Aggregation in MongoDB

Sep 12, 2013Download as PPTX, PDF0 likes1,702 views

This document discusses various MongoDB aggregation operations including count, distinct, match, limit, sort, project, group, and map reduce. It provides examples of how to use each operation in an aggregation pipeline to count, filter, sort, select fields, compute new fields, group documents, and perform more complex aggregations.

Pipeline
Unix pipeline
Piping command line operations
ls -al | grep '^d‘ |

Pipeline
• Piping aggregation operations
$match | $sort | $skip | more
Stream of documents Result document

Example
{
title : “mongo DB " ,
author : "bob" ,
posted : new Date() ,
pageViews : 5 ,
tags : [ "fun" , "good" , "fun" ] ,
language : “English”,
other : { foo : 5 }
}

1. Count – return number of documents in collection.
> db.user.count();
you can also pass query, and MongoDB will count number of result for
that query.
2. Distinct
The distinct commands find all the distinct values for given key in
collection.
db.runCommand ( {“distinct” : “collection name” ,”key” : “key field” } )
3. Match
>db.blog.aggregate({$match : {pageViews : {$gt : 1 ,$lt :50 } } } )
4. Limit
> db.blog.aggregate({$limit : 5 } )
5. Sort
>db.blog.find( ).sort({title : 1} )

$6. $project Include, exclude or rename fields Insert computed fields Create sub-document fields selecting and excluding fields >db.blog.aggregate{ { “$project” : { _id : 0 , title : 1 , language : 1} } }$

${ _id: 375, title: “mongo DB", ISBN: "9781857150193", available: true, pages: 218, subjects: [ “Test", “Pune", "1920s" ], language: "English" } { title: “mongo DB, language: "English" }$

Insert computed field
Db.blog.aggregate( {
“$project” : { title : 1 ,
newPageViews : { $add : *“$pageViews” ,10]}
}
}

Rename Page Views
db.blog.aggregate( { title : 1,
newPageViews : “$pageViews”
} )
Create and Populate new Field that hold subfields
db.blog.aggregate( {"$project" : {
title : 1 ,
stats:{pv : "$pageViews" ,
foo : "$other.foo" }
}
})

$Groups Each document in collection has following form { "_id": “413710", "city": “Pune", "state": “MH", "pop": 5574, "loc": [ -74.016323, 40.710537 ] }$

$Group db.blog.aggregate( { $group : { _id : "$state", totalPop : { $sum : "$pop" } } }, { $match : {totalPop : { $gte : 10*1000 } } } )$

Usage and Limit
• collection.aggregate() method
– Mongo shell
– Most drivers
• aggregate database command

Limitations
Result limited by BSON document size
Final command result
Intermediate shard results
Pipeline operator memory limits
Some BSON types unsupported
Binary, Code, deprecated types

Map Reduce
• Map reduce operation handle complex
aggregation task.

The new MongoDB aggregation framework provides a more powerful and performant way to perform data aggregation compared to the existing MapReduce functionality. The aggregation framework uses a pipeline of aggregation operations like $match, $project, $group and $unwind. It allows expressing data aggregation logic through a declarative pipeline in a more intuitive way without needing to write JavaScript code. This provides better performance than MapReduce as it is implemented in C++ rather than JavaScript.

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Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency. This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data. Attendees will learn: - Consumer awareness around data brokers and what consumers are doing to limit data collection - How businesses assess third-party vendors and their consent management operations - Where business preparedness needs improvement - What these trends mean for the future of privacy governance and public trust This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.

Technology Trends in 2025: AI and Big Data AnalyticsInData Labs

At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including: -Artificial Intelligence Market Overview -Strategies for AI Adoption in 2025 -Anticipated drivers of AI adoption and transformative technologies -Benefits of AI and Big data for your business -Tips on how to prepare your business for innovation -AI and data privacy: Strategies for securing data privacy in AI models, etc. Download your free copy nowand implement the key findings to improve your business.

HCL Nomad Web – Best Practices und Verwaltung von Multiuser-Umgebungenpanagenda

Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-und-verwaltung-von-multiuser-umgebungen/ HCL Nomad Web wird als die nächste Generation des HCL Notes-Clients gefeiert und bietet zahlreiche Vorteile, wie die Beseitigung des Bedarfs an Paketierung, Verteilung und Installation. Nomad Web-Client-Updates werden “automatisch” im Hintergrund installiert, was den administrativen Aufwand im Vergleich zu traditionellen HCL Notes-Clients erheblich reduziert. Allerdings stellt die Fehlerbehebung in Nomad Web im Vergleich zum Notes-Client einzigartige Herausforderungen dar. Begleiten Sie Christoph und Marc, während sie demonstrieren, wie der Fehlerbehebungsprozess in HCL Nomad Web vereinfacht werden kann, um eine reibungslose und effiziente Benutzererfahrung zu gewährleisten. In diesem Webinar werden wir effektive Strategien zur Diagnose und Lösung häufiger Probleme in HCL Nomad Web untersuchen, einschließlich - Zugriff auf die Konsole - Auffinden und Interpretieren von Protokolldateien - Zugriff auf den Datenordner im Cache des Browsers (unter Verwendung von OPFS) - Verständnis der Unterschiede zwischen Einzel- und Mehrbenutzerszenarien - Nutzung der Client Clocking-Funktion

What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat

The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.

UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity

Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts! 📕 Agenda Welcome & Introductions Orchestrator API Overview Exploring the Swagger Interface Test Manager API Highlights Streamlining Automation & Testing with APIs (Demo) Q&A and Open Discussion Perfect for developers, testers, and automation enthusiasts! 👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/ This session streamed live on April 29, 2025, 18:00 CET. Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.

Semantic Cultivators : The Critical Future Role to Enable AIartmondano

Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex

Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how: • Optimized Torizon OS & Yocto Support – Toradex provides Torizon OS, a Debian-based easy-to-use platform, and Yocto BSPs for customized Linux images on SMARC modules. • Seamless Integration with i.MX 8M Plus and i.MX 95 – Toradex SMARC solutions leverage NXP’s i.MX 8 M Plus and i.MX 95 SoCs, delivering power efficiency and AI-ready performance. • Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity. • Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications. • Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market. With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications. Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family