Better Than Protocol Buffers
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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. -
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 -
Protolite: Highly Optimized Protocol Buffer Serializers
Package ‘protolite’ July 28, 2021 Type Package Title Highly Optimized Protocol Buffer Serializers Author Jeroen Ooms Maintainer Jeroen Ooms <[email protected]> Description Pure C++ implementations for reading and writing several common data formats based on Google protocol-buffers. Currently supports 'rexp.proto' for serialized R objects, 'geobuf.proto' for binary geojson, and 'mvt.proto' for vector tiles. This package uses the auto-generated C++ code by protobuf-compiler, hence the entire serialization is optimized at compile time. The 'RProtoBuf' package on the other hand uses the protobuf runtime library to provide a general- purpose toolkit for reading and writing arbitrary protocol-buffer data in R. Version 2.1.1 License MIT + file LICENSE URL https://github.com/jeroen/protolite BugReports https://github.com/jeroen/protolite/issues SystemRequirements libprotobuf and protobuf-compiler LinkingTo Rcpp Imports Rcpp (>= 0.12.12), jsonlite Suggests spelling, curl, testthat, RProtoBuf, sf RoxygenNote 6.1.99.9001 Encoding UTF-8 Language en-US NeedsCompilation yes Repository CRAN Date/Publication 2021-07-28 12:20:02 UTC R topics documented: geobuf . .2 mapbox . .2 serialize_pb . .3 1 2 mapbox Index 5 geobuf Geobuf Description The geobuf format is an optimized binary format for storing geojson data with protocol buffers. These functions are compatible with the geobuf2json and json2geobuf utilities from the geobuf npm package. Usage read_geobuf(x, as_data_frame = TRUE) geobuf2json(x, pretty = FALSE) json2geobuf(json, decimals = 6) Arguments x file path or raw vector with the serialized geobuf.proto message as_data_frame simplify geojson data into data frames pretty indent json, see jsonlite::toJSON json a text string with geojson data decimals how many decimals (digits behind the dot) to store for numbers mapbox Mapbox Vector Tiles Description Read Mapbox vector-tile (mvt) files and returns the list of layers. -
Sustainability Forecasting for Apache Incubator Projects
Sustainability Forecasting for Apache Incubator Projects Likang Yin Zhuangzhi Chen DECAL and CS Department College of Information Engineering University of California, Davis Zhejiang University of Technology [email protected] [email protected] Qi Xuan Vladimir Filkov College of Information Engineering DECAL and CS Department Zhejiang University of Technology University of California, Davis [email protected] [email protected] ABSTRACT 80% of OSS projects become abandoned over time, especially the Although OSS development is very popular, ultimately more than smaller and younger projects [45]. Certainly not all OSS projects 80% of OSS projects fail. Identifying the factors associated with are meant to be widely used or even to persist beyond a college OSS success can help in devising interventions when a project semester. However, even the large, popular OSS software, widely takes a downturn. OSS success has been studied from a variety of used in our daily lives and by fortune 500 companies, started out angles, more recently in empirical studies of large numbers of di- as small projects. Thus, from a societal perspective it is important verse projects, using proxies for sustainability, e.g., internal metrics to ask: Why do some nascent OSS projects succeed and become related to productivity and external ones, related to community pop- self-sustaining while others do not [41]? And can the latter be ularity. The internal socio-technical structure of projects has also helped? been shown important, especially their dynamics. This points to To aid developer communities to build and maintain sustainable another angle on evaluating software success, from the perspective OSS projects, nonprofit organizations like the Apache Software of self-sustaining and self-governing communities. -
Tencentdb for Tcaplusdb Getting Started
TencentDB for TcaplusDB TencentDB for TcaplusDB Getting Started Product Documentation ©2013-2019 Tencent Cloud. All rights reserved. Page 1 of 32 TencentDB for TcaplusDB Copyright Notice ©2013-2019 Tencent Cloud. All rights reserved. Copyright in this document is exclusively owned by Tencent Cloud. You must not reproduce, modify, copy or distribute in any way, in whole or in part, the contents of this document without Tencent Cloud's the prior written consent. Trademark Notice All trademarks associated with Tencent Cloud and its services are owned by Tencent Cloud Computing (Beijing) Company Limited and its affiliated companies. Trademarks of third parties referred to in this document are owned by their respective proprietors. Service Statement This document is intended to provide users with general information about Tencent Cloud's products and services only and does not form part of Tencent Cloud's terms and conditions. Tencent Cloud's products or services are subject to change. Specific products and services and the standards applicable to them are exclusively provided for in Tencent Cloud's applicable terms and conditions. ©2013-2019 Tencent Cloud. All rights reserved. Page 2 of 32 TencentDB for TcaplusDB Contents Getting Started Basic Concepts Cluster Table Group Table Index Data Types Read/Write Capacity Mode Table Definition in ProtoBuf Table Definition in TDR Creating Cluster Creating Table Group Creating Table Getting Access Point Information Access TcaplusDB ©2013-2019 Tencent Cloud. All rights reserved. Page 3 of 32 TencentDB for TcaplusDB Getting Started Basic Concepts Cluster Last updated:2020-07-31 11:15:59 Cluster Overview A cluster is the basic TcaplusDB management unit, which provides independent TcaplusDB service for the business. -
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. -
Software License Agreement (EULA)
Third-party Computer Software AutoVu™ ALPR cameras • angular-animate (https://docs.angularjs.org/api/ngAnimate) licensed under the terms of the MIT License (https://github.com/angular/angular.js/blob/master/LICENSE). © 2010-2016 Google, Inc. http://angularjs.org • angular-base64 (https://github.com/ninjatronic/angular-base64) licensed under the terms of the MIT License (https://github.com/ninjatronic/angular-base64/blob/master/LICENSE). © 2010 Nick Galbreath © 2013 Pete Martin • angular-translate (https://github.com/angular-translate/angular-translate) licensed under the terms of the MIT License (https://github.com/angular-translate/angular-translate/blob/master/LICENSE). © 2014 [email protected] • angular-translate-handler-log (https://github.com/angular-translate/bower-angular-translate-handler-log) licensed under the terms of the MIT License (https://github.com/angular-translate/angular-translate/blob/master/LICENSE). © 2014 [email protected] • angular-translate-loader-static-files (https://github.com/angular-translate/bower-angular-translate-loader-static-files) licensed under the terms of the MIT License (https://github.com/angular-translate/angular-translate/blob/master/LICENSE). © 2014 [email protected] • Angular Google Maps (http://angular-ui.github.io/angular-google-maps/#!/) licensed under the terms of the MIT License (https://opensource.org/licenses/MIT). © 2013-2016 angular-google-maps • AngularJS (http://angularjs.org/) licensed under the terms of the MIT License (https://github.com/angular/angular.js/blob/master/LICENSE). © 2010-2016 Google, Inc. http://angularjs.org • AngularUI Bootstrap (http://angular-ui.github.io/bootstrap/) licensed under the terms of the MIT License (https://github.com/angular- ui/bootstrap/blob/master/LICENSE). -
Towards a Fully Automated Extraction and Interpretation of Tabular Data Using Machine Learning
UPTEC F 19050 Examensarbete 30 hp August 2019 Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Per Hedbrant Master Thesis in Engineering Physics Department of Engineering Sciences Uppsala University Sweden Abstract Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Teknisk- naturvetenskaplig fakultet UTH-enheten Motivation A challenge for researchers at CBCS is the ability to efficiently manage the Besöksadress: different data formats that frequently are changed. Significant amount of time is Ångströmlaboratoriet Lägerhyddsvägen 1 spent on manual pre-processing, converting from one format to another. There are Hus 4, Plan 0 currently no solutions that uses pattern recognition to locate and automatically recognise data structures in a spreadsheet. Postadress: Box 536 751 21 Uppsala Problem Definition The desired solution is to build a self-learning Software as-a-Service (SaaS) for Telefon: automated recognition and loading of data stored in arbitrary formats. The aim of 018 – 471 30 03 this study is three-folded: A) Investigate if unsupervised machine learning Telefax: methods can be used to label different types of cells in spreadsheets. B) 018 – 471 30 00 Investigate if a hypothesis-generating algorithm can be used to label different types of cells in spreadsheets. C) Advise on choices of architecture and Hemsida: technologies for the SaaS solution. http://www.teknat.uu.se/student Method A pre-processing framework is built that can read and pre-process any type of spreadsheet into a feature matrix. Different datasets are read and clustered. An investigation on the usefulness of reducing the dimensionality is also done. -
Datacenter Tax Cuts: Improving WSC Efficiency Through Protocol Buffer Acceleration
Datacenter Tax Cuts: Improving WSC Efficiency Through Protocol Buffer Acceleration Dinesh Parimi William J. Zhao Jerry Zhao University of California, Berkeley University of California, Berkeley University of California, Berkeley [email protected] william [email protected] [email protected] Abstract—According to recent literature, at least 25% of cycles will serialize some set of objects stored in memory to a in a modern warehouse-scale computer are spent on common portable format defined by the protobuf compiler (protoc). “building blocks” [1]. Referred to by Kanev et al. as a “datacenter The serialized objects can be sent to some remote device, tax”, these tasks are prime candidates for hardware acceleration, as even modest improvements here can generate immense cost which will then deserialize the object into its own memory and power savings given the scale of such systems. to execute on. Thus protobuf is widely used to implement One of these tasks is protocol buffer serialization and parsing. remote procedure calls (RPC), since it facilitates the transport Protocol buffers are an open-source mechanism for representing of arguments across a network. Protobuf remains the most structured data developed by Google, and used extensively in popular serialization framework due to its maturity, backwards their datacenters for communication and remote procedure calls. While the source code for protobufs is highly optimized, certain compatibility, and extensibility. Specifically, the encoding tasks - such as the compression/decompression of integer fields scheme enables future changes to the protobuf schema to and the encoding of variable-length strings - bottleneck the remain backwards compatible. throughput of serializing or parsing a protobuf. -
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. -
Distributed Services with Go Your Guide to Reliable, Scalable, and Maintainable Systems
Extracted from: Distributed Services with Go Your Guide to Reliable, Scalable, and Maintainable Systems This PDF file contains pages extracted from Distributed Services with Go, published by the Pragmatic Bookshelf. For more information or to purchase a paperback or PDF copy, please visit http://www.pragprog.com. Note: This extract contains some colored text (particularly in code listing). This is available only in online versions of the books. The printed versions are black and white. Pagination might vary between the online and printed versions; the content is otherwise identical. Copyright © 2021 The Pragmatic Programmers, LLC. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form, or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior consent of the publisher. The Pragmatic Bookshelf Raleigh, North Carolina Distributed Services with Go Your Guide to Reliable, Scalable, and Maintainable Systems Travis Jeffery The Pragmatic Bookshelf Raleigh, North Carolina Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and The Pragmatic Programmers, LLC was aware of a trademark claim, the designations have been printed in initial capital letters or in all capitals. The Pragmatic Starter Kit, The Pragmatic Programmer, Pragmatic Programming, Pragmatic Bookshelf, PragProg and the linking g device are trade- marks of The Pragmatic Programmers, LLC. Every precaution was taken in the preparation of this book. However, the publisher assumes no responsibility for errors or omissions, or for damages that may result from the use of information (including program listings) contained herein.