JSON Developer's Guide
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Declarative Languages for Big Streaming Data a Database Perspective
Tutorial Declarative Languages for Big Streaming Data A database Perspective Riccardo Tommasini Sherif Sakr University of Tartu Unversity of Tartu [email protected] [email protected] Emanuele Della Valle Hojjat Jafarpour Politecnico di Milano Confluent Inc. [email protected] [email protected] ABSTRACT sources and are pushed asynchronously to servers which are The Big Data movement proposes data streaming systems to responsible for processing them [13]. tame velocity and to enable reactive decision making. However, To facilitate the adoption, initially, most of the big stream approaching such systems is still too complex due to the paradigm processing systems provided their users with a set of API for shift they require, i.e., moving from scalable batch processing to implementing their applications. However, recently, the need for continuous data analysis and pattern detection. declarative stream processing languages has emerged to simplify Recently, declarative Languages are playing a crucial role in common coding tasks; making code more readable and main- fostering the adoption of Stream Processing solutions. In partic- tainable, and fostering the development of more complex appli- ular, several key players introduce SQL extensions for stream cations. Thus, Big Data frameworks (e.g., Flink [9], Spark [3], 1 processing. These new languages are currently playing a cen- Kafka Streams , and Storm [19]) are starting to develop their 2 3 4 tral role in fostering the stream processing paradigm shift. In own SQL-like approaches (e.g., Flink SQL , Beam SQL , KSQL ) this tutorial, we give an overview of the various languages for to declaratively tame data velocity. declarative querying interfaces big streaming data. -
JSON Hijacking for the Modern Web About Me
JSON hijacking For the modern web About me • I’m a researcher at PortSwigger • I love hacking JavaScript let:let{let:[x=1]}=[alert(1)] • I love breaking browsers • @garethheyes History of JSON hijacking • Array constructor attack function Array(){ for(var i=0;i<this.length;i++) { alert(this[i]); } } [1,2,3] • Found by Joe Walker in 2007 • Worked against Gmail in 2007 by Jeremiah Grossman • Fixed in every browser History of JSON hijacking • Object.prototype setter attack Object.prototype.__defineSetter__('user', function(obj){ for(var i in obj) { alert(i + '=' + obj[i]); } }); [{user:{name:"test"}}] • Worked against Twitter • Fixed in every browser Journey of bug discovery James:Can you create a polyglot js/jpeg? Me:Yeah, that sounds like fun. “Polyglot is something that executes in more than one language or format” Anatomy of a jpeg FF D8 FF E0 Anatomy of a jpeg • Start of image marker: FF D8 • Application header: FF E0 00 00 Two bytes we control Anatomy of a jpeg • Guess which two bytes I chose? Rest of app header Valid JS variable • 2F 2A JS comment • /* • FF D8 FF E0 2F 2A 4A 46 49 46 00 01 01 01 00 48 00 48 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00… Padding of nulls for 0x2f2a Anatomy of a jpeg • Inject our payload inside a jpeg comment • FF FE 00 1C • */=alert("Burp rocks.")/* Anatomy of a jpeg • At the end of the image we need to modify the image data • Close our comment • Inject a single line comment after • */// • 2A 2F 2F 2F FF D9 Anatomy of a jpeg • That should work right? <script src="polyglot/uploads/xss.jpg"></script> -
Introduction to JSON (Javascript Object Notation)
IInnttrroodduuccttiioonn ttoo JJSSOONN ((JJaavvaaSSccrriipptt OObbjjeecctt NNoottaattiioonn)) SSaanngg SShhiinn JJaavvaa TTeecchhnonollogogyy AArrcchhiitteecctt SSunun MMiiccrrososyysstteemmss,, IIncnc.. ssaanngg..sshhiinn@@ssunun..ccoomm wwwwww..jjaavvaapapassssiioon.n.ccoomm Disclaimer & Acknowledgments ● Even though Sang Shin is a full-time employee of Sun Microsystems, the contents here are created as his own personal endeavor and thus does not reflect any official stance of Sun Microsystems 2 Topics • What is JSON? • JSON Data Structure > JSON Object > JSON text • JSON and Java Technology • How to send and receive JSON data at both client and server sides • JSON-RPC • Resources 3 WWhhaatt iiss && WWhhyy JJSSOONN?? What is JSON? • Lightweight data-interchange format > Compared to XML • Simple format > Easy for humans to read and write > Easy for machines to parse and generate • JSON is a text format > Programming language independent > Uses conventions that are familiar to programmers of the C- family of languages, including C, C++, C#, Java, JavaScript, Perl, Python 5 Why Use JSON over XML • Lighter and faster than XML as on-the-wire data format • JSON objects are typed while XML data is typeless > JSON types: string, number, array, boolean, > XML data are all string • Native data form for JavaScript code > Data is readily accessible as JSON objects in your JavaScript code vs. XML data needed to be parsed and assigned to variables through tedious DOM APIs > Retrieving values is as easy as reading from an object property in your JavaScript -
OCF Core Optional 2.1.0
OCF Core - Optional Specification VERSION 2.1.0 | November 2019 CONTACT [email protected] Copyright Open Connectivity Foundation, Inc. © 2019 All Rights Reserved. 2 Legal Disclaimer 3 4 NOTHING CONTAINED IN THIS DOCUMENT SHALL BE DEEMED AS GRANTING YOU ANY KIND 5 OF LICENSE IN ITS CONTENT, EITHER EXPRESSLY OR IMPLIEDLY, OR TO ANY 6 INTELLECTUAL PROPERTY OWNED OR CONTROLLED BY ANY OF THE AUTHORS OR 7 DEVELOPERS OF THIS DOCUMENT. THE INFORMATION CONTAINED HEREIN IS PROVIDED 8 ON AN "AS IS" BASIS, AND TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, 9 THE AUTHORS AND DEVELOPERS OF THIS SPECIFICATION HEREBY DISCLAIM ALL OTHER 10 WARRANTIES AND CONDITIONS, EITHER EXPRESS OR IMPLIED, STATUTORY OR AT 11 COMMON LAW, INCLUDING, BUT NOT LIMITED TO, IMPLIED WARRANTIES OF 12 MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. OPEN CONNECTIVITY 13 FOUNDATION, INC. FURTHER DISCLAIMS ANY AND ALL WARRANTIES OF NON- 14 INFRINGEMENT, ACCURACY OR LACK OF VIRUSES. 15 The OCF logo is a trademark of Open Connectivity Foundation, Inc. in the United States or other 16 countries. *Other names and brands may be claimed as the property of others. 17 Copyright © 2016-2019 Open Connectivity Foundation, Inc. All rights reserved. 18 Copying or other form of reproduction and/or distribution of these works are strictly prohibited. 19 Copyright Open Connectivity Foundation, Inc. © 2016-2019. All rights Reserved 20 CONTENTS 21 1 Scope ............................................................................................................................. -
Understanding JSON Schema Release 2020-12
Understanding JSON Schema Release 2020-12 Michael Droettboom, et al Space Telescope Science Institute Sep 14, 2021 Contents 1 Conventions used in this book3 1.1 Language-specific notes.........................................3 1.2 Draft-specific notes............................................4 1.3 Examples.................................................4 2 What is a schema? 7 3 The basics 11 3.1 Hello, World!............................................... 11 3.2 The type keyword............................................ 12 3.3 Declaring a JSON Schema........................................ 13 3.4 Declaring a unique identifier....................................... 13 4 JSON Schema Reference 15 4.1 Type-specific keywords......................................... 15 4.2 string................................................... 17 4.2.1 Length.............................................. 19 4.2.2 Regular Expressions...................................... 19 4.2.3 Format.............................................. 20 4.3 Regular Expressions........................................... 22 4.3.1 Example............................................. 23 4.4 Numeric types.............................................. 23 4.4.1 integer.............................................. 24 4.4.2 number............................................. 25 4.4.3 Multiples............................................ 26 4.4.4 Range.............................................. 26 4.5 object................................................... 29 4.5.1 Properties........................................... -
Convert Json Into Html Table
Convert Json Into Html Table Unsatisfying and insufficient Ephrayim run-throughs her wavemeters outbalanced or uncoils brassily. Smoke-dried Waring Tedstill serialises: criticizes her derogate throttle and precinct sea-level alkalising Percival and frog seaplane quite mighty desolately. but inures her complacency vividly. Ralline and usufruct Now should return the question is that makes it as a little bit more readable html table into an array into the table header, with intent to In out output html file because i our trying to convert their huge json data. Json-to-HTML-Table 101 NuGet Gallery. Use this tool for convert JSON into an HTML Table And thanks to the MySQL JSONTABLE function we operate always transform the JSON objects into unique virtual. Ankitaps You survive try using Dataweave to convert JSON to XML and probably use XSLT to convert XML to HTML Or simply you read try using. ResponseText convert soap response object a json object appendjsondata pass the. Productivity picks for contributing an html table into the query because checkboxes allow multiple values? My knowledge approach you I built it 4-5 years ago so to embed JSON data augment the HTML page and sludge use JavaScript to crumple that JSON data. When there was this follow users and we only work fast, indentation and beautify and read data into an html generation part goes inside html table into json html tables from an online? Convert JSON to HTML Tool Slick. DOCTYPE html 2 3 4 Convert JSON Data to HTML Table 5 6 th td p input 7 font14px Verdana. -
Kodai: a Software Architecture and Implementation for Segmentation
University of Rhode Island DigitalCommons@URI Open Access Master's Theses 2017 Kodai: A Software Architecture and Implementation for Segmentation Rick Rejeleene University of Rhode Island, [email protected] Follow this and additional works at: https://digitalcommons.uri.edu/theses Recommended Citation Rejeleene, Rick, "Kodai: A Software Architecture and Implementation for Segmentation" (2017). Open Access Master's Theses. Paper 1107. https://digitalcommons.uri.edu/theses/1107 This Thesis is brought to you for free and open access by DigitalCommons@URI. It has been accepted for inclusion in Open Access Master's Theses by an authorized administrator of DigitalCommons@URI. For more information, please contact [email protected]. KODAI: A SOFTWARE ARCHITECTURE AND IMPLEMENTATION FOR SEGMENTATION BY RICK REJELEENE A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS OF MASTER OF SCIENCE IN COMPUTER SCIENCE UNIVERSITY OF RHODE ISLAND 2017 MASTER OF SCIENCE THESIS OF RICK REJELEENE APPROVED: Thesis Committee: Major Professor: Joan Peckham Lisa DiPippo Ruby Dholakia Nasser H Zawia DEAN OF GRADUATE COMMITTEE UNIVERSITY OF RHODE ISLAND 2017 ABSTRACT The purpose of this thesis is to design and implement a software architecture for segmen- tation models to improve revenues for a supermarket. This tool supports analysis of su- permarket products and generates results to interpret consumer behavior, to give busi- nesses deeper insights into targeted consumer markets. The software design developed is named as Kodai. Kodai is horizontally reusable and can be adapted across various indus- tries. This software framework allows testing a hypothesis to address the problem of in- creasing revenues in supermarkets. Kodai has several advantages, such as analyzing and visualizing data, and as a result, businesses can make better decisions. -
DARPA and Data: a Portfolio Overview
DARPA and Data: A Portfolio Overview William C. Regli Special Assistant to the Director Defense Advanced Research Projects Agency Brian Pierce Director Information Innovation Office Defense Advanced Research Projects Agency Fall 2017 Distribution Statement “A” (Approved for Public Release, Distribution Unlimited) 1 DARPA Dreams of Data • Investments over the past decade span multiple DARPA Offices and PMs • Information Innovation (I2O): Software Systems, AI, Data Analytics • Defense Sciences (DSO): Domain-driven problems (chemistry, social science, materials science, engineering design) • Microsystems Technology (MTO): New hardware to support these processes (neuromorphic processor, graph processor, learning systems) • Products include DARPA Program testbeds, data and software • The DARPA Open Catalog • Testbeds include those in big data, cyber-defense, engineering design, synthetic bio, machine reading, among others • Multiple layers and qualities of data are important • Important for reproducibility; important as fuel for future DARPA programs • Beyond public data to include “raw” data, process/workflow data • Data does not need to be organized to be useful or valuable • Software tools are getting better eXponentially, ”raw” data can be processed • Changing the economics (Forensic Data Curation) • Its about optimizing allocation of attention in human-machine teams Distribution Statement “A” (Approved for Public Release, Distribution Unlimited) 2 Working toward Wisdom Wisdom: sound judgment - governance Abstraction Wisdom (also Understanding: -
STORM: Refinement Types for Secure Web Applications
STORM: Refinement Types for Secure Web Applications Nico Lehmann Rose Kunkel Jordan Brown Jean Yang UC San Diego UC San Diego Independent Akita Software Niki Vazou Nadia Polikarpova Deian Stefan Ranjit Jhala IMDEA Software Institute UC San Diego UC San Diego UC San Diego Abstract Centralizing policy specification is not a new idea. Several We present STORM, a web framework that allows developers web frameworks (e.g., HAILS [4], JACQUELINE [5], and to build MVC applications with compile-time enforcement of LWEB [6]) already do this. These frameworks, however, have centrally specified data-dependent security policies. STORM two shortcomings that have hindered their adoption. First, ensures security using a Security Typed ORM that refines the they enforce policies at run-time, typically using dynamic (type) abstractions of each layer of the MVC API with logical information flow control (IFC). While dynamic enforcement assertions that describe the data produced and consumed by is better than no enforcement, dynamic IFC imposes a high the underlying operation and the users allowed access to that performance overhead, since the system must be modified to data. To evaluate the security guarantees of STORM, we build a track the provenance of data and restrict where it is allowed formally verified reference implementation using the Labeled to flow. More importantly, certain policy violations are only IO (LIO) IFC framework. We present case studies and end-to- discovered once the system is deployed, at which point they end applications that show how STORM lets developers specify may be difficult or expensive to fix, e.g., on applications diverse policies while centralizing the trusted code to under 1% running on IoT devices [7]. -
The Latest IBM Z COBOL Compiler: Enterprise COBOL V6.2!
The latest IBM Z COBOL compiler: Enterprise COBOL V6.2! Tom Ross Captain COBOL SHARE Providence August 7,2017 1 COBOL V6.2 ? YES! • The 4 th release of the new generation of IBM Z COBOL compilers • Announced: July 17, 2017 • The same day as IBM z14 hardware…coincidence? • GA: September 8, 2017 • Compiler support for the new IBM z14 hardware and IBM z/OS V2.3 • Ability to exploit the new Vector Packed Decimal Facility of z14 • ‘OLD’ news: • COBOL V5 EOM Sept 11, 2017 (announced Dec 6, 2016) • EOS for COBOL V4 ‘might’ be earlier than 2020, still discussing 2 COBOL V6.2 ? What else does it have? • New and changed COBOL statements, such as the new JSON PARSE statement • Support of COBOL 2002/2014 standards with the addition of the COBOL Conditional Compilation language feature • New and changed COBOL options for increased flexibility • Improved compiler listings with compiler messages at the end of the listing as in previous releases of the compiler • Improved interfaces to optional products and tools such as IBM Debug for z Systems (formerly Debug Tool for z/OS) and IBM Application Discovery and Delivery Intelligence (formerly EzSource) • Compile-time and runtime performance enhancements • Improved usability of the compiler in the z/OS UNIX System Services environment 3 Vector Packed Decimal Facility of z14 • Enterprise COBOL V6.2 adds support for exploiting the new Vector Packed Decimal Facility in z14 through the ARCH(12) compiler option. • The Vector Packed Decimal Facility allows the dominant COBOL data types, packed and zoned decimal, to be handled in wide 16-byte vector registers instead of in memory. -
FOSS Philosophy 6 the FOSS Development Method 7
1 Published by the United Nations Development Programme’s Asia-Pacific Development Information Programme (UNDP-APDIP) Kuala Lumpur, Malaysia www.apdip.net Email: [email protected] © UNDP-APDIP 2004 The material in this book may be reproduced, republished and incorporated into further works provided acknowledgement is given to UNDP-APDIP. For full details on the license governing this publication, please see the relevant Annex. ISBN: 983-3094-00-7 Design, layout and cover illustrations by: Rezonanze www.rezonanze.com PREFACE 6 INTRODUCTION 6 What is Free/Open Source Software? 6 The FOSS philosophy 6 The FOSS development method 7 What is the history of FOSS? 8 A Brief History of Free/Open Source Software Movement 8 WHY FOSS? 10 Is FOSS free? 10 How large are the savings from FOSS? 10 Direct Cost Savings - An Example 11 What are the benefits of using FOSS? 12 Security 13 Reliability/Stability 14 Open standards and vendor independence 14 Reduced reliance on imports 15 Developing local software capacity 15 Piracy, IPR, and the WTO 16 Localization 16 What are the shortcomings of FOSS? 17 Lack of business applications 17 Interoperability with proprietary systems 17 Documentation and “polish” 18 FOSS SUCCESS STORIES 19 What are governments doing with FOSS? 19 Europe 19 Americas 20 Brazil 21 Asia Pacific 22 Other Regions 24 What are some successful FOSS projects? 25 BIND (DNS Server) 25 Apache (Web Server) 25 Sendmail (Email Server) 25 OpenSSH (Secure Network Administration Tool) 26 Open Office (Office Productivity Suite) 26 LINUX 27 What is Linux? -
Plain Text & Character Encoding
Journal of eScience Librarianship Volume 10 Issue 3 Data Curation in Practice Article 12 2021-08-11 Plain Text & Character Encoding: A Primer for Data Curators Seth Erickson Pennsylvania State University Let us know how access to this document benefits ou.y Follow this and additional works at: https://escholarship.umassmed.edu/jeslib Part of the Scholarly Communication Commons, and the Scholarly Publishing Commons Repository Citation Erickson S. Plain Text & Character Encoding: A Primer for Data Curators. Journal of eScience Librarianship 2021;10(3): e1211. https://doi.org/10.7191/jeslib.2021.1211. Retrieved from https://escholarship.umassmed.edu/jeslib/vol10/iss3/12 Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 License. This material is brought to you by eScholarship@UMMS. It has been accepted for inclusion in Journal of eScience Librarianship by an authorized administrator of eScholarship@UMMS. For more information, please contact [email protected]. ISSN 2161-3974 JeSLIB 2021; 10(3): e1211 https://doi.org/10.7191/jeslib.2021.1211 Full-Length Paper Plain Text & Character Encoding: A Primer for Data Curators Seth Erickson The Pennsylvania State University, University Park, PA, USA Abstract Plain text data consists of a sequence of encoded characters or “code points” from a given standard such as the Unicode Standard. Some of the most common file formats for digital data used in eScience (CSV, XML, and JSON, for example) are built atop plain text standards. Plain text representations of digital data are often preferred because plain text formats are relatively stable, and they facilitate reuse and interoperability.