known as motes) distributed over an area, to monitor some physical conditions of the environment. Wireless sensor networks are characterized by power consumption constrains for sensors which are using batteries, by the ability to be adaptable to changes and to be scalable, and by the ability to cope sensor failures. In this project it is studied information management in wireless sensor networks. The document starts introducing basic concepts: architecture, stack of protocols, network topology… After this, the study has been focused on TinyDB, which can be considered as part of the most advanced technologies in the state of the art of information management in wireless sensor networks. TinyDB is a query processing system for extracting information from a network of sensors. It provides a SQL-like interface and it lets us to work with queries against the wireless sensor network like if it was a traditional database. In addition, TinyDB implements a lot of optimizations to manage data efficiently. In this project, it is implemented a simple wireless sensor network application too. Application’s motes are able to measure amperage through a cable. The target of the application is, by using a wireless sensor network and these sensors, to monitor energy consumption in different areas of a house. Additionally, it is implemented the most important optimizations that we have learned from the analysis of TinyDB platform. To develop this application it is used Arduino open-source electronics prototyping platform as motes, and Raspberry Pi single-board computer as coordinator.