MongoDB - Back to Basics - La tua prima ApplicazioneMassimo Brignoli
Eccoci alla seconda puntata della serie Back to Basics edizione 2017. Vedremo come sviluppare un'applicazione con MongoDB studiando come interagire con la base dati. Vedremo come fare le query, creare un indice e studiarne il piano di esecuzione
This presentation is showing how to use the Aggregation Framework, the powerful aggregation language of MongoDB. Using some real data coming from the USA Census, we will discover the most important operations.
Back to Basics: My First MongoDB ApplicationMongoDB
This Back to Basics webinar series will introduce you to NoSQL and the MongoDB database. You will find out what MongoDB is, why you would use it, and what you would use it for.
Webinaire 2 de la série « Retour aux fondamentaux » : Votre première applicat...MongoDB
Il s'agit du deuxième webinaire de la série « Retour aux fondamentaux » qui a pour but de vous présenter la base de données MongoDB. Dans ce webinaire, nous vous expliquerons comment créer une application de création de blogs dans MongoDB.
MongoDB .local Munich 2019: Best Practices for Working with IoT and Time-seri...MongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
• Common components of an IoT solution
• The challenges involved with managing time-series data in IoT applications
• Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
• How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
The flexibility of MongoDB makes it perfect for storing analytics. I'll discuss a few patterns for storing data that we have learned while growing Gaug.es from zero to millions of page views a day. You'll leave with a desire to measure everything and the ability to do it.
Webinar: General Technical Overview of MongoDB for Dev TeamsMongoDB
In this talk we will focus on several of the reasons why developers have come to love the richness, flexibility, and ease of use that MongoDB provides. First we will give a brief introduction of MongoDB, comparing and contrasting it to the traditional relational database. Next, we’ll give an overview of the APIs and tools that are part of the MongoDB ecosystem. Then we’ll look at how MongoDB CRUD (Create, Read, Update, Delete) operations work, and also explore query, update, and projection operators. Finally, we will discuss MongoDB indexes and look at some examples of how indexes are used.
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
Encryption is not a new concept to MongoDB. Encryption may occur in-transit (with TLS) and at-rest (with the encrypted storage engine). But MongoDB 4.2 introduces support for Client Side Encryption, ensuring the most sensitive data is encrypted before ever leaving the client application. Even full access to your MongoDB servers is not enough to decrypt this data. And better yet, Client Side Encryption can be enabled at the "flick of a switch".
This session covers using Client Side Encryption in your applications. This includes the necessary setup, how to encrypt data without sacrificing queryability, and what trade-offs to expect.
MongoDB - Back to Basics - La tua prima ApplicazioneMassimo Brignoli
Eccoci alla seconda puntata della serie Back to Basics edizione 2017. Vedremo come sviluppare un'applicazione con MongoDB studiando come interagire con la base dati. Vedremo come fare le query, creare un indice e studiarne il piano di esecuzione
This presentation is showing how to use the Aggregation Framework, the powerful aggregation language of MongoDB. Using some real data coming from the USA Census, we will discover the most important operations.
Back to Basics: My First MongoDB ApplicationMongoDB
This Back to Basics webinar series will introduce you to NoSQL and the MongoDB database. You will find out what MongoDB is, why you would use it, and what you would use it for.
Webinaire 2 de la série « Retour aux fondamentaux » : Votre première applicat...MongoDB
Il s'agit du deuxième webinaire de la série « Retour aux fondamentaux » qui a pour but de vous présenter la base de données MongoDB. Dans ce webinaire, nous vous expliquerons comment créer une application de création de blogs dans MongoDB.
MongoDB .local Munich 2019: Best Practices for Working with IoT and Time-seri...MongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
• Common components of an IoT solution
• The challenges involved with managing time-series data in IoT applications
• Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
• How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
The flexibility of MongoDB makes it perfect for storing analytics. I'll discuss a few patterns for storing data that we have learned while growing Gaug.es from zero to millions of page views a day. You'll leave with a desire to measure everything and the ability to do it.
Webinar: General Technical Overview of MongoDB for Dev TeamsMongoDB
In this talk we will focus on several of the reasons why developers have come to love the richness, flexibility, and ease of use that MongoDB provides. First we will give a brief introduction of MongoDB, comparing and contrasting it to the traditional relational database. Next, we’ll give an overview of the APIs and tools that are part of the MongoDB ecosystem. Then we’ll look at how MongoDB CRUD (Create, Read, Update, Delete) operations work, and also explore query, update, and projection operators. Finally, we will discuss MongoDB indexes and look at some examples of how indexes are used.
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
Encryption is not a new concept to MongoDB. Encryption may occur in-transit (with TLS) and at-rest (with the encrypted storage engine). But MongoDB 4.2 introduces support for Client Side Encryption, ensuring the most sensitive data is encrypted before ever leaving the client application. Even full access to your MongoDB servers is not enough to decrypt this data. And better yet, Client Side Encryption can be enabled at the "flick of a switch".
This session covers using Client Side Encryption in your applications. This includes the necessary setup, how to encrypt data without sacrificing queryability, and what trade-offs to expect.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
This is the fifth webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will introduce you to the aggregation framework.
Back to Basics Webinar 3: Schema Design Thinking in DocumentsMongoDB
This is the third webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will explain the architecture of document databases.
Back to Basics, webinar 2: La tua prima applicazione MongoDBMongoDB
Questo è il secondo webinar della serie Back to Basics che ti offrirà un'introduzione al database MongoDB. In questo webinar ti dimostreremo come creare un'applicazione base per il blogging in MongoDB.
This talk is focused on tuning analysing and optimizing MongoDB query and index with the use of Database Profiler and "explain()" function.
Also, performance of database can also be impacted by configuring the underline ( Linux ) OS with some recommended settings which do not come by default.
MongoDB Europe 2016 - Debugging MongoDB PerformanceMongoDB
Asya is back, and so is Sherlock Holmes and his techniques to gather and analyze data from your poorly performing MongoDB clusters. In this advanced talk we take a deep look at all the diagnostic data that lives inside MongoDB - how to interrogate and interpret it to help you solve those frustrating performance bottlenecks that we all face occasionally.
Building a Scalable Inbox System with MongoDB and Javaantoinegirbal
Many user-facing applications present some kind of news feed/inbox system. You can think of Facebook, Twitter, or Gmail as different types of inboxes where the user can see data of interest, sorted by time, popularity, or other parameter. A scalable inbox is a difficult problem to solve: for millions of users, varied data from many sources must be sorted and presented within milliseconds. Different strategies can be used: scatter-gather, fan-out writes, and so on. This session presents an actual application developed by 10gen in Java, using MongoDB. This application is open source and is intended to show the reference implementation of several strategies to tackle this common challenge. The presentation also introduces many MongoDB concepts.
Back to Basics Webinar 2 - Your First MongoDB ApplicationJoe Drumgoole
How to build a MongoDB application from scratch in the MongoDB Shell and Python. How to add indexes and use explain to make sure you are using them properly.
Back to Basics 2017: Mí primera aplicación MongoDBMongoDB
Descubra:
Cómo instalar MongoDB y usar el shell de MongoDB
Las operaciones básicas de CRUD
Cómo analizar el rendimiento de las consultas y añadir un índice
Conceptos básicos. Seminario web 2: Su primera aplicación MongoDBMongoDB
Este es el segundo seminario web de la serie Conceptos básicos, en la que se realiza una introducción a la base de datos MongoDB. En este seminario web mostraremos cómo construir una aplicación de creación de blogs en MongoDB.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
This is the fifth webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will introduce you to the aggregation framework.
Back to Basics Webinar 3: Schema Design Thinking in DocumentsMongoDB
This is the third webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will explain the architecture of document databases.
Back to Basics, webinar 2: La tua prima applicazione MongoDBMongoDB
Questo è il secondo webinar della serie Back to Basics che ti offrirà un'introduzione al database MongoDB. In questo webinar ti dimostreremo come creare un'applicazione base per il blogging in MongoDB.
This talk is focused on tuning analysing and optimizing MongoDB query and index with the use of Database Profiler and "explain()" function.
Also, performance of database can also be impacted by configuring the underline ( Linux ) OS with some recommended settings which do not come by default.
MongoDB Europe 2016 - Debugging MongoDB PerformanceMongoDB
Asya is back, and so is Sherlock Holmes and his techniques to gather and analyze data from your poorly performing MongoDB clusters. In this advanced talk we take a deep look at all the diagnostic data that lives inside MongoDB - how to interrogate and interpret it to help you solve those frustrating performance bottlenecks that we all face occasionally.
Building a Scalable Inbox System with MongoDB and Javaantoinegirbal
Many user-facing applications present some kind of news feed/inbox system. You can think of Facebook, Twitter, or Gmail as different types of inboxes where the user can see data of interest, sorted by time, popularity, or other parameter. A scalable inbox is a difficult problem to solve: for millions of users, varied data from many sources must be sorted and presented within milliseconds. Different strategies can be used: scatter-gather, fan-out writes, and so on. This session presents an actual application developed by 10gen in Java, using MongoDB. This application is open source and is intended to show the reference implementation of several strategies to tackle this common challenge. The presentation also introduces many MongoDB concepts.
Back to Basics Webinar 2 - Your First MongoDB ApplicationJoe Drumgoole
How to build a MongoDB application from scratch in the MongoDB Shell and Python. How to add indexes and use explain to make sure you are using them properly.
Back to Basics 2017: Mí primera aplicación MongoDBMongoDB
Descubra:
Cómo instalar MongoDB y usar el shell de MongoDB
Las operaciones básicas de CRUD
Cómo analizar el rendimiento de las consultas y añadir un índice
Conceptos básicos. Seminario web 2: Su primera aplicación MongoDBMongoDB
Este es el segundo seminario web de la serie Conceptos básicos, en la que se realiza una introducción a la base de datos MongoDB. En este seminario web mostraremos cómo construir una aplicación de creación de blogs en MongoDB.
Relational databases are central to web applications, but they have also been the primary source of pain when it comes to scale and performance. Recently, non-relational databases (also referred to as NoSQL) have arrived on the scene. This session explains not only what MongoDB is and how it works, but when and how to gain the most benefit.
Webinar: Build an Application Series - Session 2 - Getting StartedMongoDB
This session - presented by Matthew Bates, Solutions Architect & Consulting Engineer at MongoDB - will cover an outline of an application, schema design decisions, application functionality and design for scale out.
About the speaker
Matthew Bates is a Solutions Architect in the EMEA region for MongoDB and helps advise customers how to best use and make the most out of MongoDB in their organisations. He has a background in solutions for the acquisition, management and exploitation of big data in government and public sector and telco industries through his previous roles at consultancy firms and a major European telco. He's a Java and Python coder and has a BSc(Hons) in Computer Science from the University of Nottingham.
Next in the Series:
February 20th 2014
Build an Application Series - Session 3 - Interacting with the database:
This webinar will discuss queries and updates and the interaction between an application and a database
March 6th 2014
Build an Application Series - Session 4 - Indexing:
This session will focus on indexing strategies for the application, including geo spatial and full text search
March 20th 2014
Build an Application Series - Session 5 - Reporting in your application:
This session covers Reporting and Aggregation Framework and Building application usage reports
April 3th 2014
Operations for your application - Session 6 - Deploying the application:
By this stage, we will have built the application. Now we need to deploy it. We will discuss architecture for High Availability and scale out
April 17th 2014
Operations for your application - Session 7 - Backup and DR:
This webinar will discuss back up and restore options. Learn what you should do in the event of a failure and how to perform a backup and recovery of the data in your applications
May 6th 2014
Operations for your application - Session 8 - Monitoring and Performance Tuning:
The final webinar of the series will discuss what metrics are important and how to manage and monitor your application for key performance.
MongoDB is the trusted document store we turn to when we have tough data store problems to solve. For this talk we are going to go a little bit off the path and explore what other roles we can fit MongoDB into. Others have discussed how to turn MongoDB’s capped collections into a publish/subscribe server. We stretch that a little further and turn MongoDB into a full fledged broker with both publish/subscribe and queue semantics, and a the ability to mix them. We will provide code and a running demo of the queue producers and consumers. Next we will turn to coordination services: We will explore the fundamental features and show how to implement them using MongoDB as the storage engine. Again we will show the code and demo the coordination of multiple applications.
Wszyscy zostaliśmy oszukani! Automatyczne zarządzanie pamięci rozwiąże wszystkie Wasze problemy, mówili. W zarządzanych środowiskach takich jak CLR JVM nie będzie wycieków pamięci, mówili! Właściwie pamięć jest tania i nie musisz się już nią nigdy więcej martwić. Wszyscy kłamali. Automatyczne zarządzanie pamięcią jest wygodną abstrakcją i bardzo często działa dobrze. Ale jak każda abstrakcja, wcześniej czy później "wycieka" ona. I to najczęściej w najmniej spodziewanym i przyjemnym momencie. W tej sesji spróbuję otworzyć oczy na fakt, że błoga nieświadomość nt. tej abstrakcji może być kosztowna. Pokażę jak może się objawić frywolne traktowanie pamięci i co możemy zyskać pisząc kod zdając sobie sprawę, że pamięć jednak nie jest nieskończona, tania i zawsze jednakowo szybka.
MongoDB 2.4 enthält über hundert Verbesserungen, welche mehr Möglichkeiten und eine höhere Produktivität für Entwickler, erweiterte Datenbank Management Funktionalitäten und Geschwindigkeitsverbesserungen beinhalten. Im Webinar werden die wichtigsten Neuerungen anhand von Beispielen erläutert.
Eagle6 is a product that use system artifacts to create a replica model that represents a near real-time view of system architecture. Eagle6 was built to collect system data (log files, application source code, etc.) and to link system behaviors in such a way that the user is able to quickly identify risks associated with unknown or unwanted behavioral events that may result in unknown impacts to seemingly unrelated down-stream systems. This session is designed to present the capabilities of the Eagle6 modeling product and how we are using MongoDB to support near-real-time analysis of large disparate datasets.
MongoDB Solution for Internet of Things and Big DataStefano Dindo
Internet of Things è uno degli scenari di mercato più importanti su cui investire entro il 2020.
L'Internet of Things permette di trasferire sul Web la vita reale delle persone grazie all'interazione con oggetti e spazi fisici scambiando un grande volume di dati.
Durante il Lab è stata fornita una descrizione di architettura necessaria a supportare progetti di Internet of Things con un focus sull'organizzazione dei dati all'interno di MongoDB, database NoSQL Leader di mercato, per raccogliere ed analizzare grandi volumi di dati in tempo reale ed in modo efficiente.
Lab pratico per la progettazione di soluzioni MongoDB in ambito Internet of T...festival ICT 2016
Le aziende sono chiamate a rispondere velocemente ai cambiamenti di mercato a seguito dell’affermarsi di nuovi scenari (Internet of Things, Social Analysis, manifattura 4.0 ecc.) che richiedono sempre di più l’integrazione con nuove tecnologie. Trattandosi di progetti innovativi, che impattano su processi e contesti aziendali, è fondamentale disporre di soluzioni flessibili per la raccolta e l’analisi dei dati.
MongoDB è un database NoSQL in grado di offrire flessibilità, scalabilità e semplificazione delle attività di sviluppo. Il lab avrà lo scopo di illustrare come creare architetture MongoDB e svolgere attività di Schema Design per la gestione dei dati in ambito IoT e Big Data facendo inoltre riferimento a casi pratici reali che si basano su tecnologie Cloud, necessarie a far fronte ad un mercato sempre più globale.
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
During this talk we'll navigate through a customer's journey as they migrate an existing MongoDB deployment to MongoDB Atlas. While the migration itself can be as simple as a few clicks, the prep/post effort requires due diligence to ensure a smooth transfer. We'll cover these steps in detail and provide best practices. In addition, we’ll provide an overview of what to consider when migrating other cloud data stores, traditional databases and MongoDB imitations to MongoDB Atlas.
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB
MongoDB Kubernetes operator and MongoDB Open Service Broker are ready for production operations. Learn about how MongoDB can be used with the most popular container orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications. A demo will show you how easy it is to enable MongoDB clusters as an External Service using the Open Service Broker API for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB
Humana, like many companies, is tackling the challenge of creating real-time insights from data that is diverse and rapidly changing. This is our journey of how we used MongoDB to combined traditional batch approaches with streaming technologies to provide continues alerting capabilities from real-time data streams.
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB
Our clients have unique use cases and data patterns that mandate the choice of a particular strategy. To implement these strategies, it is mandatory that we unlearn a lot of relational concepts while designing and rapidly developing efficient applications on NoSQL. In this session, we will talk about some of our client use cases, the strategies we have adopted, and the features of MongoDB that assisted in implementing these strategies.
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB
MongoDB Kubernetes operator is ready for prime-time. Learn about how MongoDB can be used with most popular orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications.
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB
When you need to model data, is your first instinct to start breaking it down into rows and columns? Mine used to be too. When you want to develop apps in a modern, agile way, NoSQL databases can be the best option. Come to this talk to learn how to take advantage of all that NoSQL databases have to offer and discover the benefits of changing your mindset from the legacy, tabular way of modeling data. We’ll compare and contrast the terms and concepts in SQL databases and MongoDB, explain the benefits of using MongoDB compared to SQL databases, and walk through data modeling basics so you feel confident as you begin using MongoDB.
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
Query performance should be the unsung hero of an application, but without proper configuration, can become a constant headache. When used properly, MongoDB provides extremely powerful querying capabilities. In this session, we'll discuss concepts like equality, sort, range, managing query predicates versus sequential predicates, and best practices to building multikey indexes.
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB
Aggregation pipeline has been able to power your analysis of data since version 2.2. In 4.2 we added more power and now you can use it for more powerful queries, updates, and outputting your data to existing collections. Come hear how you can do everything with the pipeline, including single-view, ETL, data roll-ups and materialized views.
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
MongoDB Atlas Data Lake is a new service offered by MongoDB Atlas. Many organizations store long term, archival data in cost-effective storage like S3, GCP, and Azure Blobs. However, many of them do not have robust systems or tools to effectively utilize large amounts of data to inform decision making. MongoDB Atlas Data Lake is a service allowing organizations to analyze their long-term data to discover a wealth of information about their business.
This session will take a deep dive into the features that are currently available in MongoDB Atlas Data Lake and how they are implemented. In addition, we'll discuss future plans and opportunities and offer ample Q&A time with the engineers on the project.
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB
Virtual assistants are becoming the new norm when it comes to daily life, with Amazon’s Alexa being the leader in the space. As a developer, not only do you need to make web and mobile compliant applications, but you need to be able to support virtual assistants like Alexa. However, the process isn’t quite the same between the platforms.
How do you handle requests? Where do you store your data and work with it to create meaningful responses with little delay? How much of your code needs to change between platforms?
In this session we’ll see how to design and develop applications known as Skills for Amazon Alexa powered devices using the Go programming language and MongoDB.
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB
aux Core Data, appréciée par des centaines de milliers de développeurs. Apprenez ce qui rend Realm spécial et comment il peut être utilisé pour créer de meilleures applications plus rapidement.
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB
Il n’a jamais été aussi facile de commander en ligne et de se faire livrer en moins de 48h très souvent gratuitement. Cette simplicité d’usage cache un marché complexe de plus de 8000 milliards de $.
La data est bien connu du monde de la Supply Chain (itinéraires, informations sur les marchandises, douanes,…), mais la valeur de ces données opérationnelles reste peu exploitée. En alliant expertise métier et Data Science, Upply redéfinit les fondamentaux de la Supply Chain en proposant à chacun des acteurs de surmonter la volatilité et l’inefficacité du marché.
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDBMongoDB
Chaque entreprise devient une entreprise de logiciels, fournissant des solutions client pour accéder à une variété de services et d'informations. Les entreprises commencent maintenant à valoriser leurs données et à obtenir de meilleures informations pour l'entreprise. Un défi crucial consiste à s'assurer que ces données sont toujours disponibles et sécurisées pour être conformes aux objectifs commerciaux de l'entreprise et aux contraintes réglementaires des pays. MongoDB fournit la couche de sécurité dont vous avez besoin, venez découvrir comment sécuriser vos données avec MongoDB.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
In the ever-evolving landscape of technology, enterprise software development is undergoing a significant transformation. Traditional coding methods are being challenged by innovative no-code solutions, which promise to streamline and democratize the software development process.
This shift is particularly impactful for enterprises, which require robust, scalable, and efficient software to manage their operations. In this article, we will explore the various facets of enterprise software development with no-code solutions, examining their benefits, challenges, and the future potential they hold.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
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(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Providing Globus Services to Users of JASMIN for Environmental Data Analysis
Back to basics Italian webinar 2 Mia prima applicazione MongoDB
1.
2. Back to Basics 2017 : Webinar 2
La Tua Prima Applicazione
Massimo Brignoli
Principal Solution Architect
MongoDB
massimo@mongodb.com
@massimobrignoli
V1.0
3. 3
Riassunto della Parte 1
• Perché esistono i NoSQL
• I vari tipi di database NoSQL
• Le caratteristiche principali di MongoDB
4. 4
Agenda
• I concetti base
• Installare MongoDB
• Costruire un’applicazione base di blogging
• Aggiungere gli indici
• Ottimizzare le query con l’explain
9. 9
Installare MongoDB
$ curl -O https://fastdl.mongodb.org/osx/mongodb-osx-ssl-x86_64-3.4.1.tgz
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 60.9M 100 60.9M 0 0 2730k 0 0:00:22 0:00:22 --:--:-- 1589k
$ tar xzvf mongodb-osx-x86_64-3.2.6.tgz
x mongodb-osx-x86_64-3.2.6/README
x mongodb-osx-x86_64-3.2.6/THIRD-PARTY-NOTICES
x mongodb-osx-x86_64-3.2.6/MPL-2
x mongodb-osx-x86_64-3.2.6/GNU-AGPL-3.0
x mongodb-osx-x86_64-3.2.6/bin/mongodump
x mongodb-osx-x86_64-3.2.6/bin/mongorestore
x mongodb-osx-x86_64-3.2.6/bin/mongoexport
x mongodb-osx-x86_64-3.2.6/bin/mongoimport
x mongodb-osx-x86_64-3.2.6/bin/mongostat
x mongodb-osx-x86_64-3.2.6/bin/mongotop
x mongodb-osx-x86_64-3.2.6/bin/bsondump
x mongodb-osx-x86_64-3.2.6/bin/mongofiles
x mongodb-osx-x86_64-3.2.6/bin/mongooplog
x mongodb-osx-x86_64-3.2.6/bin/mongoperf
x mongodb-osx-x86_64-3.2.6/bin/mongosniff
x mongodb-osx-x86_64-3.2.6/bin/mongod
x mongodb-osx-x86_64-3.2.6/bin/mongos
x mongodb-osx-x86_64-3.2.6/bin/mongo
$ ln -s mongodb-osx-x86_64-3.2.6 mongodb
10. 10
Eseguire mongod
JD10Gen:mongodb mbrignoli$ ./bin/mongod --dbpath /data/b2b
2016-05-23T19:21:07.767+0100 I CONTROL [initandlisten] MongoDB starting : pid=49209 port=27017 dbpath=/data/b2b 64-
bit host=JD10Gen.local
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] db version v3.4.1
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] git version: 05552b562c7a0b3143a729aaa0838e558dc49b25
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] allocator: system
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] modules: none
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] build environment:
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] distarch: x86_64
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] target_arch: x86_64
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] options: { storage: { dbPath: "/data/b2b" } }
2016-05-23T19:21:07.769+0100 I - [initandlisten] Detected data files in /data/b2b created by the 'wiredTiger'
storage engine, so setting the active storage engine to 'wiredTiger'.
2016-05-23T19:21:07.769+0100 I STORAGE [initandlisten] wiredtiger_open config:
create,cache_size=4G,session_max=20000,eviction=(threads_max=4),config_base=false,statistics=(fast),log=(enabled=true
,archive=true,path=journal,compressor=snappy),file_manager=(close_idle_time=100000),checkpoint=(wait=60,log_size=2GB)
,statistics_log=(wait=0),
2016-05-23T19:21:08.837+0100 I CONTROL [initandlisten]
2016-05-23T19:21:08.838+0100 I CONTROL [initandlisten] ** WARNING: soft rlimits too low. Number of files is 256,
should be at least 1000
2016-05-23T19:21:08.840+0100 I NETWORK [HostnameCanonicalizationWorker] Starting hostname canonicalization worker
2016-05-23T19:21:08.840+0100 I FTDC [initandlisten] Initializing full-time diagnostic data capture with directory
'/data/b2b/diagnostic.data'
2016-05-23T19:21:08.841+0100 I NETWORK [initandlisten] waiting for connections on port 27017
2016-05-23T19:21:09.148+0100 I NETWORK [initandlisten] connection accepted from 127.0.0.1:59213 #1 (1 connection now
open)
11. 11
Connettersi Via Shell
$ ./bin/mongo
MongoDB shell version: 3.4.1
connecting to: test
Server has startup warnings:
2016-05-17T11:46:03.516+0100 I CONTROL [initandlisten]
2016-05-17T11:46:03.516+0100 I CONTROL [initandlisten] ** WARNING: soft rlimits too low. Number of
files is 256, should be at least 1000
>
12. 12
Inserire il Vostro Primo Record
> show databases
local 0.000GB
> use test
switched to db test
> show databases
local 0.000GB
> db.demo.insert( { "key" : "value" } )
WriteResult({ "nInserted" : 1 })
> show databases
local 0.000GB
test 0.000GB
> show collections
demo
> db.demo.findOne()
{ "_id" : ObjectId("573af7085ee4be80385332a6"), "key" : "value" }
>
17. 17
In MongoDB possiamo farlo in modo organico
> use blog
switched to db blog
> db.users.insert( { "username" : ”mbrignoli", "password" : "top secret", "lang" : ”IT" } )
WriteResult({ "nInserted" : 1 })
> db.users.findOne()
{
"_id" : ObjectId("573afff65ee4be80385332a7"),
"username" : ”mbrignoli",
"password" : "top secret",
"lang" : ”IT"
}
18. 18
Come lo facciamo in un programma?
'''
Created on 17 May 2016
@author: mbrignoli
'''
import pymongo
#
# client defaults to localhost and port 27017. eg MongoClient('localhost', 27017)
client = pymongo.MongoClient()
blogDatabase = client[ "blog" ]
usersCollection = blogDatabase[ "users" ]
usersCollection.insert_one( { "username" : ”mbrignoli",
"password" : "top secret",
"lang" : “IT" })
user = usersCollection.find_one()
print( user )
19. 19
Passiamo agli Articles
…
articlesCollection = blogDatabase[ "articles" ]
author = ”mbrignoli"
article = { "title" : ”Questo è il mio primo post",
"body" : ”Questo è il contenuto del mio post, posso aggiungere un sacco di testo qua.",
"author" : author,
"tags" : [ ”massimo", "general", ”Italia", "admin" ]
}
#
# Lets check if our author exists
#
if usersCollection.find_one( { "username" : author }) :
articlesCollection.insert_one( article )
else:
raise ValueError( "Author %s does not exist" % author )
20. 20
Creiamo un nuovo tipo di articolo
#
# Lets add a new type of article with a posting date and a section
#
author = ”mbrignoli"
title = ”Questo è un post su MongoDB"
newPost = { "title" : title,
"body" : ”MongoDB è il database NoSQL più popolare del mondo. E’ un database a
documenti.",
"author" : author,
"tags" : [ ”massimo", "mongodb", ”Italia" ],
"section" : "technology",
"postDate" : datetime.datetime.now(),
}
#
# Lets check if our author exists
#
if usersCollection.find_one( { "username" : author }) :
articlesCollection.insert_one( newPost )
34. 34
Overview degli Indici
• Parametri
– Background : Crea un indice in background senza lockare il db
– Unique : Tutte le chiavi nella collection devono essere uniche.
– Name : Da un nome all’indice, altrimenti il nome sarà generato automaticamente
• Cancellare un indice
– db.users.dropIndex({ “username” : 1 })
• Mostrare tutti gli indici
– db.users.getIndexes()
35. 35
Passaggi nell’esecuzione del Query Plan
• COLLSCAN : full scan di una collection
• IXSCAN : Scansione di un indice
• FETCH : per leggere i documenti
• SHARD_MERGE : Per unire i risultati dagli shard
38. 38
Cosa Abbiamo Imparato
• Come creare un database e una collection
• Come inserire contenuto in una collection
• Come interrogare una collection
• Come aggiornare un documento
• Come cancellare un documento
• Come controllare l’efficienza di una query
• Come aggiungere un indice
• Come controllare che un indice sia usato durante una
query
39. 39
Prossimo Webinar : Introduzione ai Replica Sets
• Come assicurare che I vostri dati sia durabili
• Come recuperare da failure automaticamente
• Come scrivere codice sicuro lato clienti
Martedì, 20 Giugno 2017, 11:00 CET.