Using Graph Databases
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Introduction to Hbase Schema Design
Introduction to HBase Schema Design AmANDeeP KHURANA Amandeep Khurana is The number of applications that are being developed to work with large amounts a Solutions Architect at of data has been growing rapidly in the recent past . To support this new breed of Cloudera and works on applications, as well as scaling up old applications, several new data management building solutions using the systems have been developed . Some call this the big data revolution . A lot of these Hadoop stack. He is also a co-author of HBase new systems that are being developed are open source and community driven, in Action. Prior to Cloudera, Amandeep worked deployed at several large companies . Apache HBase [2] is one such system . It is at Amazon Web Services, where he was part an open source distributed database, modeled around Google Bigtable [5] and is of the Elastic MapReduce team and built the becoming an increasingly popular database choice for applications that need fast initial versions of their hosted HBase product. random access to large amounts of data . It is built atop Apache Hadoop [1] and is [email protected] tightly integrated with it . HBase is very different from traditional relational databases like MySQL, Post- greSQL, Oracle, etc . in how it’s architected and the features that it provides to the applications using it . HBase trades off some of these features for scalability and a flexible schema . This also translates into HBase having a very different data model . Designing HBase tables is a different ballgame as compared to relational database systems . I will introduce you to the basics of HBase table design by explaining the data model and build on that by going into the various concepts at play in designing HBase tables through an example . -
Administration and Configuration Guide
Red Hat JBoss Data Virtualization 6.4 Administration and Configuration Guide This guide is for administrators. Last Updated: 2018-09-26 Red Hat JBoss Data Virtualization 6.4 Administration and Configuration Guide This guide is for administrators. Red Hat Customer Content Services Legal Notice Copyright © 2018 Red Hat, Inc. This document is licensed by Red Hat under the Creative Commons Attribution-ShareAlike 3.0 Unported License. If you distribute this document, or a modified version of it, you must provide attribution to Red Hat, Inc. and provide a link to the original. If the document is modified, all Red Hat trademarks must be removed. Red Hat, as the licensor of this document, waives the right to enforce, and agrees not to assert, Section 4d of CC-BY-SA to the fullest extent permitted by applicable law. Red Hat, Red Hat Enterprise Linux, the Shadowman logo, JBoss, OpenShift, Fedora, the Infinity logo, and RHCE are trademarks of Red Hat, Inc., registered in the United States and other countries. Linux ® is the registered trademark of Linus Torvalds in the United States and other countries. Java ® is a registered trademark of Oracle and/or its affiliates. XFS ® is a trademark of Silicon Graphics International Corp. or its subsidiaries in the United States and/or other countries. MySQL ® is a registered trademark of MySQL AB in the United States, the European Union and other countries. Node.js ® is an official trademark of Joyent. Red Hat Software Collections is not formally related to or endorsed by the official Joyent Node.js open source or commercial project. -
Reference Guide
Apache Syncope - Reference Guide Version 2.1.9 Table of Contents 1. Introduction. 2 1.1. Identity Technologies. 2 1.1.1. Identity Stores . 2 1.1.2. Provisioning Engines . 4 1.1.3. Access Managers . 5 1.1.4. The Complete Picture . 5 2. Architecture. 7 2.1. Core . 7 2.1.1. REST . 7 2.1.2. Logic . 8 2.1.3. Provisioning . 8 2.1.4. Workflow. 9 2.1.5. Persistence . 9 2.1.6. Security . 9 2.2. Admin UI. 10 2.2.1. Accessibility . 10 2.3. End-user UI. 12 2.3.1. Password Reset . 12 2.3.2. Accessibility . 13 2.4. CLI . 15 2.5. Third Party Applications. 15 2.5.1. Eclipse IDE Plugin . 15 2.5.2. Netbeans IDE Plugin. 15 3. Concepts . 16 3.1. Users, Groups and Any Objects . 16 3.2. Type Management . 17 3.2.1. Schema . 17 Plain . 17 Derived . 18 Virtual . 18 3.2.2. AnyTypeClass . 19 3.2.3. AnyType . 19 3.2.4. RelationshipType . 21 3.2.5. Type Extensions . 22 3.3. External Resources. 23 3.3.1. Connector Bundles . 24 3.3.2. Connector Instance details . 24 3.3.3. External Resource details . 25 3.3.4. Mapping . 26 3.3.5. Linked Accounts . 29 3.4. Realms . 29 3.4.1. Realm Provisioning . 30 3.4.2. LogicActions . 31 3.5. Entitlements. 31 3.6. Privileges . 31 3.7. Roles. 31 3.7.1. Delegated Administration . 32 3.8. Provisioning. 33 3.8.1. Overview. 33 3.8.2. -
Demonstrate an Understanding of Computer Database Management Systems 114049
Demonstrate an understanding of Computer Database Management Systems 114049 PURPOSE OF THE UNIT STANDARD This unit standard is intended: To provide a fundamental knowledge of the areas covered For those working in, or entering the workplace in the area of Information Technology As additional knowledge for those wanting to understand the areas covered People credited with this unit standard are able to: Describe data management issues and how it is addressed by a DBMS. Describe commonly implemented features of commercial computer DBMS`s Describe different type of DBMS`s Review DBMS end-user tools The performance of all elements is to a standard that allows for further learning in this area. LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING The credit value of this unit is based on a person having prior knowledge and skills to: Demonstrate an understanding of fundamental mathematics (at least NQF level 3). Demonstrate PC competency skills (End-User Computing unit Standards, at least up to NQF level 3) NC: IT: SYSTEMS DEVELOPMENT AUTHOR: LEARNER MANUAL REL DATE: 27/01/2020 REV DATE: 01/01/2023 DOC REF: 48872 LM MOD 5 V-1 PAGE 50 INDEX Competence Requirements Page Unit Standard 114049 alignment index Here you will find the different outcomes explained which you need to be 52 proved competent in, in order to complete the Unit Standard 114049. Unit Standard 114049 54 Describe data management issues 57 Commonly implemented features of commercial database management systems 63 Different types of DBMS’s 67 Review DBMS end-user tools 73 Self-assessment Once you have completed all the questions after being facilitated, you need to check the progress you have made. -
Synthesis and Development of a Big Data Architecture for the Management of Radar Measurement Data
1 Faculty of Electrical Engineering, Mathematics & Computer Science Synthesis and Development of a Big Data architecture for the management of radar measurement data Alex Aalbertsberg Master of Science Thesis November 2018 Supervisors: dr. ir. Maurice van Keulen (University of Twente) prof. dr. ir. Mehmet Aks¸it (University of Twente) dr. Doina Bucur (University of Twente) ir. Ronny Harmanny (Thales) University of Twente P.O. Box 217 7500 AE Enschede The Netherlands Approval Internship report/Thesis of: …………………………………………………………………………………………………………Alexander P. Aalbertsberg Title: …………………………………………………………………………………………Synthesis and Development of a Big Data architecture for the management of radar measurement data Educational institution: ………………………………………………………………………………..University of Twente Internship/Graduation period:…………………………………………………………………………..2017-2018 Location/Department:.…………………………………………………………………………………435 Advanced Development, Delft Thales Supervisor:……………………………………………………………………………R. I. A. Harmanny This report (both the paper and electronic version) has been read and commented on by the supervisor of Thales Netherlands B.V. In doing so, the supervisor has reviewed the contents and considering their sensitivity, also information included therein such as floor plans, technical specifications, commercial confidential information and organizational charts that contain names. Based on this, the supervisor has decided the following: o This report is publicly available (Open). Any defence may take place publicly and the report may be included in public libraries and/or published in knowledge bases. • o This report and/or a summary thereof is publicly available to a limited extent (Thales Group Internal). tors . It will be read and reviewed exclusively by teachers and if necessary by members of the examination board or review ? committee. The content will be kept confidential and not disseminated through publication or inclusion in public libraries and/or knowledge bases. -
An Evaluation of the Design Space for Scalable Data Loading Into Graph Databases
Otto-von-Guericke-Universit¨at Magdeburg Faculty of Computer Science Databases D B and Software S E Engineering Master's Thesis An Evaluation of the Design Space for Scalable Data Loading into Graph Databases Author: Jingyi Ma February 23, 2018 Advisors: M.Sc. Gabriel Campero Durand Data and Knowledge Engineering Group Prof. Dr. rer. nat. habil. Gunter Saake Data and Knowledge Engineering Group Ma, Jingyi: An Evaluation of the Design Space for Scalable Data Loading into Graph Databases Master's Thesis, Otto-von-Guericke-Universit¨at Magdeburg, 2018. Abstract In recent years, computational network science has become an active area. It offers a wealth of tools to help us gain insight into the interconnected systems around us. Graph databases are non-relational database systems which have been developed to support such network-oriented workloads. Graph databases build a data model based on graph abstractions (i.e. nodes/vertexes and edges) and can use different optimizations to speed up the basic graph processing tasks, such as traversals. In spite of such benefits, some tasks remain challenging in graph databases, such as the task of loading the complete dataset. The loading process has been considered to be a performance bottleneck, specifically a scalability bottleneck, and application developers need to conduct performance tuning to improve it. In this study, we study some optimization alternatives that developers have for load data into a graph databases. With this goal, we propose simple microbenchmarks of application-level load optimizations and evaluate these optimizations experimentally for loading real world graph datasets. We run our tests using JanusGraphLab, a JanusGraph prototype. -
L21: Data Models & Relational Algebra
L21: Data models & Relational Algebra CS3200 Database design (fa18 s2) https://northeastern-datalab.github.io/cs3200/ Version 11/26/2018 1 Announcements! • Exam 2 comments - Based on feedback: Separate "select all" and negative points • We may have "select all" again: but minimum points is 0 • We may have negative points again: but for MCQ only (select one single answer) • Please don't yet submit HW7 - We are adopting Gradescope to handle your submissions too! • Today - Exam 2 take-aways - Data models - Relational Algebra 2 Schedule 3 From 1 = Q3 to 11 = Q13 (thus add 2 to the number) 4 5 Grading from the "other side" 6 Q6 7 Q6 8 Q12 Answer: only the first! Also see post on Piazza: https://piazza.com/class/jj55fszwtpj7fx?cid=135 9 10 L21: A short history of data models Based on article "What goes around comes around", Hellerstein, Stonebraker, 2005. Several slides courtesy of Dan Suciu CS3200 Database design (fa18 s2) https://northeastern-datalab.github.io/cs3200/ Version 11/26/2018 11 Hierarchical data Source: https://en.wikipedia.org/wiki/Nested_set_model 12 Hierarchies are powerful, but can be misleading... 13 “Data Model” • Applications need to model real-world data - Typically includes entities and relationships between them - Entities: e.g. students, courses, products, clients - Relationships: e.g. course registrations, product purchases • A data model enables a user to define the data using high-level constructs without worrying about many low-level details of how data will be stored on disk 14 Levels of Abstraction schema as seen -
Unravel Data Systems Version 4.5
UNRAVEL DATA SYSTEMS VERSION 4.5 Component name Component version name License names jQuery 1.8.2 MIT License Apache Tomcat 5.5.23 Apache License 2.0 Tachyon Project POM 0.8.2 Apache License 2.0 Apache Directory LDAP API Model 1.0.0-M20 Apache License 2.0 apache/incubator-heron 0.16.5.1 Apache License 2.0 Maven Plugin API 3.0.4 Apache License 2.0 ApacheDS Authentication Interceptor 2.0.0-M15 Apache License 2.0 Apache Directory LDAP API Extras ACI 1.0.0-M20 Apache License 2.0 Apache HttpComponents Core 4.3.3 Apache License 2.0 Spark Project Tags 2.0.0-preview Apache License 2.0 Curator Testing 3.3.0 Apache License 2.0 Apache HttpComponents Core 4.4.5 Apache License 2.0 Apache Commons Daemon 1.0.15 Apache License 2.0 classworlds 2.4 Apache License 2.0 abego TreeLayout Core 1.0.1 BSD 3-clause "New" or "Revised" License jackson-core 2.8.6 Apache License 2.0 Lucene Join 6.6.1 Apache License 2.0 Apache Commons CLI 1.3-cloudera-pre-r1439998 Apache License 2.0 hive-apache 0.5 Apache License 2.0 scala-parser-combinators 1.0.4 BSD 3-clause "New" or "Revised" License com.springsource.javax.xml.bind 2.1.7 Common Development and Distribution License 1.0 SnakeYAML 1.15 Apache License 2.0 JUnit 4.12 Common Public License 1.0 ApacheDS Protocol Kerberos 2.0.0-M12 Apache License 2.0 Apache Groovy 2.4.6 Apache License 2.0 JGraphT - Core 1.2.0 (GNU Lesser General Public License v2.1 or later AND Eclipse Public License 1.0) chill-java 0.5.0 Apache License 2.0 Apache Commons Logging 1.2 Apache License 2.0 OpenCensus 0.12.3 Apache License 2.0 ApacheDS Protocol -
Data-Centric Graphical User Interface of the ATLAS Event Index Service
EPJ Web of Conferences 245, 04036 (2020) https://doi.org/10.1051/epjconf/202024504036 CHEP 2019 Data-centric Graphical User Interface of the ATLAS Event Index Service Julius Hrivnᡠcˇ1,∗, Evgeny Alexandrov2, Igor Alexandrov2, Zbigniew Baranowski3, Dario Barberis4, Gancho Dimitrov3, Alvaro Fernandez Casani5, Elizabeth Gallas6, Carlos Gar- cía Montoro5, Santiago Gonzalez de la Hoz5, Andrei Kazymov2, Mikhail Mineev2, Fedor Prokoshin2, Grigori Rybkin1, Javier Sanchez5, Jose Salt5, Miguel Villaplana Perez7 1Université Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay, France 2Joint Institute for Nuclear Research, 6 Joliot-Curie St., Dubna, Moscow Region, 141980, Russia 3CERN, 1211 Geneva 23, Switzerland 4Physics Department of the University of Genoa and INFN Sezione di Genova, Via Dodecaneso 33, I-16146 Genova, Italy 5Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain 6Department of Physics, Oxford University, Oxford, United Kingdom 7Department of Physics, University of Alberta, Edmonton AB, Canada Abstract. The Event Index service of the ATLAS experiment at the LHC keeps references to all real and simulated events. Hadoop Map files and HBase tables are used to store the Event Index data, a subset of data is also stored in the Oracle database. Several user interfaces are currently used to access and search the data, from a simple command line interface, through a programmable API, to sophisticated graphical web services. It provides a dynamic graph-like overview of all available data (and data collections). Data are shown together with their relations, like paternity or overlaps. Each data entity then gives users a set of actions available for the referenced data. Some actions are provided directly by the Event Index system, others are just interfaces to different ATLAS services. -
A.13 Apache Groovy
Oracle® Big Data Spatial and Graph User©s Guide and Reference Release 1.2 E67958-03 May 2016 Oracle Big Data Spatial and Graph User's Guide and Reference, Release 1.2 E67958-03 Copyright © 2015, 2016, Oracle and/or its affiliates. All rights reserved. Primary Authors: Chuck Murray, Harihara Subramanian, Donna Carver Contributors: Bill Beauregard, Hector Briseno, Hassan Chafi, Zazhil Herena, Sungpack Hong, Roberto Infante, Hugo Labra, Gabriela Montiel-Moreno, Siva Ravada, Carlos Reyes, Korbinian Schmid, Jane Tao, Zhe (Alan) Wu This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency- specific supplemental regulations. -
What Is Database? Types and Examples
What is database? Types and Examples Visit our site for more information: www.examplanning.com Facebook Page: https://www.facebook.com/examplanning10/ Twitter: https://twitter.com/examplanning10 TABLE OF CONTENTS Sr. Description 1 What is database? 2 Different definitions of database 3 Growth of Database 4 Elements of Database 5 Components of database 6 Database System Environment 7 Types of Databas 8 Characteristics of database 9 Advantages of Database 10 Disadvantages of Database What is Database? A database is a collection of information or data which are organized in such a way that it can be easily accessed, managed and retrieved. Database is abbreviated ad DB. Different definitions of database. “a usually large collection of data organized especially for rapid search and retrieval (as by a computer) an online database” (merriam-webster) “a comprehensive collection of related data organized for convenient access, generally in a computer.” (dictionary) A database is an organized collection of data. (Wikipedia) What is data? It is used as both singular and plural form. It can be a quantity, symbol or character on which operations are performed. Data is information which are converted into digital form. Growth of Database Database was evolved in 1960's started with the hierarchical database. Relational database was invented by EF Codd in 1970s while object oriented database was invented in 1980s. In 1990s object oriented database rose with the growth of object oriented programming languages. Nowadays, databases with SQL and NoSQL are popular. Elements of Database Database elements are fields, rows, columns, tables. All these are building blocks of database. -
Apache Hbase, the Scaling Machine Jean-Daniel Cryans Software Engineer at Cloudera @Jdcryans
Apache HBase, the Scaling Machine Jean-Daniel Cryans Software Engineer at Cloudera @jdcryans Tuesday, June 18, 13 Agenda • Introduction to Apache HBase • HBase at StumbleUpon • Overview of other use cases 2 Tuesday, June 18, 13 About le Moi • At Cloudera since October 2012. • At StumbleUpon for 3 years before that. • Committer and PMC member for Apache HBase since 2008. • Living in San Francisco. • From Québec, Canada. 3 Tuesday, June 18, 13 4 Tuesday, June 18, 13 What is Apache HBase Apache HBase is an open source distributed scalable consistent low latency random access non-relational database built on Apache Hadoop 5 Tuesday, June 18, 13 Inspiration: Google BigTable (2006) • Goal: Low latency, consistent, random read/ write access to massive amounts of structured data. • It was the data store for Google’s crawler web table, gmail, analytics, earth, blogger, … 6 Tuesday, June 18, 13 HBase is in Production • Inbox • Storage • Web • Search • Analytics • Monitoring 7 Tuesday, June 18, 13 HBase is in Production • Inbox • Storage • Web • Search • Analytics • Monitoring 7 Tuesday, June 18, 13 HBase is in Production • Inbox • Storage • Web • Search • Analytics • Monitoring 7 Tuesday, June 18, 13 HBase is in Production • Inbox • Storage • Web • Search • Analytics • Monitoring 7 Tuesday, June 18, 13 HBase is Open Source • Apache 2.0 License • A Community project with committers and contributors from diverse organizations: • Facebook, Cloudera, Salesforce.com, Huawei, eBay, HortonWorks, Intel, Twitter … • Code license means anyone can modify and use the code. 8 Tuesday, June 18, 13 So why use HBase? 9 Tuesday, June 18, 13 10 Tuesday, June 18, 13 Old School Scaling => • Find a scaling problem.