Learn about Couchbase Server 2.0 the Open Source NoSQL database.
This presentation was delivered on Feb 3rd during the FOSDEM conference ( http://fosdem.org )
Silicon Valley NoSQL Meetup - Nov 2012. View with animations: video version here: https://vimeo.com/54691785
http://www.meetup.com/Silicon-Valley-NoSQL/events/88257222/
For more information visit: www.couchbase.com
Launch webinar-introducing couchbase server 2.0-01202013Dipti Borkar
Couchbase Server 2.0 introduces new features for NoSQL document databases including JSON support, indexing and querying, incremental MapReduce, and cross data center replication. It provides easy scalability, high performance, and flexibility. The architecture includes components like the query engine, data manager, and cluster manager distributed across nodes. Couchbase is used by companies for applications requiring scalability, availability, and flexible data models.
Introduction to Couchbase Server 2.0 - CouchConf SF - Tour and DemoDipti Borkar
This document introduces Couchbase Server 2.0, a NoSQL document database. It highlights key features such as easy scalability through horizontal clustering without application changes, consistent high performance, and always-on availability. New features in version 2.0 include support for JSON, indexing and querying, incremental map reduce, and cross data center replication. The architecture utilizes distributed Erlang and supports flexible schemaless data modeling through storage of JSON documents.
Couchbase Korea User Gorup 2nd Meetup #1won min jang
This document provides an introduction to Couchbase Server 2.0, a NoSQL document database. Some key points covered include: Couchbase Server 2.0 provides easy scalability, consistent high performance, and flexible data modeling using JSON documents without a fixed schema. It features built-in clustering, data replication, zero downtime maintenance and cloning for horizontal scaling. New in version 2.0 is support for indexing, querying and cross data center replication.
This document discusses different approaches for upgrading from Microsoft Office SharePoint Server 2007 or Windows SharePoint Services 3.0 to Microsoft SharePoint 2010 Products. It describes an in-place upgrade approach where the new version of SharePoint 2010 Products is installed on the same hardware as the previous version, upgrading the content and settings during a single process. The advantages are that farm-wide settings are preserved and upgraded and customizations remain available after upgrade, though manual steps may be needed. The disadvantages are servers and farms are offline during the upgrade and it proceeds continuously without pausing.
Virt Exchange2k7 Final Frontier V Mworld2007Kong Yang
Virtualizing Exchange 2007: The Final Frontier?
This 3-page document discusses virtualizing Microsoft Exchange 2007 and evaluates it as a candidate application for virtualization. It finds that while Exchange 2007 has demanding requirements of 64-bit processors, large memory and storage, virtualizing it could provide benefits like leveraging existing virtualization infrastructure and increased flexibility. The document provides guidance on capacity planning and reference architectures for virtualizing Exchange 2007, including example virtual machine configurations sized for small, medium and large user loads. It also shares the results of testing a single Exchange 2007 virtual machine with 1, 2 and 4 vCPUs, finding response times remained low and CPU utilization was below 13% even for 1,000 heavy users.
The document discusses using NetApp snapshot technology to improve database refreshes for development, QA, and testing environments. Currently refresh takes over 10 days using RMAN backup and restore. The proposed solution uses FlexVol cloning to create private copies of the production database with minimal storage. This allows frequent refreshes without impacting production performance or other environments. It provides scalability improvements over the existing process.
The Oracle Server Architecture document outlines the core components that make up an Oracle database instance, including background processes, memory structures like the system global area (SGA) and program global area (PGA), online redo logs, control files, and more. It shows how client connections are handled by the database and how resources are shared between users. Key processes keep the database functioning and recoverable, while memory areas cache data and SQL for fast access.
Silicon Valley NoSQL Meetup - Nov 2012. View with animations: video version here: https://vimeo.com/54691785
http://www.meetup.com/Silicon-Valley-NoSQL/events/88257222/
For more information visit: www.couchbase.com
Launch webinar-introducing couchbase server 2.0-01202013Dipti Borkar
Couchbase Server 2.0 introduces new features for NoSQL document databases including JSON support, indexing and querying, incremental MapReduce, and cross data center replication. It provides easy scalability, high performance, and flexibility. The architecture includes components like the query engine, data manager, and cluster manager distributed across nodes. Couchbase is used by companies for applications requiring scalability, availability, and flexible data models.
Introduction to Couchbase Server 2.0 - CouchConf SF - Tour and DemoDipti Borkar
This document introduces Couchbase Server 2.0, a NoSQL document database. It highlights key features such as easy scalability through horizontal clustering without application changes, consistent high performance, and always-on availability. New features in version 2.0 include support for JSON, indexing and querying, incremental map reduce, and cross data center replication. The architecture utilizes distributed Erlang and supports flexible schemaless data modeling through storage of JSON documents.
Couchbase Korea User Gorup 2nd Meetup #1won min jang
This document provides an introduction to Couchbase Server 2.0, a NoSQL document database. Some key points covered include: Couchbase Server 2.0 provides easy scalability, consistent high performance, and flexible data modeling using JSON documents without a fixed schema. It features built-in clustering, data replication, zero downtime maintenance and cloning for horizontal scaling. New in version 2.0 is support for indexing, querying and cross data center replication.
This document discusses different approaches for upgrading from Microsoft Office SharePoint Server 2007 or Windows SharePoint Services 3.0 to Microsoft SharePoint 2010 Products. It describes an in-place upgrade approach where the new version of SharePoint 2010 Products is installed on the same hardware as the previous version, upgrading the content and settings during a single process. The advantages are that farm-wide settings are preserved and upgraded and customizations remain available after upgrade, though manual steps may be needed. The disadvantages are servers and farms are offline during the upgrade and it proceeds continuously without pausing.
Virt Exchange2k7 Final Frontier V Mworld2007Kong Yang
Virtualizing Exchange 2007: The Final Frontier?
This 3-page document discusses virtualizing Microsoft Exchange 2007 and evaluates it as a candidate application for virtualization. It finds that while Exchange 2007 has demanding requirements of 64-bit processors, large memory and storage, virtualizing it could provide benefits like leveraging existing virtualization infrastructure and increased flexibility. The document provides guidance on capacity planning and reference architectures for virtualizing Exchange 2007, including example virtual machine configurations sized for small, medium and large user loads. It also shares the results of testing a single Exchange 2007 virtual machine with 1, 2 and 4 vCPUs, finding response times remained low and CPU utilization was below 13% even for 1,000 heavy users.
The document discusses using NetApp snapshot technology to improve database refreshes for development, QA, and testing environments. Currently refresh takes over 10 days using RMAN backup and restore. The proposed solution uses FlexVol cloning to create private copies of the production database with minimal storage. This allows frequent refreshes without impacting production performance or other environments. It provides scalability improvements over the existing process.
The Oracle Server Architecture document outlines the core components that make up an Oracle database instance, including background processes, memory structures like the system global area (SGA) and program global area (PGA), online redo logs, control files, and more. It shows how client connections are handled by the database and how resources are shared between users. Key processes keep the database functioning and recoverable, while memory areas cache data and SQL for fast access.
The document describes the z Environment, which provides a solution for managing the lifecycle of Java solutions. The z Environment allows solutions to be self-updating from source code, cost-effective to operate, and easy to distribute. It aims to make continuous integration and deployment of applications transparent, auditable, and versioned. Key aspects of the z Environment include synchronizing changes from source code repositories to runtime environments, managing system states, and supporting development, testing, and production.
L0001 - The Terminology of the Eclipse PlatformTonny Madsen
This is a basic walk-through of all the central concepts of the Eclipse platform and how these fit together. The primary goal of this module is to establish a common terminology.
This document discusses the steps for deploying a SharePoint farm. It involves:
1. Preparing servers by installing software and configuring authentication and security.
2. Creating the farm by deploying the databases, services, and front-end servers.
3. Configuring settings, services, solutions and sites on the farm.
The deployment process includes planning the farm topology and security, installing prerequisites, and configuring services and sites on application servers, database servers, and front-end servers. Additional environments like authoring and services farms may also be deployed.
This talk/tutorial was one that I delivered to multiple organizations -- ranging from semiconductor houses, to start-up system vendors, to research and academic institutions, back in the 2002 time frame. As the abstract below illustrates, it captures the key essence & principles behind the router designs of two of the most popular and landmark switch/routers in our industry -- the Cisco...
This document provides an overview of advanced MySQL replication techniques. It begins with an introduction to replication basics like principles, setup, and monitoring. It then discusses challenges with replication including master switchovers during failures and slaves falling behind. The document outlines various replication power techniques and features that can help address these issues like row-based and semi-synchronous replication. It also covers tools for replication and techniques for replication outside of the traditional setup.
This document provides a comparison of Netgear's ReadyNAS network storage products. It outlines the key specifications of 10 desktop and rackmount models including their form factor, supported file/block protocols, hard drive options, networking ports, reliability features, RAID support, performance metrics, included software, warranty and support options. The ReadyNAS models range from 2-bay desktop options to 12-bay rackmount solutions with 1 or 2 GbE and optional 10GbE networking.
Obamacare markets debut as early hurdles may slow signups hCentive newsAlisha North
The Affordable Care Act's health insurance exchanges opened amid logistical delays and a U.S. government shutdown. Some states delayed their exchange openings by hours or days to avoid overwhelming their websites and call centers. While the federal exchanges in 36 states opened as scheduled, states were encouraging people to wait before signing up to allow time to work out issues. The exchanges aim to provide medical coverage to most of the nation's 48 million uninsured, though the Obama administration is seeking 7 million signups in the initial enrollment period running through March.
Obamacare crashes onths in coming not easily repaired - hCentive newsAlisha North
In the weeks before the start of Obamacare, officials failed to complete exhaustive testing of the program’s website in a push to begin signups by Oct. 1, according to people involved in the rollout.
Health care law providing work for local companies - hCentive newsAlisha North
A number of local companies are winning contracts to build state health insurance exchanges and connect insurers to those networks as states implement the Affordable Care Act. A Reston-based company called Maximus won a $4 million contract over two years to build Minnesota's health insurance exchange. A company called hCentive is finding that after building health insurance exchanges, it can then help insurers connect to those exchanges, creating many opportunities as there are hundreds of insurers and different programs in each state. As states take varying approaches and move at different paces in developing their exchanges, it is creating a wide range of contracting opportunities for companies beyond just system integrators.
Obamacare markets debut as early hurdles may slow signups - hCentive newsAlisha North
The three-year effort to open the Obamacare health-insurance exchanges culminates today, beset by logistical delays and a U.S. government shutdown borne of Republican opposition to the Affordable Care Act.
6 fields where obamacare is creating jobs- hCentive newsAlisha North
Increasingly, it's a technology-driven world, and health care is no exception. Those who work at the intersection between health care and information technology say the Affordable Care Act will only bring the two fields even closer.
This document provides instructions for creating a caricature portrait using a grid for proportion guidance. The goal is to exaggerate distinctive facial features to create a cartoon-like likeness. Guidelines include sketching the subject's proportions within a grid, then adding shading with hatched lines using different pencil grades to create values. Basic caricature and drawing terms are defined. The multi-step process involves establishing an accurate grid, then sketching key facial elements and proportions within the grid for an exaggerated portrait.
This document discusses converting diesel vehicles to run on vegetable oil. It provides information on the different conversion methods, including making biodiesel, straight vegetable oil conversions, and hybrid two-tank and one-tank systems. Benefits of vegetable oil include it being renewable and having lower emissions than diesel. Challenges include the need to heat the thicker vegetable oil and remove glycerin when making biodiesel. Resources for conversions and purchasing vegetable oil are also listed.
In obamacare, tech entrepreneur envisions a new expedia - hCentive newsAlisha North
Sanjay Singh's technology company hCentive is helping build state-run health insurance exchanges as envisioned under the Affordable Care Act, enabling his growing business. HCentive provides the technology platform for exchanges in states like New York, Colorado, and Kentucky, and was recently awarded a contract in Illinois. The company expects to continue assisting states in developing their exchanges and helping insurance companies connect to exchanges. Singh believes exchanges will evolve significantly in coming years as more states establish their own systems.
Back end errors at u.s. health website jeopardize sign-up-hCentive newsAlisha North
There’s no way to tell how many people who think they enrolled for health insurance through the U.S. Obamacare exchange actually have, after about 1 in 4 files sent to insurers had garbled and incomplete information.
The document discusses Simplify, a framework for enabling fast functional simulation of multiprocessor system-on-chips (MPSoCs). Simplify uses an abstract MPSoC platform model to allow for easy modeling of MPSoC architectures and fast behavioral simulation. It integrates an operating system and supports tasks migration and communication between processors. Experimental results show that Simplify achieves scalable simulation performance and allows for online design, simulation, and debugging of MPSoCs.
Shared personalization service. How to scale to 15 k rps (Patrice Pelland)Ontico
1) SPS is a backend storage and personalization service that enables explicit personalization, implicit content optimization, and geo-based customization.
2) It is designed to scale to 15,000 requests per second with latency goals of under 25ms for reads and under 50ms for updates.
3) The overall architecture is stateless and uses Windows AppFabric caching, SQL Server database partitioning, and load balancing for high availability and scalability.
Sailfin is a SIP servlet container that allows developers to build converged web and telecommunications applications. It integrates SIP functionality into the Java EE platform through SIP servlets. This allows adding features like click-to-dial buttons to web pages. Sailfin uses the SIP protocol for communication and is accessible to web developers through a servlet programming model. It provides load balancing, failover, security, and tools to help develop and test converged applications.
GlassFish is a popular open source application server. The top 10 reasons to use GlassFish are:
10. GlassFish Embedded
9. Provisioning and administration tools like the Update Center
8. Early access to new Java EE technologies through the standardization process
7. Interoperability with other standards like Metro
The document describes the z Environment, which provides a solution for managing the lifecycle of Java solutions. The z Environment allows solutions to be self-updating from source code, cost-effective to operate, and easy to distribute. It aims to make continuous integration and deployment of applications transparent, auditable, and versioned. Key aspects of the z Environment include synchronizing changes from source code repositories to runtime environments, managing system states, and supporting development, testing, and production.
L0001 - The Terminology of the Eclipse PlatformTonny Madsen
This is a basic walk-through of all the central concepts of the Eclipse platform and how these fit together. The primary goal of this module is to establish a common terminology.
This document discusses the steps for deploying a SharePoint farm. It involves:
1. Preparing servers by installing software and configuring authentication and security.
2. Creating the farm by deploying the databases, services, and front-end servers.
3. Configuring settings, services, solutions and sites on the farm.
The deployment process includes planning the farm topology and security, installing prerequisites, and configuring services and sites on application servers, database servers, and front-end servers. Additional environments like authoring and services farms may also be deployed.
This talk/tutorial was one that I delivered to multiple organizations -- ranging from semiconductor houses, to start-up system vendors, to research and academic institutions, back in the 2002 time frame. As the abstract below illustrates, it captures the key essence & principles behind the router designs of two of the most popular and landmark switch/routers in our industry -- the Cisco...
This document provides an overview of advanced MySQL replication techniques. It begins with an introduction to replication basics like principles, setup, and monitoring. It then discusses challenges with replication including master switchovers during failures and slaves falling behind. The document outlines various replication power techniques and features that can help address these issues like row-based and semi-synchronous replication. It also covers tools for replication and techniques for replication outside of the traditional setup.
This document provides a comparison of Netgear's ReadyNAS network storage products. It outlines the key specifications of 10 desktop and rackmount models including their form factor, supported file/block protocols, hard drive options, networking ports, reliability features, RAID support, performance metrics, included software, warranty and support options. The ReadyNAS models range from 2-bay desktop options to 12-bay rackmount solutions with 1 or 2 GbE and optional 10GbE networking.
Obamacare markets debut as early hurdles may slow signups hCentive newsAlisha North
The Affordable Care Act's health insurance exchanges opened amid logistical delays and a U.S. government shutdown. Some states delayed their exchange openings by hours or days to avoid overwhelming their websites and call centers. While the federal exchanges in 36 states opened as scheduled, states were encouraging people to wait before signing up to allow time to work out issues. The exchanges aim to provide medical coverage to most of the nation's 48 million uninsured, though the Obama administration is seeking 7 million signups in the initial enrollment period running through March.
Obamacare crashes onths in coming not easily repaired - hCentive newsAlisha North
In the weeks before the start of Obamacare, officials failed to complete exhaustive testing of the program’s website in a push to begin signups by Oct. 1, according to people involved in the rollout.
Health care law providing work for local companies - hCentive newsAlisha North
A number of local companies are winning contracts to build state health insurance exchanges and connect insurers to those networks as states implement the Affordable Care Act. A Reston-based company called Maximus won a $4 million contract over two years to build Minnesota's health insurance exchange. A company called hCentive is finding that after building health insurance exchanges, it can then help insurers connect to those exchanges, creating many opportunities as there are hundreds of insurers and different programs in each state. As states take varying approaches and move at different paces in developing their exchanges, it is creating a wide range of contracting opportunities for companies beyond just system integrators.
Obamacare markets debut as early hurdles may slow signups - hCentive newsAlisha North
The three-year effort to open the Obamacare health-insurance exchanges culminates today, beset by logistical delays and a U.S. government shutdown borne of Republican opposition to the Affordable Care Act.
6 fields where obamacare is creating jobs- hCentive newsAlisha North
Increasingly, it's a technology-driven world, and health care is no exception. Those who work at the intersection between health care and information technology say the Affordable Care Act will only bring the two fields even closer.
This document provides instructions for creating a caricature portrait using a grid for proportion guidance. The goal is to exaggerate distinctive facial features to create a cartoon-like likeness. Guidelines include sketching the subject's proportions within a grid, then adding shading with hatched lines using different pencil grades to create values. Basic caricature and drawing terms are defined. The multi-step process involves establishing an accurate grid, then sketching key facial elements and proportions within the grid for an exaggerated portrait.
This document discusses converting diesel vehicles to run on vegetable oil. It provides information on the different conversion methods, including making biodiesel, straight vegetable oil conversions, and hybrid two-tank and one-tank systems. Benefits of vegetable oil include it being renewable and having lower emissions than diesel. Challenges include the need to heat the thicker vegetable oil and remove glycerin when making biodiesel. Resources for conversions and purchasing vegetable oil are also listed.
In obamacare, tech entrepreneur envisions a new expedia - hCentive newsAlisha North
Sanjay Singh's technology company hCentive is helping build state-run health insurance exchanges as envisioned under the Affordable Care Act, enabling his growing business. HCentive provides the technology platform for exchanges in states like New York, Colorado, and Kentucky, and was recently awarded a contract in Illinois. The company expects to continue assisting states in developing their exchanges and helping insurance companies connect to exchanges. Singh believes exchanges will evolve significantly in coming years as more states establish their own systems.
Back end errors at u.s. health website jeopardize sign-up-hCentive newsAlisha North
There’s no way to tell how many people who think they enrolled for health insurance through the U.S. Obamacare exchange actually have, after about 1 in 4 files sent to insurers had garbled and incomplete information.
The document discusses Simplify, a framework for enabling fast functional simulation of multiprocessor system-on-chips (MPSoCs). Simplify uses an abstract MPSoC platform model to allow for easy modeling of MPSoC architectures and fast behavioral simulation. It integrates an operating system and supports tasks migration and communication between processors. Experimental results show that Simplify achieves scalable simulation performance and allows for online design, simulation, and debugging of MPSoCs.
Shared personalization service. How to scale to 15 k rps (Patrice Pelland)Ontico
1) SPS is a backend storage and personalization service that enables explicit personalization, implicit content optimization, and geo-based customization.
2) It is designed to scale to 15,000 requests per second with latency goals of under 25ms for reads and under 50ms for updates.
3) The overall architecture is stateless and uses Windows AppFabric caching, SQL Server database partitioning, and load balancing for high availability and scalability.
Sailfin is a SIP servlet container that allows developers to build converged web and telecommunications applications. It integrates SIP functionality into the Java EE platform through SIP servlets. This allows adding features like click-to-dial buttons to web pages. Sailfin uses the SIP protocol for communication and is accessible to web developers through a servlet programming model. It provides load balancing, failover, security, and tools to help develop and test converged applications.
GlassFish is a popular open source application server. The top 10 reasons to use GlassFish are:
10. GlassFish Embedded
9. Provisioning and administration tools like the Update Center
8. Early access to new Java EE technologies through the standardization process
7. Interoperability with other standards like Metro
Plugin-able POS Solutions by Javascript @HDM9 TaiwanRack Lin
This document discusses the author's experience developing point-of-sale (POS) systems using JavaScript and XULRunner. It describes building a POS SDK called VIVIPOS using JavaScript, XUL, and XPCOM to provide a cross-platform solution. Key components of the SDK included GREUTLs for utilities, GeckoJS for an MVC framework, and XBL components for reusable UI elements. The document emphasizes building a flexible, component-based system to facilitate customization for different customers rather than a single monolithic product.
Couchbase is a distributed database that provides simple, fast, and elastic scalability. A social game company called Tribal Crossing was facing challenges with scaling their MySQL database for their game Animal Party. They deployed Couchbase on Amazon EC2 to take advantage of Couchbase's speed, simplicity, and ability to scale out elastically. Tribal Crossing represented their game data as JSON documents in Couchbase and was able to easily access and modify player and game object data.
Get the latest update from Panasas on the status of pNFS - parallel NFS. This presentation explains how you can innovate faster, better, and at a lower cost with Panasas and pNFS, the emerging standard for parallel I/O and the next major extension to the ubiquitous standard, NFS.
Eclipse Swordfish is an open source SOA runtime framework based on Eclipse Equinox. It provides a framework for integrating additional open source components like a service registry, messaging system, and process engine to form a comprehensive SOA runtime environment. Swordfish supports relevant SOA standards including SCA, JBI, and OSGi. It adds functionality like policies, monitoring, and configuration to complement components like ServiceMix. The project has 5 committers working on it and version 1.0M3 has been released with the goal of inclusion in Eclipse Galileo in June 2009.
Making Portals Cool: The Compelling Advantages of a Portlet BridgeWesley Hales
1) The document discusses the advantages of using the JBoss Portlet Bridge which allows developers to use JavaServer Faces (JSF) to build portlets.
2) Some key benefits of the portlet bridge mentioned include having a smooth learning curve, being enterprise ready with support for clustering and security, and allowing reuse of existing JSF development skills and applications.
3) The portlet bridge handles mapping the JSF lifecycle to the portlet API and provides features for handling public render parameters, portlet events, and navigation between portlet modes.
The document describes COSBench, a benchmark tool for evaluating the performance of cloud object storage services. It provides an overview of COSBench's key components, including its configurable workload definition file, controller for managing tests, and drivers for generating load. The document also shares sample results from using COSBench to measure the throughput and response times of OpenStack Swift in different configurations. It found that the proxy node's CPU was the bottleneck for larger workloads on one setup. The goal is to open source COSBench to help storage providers optimize performance.
This document summarizes a presentation titled "Build & Deploy on your own cloud" given by Xavier Coulon. The presentation introduced OpenShift, an open source Platform as a Service (PaaS) that allows developers to build and deploy applications on their own cloud. OpenShift automates the build, test, and publish process of applications configured with cartridges. It provides developer tools like a web console and command line interface to manage applications and domains. The presentation concluded with a demonstration of application management and logging features using these tools.
The document discusses Java EE 6 and its evolution over time. It outlines key features of Java EE 6 including lightweight profiles, annotations, managed beans, interceptors, and Servlets 3.0. It provides examples of using managed beans, interceptors, and the new annotations-based approach in Servlets 3.0. The document aims to educate developers on the nuts and bolts of Java EE 6.
This document discusses techniques for successfully launching and scaling social games. It covers common database architectures using PHP, MySQL, and Apache. It also discusses issues with replication, auto-increment values, and large log files. Solutions proposed include implementing Redis for leaderboards and caching, configuring MySQL for faster replication, and expiring log files regularly.
The document provides information about handling events in JavaServer Faces (JSF), including comparing action controllers to event listeners, implementing different types of event listeners like action listeners and value change listeners, and using JavaScript to submit forms. It also summarizes the typical flow of control in JSF applications from form submission to result display, and provides an example of how to create a JSF application that uses both action listeners and action controllers.
(ATS3-PLAT06) Handling “Big Data” with Pipeline Pilot (MapReduce/NoSQL)BIOVIA
Pipeline Pilot has wrangled large volumes of scientific data for many years. The emergence of "Big Data" challenges in other fields has brought many new tools and techniques to the table. This session will demonstrate various approaches to handling big data in Pipeline Pilot and show now Pipeline Pilot can integrate with "NoSQL" data stores such as Apache Cassandra and MongoDB. The second half of this session will be focus on audience participation and open discussion around big data tools and techniques to help inform our community and our future product road map.
This document describes a tutorial on using semantic metadata with Grid services. The tutorial will cover:
1. Setting up a Globus container and deploying various semantic services and operation providers to enable semantic capabilities for Grid resources like sticky notes.
2. Attaching RDF metadata to sticky note resources using semantic bindings.
3. Querying the semantic bindings of resources using SPARQL or other query languages and making inferences over the metadata by using an ontology.
The hands-on exercises will guide participants in deploying the necessary software components, adding semantic description and querying capabilities to a sticky note service, and executing queries that leverage an ontology to infer additional information from the semantic metadata.
Introduction to JSR-283 at the magnolia user conference in Basel, Switzerland.
- A Content Repository?
- JCR History, Adoption
- Top 10 New Features
- Beyond the Spec (Demo)
- Future Plans
This document summarizes a research paper on scalable NetFlow analysis using Hadoop. It discusses:
1) The challenges of analyzing large volumes of Internet traffic data, including scalability, fault tolerance, and extensibility.
2) How Hadoop can help address these challenges by providing distributed computing and storage capabilities to process petabytes of data across thousands of nodes.
3) The design of a Hadoop-based traffic processing tool for collecting, storing, and analyzing NetFlow and packet data at scale through MapReduce jobs.
Similar to FOSDEM 2013 : Getting Started with Couchhbase Server 2.0 (20)
Introduction to Streaming with Apache FlinkTugdual Grall
This document discusses stream processing with Apache Flink. It provides an overview of Flink's architecture, including its deployment options and APIs for batch and stream processing. It also covers core Flink concepts like windows, event-time processing, and an example of complex event processing (CEP) to detect patterns in event streams and generate real-time warnings. The document concludes with a demonstration of Flink's streaming analytics capabilities.
Fast Cars, Big Data - How Streaming Can Help Formula 1Tugdual Grall
Modern cars produce data. Lots of data. And Formula 1 cars produce more than their share. I will present a working demonstration of how modern data streaming can be applied to the data acquisition and analysis problem posed by modern motorsports.
Instead of bringing multiple Formula 1 cars to the talk, I will show how we instrumented a high fidelity physics-based automotive simulator to produce realistic data from simulated cars running on the Spa-Francorchamps track. We move data from the cars, to the pits, to the engineers back at HQ.
The result is near real-time visualization and comparison of performance and a great exposition of how to move data using messaging systems like Kafka, and process data in real time with Apache Spark, then analyse data using SQL with Apache Drill.
Code available here: https://github.com/mapr-demos/racing-time-series
Lambda Architecture: The Best Way to Build Scalable and Reliable Applications!Tugdual Grall
Lambda Architecture is a useful framework to think about designing big data applications. This framework has been built initially at Twitter. In this presentation you will learn, based on concrete examples how to build deploy scalable and fault tolerant applications, with a focus on Big Data and Hadoop.
This presentation was delivered at the OOP conference, Munich, Feb 2016
Generic presentation about Big Data Architecture/Components. This presentation was delivered by David Pilato and Tugdual Grall during JUG Summer Camp 2015 in La Rochelle, France
Proud to be Polyglot - Riviera Dev 2015Tugdual Grall
The document discusses the benefits of using multiple programming languages and data stores, or a "polyglot" approach, for modern applications. A polyglot approach allows using the right tool for each task, rather than trying to force a single technology to fit all needs. This improves performance, scalability, and the ability to adapt applications to changing requirements compared to traditional monolithic architectures. The document provides examples of when to use different languages and data stores and concludes that a polyglot approach makes applications easier to maintain over time.
Enabling Telco to Build and Run Modern Applications Tugdual Grall
This document discusses how MongoDB can help enable businesses to build and run modern applications. It begins with an overview of Tugdual Grall and his background. It then discusses how industries and data have changed, driving the need for a next generation database. The rest of the document provides an overview of MongoDB, including the company, technology, and community. Examples are given of how MongoDB has helped companies in the telecommunications industry achieve a single customer view, improve product catalogs and personalization, and build mobile and open data APIs.
The document discusses MongoDB and Hadoop. It provides an overview of how MongoDB and Hadoop can be used together, including use cases in commerce, insurance and fraud detection. It describes the MongoDB Connector for Hadoop, which allows reading and writing to MongoDB from Hadoop tools like MapReduce, Pig and Hive. A demo is shown of a movie recommendation application that uses both MongoDB and Spark on Hadoop to power a web application.
New developers and teams are now polyglot :
- they use multiple programming languages (Java, Javascript, Ruby, ...)
- they use multiple persistence store (RDBMS, NoSQL, Hadoop)
In this talk you will learn about the benefits if being polyglot: use the good language or framework for the good cause, select the good persistence for specific constraints.
This presentation will show how developer could mix the Java platform with other technologies such as NodeJS and AngularJS to build application in a more productive way. This is also the opportunity to talk about the new Command Query Responsibility Segregation (CQRS) pattern to allow developers to be more effective and deliver the proper application to the user quicker.
This presentation was delivered during Devfest Nantes 2014
Drop your table ! MongoDB Schema DesignTugdual Grall
MongoDB’s basic unit of storage is a document. Documents can represent rich, schema-free data structures, meaning that we have several viable alternatives to the normalized, relational model. In this talk, we’ll discuss the tradeoff of various data modeling strategies in MongoDB using various example. You will learn how to work with documents, evolve your schema, and common schema design patterns.
Delivered at Soft Shake '14 and Jug Summer Camp '14
Building Your First MongoDB ApplicationTugdual Grall
This document contains slides from a presentation on using MongoDB with Java. It introduces several Java drivers and ORM libraries for MongoDB, including the MongoDB Java driver, Morphia, Spring Data MongoDB, Jongo, and Hibernate OGM. For each library, it provides brief descriptions and examples of inserting and querying data. The presenter recommends Morphia for its easy mapping and queries, Spring Data for developers already using Spring, and Jongo for those who prefer MongoDB's query language. Hibernate OGM is noted as still being under development.
This document discusses the growth of the Internet of Things and the need for databases that can handle large amounts of data from connected devices. It notes that by 2020, there will be over 50 billion connected devices generating huge amounts of diverse data. MongoDB is presented as a database that can meet the needs of IoT applications by allowing flexible schemas, easy ingestion of new data types, horizontal scaling through sharding, and high availability through replication. Specific use cases for MongoDB in IoT applications are also mentioned, including Bosch's IoT platform.
- MongoDB is a general purpose database that uses documents rather than tables, making data storage more flexible. It can scale horizontally using sharding to distribute data across multiple servers.
- Choosing the right shard key is important for write and query performance. The shard key should distribute data evenly across shards and avoid scatter-gather queries that retrieve data from multiple servers.
- MongoDB uses replication for high availability so data is copied to secondary servers. Monitoring tools check for replication lag and assess if data is being copied over quickly enough.
Softshake 2013: Introduction to NoSQL with CouchbaseTugdual Grall
This presentation was delivered during Softshake 2013. Learn why RDBMS are not enought and why NoSQL help developers to scale their applications and provide agility.
The document introduces Couchbase Server 2.0, a NoSQL document database. It discusses how relational databases do not scale well for growing applications, while NoSQL databases like Couchbase can scale out horizontally across commodity servers to meet increasing demand. Couchbase Server provides features like flexible JSON document data model, easy scalability, high performance, and always-on availability. It also shows the Couchbase Server architecture and how data is distributed and replicated across nodes in a cluster.
Why and How to integrate Hadoop and NoSQL?Tugdual Grall
This document contains a presentation on integrating Hadoop with NoSQL databases. It discusses using Sqoop to transfer data between Hadoop and NoSQL databases like Couchbase and MongoDB. It provides examples of using Sqoop to import and export data between these systems. The presentation also highlights some key uses cases and benefits of using Hadoop and NoSQL databases together for applications involving large datasets.
NoSQL Matters 2013 - Introduction to Map Reduce with Couchbase 2.0Tugdual Grall
The document provides an introduction to MapReduce and how it can be used with Couchbase. It discusses that MapReduce is a programming model for processing large datasets in a distributed manner. It describes the basic MapReduce concepts of mapping input data to intermediate keys and values, and reducing to merge results for a given key. The document then explains how Couchbase Server implements these concepts and can be used for distributed computing applications with its flexible data model and built-in clustering.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Things to Consider When Choosing a Website Developer for your Website | FODUUFODUU
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GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
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Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
2. Ge#ng
Started
with
Couchbase
Tugdual
“Tug”
Grall
Technical
Evangelist
email:
tug@couchbase.com twi0er:
@tgrall
Monday, February 4, 13
3. Ge#ng
Started
with
Couchbase
Tugdual
“Tug”
Grall
Technical
Evangelist
email:
tug@couchbase.com twi0er:
@tgrall
Monday, February 4, 13
4. Couchbase
Server
Core
Principles
Easy
Consistent
High
Scalability PE
RF O R M A N C E Performance
Grow
cluster
without
Consistent
sub-‐millisecond
applica7on
changes,
without
read
and
write
response
7mes
down7me
with
a
single
click with
consistent
high
throughput
Always
On
JSON
JSON JSO
Flexible
Data
24x365 Model
JSON N
JSON
No
down7me
for
so>ware
JSON
document
model
with
no
upgrades,
hardware
fixed
schema.
maintenance,
etc.
Monday, February 4, 13
5. Couchbase
2.0
New
Features
JSON support Indexing and
Querying
Incremental Map Cross data center
Reduce replication
Monday, February 4, 13
7. 8092
Couchbase
Server
2.0
Architecture
11211 11210
Query
API Memcapable
1.0 Memcapable
2.0 Sub:tle
Moxi
Query
Engine
REST
management
API/Web
UI
vBucket
state
and
replica7on
manager
Memcached
Global
singleton
supervisor
Rebalance
orchestrator
Configura7on
manager
Node
health
monitor
Process
monitor
Couchbase
EP
Engine
Heartbeat
Data
Manager Cluster
Manager
storage
interface
New
Persistence
Layer hDp on
each
node one
per
cluster
Erlang/OTP
HTTP Erlang
port
mapper Distributed
Erlang
8091 4369 21100
-‐
21199
Monday, February 4, 13
8. Couchbase
Server
2.0
Architecture
8092 11211 11210
Query
API Memcapable
1.0 Memcapable
2.0
Moxi
Query
Engine
REST
management
API/Web
UI
vBucket
state
and
replica7on
manager
Object-‐level
Cache
Global
singleton
supervisor
RAM
Cache,
Rebalance
orchestrator
Configura7on
manager
Node
health
monitor
Server/Cluster
Process
monitor
Indexing
&
Heartbeat
Couchbase
EP
Engine
Management
&
Persistence
storage
interface
CommunicaYon
Management (Erlang)
New
(C
Persistence
Disk
&
V8)
Persistence
Layer hDp on
each
node one
per
cluster
Erlang/OTP
The Unreasonable Effectiveness of C by Damien Katz
HTTP Erlang
port
mapper Distributed
Erlang
8091 4369 21100
-‐
21199
Monday, February 4, 13
9. Open
Source
Project
Apache
2.0
hIps://github.com/couchbase/ Gerrit: hIp://review.couchbase.org/
hIps://github.com/couchbaselabs/
Monday, February 4, 13
18. Write
OperaJon
Doc
1
App
Server
3 3
Managed
Cache 2
To
other
node Replica7on
Queue
Disk
Queue
Disk
Couchbase
Server
Node
Monday, February 4, 13
19. Write
OperaJon
App
Server
3 3
Managed
Cache 2
To
other
node Replica7on
Doc
1
Queue
Disk
Queue
Disk
Couchbase
Server
Node
Monday, February 4, 13
20. Write
OperaJon
App
Server
3 3
Managed
Cache 2
To
other
node Replica7on
Doc
1 Doc
1 Doc
1
Queue
Disk
Queue
Disk
Couchbase
Server
Node
Monday, February 4, 13
21. Basic
OperaJons
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc App
never
needs
to
know
• App
reads,
writes,
updates
docs
• MulYple
app
servers
can
access
same
document
at
same
Yme
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
22. Basic
OperaJons
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc App
never
needs
to
know
• App
reads,
writes,
updates
docs
REPLICA REPLICA REPLICA
• MulYple
app
servers
can
access
same
Doc
4 Doc Doc
6 Doc Doc
7 Doc
document
at
same
Yme
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
23. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc App
never
needs
to
know
• App
reads,
writes,
updates
docs
REPLICA REPLICA REPLICA
• MulYple
app
servers
can
access
same
Doc
4 Doc Doc
6 Doc Doc
7 Doc
document
at
same
Yme
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
24. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
ACTIVE ACTIVE ACTIVE
Doc
5 Doc Doc
4 Doc Doc
1 Doc
Doc
2 Doc Doc
7 Doc Doc
2 Doc
Doc
9 Doc Doc
8 Doc Doc
6 Doc
REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
25. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
Doc
5 Doc Doc
4 Doc Doc
1 Doc
Doc
2 Doc Doc
7 Doc Doc
2 Doc
Doc
9 Doc Doc
8 Doc Doc
6 Doc
REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
26. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc
Doc
9 Doc Doc
8 Doc Doc
6 Doc
REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
27. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc
REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
28. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc App
never
needs
to
know
REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
29. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc App
never
needs
to
know
• App
reads,
writes,
updates
docs
REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
30. Basic
OperaJons
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
• Docs
distributed
evenly
across
servers
READ/WRITE/UPDATE
• Each
server
stores
both
acYve
and
replica
SERVER
1 SERVER
2 SERVER
3 docs
Only
one
doc
ac7ve
at
a
7me
ACTIVE ACTIVE ACTIVE
• Client
library
provides
app
with
simple
Doc
5 Doc Doc
4 Doc Doc
1 Doc
interface
to
database
Doc
2 Doc Doc
7 Doc Doc
2 Doc • Cluster
map
provides
map
to
which
server
doc
is
on
Doc
9 Doc Doc
8 Doc Doc
6 Doc App
never
needs
to
know
• App
reads,
writes,
updates
docs
REPLICA REPLICA REPLICA
• MulYple
app
servers
can
access
same
Doc
4 Doc Doc
6 Doc Doc
7 Doc
document
at
same
Yme
Doc
1 Doc Doc
3 Doc Doc
9 Doc
Doc
8 Doc Doc
2 Doc Doc
5 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
31. Basic
OperaJons
• get
(key)
–
Retrieve
a
document
• set
(key,
value)
–
Store
a
document,
overwrites
if
exists
• add
(key,
value)
–
Store
a
document,
error/excep7on
if
exists
• replace
(key,
value)
–
Store
a
document,
error/excep7on
if
doesn’t
exist
• cas
(key,
value,
cas)
–
Compare
and
swap,
mutate
document
only
if
it
hasn’t
changed
while
execu7ng
this
opera7on
Monday, February 4, 13
32. Fail
Over
Node
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3 SERVER
4 SERVER
5
• App
servers
accessing
docs
ACTIVE ACTIVE ACTIVE ACTIVE ACTIVE
Doc
5 Doc Doc
4 Doc Doc
1 Doc Doc
9 Doc Doc
6 Doc • Requests
to
Server
3
fail
Doc
2 Doc Doc
7 Doc Doc
2 Doc Doc
8 Doc
• Cluster
detects
server
failed
Promotes
replicas
of
docs
to
ac7ve
Updates
cluster
map
• Requests
for
docs
now
go
to
appropriate
server
REPLICA REPLICA REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc Doc
5 Doc Doc
8 Doc
• Typically
rebalance
would
follow
Doc
1 Doc Doc
3 Doc Doc
9 Doc Doc
2 Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
Monday, February 4, 13
33. Fail
Over
Node
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3 SERVER
4 SERVER
5
• App
servers
accessing
docs
ACTIVE ACTIVE ACTIVE ACTIVE ACTIVE
Doc
5 Doc Doc
4 Doc Doc
1 Doc Doc
9 Doc Doc
6 Doc • Requests
to
Server
3
fail
Doc
2 Doc Doc
7 Doc Doc
2 Doc Doc
8 Doc
• Cluster
detects
server
failed
Promotes
replicas
of
docs
to
ac7ve
Updates
cluster
map
• Requests
for
docs
now
go
to
appropriate
server
REPLICA REPLICA REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc Doc
5 Doc Doc
8 Doc
• Typically
rebalance
would
follow
Doc
1 Doc Doc
3 Doc Doc
9 Doc Doc
2 Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
Monday, February 4, 13
34. Fail
Over
Node
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3 SERVER
4 SERVER
5
• App
servers
accessing
docs
ACTIVE ACTIVE ACTIVE ACTIVE ACTIVE
Doc
5 Doc Doc
4 Doc Doc
1 Doc Doc
9 Doc Doc
6 Doc • Requests
to
Server
3
fail
Doc
2 Doc Doc
7 Doc Doc
2 Doc Doc
8 Doc
REPLICA REPLICA REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc Doc
5 Doc Doc
8 Doc
Doc
1 Doc Doc
3 Doc Doc
9 Doc Doc
2 Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
Monday, February 4, 13
35. Fail
Over
Node
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3 SERVER
4 SERVER
5
• App
servers
accessing
docs
ACTIVE ACTIVE ACTIVE ACTIVE ACTIVE
Doc
5 Doc Doc
4 Doc Doc
1 Doc Doc
9 Doc Doc
6 Doc • Requests
to
Server
3
fail
Doc
2 Doc Doc
7 Doc Doc
2 Doc Doc
8 Doc Doc
• Cluster
detects
server
failed
Promotes
replicas
of
docs
to
ac7ve
Updates
cluster
map
Doc
1 Doc
3
• Requests
for
docs
now
go
to
appropriate
server
REPLICA REPLICA REPLICA REPLICA REPLICA
Doc
4 Doc Doc
6 Doc Doc
7 Doc Doc
5 Doc
8 Doc
• Typically
rebalance
would
follow
Doc Doc Doc
9 Doc Doc
2 Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
Monday, February 4, 13
36. Indexing
and
Querying
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3
ACTIVE
• Indexing
work
is
distributed
amongst
ACTIVE ACTIVE
nodes
Doc
5 Doc Doc
5 Doc Doc
5 Doc
• Large
data
set
possible
Doc
2 Doc Doc
2 Doc Doc
2 Doc
• Parallelize
the
effort
Doc
9 Doc Doc
9 Doc Doc
9 Doc • Each
node
has
index
for
data
stored
on
it
REPLICA REPLICA REPLICA • Queries
combine
the
results
from
required
nodes
Doc
4 Doc Doc
4 Doc Doc
4 Doc
Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
8 Doc Doc
8 Doc Doc
8 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
37. Indexing
and
Querying
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3
ACTIVE
• Indexing
work
is
distributed
amongst
ACTIVE ACTIVE
nodes
Doc
5 Doc Doc
5 Doc Doc
5 Doc
• Large
data
set
possible
Doc
2 Doc Doc
2 Doc Doc
2 Doc
• Parallelize
the
effort
Doc
9 Doc Doc
9 Doc Doc
9 Doc • Each
node
has
index
for
data
stored
on
it
REPLICA REPLICA REPLICA • Queries
combine
the
results
from
required
nodes
Doc
4 Doc Doc
4 Doc Doc
4 Doc
Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
8 Doc Doc
8 Doc Doc
8 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
38. Indexing
and
Querying
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3
ACTIVE
• Indexing
work
is
distributed
amongst
ACTIVE ACTIVE
nodes
Doc
5 Doc Doc
5 Doc Doc
5 Doc
• Large
data
set
possible
Doc
2 Doc Doc
2 Doc Doc
2 Doc
• Parallelize
the
effort
Doc
9 Doc Doc
9 Doc Doc
9 Doc • Each
node
has
index
for
data
stored
on
it
REPLICA REPLICA REPLICA • Queries
combine
the
results
from
required
nodes
Doc
4 Doc Doc
4 Doc Doc
4 Doc
Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
8 Doc Doc
8 Doc Doc
8 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
39. Indexing
and
Querying
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
Query
SERVER
1 SERVER
2 SERVER
3
ACTIVE
• Indexing
work
is
distributed
amongst
ACTIVE ACTIVE
nodes
Doc
5 Doc Doc
5 Doc Doc
5 Doc
• Large
data
set
possible
Doc
2 Doc Doc
2 Doc Doc
2 Doc
• Parallelize
the
effort
Doc
9 Doc Doc
9 Doc Doc
9 Doc • Each
node
has
index
for
data
stored
on
it
REPLICA REPLICA REPLICA • Queries
combine
the
results
from
required
nodes
Doc
4 Doc Doc
4 Doc Doc
4 Doc
Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
8 Doc Doc
8 Doc Doc
8 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
40. Indexing
and
Querying
APP
SERVER
1 APP
SERVER
2
COUCHBASE
Client
Library COUCHBASE
Client
Library
CLUSTER
MAP CLUSTER
MAP
SERVER
1 SERVER
2 SERVER
3
ACTIVE
• Indexing
work
is
distributed
amongst
ACTIVE ACTIVE
nodes
Doc
5 Doc Doc
5 Doc Doc
5 Doc
• Large
data
set
possible
Doc
2 Doc Doc
2 Doc Doc
2 Doc
• Parallelize
the
effort
Doc
9 Doc Doc
9 Doc Doc
9 Doc • Each
node
has
index
for
data
stored
on
it
REPLICA REPLICA REPLICA • Queries
combine
the
results
from
required
nodes
Doc
4 Doc Doc
4 Doc Doc
4 Doc
Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
8 Doc Doc
8 Doc Doc
8 Doc
COUCHBASE
SERVER
CLUSTER
Monday, February 4, 13
41. Cross
Data
Center
ReplicaJon
(XDCR)
Couchbase
Cluster Couchbase
Cluster
West
Coast
Data
Center East
Coast
Data
Center
SERVER
1 SERVER
2 SERVER
3 SERVER
1 SERVER
2 SERVER
3
RAM
CACHE RAM
CACHE RAM
CACHE RAM
CACHE RAM
CACHE RAM
CACHE
Doc
1 Doc Doc
1 Doc Doc
1 Doc Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
2 Doc Doc
2 Doc Doc
2 Doc Doc
2 Doc Doc
2 Doc Doc
2 Doc
Doc
6 Doc Doc
6 Doc Doc
6 Doc Doc
6 Doc Doc
6 Doc Doc
6 Doc
DISK DISK DISK DISK DISK DISK
Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc
Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc
Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc
Monday, February 4, 13
42. Cross
Data
Center
ReplicaJon
(XDCR)
Couchbase
Cluster Couchbase
Cluster
West
Coast
Data
Center East
Coast
Data
Center
SERVER
1 SERVER
2 SERVER
3 SERVER
1 SERVER
2 SERVER
3
RAM
CACHE RAM
CACHE RAM
CACHE RAM
CACHE RAM
CACHE RAM
CACHE
Doc
1 Doc Doc
1 Doc Doc
1 Doc Doc
1 Doc Doc
1 Doc Doc
1 Doc
Doc
2 Doc Doc
2 Doc Doc
2 Doc Doc
2 Doc Doc
2 Doc Doc
2 Doc
Doc
6 Doc Doc
6 Doc Doc
6 Doc Doc
6 Doc Doc
6 Doc Doc
6 Doc
DISK DISK DISK DISK DISK DISK
Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc
Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc
Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc Doc
Monday, February 4, 13
43. GeoCouch
R-‐Tree
Index
• Optimized for bulk loading of large data sets
• Simplified query model (bounding box, nearest neighbor)
Monday, February 4, 13
44. ElasJc
Search
Adaptor
• Elastic Search is good for ad-hoc queries and faceted browsing
• Our adapter is aware of changing Couchbase topology
• Indexed by Elastic Search after stored to disk in Couchbase
ElasYcSearch
Monday, February 4, 13
45. I’m
Excited
to
See
What
You
Build,
Q
&
A
Couchbase
Docs Contact
me
on
TwiDer
www.couchbase.com/docs/index-‐full.html @tgrall
Couchbase
Forums Contact
me
by
Email
www.couchbase.com/forums tug@couchbase.com
IRC Learn
More
About
Design
PaDerns
#couchbase CouchbaseModels.com
#libcouchbase
Seeng
up
for
Ruby
on
Rails
CouchbaseOnRails.com
Monday, February 4, 13