When to Use a Document Database
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Oracle Metadata Management V12.2.1.3.0 New Features Overview
An Oracle White Paper October 12 th , 2018 Oracle Metadata Management v12.2.1.3.0 New Features Overview Oracle Metadata Management version 12.2.1.3.0 – October 12 th , 2018 New Features Overview Disclaimer This document is for informational purposes. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described in this document remains at the sole discretion of Oracle. This document in any form, software or printed matter, contains proprietary information that is the exclusive property of Oracle. This document and information contained herein may not be disclosed, copied, reproduced, or distributed to anyone outside Oracle without prior written consent of Oracle. This document is not part of your license agreement nor can it be incorporated into any contractual agreement with Oracle or its subsidiaries or affiliates. 1 Oracle Metadata Management version 12.2.1.3.0 – October 12 th , 2018 New Features Overview Table of Contents Executive Overview ............................................................................ 3 Oracle Metadata Management 12.2.1.3.0 .......................................... 4 METADATA MANAGER VS METADATA EXPLORER UI .............. 4 METADATA HOME PAGES ........................................................... 5 METADATA QUICK ACCESS ........................................................ 6 METADATA REPORTING ............................................................. -
Apache Log4j 2 V
...................................................................................................................................... Apache Log4j 2 v. 2.4.1 User's Guide ...................................................................................................................................... The Apache Software Foundation 2015-10-08 T a b l e o f C o n t e n t s i Table of Contents ....................................................................................................................................... 1. Table of Contents . i 2. Introduction . 1 3. Architecture . 3 4. Log4j 1.x Migration . 10 5. API . 16 6. Configuration . 19 7. Web Applications and JSPs . 50 8. Plugins . 58 9. Lookups . 62 10. Appenders . 70 11. Layouts . 128 12. Filters . 154 13. Async Loggers . 167 14. JMX . 181 15. Logging Separation . 188 16. Extending Log4j . 190 17. Programmatic Log4j Configuration . 198 18. Custom Log Levels . 204 © 2 0 1 5 , T h e A p a c h e S o f t w a r e F o u n d a t i o n • A L L R I G H T S R E S E R V E D . T a b l e o f C o n t e n t s ii © 2 0 1 5 , T h e A p a c h e S o f t w a r e F o u n d a t i o n • A L L R I G H T S R E S E R V E D . 1 I n t r o d u c t i o n 1 1 Introduction ....................................................................................................................................... 1.1 Welcome to Log4j 2! 1.1.1 Introduction Almost every large application includes its own logging or tracing API. In conformance with this rule, the E.U. -
Chainsys-Platform-Technical Architecture-Bots
Technical Architecture Objectives ChainSys’ Smart Data Platform enables the business to achieve these critical needs. 1. Empower the organization to be data-driven 2. All your data management problems solved 3. World class innovation at an accessible price Subash Chandar Elango Chief Product Officer ChainSys Corporation Subash's expertise in the data management sphere is unparalleled. As the creative & technical brain behind ChainSys' products, no problem is too big for Subash, and he has been part of hundreds of data projects worldwide. Introduction This document describes the Technical Architecture of the Chainsys Platform Purpose The purpose of this Technical Architecture is to define the technologies, products, and techniques necessary to develop and support the system and to ensure that the system components are compatible and comply with the enterprise-wide standards and direction defined by the Agency. Scope The document's scope is to identify and explain the advantages and risks inherent in this Technical Architecture. This document is not intended to address the installation and configuration details of the actual implementation. Installation and configuration details are provided in technology guides produced during the project. Audience The intended audience for this document is Project Stakeholders, technical architects, and deployment architects The system's overall architecture goals are to provide a highly available, scalable, & flexible data management platform Architecture Goals A key Architectural goal is to leverage industry best practices to design and develop a scalable, enterprise-wide J2EE application and follow the industry-standard development guidelines. All aspects of Security must be developed and built within the application and be based on Best Practices. -
Elasticsearch Update Multiple Documents
Elasticsearch Update Multiple Documents Noah is heaven-sent and shovel meanwhile while self-appointed Jerrome shack and squeeze. Jean-Pierre is adducible: she salvings dynastically and fluidizes her penalty. Gaspar prevaricate conformably while verbal Reynold yip clamorously or decides injunctively. Currently we start with multiple elasticsearch documents can explore the process has a proxy on enter request that succeed or different schemas across multiple data Needed for a has multiple documents that step api is being paired with the clients. Remember that it would update the single document only, not all. Ghar mein ghuskar maarta hai. So based on this I would try adding those values like the following. The update interface only deletes documents by term while delete supports deletion by term and by query. Enforce this limit in your application via a rate limiter. Adding the REST client in your dependencies will drag the entire Elasticsearch milkyway into your JAR Hell. Why is it a chain? When the alias switches to this new index it will be incomplete. Explain a search query. Can You Improve This Article? This separation means that a synchronous API considers only synchronous entity callbacks and a reactive implementation considers only reactive entity callbacks. Sets the child document index. For example, it is possible that another process might have already updated the same document in between the get and indexing phases of the update. Some store modules may define their own result wrapper types. It is an error to index to an alias which points to more than one index. The following is a simple List. -
15 Minutes Introduction to ELK (Elastic Search,Logstash,Kibana) Kickstarter Series
KickStarter Series 15 Minutes Introduction to ELK 15 Minutes Introduction to ELK (Elastic Search,LogStash,Kibana) KickStarter Series Karun Subramanian www.karunsubramanian.com ©Karun Subramanian 1 KickStarter Series 15 Minutes Introduction to ELK Contents What is ELK and why is all the hoopla? ................................................................................................................................................ 3 The plumbing – How does it work? ...................................................................................................................................................... 4 How can I get started, really? ............................................................................................................................................................... 5 Installation process ........................................................................................................................................................................... 5 The Search ............................................................................................................................................................................................ 7 Most important Plugins ........................................................................................................................................................................ 8 Marvel .............................................................................................................................................................................................. -
Red Hat Openstack Platform 9 Red Hat Openstack Platform Operational Tools
Red Hat OpenStack Platform 9 Red Hat OpenStack Platform Operational Tools Centralized Logging and Monitoring of an OpenStack Environment OpenStack Team Red Hat OpenStack Platform 9 Red Hat OpenStack Platform Operational Tools Centralized Logging and Monitoring of an OpenStack Environment OpenStack Team [email protected] Legal Notice Copyright © 2017 Red Hat, Inc. The text of and illustrations in this document are licensed by Red Hat under a Creative Commons Attribution–Share Alike 3.0 Unported license ("CC-BY-SA"). An explanation of CC-BY-SA is available at http://creativecommons.org/licenses/by-sa/3.0/ . In accordance with CC-BY-SA, if you distribute this document or an adaptation of it, you must provide the URL for the original version. 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. -
Pick Technologies & Tools Faster by Coding with Jhipster: Talk Page At
Picks, configures, and updates best technologies & tools “Superstar developer” Writes all the “boring plumbing code”: Production grade, all layers What is it? Full applications with front-end & back-end Open-source Java application generator No mobile apps Generates complete application with user Create it by running wizard or import management, tests, continuous integration, application configuration from JHipster deployment & monitoring Domain Language (JDL) file Import data model from JDL file Generates CRUD front-end & back-end for our entities Re-import after JDL file changes Re-generates application & entities with new JHipster version What does it do? Overwriting your own code changes can be painful! Microservices & Container Updates application Receive security patches or framework Fullstack Developer updates (like Spring Boot) Shift Left Sometimes switches out library: yarn => npm, JavaScript test libraries, Webpack => Angular Changes for Java developers from 10 years CLI DevOps ago JHipster picked and configured technologies & Single Page Applications tools for us Mobile Apps We picked architecture: monolith Generate application Generated project Cloud Live Demo We picked technologies & tools (like MongoDB or React) Before: Either front-end or back-end developer inside app server with corporate DB Started to generate CRUD screens Java back-end Generate CRUD Before and after Web front-end Monolith and microservices After: Code, test, run & support up to 4 applications iOS front-end Java and Kotlin More technologies & tools? Android -
D3.2 - Transport and Spatial Data Warehouse
Holistic Approach for Providing Spatial & Transport Planning Tools and Evidence to Metropolitan and Regional Authorities to Lead a Sustainable Transition to a New Mobility Era D3.2 - Transport and Spatial Data Warehouse Technical Design @Harmony_H2020 #harmony-h2020 D3.2 - Transport and SpatialData Warehouse Technical Design SUMMARY SHEET PROJECT Project Acronym: HARMONY Project Full Title: Holistic Approach for Providing Spatial & Transport Planning Tools and Evidence to Metropolitan and Regional Authorities to Lead a Sustainable Transition to a New Mobility Era Grant Agreement No. 815269 (H2020 – LC-MG-1-2-2018) Project Coordinator: University College London (UCL) Website www.harmony-h2020.eu Starting date June 2019 Duration 42 months DELIVERABLE Deliverable No. - Title D3.2 - Transport and Spatial Data Warehouse Technical Design Dissemination level: Public Deliverable type: Demonstrator Work Package No. & Title: WP3 - Data collection tools, data fusion and warehousing Deliverable Leader: ICCS Responsible Author(s): Efthimios Bothos, Babis Magoutas, Nikos Papageorgiou, Gregoris Mentzas (ICCS) Responsible Co-Author(s): Panagiotis Georgakis (UoW), Ilias Gerostathopoulos, Shakur Al Islam, Athina Tsirimpa (MOBY X SOFTWARE) Peer Review: Panagiotis Georgakis (UoW), Ilias Gerostathopoulos (MOBY X SOFTWARE) Quality Assurance Committee Maria Kamargianni, Lampros Yfantis (UCL) Review: DOCUMENT HISTORY Version Date Released by Nature of Change 0.1 02/12/2019 ICCS ToC defined 0.3 15/01/2020 ICCS Conceptual approach described 0.5 10/03/2020 ICCS Data descriptions updated 0.7 15/04/2020 ICCS Added sections 3 and 4 0.9 12/05/2020 ICCS Ready for internal review 1.0 01/06/2020 ICCS Final version 1 D3.2 - Transport and SpatialData Warehouse Technical Design TABLE OF CONTENTS EXECUTIVE SUMMARY .................................................................................................................... -
Google Cloud Search Benefits Like These Are All Within Reach
GETTING THE BEST FROM ENTERPRISE CLOUD SEARCH SOLUTIONS Implementing effective enterprise cloud search demands in-depth know-how, tuning, and maintenance WHY MOVE TO THE CLOUD? More and more organizations recognize that moving enterprise systems to the cloud is a cost-effective, highly-scalable option. In fact, by 2020, according to IDC, 67 percent of enterprise infrastructure and software will include cloud-based offerings. GUIDE TO ENTERPRISE CLOUD SEARCH SOLUTIONS | 2 No surprise then that we’re seeing such rapid growth in With so many options, and more cloud solutions launching enterprise cloud search solutions. all the time, what’s the right option for you? These can help modern organizations stay agile, providing This white paper provides a useful guide, exploring some of multiple benefits including: today’s leading enterprise cloud search solutions, unpacking their key features, and highlighting challenges that can arise in their • high availability deployment: • flexibility and scalability • security • Cloud search use cases • ease of maintenance and management • cost reduction (no cost for an on-premise infrastructure • Cloud search solutions, pricing models, and key features: and more transparent pricing models) - Elastic Cloud • improved relevance – accessing more data to feed into - AWS Elasticsearch search machine-learning algorithms - AWS CloudSearch • unified search – easier integration with content from - SharePoint Online other products offered by the same vendor - Azure Search - Google Cloud Search Benefits like these are all within reach. But how to capture - Coveo Cloud them? While cloud companies provide the infrastructure and - SearchStax toolsets for most search use cases – from intranet search and - Algolia public website search to search-based analytics applications – truly effective search capabilities demand in-depth knowledge • Challenges and considerations when deploying a and expert implementation, tuning, and maintenance. -
Apache Couchdb Tutorial Apache Couchdb Tutorial
Apache CouchDB Tutorial Apache CouchDB Tutorial Welcome to CouchDB Tutorial. In this CouchDB Tutorial, we will learn how to install CouchDB, create database in CouchDB, create documents in a database, replication between CouchDBs, configure databases, and many other concepts. What is CouchDB? CouchDB is a NoSQL Database that uses JSON for documents. CouchDB uses JavaScript for MapReduce indexes. CouchDB uses HTTP for the REST API. CouchDB Installation To install CouchDB, visit [https://couchdb.apache.org/] and click on the download button as shown below. When you click on the download button, it scrolls to the section, where based on your Operating System, you can download the installer. In this tutorial, we have downloaded for Windows (x64), and it should not make any difference if you download for macOs or Debian/Ubuntu/RHEL/CentOS. Double click the downloaded installer and follow through the steps. Once the installation is complete, you can check if CouchDB is installed successfully by requesting the URL http://127.0.0.1:5984/ in your browser. This is CouchDB saying welcome to you, along with information about CouchDB version, GIT hash, UUID, features and vendor. Fauxton Fauxton is a web based interface built into CouchDB. You can do actions like creating and deleting databases, CRUD operations on documents, user management, running MapReduce on indexex, replication between CouchDB instances. You can access CouchDB through Fauxton available at the URL http://127.0.0.1:5984/_utils/. Here you can access the following tabs in the left menu. All Databases Setup Active Tasks Configuration Replication Documentation Verify Create Database in CouchDB To create a CouchDB Database, click on Databases tab in the left menu and then click on Create Database. -
HPC-ABDS High Performance Computing Enhanced Apache Big Data Stack
HPC-ABDS High Performance Computing Enhanced Apache Big Data Stack Geoffrey C. Fox, Judy Qiu, Supun Kamburugamuve Shantenu Jha, Andre Luckow School of Informatics and Computing RADICAL Indiana University Rutgers University Bloomington, IN 47408, USA Piscataway, NJ 08854, USA fgcf, xqiu, [email protected] [email protected], [email protected] Abstract—We review the High Performance Computing En- systems as they illustrate key capabilities and often motivate hanced Apache Big Data Stack HPC-ABDS and summarize open source equivalents. the capabilities in 21 identified architecture layers. These The software is broken up into layers so that one can dis- cover Message and Data Protocols, Distributed Coordination, Security & Privacy, Monitoring, Infrastructure Management, cuss software systems in smaller groups. The layers where DevOps, Interoperability, File Systems, Cluster & Resource there is especial opportunity to integrate HPC are colored management, Data Transport, File management, NoSQL, SQL green in figure. We note that data systems that we construct (NewSQL), Extraction Tools, Object-relational mapping, In- from this software can run interoperably on virtualized or memory caching and databases, Inter-process Communication, non-virtualized environments aimed at key scientific data Batch Programming model and Runtime, Stream Processing, High-level Programming, Application Hosting and PaaS, Li- analysis problems. Most of ABDS emphasizes scalability braries and Applications, Workflow and Orchestration. We but not performance and one of our goals is to produce summarize status of these layers focusing on issues of impor- high performance environments. Here there is clear need tance for data analytics. We highlight areas where HPC and for better node performance and support of accelerators like ABDS have good opportunities for integration. -
Optimizing Data Retrieval by Using Mongodb with Elasticsearch
Optimizing data retrieval by using MongoDb with Elasticsearch Silvana Greca Anxhela Kosta Suela Maxhelaku Computer Science Dept. Computer Science Dept Computer Science Dept [email protected] [email protected] [email protected] Keywords: Elasticsearch, MongoDb, Performance, Abstract Optimizing data, Agriculture More and more organizations are facing with massive volumes of new, 1. Introduction rapidly changing data types: structured, semi-structured, The amount of data that businesses can collect is really unstructured and polymorphic data. enormous and hence the volume of the data becomes a The performance for these critical factor in analyzing them. Business use different organizations is directly dependent on database to store data, but it can be difficult to choose the efficiency of data access, data the right DBMS, or NOSQ, so they based on processing, and data management. requirements related to the quality attributes Data is storing in one environment that Consistency, Scalability and Performance [Nilsson17]. is called database. One database Today on modern applications, most of developer should be able to cover all the use NOSQL technologies to provide superior organizations database needs. Storing, performance because NOSQL databases are built to indexing, filtering and returning data allow the insertion of data without a predefined on real-time, are four very important schema. There are many different NOSQL systems issues that affect directly at high which differ from each other and are develop for performance. But, how to get these different purposes. In Albania, the Ministry of features in one database? You can Agriculture, Rural Development has the necessary for optimize data by using MongoDb tracking and analyzing agricultural products data, but combined with Elasticsearch.