Pular para o conteúdo principal

ER2020 - Others interesting articles about Data Modeling Databases

 

Diagram depicting the key differences between SQL Database and NoSQL Databases.
https://www.scylladb.com/resources/nosql-vs-sql/

A Workload-driven Document Database Schema Recommender (DBSR)

  • https://youtu.be/APVlxebtmLI

Aggregate oriented modeling

Input: ER Model, Read Workload (JOIN), Configurations 

First step: create a Normalize document structure and analyze the JOIN steps

Refinements of query plans removing JOINS and embeddings documents, merging document structures based on entities relationships, in order to reduce Read Operations costs

Outuput: Doument collections, query plans (with indexes) and utility matrix of recommendations

An Empirical Study on the Design and Evolution of NoSQL Database Schemas

  • https://youtu.be/Mz7P6pp5TvY

 Lack of empirical study in NoSQL

10 selected projects from GitHub: denormalized is commom but it isn't a rule, NoSQL takes longer to stabilize compared to SQL (in general), change the type of the attribute is more frequent than other schemas changes


Neo4j Keys

  • https://youtu.be/qQQ9DuBPIrU

 
Neo4J key = label + property attributes
Complete: all node have
Uniqueness: there is no two or more nodes with the value
Neo4J don't support multi-label key
 

Discovering Data Models from Event Logs

  •  https://youtu.be/J2nxUxE-r_I
 
Process Model and Data Model
Step 1 => Input: Event Log     Output:A2A Diagram = Activities x Attributes relationship
Four rule to separate A2A
 
 
 
 

Comentários

  1. Veronica dos Santos28 de abril de 2021 às 22:03

    Esse que usou o GitHub é bem interessante pq partiu de projetos de aplicações e conseguiu identificar um padrão de comportamento para NoSQL

    ResponderExcluir

Postar um comentário

Sinta-se a vontade para comentar. Críticas construtivas são sempre bem vindas.

Postagens mais visitadas deste blog

Connected Papers: Uma abordagem alternativa para revisão da literatura

Durante um projeto de pesquisa podemos encontrar um artigo que nos identificamos em termos de problema de pesquisa e também de solução. Então surge a vontade de saber como essa área de pesquisa se desenvolveu até chegar a esse ponto ou quais desdobramentos ocorreram a partir dessa solução proposta para identificar o estado da arte nesse tema. Podemos seguir duas abordagens:  realizar uma revisão sistemática usando palavras chaves que melhor caracterizam o tema em bibliotecas digitais de referência para encontrar artigos relacionados ou realizar snowballing ancorado nesse artigo que identificamos previamente, explorando os artigos citados (backward) ou os artigos que o citam (forward)  Mas a ferramenta Connected Papers propõe uma abordagem alternativa para essa busca. O problema inicial é dado um artigo de interesse, precisamos encontrar outros artigos relacionados de "certa forma". Find different methods and approaches to the same subject Track down the state of the art rese...
3 comentários
Leia mais

Knowledge Graph Embedding with Triple Context - Leitura de Abstract

  Jun Shi, Huan Gao, Guilin Qi, and Zhangquan Zhou. 2017. Knowledge Graph Embedding with Triple Context. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM '17). Association for Computing Machinery, New York, NY, USA, 2299–2302. https://doi.org/10.1145/3132847.3133119 ABSTRACT Knowledge graph embedding, which aims to represent entities and relations in vector spaces, has shown outstanding performance on a few knowledge graph completion tasks. Most existing methods are based on the assumption that a knowledge graph is a set of separate triples, ignoring rich graph features, i.e., structural information in the graph. In this paper, we take advantages of structures in knowledge graphs, especially local structures around a triple, which we refer to as triple context. We then propose a Triple-Context-based knowledge Embedding model (TCE). For each triple, two kinds of structure information are considered as its context in the graph; one is the out...
Postar um comentário
Leia mais

Exploratory Search: From Finding to Understanding - Leitura de Artigo

Gary Marchionini. 2006. Exploratory search: from finding to understanding. Commun. ACM  49, 4 (April 2006), 41–46. https://doi.org/10.1145/1121949.1121979   This article distinguishes exploratory search that blends quer ying and browsing strategies from retrieval that is best served by analytical strategies ...   Exploratory search. Search is a fundamental life activity.   A hierarchy of information needs may also be defined that ranges from basic facts that guide short-term actions (for example, the predicted chance for rain today to decide whether to bring an umbr ella) to networks of related concepts that help us under stand phenomena or execute complex activities (for example, the relationships between bond prices and stock prices to manage a retirement portfolio) to com plex networks of tacit and explicit knowledge that accretes as expertise over a lifetime (for example, the most promising paths of investigation for the sea soned scholar or designer)....
2 comentários
Leia mais