This paper is about Java object relational frameworks and related processes. The goal of this work consists of showing design patterns for ORM, introducing Java ORM standards along with the main implementations, finding criteria for comparison of ORM frameworks and showing working ORM example in a case study. This paper has the following structure: The first part of this paper discusses main ORM design patters, approaches to ORM and performance related features of Java ORM frameworks. Next part describes available Java ORM standards and implementations and introduces case study attached to this part as appendix. The last part of this paper presents ORM frameworks comparison criteria and compares main implementations of the JPA standard.

The World Wide Web is a rich source of information and continues to expand in size and complexity. Mainly because the data on the web is lack of rigid and uniform data models or schemas, how to effectively and efficiently manage web data and retrieve information is becoming a challenge problem. Discovering web page communities, which capture the features of the web and web-based data to find intrinsic relationships among the data, is one of the effective ways to solve this problem. A web page community is a set of web pages that has its own logical and semantic structures. In this work, we concentrate on the web data in web page format and exploit hyperlink information to discover (construct) web page communities. Three main web page communities are studied in this work: the first one is consisted of hub and authority pages, the second one is composed of relevant web pages with respect to a given page (URL), and the last one is the community with hierarchical cluster structures. For analysing hyperlinks, we establish a mathematical framework, especially the matrix-based framework, to model hyperlinks. Within this mathematical framework, hyperlink analysis is placed on a solid mathematic base and the results are reliable. For the web page community that is consisted of hub and authority pages, we focus on eliminating noise pages from the concerned page source to obtain another good quality page source, and in turn improve the quality of web page communities. We propose an innovative noise page elimination algorithm based on the hyperlink matrix model and mathematic operations, especially the singular value decomposition (SVD) of matrix. The proposed algorithm exploits hyperlink information among the web pages, reveals page relationships at a deeper level, and numerically defines thresholds for noise page elimination. The experiment results show the effectiveness and feasibility of the algorithm. This algorithm could also be used solely for web-based data management systems to filter unnecessary web pages and reduce the management cost. In order to construct a web page community that is consisted of relevant pages with respect to a given page (URL), we propose two hyperlink based relevant page finding algorithms. The first algorithm comes from the extended co-citation analysis of web pages. It is intuitive and easy to be implemented. The second one takes advantage of linear algebra theories to reveal deeper relationships among the web pages and identify relevant pages more precisely and effectively. The corresponding page source construction for these two algorithms can prevent the results from being affected by malicious hyperlinks on the web. The experiment results show the feasibility and effectiveness of the algorithms. The research results could be used to enhance web search by caching the relevant pages for certain searched pages. For the purpose of clustering web pages to construct a community with its hierarchical cluster structures, we propose an innovative web page similarity measurement that incorporates hyperlink transitivity and page importance (weight).Based on this similarity measurement, two types of hierarchical web page clustering algorithms are proposed. The first one is the improvement of the conventional K-mean algorithms. It is effective in improving page clustering, but is sensitive to the predefined similarity thresholds for clustering. Another type is the matrix-based hierarchical algorithm. Two algorithms of this type are proposed in this work. One takes cluster-overlapping into consideration, another one does not. The matrix-based algorithms do not require predefined similarity thresholds for clustering, are independent of the order in which the pages are presented, and produce stable clustering results. The matrix-based algorithms exploit intrinsic relationships among web pages within a uniform matrix framework, avoid much influence of human interference in the clustering procedure, and are easy to be implemented for applications. The experiments show the effectiveness of the new similarity measurement and the proposed algorithms in web page clustering improvement. For applying above mathematical algorithms better in practice, we generalize the web page discovering as a special case of information retrieval and present a visualization system prototype, as well as technical details on visualization algorithm design, to support information retrieval based on linear algebra. The visualization algorithms could be smoothly applied to web applications. XML is a new standard for data representation and exchange on the Internet. In order to extend our research to cover this important web data, we propose an object representation model (ORM) for XML data. A set of transformation rules and algorithms are established to transform XML data (DTD and XML documents with DTD or without DTD) into this model. This model capsulizes elements of XML data and data manipulation methods. DTD-Tree is also defined to describe the logical structure of DTD. It also can be used as an application program interface (API) for processing DTD, such as transforming a DTD document into the ORM. With this data model, semantic meanings of the tags (elements) in XML data can be used for further research in XML data management and information retrieval, such as community construction for XML data.

Large scale application design and development involve some critical decisions, and one of the most important issues that a ect software application design and development is the technology stack used to develop an extensive system. In a JPA API, response time is often a measure of how quickly an interactive system responds to user input. Persisting framework, such as Object Relational Mapping (ORM) are applied to manage communications between an object model and data model components and are vital for such systems. Hibernate is considered the most e ective ORM framework due to its advanced features, and it is the de-facto standard for Java Persistence API (JPA)-based data persistent frameworks. This thesis comprises a review of the most widely used JPA providers, particularly frameworks that provide JPA support such as Hibernate JPA, EclipseLink, OpenJPA and DataNucleus JPA. In current java programming, APIs based on persistence and performance are integral aspects of an application. Performance analysis of the above four JPA implementations is based on the ORM framework that contributed most signi cantly to discovering the challenges and veri ed the programming considerations in the language. For a large-scale enterprise, working on JPA is always tedious due to the potential pressures and overloads of the implementations, as well as the comprehensive guarantee, that is required while adopting the technology. A JPA implementation continually persists data into the database at runtime, by managing persistence processes through interfaces and classes, that often needs optimization, to provide performance-oriented results at heavy loads. Therefore, in this thesis a detail feature analysis was performed, before the performance analysis. To enhance the comparison of the persistence framework, an extended experiment with a cloud database using Database-as-a-service (DBaaS) versus Physical Persistence was performed, using a comparative approach for all four JPA implementations. Di erent SQL queries on cloud versus physical persistence for JPA applications were measured using CPU, GC, and threads (live and daemon). Finally, a statistical analysis was performed using the Pearson's correlation coe cient and a steady/start-up phase.

The Manta platform is a unified commercial product for data flow analysis and vi- sualization. Manta platform supports many technologies. One category of technologies is intermediate languages. These include, for example, Java or C#. There is a scanner for each of these technologies. This thesis focuses on extending the C# Scanner with support for database and ORM related plugins. First, we provide a brief description of how the Manta platform works. Then we quickly introduce the C# Scanner, some of its important parts, and explain some of the concepts and algorithms that are used to analyze C# code. This is followed by an analysis of the context of ORM frameworks and Entity Framework Core from the perspective of data flow analysis. After explaining the context, we describe the C# Scanner extensions, solutions and troubleshooting. Towards the end of the thesis we describe support for one specific ORM framework - Entity Framework Core. Again, we discuss problem solving and solution description. At the end of the thesis it is possible to find limitations of the solution and possible extensions. 1

Vården är Sveriges mest viktiga sektor. Med den dagliga ökningen av personer som söker medicinsk vård behöver sjukvården ha ett väl fungerande system lämpligt för databaser, med målet att minimera den nuvarande belastning som redan vilar på sjukvårdssystemet. Regionerna har olika system, vilket leder till ökade kostnader vid drift och uppdatering av dessa system. Vården idag har inte tiden att lägga på långsamma och icke effektiva system utan fokuset måste läggas på patienterna. Målet med detta arbete har varit att utveckla pålitlig teknik som skapar de bästa förutsättningar för att vården ska kunna hantera patientinformation, genom att implementera de bästa databasmetoderna. ADO och Dapper är de två ORM:en som den här studien ägnar sig åt, där en jämförelse mellan som dessa två ORM har gjorts för att svara på följande frågorna som är, hastighet, kod komplexitet, prestanda och flexibilitet. Målen som det här arbetet fokuserar på kommer att ge en tydlig bild för de andra utvecklare vid de senare utvecklingsfaserna av dessa system på vilka för och nackdelar varje teknik har och vilken är mest lämplig att satsa på beroende på behovet. Studien har visat att ADO generellt sätt hade bättre mätningsresultat när det gällde hastigheten men mindre bra resultat än Dapper när det kom till kod komplexiteten. Dapper hade några bekymmer när det kom till prestanda dock så var den enklare att bygga vidare på tack var det hur flexibel den är som ORM. / The healthcare sector is Sweden's most crucial sector. With the daily increase of people seeking medical care, healthcare needs to have a well-functioning system suitable for databases, aiming to minimize the current burden the healthcare system already faces. The regions have different systems, which leads to increased costs when operating and updating these systems. Healthcare today needs more time on slow and ineffective systems, but the focus must be on the patients. This work aims to develop reliable technology that creates the best conditions for healthcare to manage patient information by implementing the best database methods. ADO and Dapper are the two ORMs that this study deals with, and a comparison between these ORMs has been made to answer the following questions: speed, code complexity, performance, and flexibility. These goals that this work focuses on will give a clear picture to the other developers at the later development phases of these systems on which pros and cons each technology has and which one is most suitable to bet on depending on the need. The study showed that ADO generally had better saturation results regarding speed but less good results than Dapper regarding code complexity. Dapper had some performance concerns; however, it was easier to build on thanks to its flexibility as an ORM.

Nearly all modern software applications, from the simplest website user account system to the most complex, enterprise-level, completely-integrated infrastructure, utilize some sort of backend data storage and business logic that interacts with the backend. The ubiquitous nature of this backend/business dichotomy makes sense as the need to both store and manipulate data can be traced as far back as the Turing Machine in Computer Science. The most commonly used technologies for these two aspects are Relational Database Management Systems (RDBMS) for backend and Object-Oriented Programming (OOP) for business logic. However, these two methodologies are not immediately compatible and the inherent differences between data represented in RDBMS and data represented in OOP are not trivial. Taking a .NET developer’s perspective, this report aims to explore the RDBMS/OO dichotomy and its inherent issues. Schema management theory and algebra are discussed to gain better perspective of the domain and a survey of existing solutions for the .NET environment is explored. Additionally, methods outside the mainstream are discussed. The advantages and disadvantages of each are weighed and presented to the reader to help aid in design implementations in the future. / text

This work is analyzing problems, arising because of sematical gap between relational and object-oriented approaches and discusses how to utilize object-relational mapping for solving this problem. After analysis of object-relational mapping framework (further – ORM) principles and features of existing ORM frameworks a model is suggested, that allows to implement ORM by utilizing MVP principles in a way that retains major portion of both approach pros and is perfect for transitioning existing relational structures to object-oriented. Further, project and implementation of prototype framework, that uses the following principles and suggested model, is described and utilized as for implementing imaginary domain ORM mapping example application.

Using an object relational mapper, ORM, is a good idea if you have an object relational code base and are following standards. By using an ORM you get a separation between actual objects and data persistence. This also makes it possible for the programmer to fully focus on the application without knowing much about how the database itself works.  However, this doesn’t come without drawbacks. Depending what ORM you use and how you use it, it may sacrifice performance.  The research in this thesis shows that using an ORM in a very small application does not sacrifice performance.

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ORM-Frameworks sind eine häufig genutzte Möglichkeit, die Unterschiede zwischen der objektorientierten Programmierung und der relationalen Datenspeicherung zu überbrücken. Gleichzeitig sind rekursive Beziehungen in vielen Datenmodellen vorhanden, um Hierarchien und andere baum- oder netzartigen Strukturen abzubilden. Diese Arbeit beschäftigt sich mit der Problemstellung, wie man Daten in rekursiven Beziehungen in einem ORM-Framework möglichst effizient aus der Datenbank laden kann. Zur Lösung des Problems werden zuerst fünf verschiedene Lösungsansätze theoretisch entwickelt, und anschließend in Entity Framework Core (EF Core) umgesetzt. Dies geschieht so, dass sich die entstandenen Implementierungen wie normale LINQ-Abfragen in EF Core nutzen lassen. Anschließend wurden die Lösungsansätze in verschiedenen Szenarien mit verschiedenen SQL-Dialekten getestet, gefolgt von einer Betrachtung der Testergebnisse nach den verschiedenen Test-Parametern. Diese Auswertung zeigt, dass Abfragen mit rekursiven allgemeinen Tabellenausdrücken und Abfragen mit KeyLoading in den meisten Fällen am effizientesten sind. Die anderen drei Ansätze sind entweder generell zu langsam oder nur in speziellen Situationen nutzbar. Die Auswertung zeigt auch, dass die Performance der verschiedenen Lösungsansätze immer von der Situation abhängig ist, besonders vom ge- nutzten SQL-Dialekt.:1 Einleitung 2 Rekursive Beziehungen in relationalen Datenbanken 2.1 Definition 2.2 Rekursive Abfragen durch allgemeine Tabellenausdrücke 3 Object-Relational Mapping und Entity Framework Core 3.1 Object Relational Impedance Mismatch 3.1.1 Konzepte der objektorientierten Programmierung 3.1.2 Konzepte von relationalen Datenbanken 3.1.3 Probleme durch Unterschiede zwischen den Konzepten 3.2 Überbrückung des Impedance Mismatch durch Object-Relational Mapping 3.2.1 ORM-Frameworks 3.2.2 Allgemeine Lösungsansätze 3.2.3 Zugehörige Daten laden 3.3 Entity Framework Core 3.3.1 Generierung des Datenbankschemas 3.3.2 Abfragen mit LINQ 3.3.3 C# Expressions 3.3.4 Ablauf einer Abfrage in Entity Framework Core 3.3.5 Der ChangeTracker 3.3.6 Abfragen mit RawSql 4 Rekursive Abfragen in ORM Frameworks 4.1 Allgemeine Lösungsansätze 4.1.1 Anforderungen an die Lösungsansätze 4.1.2 Grundlegende Überlegungen 4.1.3 Rekursive allgemeine Tabellenausdrücke 4.1.4 Benutzerdefinierte Funktionen 4.1.5 Laden mit Hilfseigenschaft 4.1.6 Vertikales und horizontales Aufrollen 4.1.7 KeyLoading 4.2 Umsetzung in Entity Framework Core 4.2.1 Anforderungen im Kontext von Entity Framework Core 4.2.2 Rekursive allgemeine Tabellenausdrücke 4.2.3 Laden mit Hilfseigenschaft 4.2.4 Vertikales Aufrollen 4.2.5 Horizontales Aufrollen 4.2.6 KeyLoading 5 Test der Lösungsansätze 5.1 Testverfahren 5.1.1 Performancemessung in C# 5.1.2 Messung der SQL-Abfragedauer 5.2 Test-Szenarien 5.3 Auswertung der Testergebnisse 5.3.1 Anmerkungen zu Messungen mit TotalProcessTime 5.3.2 Auswertung nach verschiedenen Kriterien 5.3.3 Allgemeine Auswertung 5.3.4 Auswertung nach Verzweigungen 5.3.5 Auswertung nach Rekursionstiefe 5.3.6 Auswertung nach Anzahl der Strukturen 5.3.7 Auswertung nach dem Laden zugehöriger Daten 5.3.8 Auswertung nach SQL-Dialekt 5.3.9 Auswertung nach Beziehungstyp 5.3.10 Auswertung nach Schlüsseltyp 6 Fazit A Messwerte