The Forgotten Document-Oriented Database Management Systems
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Document Databases, JSON, Mongodb 17
MI-PDB, MIE-PDB: Advanced Database Systems http://www.ksi.mff.cuni.cz/~svoboda/courses/2015-2-MIE-PDB/ Lecture 13: Document Databases, JSON, MongoDB 17. 5. 2016 Lecturer: Martin Svoboda [email protected] Authors: Irena Holubová, Martin Svoboda Faculty of Mathematics and Physics, Charles University in Prague Course NDBI040: Big Data Management and NoSQL Databases Document Databases Basic Characteristics Documents are the main concept Stored and retrieved XML, JSON, … Documents are Self-describing Hierarchical tree data structures Can consist of maps, collections, scalar values, nested documents, … Documents in a collection are expected to be similar Their schema can differ Document databases store documents in the value part of the key-value store Key-value stores where the value is examinable Document Databases Suitable Use Cases Event Logging Many different applications want to log events Type of data being captured keeps changing Events can be sharded by the name of the application or type of event Content Management Systems, Blogging Platforms Managing user comments, user registrations, profiles, web-facing documents, … Web Analytics or Real-Time Analytics Parts of the document can be updated New metrics can be easily added without schema changes E-Commerce Applications Flexible schema for products and orders Evolving data models without expensive data migration Document Databases When Not to Use Complex Transactions Spanning Different Operations Atomic cross-document operations Some document databases do support (e.g., RavenDB) Queries against Varying Aggregate Structure Design of aggregate is constantly changing → we need to save the aggregates at the lowest level of granularity i.e., to normalize the data Document Databases Representatives Lotus Notes Storage Facility JSON JavaScript Object Notation Introduction • JSON = JavaScript Object Notation . -
Smart Grid Serialization Comparison
Downloaded from orbit.dtu.dk on: Sep 28, 2021 Smart Grid Serialization Comparison Petersen, Bo Søborg; Bindner, Henrik W.; You, Shi; Poulsen, Bjarne Published in: Computing Conference 2017 Link to article, DOI: 10.1109/SAI.2017.8252264 Publication date: 2017 Document Version Peer reviewed version Link back to DTU Orbit Citation (APA): Petersen, B. S., Bindner, H. W., You, S., & Poulsen, B. (2017). Smart Grid Serialization Comparison. In Computing Conference 2017 (pp. 1339-1346). IEEE. https://doi.org/10.1109/SAI.2017.8252264 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Computing Conference 2017 18-20 July 2017 | London, UK Smart Grid Serialization Comparision Comparision of serialization for distributed control in the context of the Internet of Things Bo Petersen, Henrik Bindner, Shi You Bjarne Poulsen DTU Electrical Engineering DTU Compute Technical University of Denmark Technical University of Denmark Lyngby, Denmark Lyngby, Denmark [email protected], [email protected], [email protected] [email protected] Abstract—Communication between DERs and System to ensure that the control messages are received within a given Operators is required to provide Demand Response and solve timeframe, depending on the needs of the power grid. -
Health Sensor Data Management in Cloud
Special Issue - 2015 International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 NCRTS-2015 Conference Proceedings Health Sensor Data Management in Cloud Rashmi Sahu Department of Computer Science and Engineering BMSIT,Avallahalli,Yelahanka,Bangalore Visveswariya Technological University Abstract--Wearable sensor devices with cloud computing uses its software holds 54% of patient records in US and feature have great impact in our daily lives. This 2.5% of patient records in world wide.[9] technology provides services to acquire, consume and share personal health information. Apart from that we can be How resource wastage can be refused by using cloud connected with smart phones through which we can access technology information through sensor devices equipped with our smart phone. Now smartphones has been resulted in the new ways. It is getting embedded with sensor devices such as Suppose there are 3 Hospitals A,B,C.Each hospital cameras, microphones, accelerometers, proximity sensors, maintains their own network database server,they have GPS etc. through which we can track information and management department and softwares,maintainance significant parameter about physiology. Some of the department and softwares.They organizes their own data wearable tech devices are popular today like Jawbone Up and they maintained by their own.But there is resource and Fitbit Flex, HeartMath Inner Balance Sensor, wastage,means three different health organizations Tinke.This paper is survey in area of medical field that utilizing resources having paid and costs three times of represents why cloud technologies used in medical field and single plus waste of data space also.so why can’t we how health data managed in cloud. -
Spindle Documentation Release 2.0.0
spindle Documentation Release 2.0.0 Jorge Ortiz, Jason Liszka June 08, 2016 Contents 1 Thrift 3 1.1 Data model................................................3 1.2 Interface definition language (IDL)...................................4 1.3 Serialization formats...........................................4 2 Records 5 2.1 Creating a record.............................................5 2.2 Reading/writing records.........................................6 2.3 Record interface methods........................................6 2.4 Other methods..............................................7 2.5 Mutable trait...............................................7 2.6 Raw class.................................................7 2.7 Priming..................................................7 2.8 Proxies..................................................8 2.9 Reflection.................................................8 2.10 Field descriptors.............................................8 3 Custom types 9 3.1 Enhanced types..............................................9 3.2 Bitfields..................................................9 3.3 Type-safe IDs............................................... 10 4 Enums 13 4.1 Enum value methods........................................... 13 4.2 Companion object methods....................................... 13 4.3 Matching and unknown values...................................... 14 4.4 Serializing to string............................................ 14 4.5 Examples................................................. 14 5 Working -
Rdf Repository Replacing Relational Database
RDF REPOSITORY REPLACING RELATIONAL DATABASE 1B.Srinivasa Rao, 2Dr.G.Appa Rao 1,2Department of CSE, GITAM University Email:[email protected],[email protected] Abstract-- This study is to propose a flexible enable it. One such technology is RDF (Resource information storage mechanism based on the Description Framework)[2]. RDF is a directed, principles of Semantic Web that enables labelled graph for representing information in the information to be searched rather than queried. Web. This can be perceived as a repository In this study, a prototype is developed where without any predefined structure the focus is on the information rather than the The information stored in the traditional structure. Here information is stored in a RDBMS’s requires structure to be defined structure that is constructed on the fly. Entities upfront. On the contrary, information could be in the system are connected and form a graph, very complex to structure upfront despite the similar to the web of data in the Internet. This tremendous potential offered by the existing data is persisted in a peculiar way to optimize database systems. In the ever changing world, querying on this graph of data. All information another important characteristic of information relating to a subject is persisted closely so that in a system that impacts its structure is the reqeusting any information of a subject could be modification/enhancement to the system. This is handled in one call. Also, the information is a big concern with many software systems that maintained in triples so that the entire exist today and there is no tidy approach to deal relationship from subject to object via the with the problem. -
Basex Server
BaseX Documentation Version 7.8 BaseX Documentation: Version 7.8 Content is available under Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0). Table of Contents 1. Main Page .............................................................................................................................. 1 Getting Started .................................................................................................................. 1 XQuery Portal .................................................................................................................... 1 Advanced User's Guide ..................................................................................................... 2 I. Getting Started ........................................................................................................................ 3 2. Command-Line Options ................................................................................................... 4 BaseX Standalone ..................................................................................................... 4 BaseX Server ............................................................................................................ 6 BaseX Client ............................................................................................................. 7 BaseX HTTP Server .................................................................................................. 9 BaseX GUI ............................................................................................................. -
CBOR (RFC 7049) Concise Binary Object Representation
CBOR (RFC 7049) Concise Binary Object Representation Carsten Bormann, 2015-11-01 1 CBOR: Agenda • What is it, and when might I want it? • How does it work? • How do I work with it? 2 CBOR: Agenda • What is it, and when might I want it? • How does it work? • How do I work with it? 3 Slide stolen from Douglas Crockford History of Data Formats • Ad Hoc • Database Model • Document Model • Programming Language Model Box notation TLV 5 XML XSD 6 Slide stolen from Douglas Crockford JSON • JavaScript Object Notation • Minimal • Textual • Subset of JavaScript Values • Strings • Numbers • Booleans • Objects • Arrays • null Array ["Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"] [ [0, -1, 0], [1, 0, 0], [0, 0, 1] ] Object { "name": "Jack B. Nimble", "at large": true, "grade": "A", "format": { "type": "rect", "width": 1920, "height": 1080, "interlace": false, "framerate": 24 } } Object Map { "name": "Jack B. Nimble", "at large": true, "grade": "A", "format": { "type": "rect", "width": 1920, "height": 1080, "interlace": false, "framerate": 24 } } JSON limitations • No binary data (byte strings) • Numbers are in decimal, some parsing required • Format requires copying: • Escaping for strings • Base64 for binary • No extensibility (e.g., date format?) • Interoperability issues • I-JSON further reduces functionality (RFC 7493) 12 BSON and friends • Lots of “binary JSON” proposals • Often optimized for data at rest, not protocol use (BSON ➔ MongoDB) • Most are more complex than JSON 13 Why a new binary object format? • Different design goals from current formats – stated up front in the document • Extremely small code size – for work on constrained node networks • Reasonably compact data size – but no compression or even bit-fiddling • Useful to any protocol or application that likes the design goals 14 Concise Binary Object Representation (CBOR) 15 “Sea Boar” “Sea Boar” 16 Design goals (1 of 2) 1. -
JSON JSON (Javascript Object Notation) Ecmascript Javascript
ECMAScript JSON ECMAScript is standardized JavaScript. The current version is the 12th edition: Péter Jeszenszky Ecma International, ECMAScript 2021 Language Specification, Standard ECMA-262, 12th ed., June 2021. https://www.ecma- international.org/publications-and-standards/standards/ecma-262/ October 8, 2021 The next version currently under development is ECMAScript 2022: ECMAScript 2022 Language Specification https://tc39.es/ecma262/ Péter Jeszenszky JSON October 8, 2021 1 / 94 Péter Jeszenszky JSON October 8, 2021 3 / 94 JSON (JavaScript Object Notation) JavaScript Lightweight, textual, and platform independent data exchange format. Used for representing structured data. The term JavaScript is used for the implementations of ECMAScript by different vendors. Can be read and written easily by humans. See also: JavaScript technologies overview Can be generated and processed easily by computer programs. https://developer.mozilla.org/en- US/docs/Web/JavaScript/JavaScript_technologies_overview Originates from the ECMAScript programming language. Website: https://www.json.org/ Péter Jeszenszky JSON October 8, 2021 2 / 94 Péter Jeszenszky JSON October 8, 2021 4 / 94 JavaScript Engines (1) Node.js (1) SpiderMonkey (written in: C/C++; license: Mozilla Public License 2.0) https://spidermonkey.dev/ A JavaScript runtime environment built on the V8 JavaScript engine The JavaScript engine of the Mozilla Project. that is designed to build scalable network applications. V8 (written in: C++; license: New BSD License) https://v8.dev/ Website: https://nodejs.org/ https://github.com/nodejs/node https://github.com/v8/v8/ License: MIT License The JavaScript engine of Chromium. Written in: C++, JavaScript JavaScriptCore (written in: C++; license: LGPLv2) https://developer.apple.com/documentation/javascriptcore https: Platform: Linux, macOS, Windows //github.com/WebKit/webkit/tree/master/Source/JavaScriptCore The JavaScript engine developed for the WebKit rendering engine. -
Declarative Access to Filesystem Data New Application Domains for XML Database Management Systems
Declarative Access to Filesystem Data New application domains for XML database management systems Alexander Holupirek Dissertation zur Erlangung des akademischen Grades Doktor der Naturwissenschaften (Dr. rer. nat.) Fachbereich Informatik und Informationswissenschaft Mathematisch-Naturwissenschaftliche Sektion Universität Konstanz Referenten: Prof. Dr. Marc H. Scholl Prof. Dr. Marcel Waldvogel Tag der mündlichen Prüfung: 17. Juli 2012 Abstract XML and state-of-the-art XML database management systems (XML-DBMSs) can play a leading role in far more application domains as it is currently the case. Even in their basic configuration, they entail all components necessary to act as central systems for complex search and retrieval tasks. They provide language-specific index- ing of full-text documents and can store structured, semi-structured and binary data. Besides, they offer a great variety of standardized languages (XQuery, XSLT, XQuery Full Text, etc.) to develop applications inside a pure XML technology stack. Benefits are obvious: Data, logic, and presentation tiers can operate on a single data model, and no conversions have to be applied when switching in between. This thesis deals with the design and development of XML/XQuery driven informa- tion architectures that process formerly heterogeneous data sources in a standardized and uniform manner. Filesystems and their vast amounts of different file types are a prime example for such a heterogeneous dataspace. A new XML dialect, the Filesystem Markup Language (FSML), is introduced to construct a database view of the filesystem and its contents. FSML provides a uniform view on the filesystem’s contents and allows developers to leverage the complete XML technology stack on filesystem data. -
Requirements for XML Document Database Systems Airi Salminen Frank Wm
Requirements for XML Document Database Systems Airi Salminen Frank Wm. Tompa Dept. of Computer Science and Information Systems Department of Computer Science University of Jyväskylä University of Waterloo Jyväskylä, Finland Waterloo, ON, Canada +358-14-2603031 +1-519-888-4567 ext. 4675 [email protected] [email protected] ABSTRACT On the other hand, XML will also be used in ways SGML and The shift from SGML to XML has created new demands for HTML were not, most notably as the data exchange format managing structured documents. Many XML documents will be between different applications. As was the situation with transient representations for the purpose of data exchange dynamically created HTML documents, in the new areas there is between different types of applications, but there will also be a not necessarily a need for persistent storage of XML documents. need for effective means to manage persistent XML data as a Often, however, document storage and the capability to present database. In this paper we explore requirements for an XML documents to a human reader as they are or were transmitted is database management system. The purpose of the paper is not to important to preserve the communications among different parties suggest a single type of system covering all necessary features. in the form understood and agreed to by them. Instead the purpose is to initiate discussion of the requirements Effective means for the management of persistent XML data as a arising from document collections, to offer a context in which to database are needed. We define an XML document database (or evaluate current and future solutions, and to encourage the more generally an XML database, since every XML database development of proper models and systems for XML database must manage documents) to be a collection of XML documents management. -
Using Map and Reduce for Querying Distributed XML Data
Using Map and Reduce for Querying Distributed XML Data Lukas Lewandowski Master Thesis in fulfillment of the requirements for the degree of Master of Science (M.Sc.) Submitted to the Department of Computer and Information Science at the University of Konstanz Reviewer: Prof. Dr. Marc H. Scholl Prof. Dr. Marcel Waldvogel Abstract Semi-structured information is often represented in the XML format. Although, a vast amount of appropriate databases exist that are responsible for efficiently storing semi- structured data, the vastly growing data demands larger sized databases. Even when the secondary storage is able to store the large amount of data, the execution time of complex queries increases significantly, if no suitable indexes are applicable. This situation is dramatic when short response times are an essential requirement, like in the most real-life database systems. Moreover, when storage limits are reached, the data has to be distributed to ensure availability of the complete data set. To meet this challenge this thesis presents two approaches to improve query evaluation on semi- structured and large data through parallelization. First, we analyze Hadoop and its MapReduce framework as candidate for our distributed computations and second, then we present an alternative implementation to cope with this requirements. We introduce three distribution algorithms usable for XML collections, which serve as base for our distribution to a cluster. Furthermore, we present a prototype implementation using a current open source database, named BaseX, which serves as base for our comprehensive query results. iii Acknowledgments I would like to thank my advisors Professor Marc H. Scholl and Professor Marcel Wald- vogel, who have supported me with advice and guidance throughout my master thesis. -
XML Normal Form (XNF)
Ryan Marcotte www.cs.uregina.ca/~marcottr CS 475 (Advanced Topics in Databases) March 14, 2011 Outline Introduction to XNF and motivation for its creation Analysis of XNF’s link to BCNF Algorithm for converting a DTD to XNF Example March 14, 2011 Ryan Marcotte 2 March 14, 2011 Ryan Marcotte 3 Introduction XML is used for data storage and exchange Data is stored in a hierarchical fashion Duplicates and inconsistencies may exist in the data store March 14, 2011 Ryan Marcotte 4 Introduction Relational databases store data according to some schema XML also stores data according to some schema, such as a Document Type Definition (DTD) Obviously, some schemas are better than others A normal form is needed that reduces the amount of storage needed while ensuring consistency and eliminating redundancy March 14, 2011 Ryan Marcotte 5 Introduction XNF was proposed by Marcelo Arenas and Leonid Libkin (University of Toronto) in a 2004 paper titled “A Normal Form for XML Documents” Recognized a need for good XML data design as “a lot of data is being put on the web” “Once massive web databases are created, it is very hard to change their organization; thus, there is a risk of having large amounts of widely accessible, but at the same time poorly organized legacy data.” March 14, 2011 Ryan Marcotte 6 Introduction XNF provides a set of rules that describe well-formed DTDs Poorly-designed DTDs can be transformed into well- formed ones (through normalization – just like relational databases!) Well-formed DTDs avoid redundancies and update