Iskanje po katalogu digitalne knjižnice

Ključne besede: cardinality constraint, graph database, constraint modeling, graph database integrity, property graphroperty graph, graph schema
Objavljeno v DKUM: 12.06.2024; Ogledov: 120; Prenosov: 2
Celotno besedilo (1,33 MB)
Gradivo ima več datotek! Več...

Opis: V tej diplomski nalogi smo raziskali ogrodje Hadoop, ki s svojimi komponentami tvori celovito rešitev za hranjenje in analiziranje velikih podatkov. V diplomski nalogi najprej predstavimo ogrodje in njegove glavne oziroma najbolj uporabljene komponente, kot so HDFS, MapReduce in YARN. Sledi primer vzpostavitve ogrodja na Linux distribuciji Ubuntu, ter primeri uporabe, ki podajajo smernice za shranjevanje in analiziranje različnih vrst podatkov s Hadoop.
Ključne besede: Hadoop, vele podatki, porazdeljen datotečni sistem, shranjevanje in analiza podatkov
Objavljeno v DKUM: 05.10.2023; Ogledov: 418; Prenosov: 23
Celotno besedilo (2,32 MB)

Opis: The increasing number of network-shaped domains calls for the use of graph database technology, where there are continuous efforts to develop mechanisms to address domain challenges. Relationships as 'first-class citizens' in graph databases can play an important role in studying the structural and behavioural characteristics of the domain. In this dissertation, we focus on studying the cardinality constraints mechanism, which also exploits the edges of the underlying property graph. The results of our literature review indicate an obvious research gap when it comes to concepts and approaches for specifying and representing complex cardinality constraints for graph databases validated in practice. To address this gap, we present a novel and comprehensive approach called the k-vertex cardinality constraints model for enforcing higher-order cardinality constraints rules on edges, which capture domain-related business rules of varying complexity. In our formal k-vertex cardinality constraint concept definition, we go beyond simple patterns formed between two nodes and employ more complex structures such as hypernodes, which consist of nodes connected by edges. We formally introduce the concept of k-vertex cardinality constraints and their properties as well as the property graph-based model used for their representation. Our k-vertex model includes the k-vertex cardinality constraint specification by following a pre-defined syntax followed by a visual representation through a property graph-based data model and a set of algorithms for the implementation of basic operations relevant for working with k-vertex cardinality constraints. In the practical part of the dissertation, we evaluate the applicability of the k-vertex model on use cases by carrying two separate case studies where we present how the model can be implemented on fraud detection and data classification use cases. We build a set of relevant k-vertex cardinality constraints based on real data and explain how each step of our approach is to be done. The results obtained from the case studies prove that the k-vertex model is entirely suitable to represent complex business rules as cardinality constraints and can be used to enforce these cardinality constraints in real-world business scenarios. Next, we analyze the performance efficiency of our model on inserting new edges into graph databases with varying number of edges and outgoing node degree and compare it against the case when there is no cardinality constraints checking. The results of the statistical analysis confirm a stable performance of the k-vertex model on varying datasets when compared against a case with no cardinality constraints checking. The k-vertex model shows no significant performance effect on property graphs with varying complexity and it is able to serve as a cardinality constraints enforcement mechanism without large effects on the database performance.
Ključne besede: Graph database, K-vertex cardinality constraint, Cardinality, Business rule, Property graph data model, Property graph schema, Hypernode, Performance analysis, Fraud detection, Data classification
Objavljeno v DKUM: 10.08.2022; Ogledov: 771; Prenosov: 103
Celotno besedilo (3,43 MB)

Opis: Namen diplomskega dela je predstaviti računalništvo v oblaku in podrobno raziskati ter analizirati prednosti in morebitne slabosti ne-relacijskih podatkovnih shramb, s posebno pozornostjo na dokumentnem tipu. Končni cilj je analizirati in primerjati dokumentne podatkovne shrambe kot storitve. Cilji diplomskega dela so torej analiza in primerjava oblačnih storitev dokumentnih podatkovnih shramb, izvedba testne implementacije, ki nam bo omogočila to analizo in ugotovitev funkcionalnosti, ki nam takšne shrambe ponujajo.
Ključne besede: računalništvo v oblaku, dokumentne podatkovne shrambe, oblačne storitve podatkovnih shramb
Objavljeno v DKUM: 18.10.2021; Ogledov: 1247; Prenosov: 103
Celotno besedilo (1,49 MB)

Opis: Data has never been as desired or valued as it is today. The value of data and information over the past decade has not only changed trends in business and the IT industry but has also changed the dynamic of work. Enormous amounts of aggregate data offer companies and other corporations the option to explore and study data samples. Data collection and information processing are new dynamic factors, not only for individuals but also for corporations. Companies and corporations who are able to process large amounts of data in the shortest possible time can place themselves in a leading position in certain professions. In this bachelor’s thesis we will describe the basic concepts and factors that have shaped new, cloud-based data warehouse technologies. At the same time, we also emphasize why and how these technologies are used. We focus on how the changing technology influenced the users and their consumption of data, the changing dynamics of work as well as the changes of data itself. In the practical part, we created two DWH environments (on-premises and cloud) that we compare with each other. In the experiment, we underlined the fact that CDWHs are in certain situations not always faster than TDWH.
Ključne besede: Data Warehouses, Cloud Computing, Outsourcing, Data, Information
Objavljeno v DKUM: 18.10.2021; Ogledov: 1121; Prenosov: 178
Celotno besedilo (3,58 MB)