This document provides an introduction to MongoDB, including:
1) MongoDB is a schemaless database that supports features like replication, sharding, indexing, file storage, and aggregation.
2) The main concepts include databases containing collections of documents like tables containing rows in SQL databases, but documents can have different structures.
3) Examples demonstrate inserting, querying, updating, and embedding documents in MongoDB collections.
MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. MongoDB obviates the need for an Object Relational Mapping (ORM) to facilitate development.
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.
Webinar: Back to Basics: Thinking in DocumentsMongoDB
New applications, users and inputs demand new types of data, like unstructured, semi-structured and polymorphic data. Adopting MongoDB means adopting to a new, document-based data model.
While most developers have internalized the rules of thumb for designing schemas for relational databases, these rules don't apply to MongoDB. Documents can represent rich data structures, providing lots of viable alternatives to the standard, normalized, relational model. In addition, MongoDB has several unique features, such as atomic updates and indexed array keys, that greatly influence the kinds of schemas that make sense.
In this session, Buzz Moschetti explores how you can take advantage of MongoDB's document model to build modern applications.
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.
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.
MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. MongoDB obviates the need for an Object Relational Mapping (ORM) to facilitate development.
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.
Webinar: Back to Basics: Thinking in DocumentsMongoDB
New applications, users and inputs demand new types of data, like unstructured, semi-structured and polymorphic data. Adopting MongoDB means adopting to a new, document-based data model.
While most developers have internalized the rules of thumb for designing schemas for relational databases, these rules don't apply to MongoDB. Documents can represent rich data structures, providing lots of viable alternatives to the standard, normalized, relational model. In addition, MongoDB has several unique features, such as atomic updates and indexed array keys, that greatly influence the kinds of schemas that make sense.
In this session, Buzz Moschetti explores how you can take advantage of MongoDB's document model to build modern applications.
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.
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.
The agenda of the slides are to discuss some basic and in-depth details of MongoDB and NoSQL.
A snapshot of the topics discussed:
- Introduction to NoSQL and MongoDB
- Installation
- Queries
- Indexing
- Schema modeling
- Aggregation
This tutorial is an introduction to MongoDB and NoSQL. The tutorial includes an introduction to MongoDb and NoSQL, installation, queries related to MongoDB and NoSQL, aggregation framework, indexing of MongoDB and NoSQL and schema modelling. The tutorial begins with a section on introduction. This section includes an introduction to NoSQL, its data models like document model, graph model, key value etc. It also includes an introduction to MongoDB and its data model.
The introduction section is then followed by the installation section. This section includes installing MongoDB, default directory, starting MongoDB server, starting Mongo shell and more steps. It also includes adding documents. The next section is about queries related to MongoDB and NoSQL. This section includes query collection which are selecting all documents, find by example, use OR condition, use AND condition, update query. It also includes removing documents.
Then comes a section about aggregation framework. This section includes a brief about aggregation framework process and its samples. The next section is about indexing. This section involves indexing for speeding up of search and sorting, types of indexes like single field, compound field, multiple index etc. The last section of the tutorial is about schema modelling. This section includes schema design factors like rich documents, no mongo joins, no constraints, atomic operation etc.
Socialite, the Open Source Status Feed Part 2: Managing the Social GraphMongoDB
There are many possible approaches to storing and querying relationships between users in social networks. This section will dive into the details of storing a social user graph in MongoDB. It will cover the various schema designs for storing the follower networks of users and propose an optimal design for insert and query performance, as well as looking at performance differences between them.
A presentation by Aicha Khabil (Responsable IT à l'université Alger 3) done during the 11th edition of Algiers Tech Meetup on October 8th 2016, at Djezzy Training Center (Algiers)
MongoDB is an open source document database, and the leading NoSQL database. MongoDB is a document oriented database that provides high performance, high availability, and easy scalability. It is Maintained and supported by 10gen.
Socialite, the Open Source Status Feed Part 3: Scaling the Data FeedMongoDB
Scaling the delivery of posts and content to the follower networks of millions of users has many challenges. In this section we look at the various approaches to fanning out posts and look at a performance comparison between them. We will highlight some tricks for caching the recent timeline of active users to drive down read latency. We will also look at overall performance metrics from Socialite as we scale from a single replica set to a large sharded environment using MMS Automation.
Building a complete social networking platform presents many challenges at scale. Socialite is a reference architecture and open source Java implementation of a scalable social feed service built on DropWizard and MongoDB. We'll provide an architectural overview of the platform, explaining how you can store an infinite timeline of data while optimizing indexing and sharding configuration for access to the most recent window of data. We'll also dive into the details of storing a social user graph in MongoDB.
The agenda of the slides are to discuss some basic and in-depth details of MongoDB and NoSQL.
A snapshot of the topics discussed:
- Introduction to NoSQL and MongoDB
- Installation
- Queries
- Indexing
- Schema modeling
- Aggregation
This tutorial is an introduction to MongoDB and NoSQL. The tutorial includes an introduction to MongoDb and NoSQL, installation, queries related to MongoDB and NoSQL, aggregation framework, indexing of MongoDB and NoSQL and schema modelling. The tutorial begins with a section on introduction. This section includes an introduction to NoSQL, its data models like document model, graph model, key value etc. It also includes an introduction to MongoDB and its data model.
The introduction section is then followed by the installation section. This section includes installing MongoDB, default directory, starting MongoDB server, starting Mongo shell and more steps. It also includes adding documents. The next section is about queries related to MongoDB and NoSQL. This section includes query collection which are selecting all documents, find by example, use OR condition, use AND condition, update query. It also includes removing documents.
Then comes a section about aggregation framework. This section includes a brief about aggregation framework process and its samples. The next section is about indexing. This section involves indexing for speeding up of search and sorting, types of indexes like single field, compound field, multiple index etc. The last section of the tutorial is about schema modelling. This section includes schema design factors like rich documents, no mongo joins, no constraints, atomic operation etc.
Socialite, the Open Source Status Feed Part 2: Managing the Social GraphMongoDB
There are many possible approaches to storing and querying relationships between users in social networks. This section will dive into the details of storing a social user graph in MongoDB. It will cover the various schema designs for storing the follower networks of users and propose an optimal design for insert and query performance, as well as looking at performance differences between them.
A presentation by Aicha Khabil (Responsable IT à l'université Alger 3) done during the 11th edition of Algiers Tech Meetup on October 8th 2016, at Djezzy Training Center (Algiers)
MongoDB is an open source document database, and the leading NoSQL database. MongoDB is a document oriented database that provides high performance, high availability, and easy scalability. It is Maintained and supported by 10gen.
Socialite, the Open Source Status Feed Part 3: Scaling the Data FeedMongoDB
Scaling the delivery of posts and content to the follower networks of millions of users has many challenges. In this section we look at the various approaches to fanning out posts and look at a performance comparison between them. We will highlight some tricks for caching the recent timeline of active users to drive down read latency. We will also look at overall performance metrics from Socialite as we scale from a single replica set to a large sharded environment using MMS Automation.
Building a complete social networking platform presents many challenges at scale. Socialite is a reference architecture and open source Java implementation of a scalable social feed service built on DropWizard and MongoDB. We'll provide an architectural overview of the platform, explaining how you can store an infinite timeline of data while optimizing indexing and sharding configuration for access to the most recent window of data. We'll also dive into the details of storing a social user graph in MongoDB.
Professional Qualifications - Darin JanecekDarin Janecek
Discusses my professional background and qualifications, and how I can help your organization accelerate profitable growth through my analytical, strategic, transactional, and transformational leadership capabilities.
Presskit for the new release of the Director's Cut of 'GIROTONDO, GIRO ATTORNO AL MONDO'. First Cult underground movie of Davide Manuli. World Première in collaboration with GIORNATE DEGLI AUTORI - VENICE DAYS. Produced by Davide Manuli and Gianluca Arcopinto. Distributed by Zaroff-Kimera Film.
Recensione del Mucchio di Alessandra Sciamanna e Daniele Silipo, per il film "La Leggenda di Kaspar Hauser" presentato in Anteprima Mondiale a Rotterdam 2012.
Article from Roberto Silvestri on ALIAS, (supplement of the daily newspaper IL MANIFESTO) for the Rotterdam Film Festival World Première of "Tthe Legend of Kaspar Hauser" starring Vincent Gallo.
Media owners are turning to MongoDB to drive social interaction with their published content. The way customers consume information has changed and passive communication is no longer enough. They want to comment, share and engage with publishers and their community through a range of media types and via multiple channels whenever and wherever they are. There are serious challenges with taking this semi-structured and unstructured data and making it work in a traditional relational database. This webinar looks at how MongoDB’s schemaless design and document orientation gives organisation’s like the Guardian the flexibility to aggregate social content and scale out.
MongoDB for Coder Training (Coding Serbia 2013)Uwe Printz
Slides of my MongoDB Training given at Coding Serbia Conference on 18.10.2013
Agenda:
1. Introduction to NoSQL & MongoDB
2. Data manipulation: Learn how to CRUD with MongoDB
3. Indexing: Speed up your queries with MongoDB
4. MapReduce: Data aggregation with MongoDB
5. Aggregation Framework: Data aggregation done the MongoDB way
6. Replication: High Availability with MongoDB
7. Sharding: Scaling with MongoDB
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.
This talk will introduce the philosophy and features of the open source, NoSQL MongoDB. We’ll discuss the benefits of the document-based data model that MongoDB offers by walking through how one can build a simple app to store books. We’ll cover inserting, updating, and querying the database of books.
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.
MongoDB presentation for NYC Python's June meetup. Brief discussion on non-relational databases in general followed by an example of using MongoDB as a blog's backend
Dev Jumpstart: Build Your First App with MongoDBMongoDB
New to MongoDB? This talk will introduce the philosophy and features of MongoDB. We’ll discuss the benefits of the document-based data model that MongoDB offers by walking through how one can build a simple app. We’ll cover inserting, updating, and querying the database of books. This session will jumpstart your knowledge of MongoDB development, providing you with context for the rest of the day's content.
OSDC 2012 | Building a first application on MongoDB by Ross LawleyNETWAYS
MongoDB – from "humongous" – is an open source, non-relational, document-oriented database. Trading off a few traditional features of databases (notably joins and transactions) in order to achieve much better performance, MongoDB is fast, scalable, and designed for web development. The goal of the MongoDB project is to bridge the gap between key-value stores (which are fast and highly scalable) and traditional RDBMS systems (which provide rich queries and deep functionality).
This talk will introduce the features of MongoDB by walking through how one can building a simple location-based application using MongoDB. The talk will cover the basics of MongoDB's document model, query language, map-reduce framework and deployment architecture.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
7. Benefits of MongoDB
• Great choice for agile projects
– no schema = no limitations
– ease of use
• Scalability & high availability
– thanks to shardling and replication
• Failover and automatic recovery
8. Main Concepts
• Database is set of collections
• Collection is like a table in MySQL (e.g events
collection)
• Document belongs to a collection, like row in
MySQL, unlike in MySQL documents in same
collection can have different structure
• Documents store fields as key-value pairs, where
value can be basic data type, another document
or array
• Data is stored in JSON format (serialized as BSON)
9. Example
• Inserting document into events collection:
> db.events.insert({
“title” : “CodeCraft Meeting”,
“description” : “CodeCraft meeting in Dunedin on Tuesday evening”,
“start_datetime” : ISODate(“2012-04-03T17:30:00”),
“category” : “social”
})
> db.events.insert({
“title” : “CodeCraft Meeting 2”,
“description” : “CodeCraft meeting in Dunedin on Tuesday evening”,
“start_datetime” : ISODate(“2012-05-03 17:30:00”),
“category” : “social”,
“participants” : 50
})
• When Inserting, indexed field _id is created automatically for each inserted
document
10. Embedded Documents
• Linking versus Embedding
– e.g instead of creating separate collection for comments,
just embed comments in events collection
– MongoDB doesn’t support JOINs = use embedding
> db.events.insert({
“title” : “Title”,
“description” : “Description”,
“start_date” : ISODate(“2012-04-03T17:30:00”),
“category” : “social”,
“comments”: [
{“author”: <user_id>, “comment” :“My First Comment”},
{“author”: <user_id>, “comment”: “My Second Comment”}]
})
15. Files (GridFS)
• In MySQL it’s a bad practice to save large binary
files into the database
• In MongoDB it’s a bad practice NOT TO save large
files into the database.
• MongoDB splits saved files into chunks, which
allows querying of only necessary parts of the
binary files
• Example(pymongo library)
>>> fs = gridfs.GridFs(db_name)
>>> filename = fs.put(“Example file data”)
>>> file_data = fs.get(filename).read()
17. Language Drivers
• Different language drivers for MongoDB provide different levels of
abstraction
– PyMongo (similar to mongo shell) vs MongoEngine (ORM-like)
class Event(mongoengine.Document):
title = StringField()
description = StringField()
start_date = DateTimeField(default=datetime.now)
category = StringField()
comments = ListField(EmbeddedDocumentField(Comment))
#querying
event = Events.objects(title = “Title”)
#adding comments
event.update(push__comments = comment)