Resources

Webinar: MongoDB for Time Series Data: Analyzing Time Series Data Using the Aggregation Framework and Hadoop

The United States will be deploying 16,000 traffic speed monitoring sensors - 1 on every mile of US interstate in urban centers. These sensors update the speed, weather, and pavement conditions once per minute. MongoDB will collect and aggregate live sensor data feeds from roadways around the country, support real-time queries from cars on traffic conditions on their route as well as be the platform for real-time dashboards displaying traffic conditions and more complex analytical queries used to identify traffic trends. In this second webinar of our webinar series, we’ll implement a few different data aggregation techniques to query and dashboard the metrics gathered from the US interstate.

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Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyze Disparate Data in a Single MongoDB View

Creating a single, 360° analytical view of an entity such as a customer, employee or financial investment can have a big impact on your business, but blending data from proprietary and open, unstructured data sources can be a development challenge. Pentaho can accelerate your MongoDB development efforts by making it easy to enrich data with predictive scoring and blend data from disparate sources into a single MongoDB view. In this session we will discuss the single view use case and perform a live demonstration of blending real-time Twitter feeds with NASDAQ stock quotes into a single MongoDB view for understanding the impact of Twitter sentiment on stock valuations.

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Service-Oriented Clusters at Foursquare

Foursquare has been a long time user of MongoDB and currently uses it to serve almost all hot data. We've always run multiple sharded clusters to handle different types of data, but recently we started to split out collections into clusters that align with specialized services. I'm going to talk about the motivation behind isolating MongoDB clusters for specific internal applications and the tools we've used to make that possible without any downtime.

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MongoDB for Time Series Data Part 3: Sharding

Now that MongoDB is set up to aggregate our sensor data, we’ll need to set it up to perform under heavy loads. MongoDB offers sharding capabilities so we can horizontally scale our application and ensure consistent performance. In this session, Jake Angerman will go through sharding options in our Time Series application. You will walk away deeper understanding of how to configure your sharding setup, choose a shard key and leverage this feature for optimal scale.

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Accelerate Your Business with Flash-Fueled MongoDB

Beyond the tremendous performance benefits that can be achieved by deploying MongoDB on an all flash array, key features like high availability, data encryption and advanced data reduction allow customers to maximize the business value they can derive from their MongoDB investment, at a lower cost than traditional storage arrays. Learn how some of the world leading companies have decided to deploy their MongoDB environment on the Pure Storage platform.

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Using NoSQL and Enterprise Shared Services (ESS) to Achieve a More Efficient and Agile IT Environment at the VA

The VA is implementing an enterprise NoSQL data store to provide efficiency, increased security and enhanced information agility. It wants to reduce Database Management System (DBMS) proliferation, as the use of many DBMS products can cause confusion and hinder development activities. In this session, we discuss 1) lessons learned from 20 years of SQL to avoid mistakes of the past, 2) how to Unlock enterprise services via ESS eCRUD services, and 3) how to achieve increased security by consolidating data under standardized enterprise controls. View the Using NoSQL and Enterprise Shared Services (ESS) to Achieve a More Efficient and Agile IT Environment at the VA Transcript.

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MongoDB on Azure - Tips, Tricks and Examples

In this session we'll show you how MongoDB scales with Azure, including an introduction to our options for MongoDB-as-a-Service, options for different types of workloads, integration with other types of data, mobile services, Web sites and applications, and other tools and materials we've developed for MongoDB developers. Expect lots of working examples showing tips and tricks for building, deploying, connecting, and maintaining scalable multi-tier Web and mobile applications that access data, servers and services on Azure, including Linux Virtual Machines.

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Basic Ops Skills and Tools for Beginners

Your datastore, MongoDB, is likely critical to your project; if you're new to MongoDB or Ops and have to keep things running in production this is the talk for you. We will cover Ops with MongoDB from the ground up; which parts of servers you should monitor and why, and show how to take and test backups. Also, we'll run through different tools you can use for installing, running, and monitoring MongoDB. After this you should be comfortable with the basics of running MongoDB in production, as well as have a head start on what you should do next.

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MongoDB and Red Hat: Docker, geard, and OpenShift

Docker is an open-source engine that helps automate deployment of any process as a lightweight, portable, self-sufficient container that will run virtually anywhere. Come hear how Red Hat is adopting Docker in Red Hat Enterprise Linux 7 and Red Hat's Platform-as-a-Service OpenShift, and how MongoDB can leverage Docker for high-performance deployments.

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Replication Internals: The Life of a Write

Come to this session to learn about the internal workings of MongoDB replication and replica sets. We will track the lifetime of a replicated write: from the moment it enters the primary server, as it travels out to secondary servers, and finally as it is reflected back to the primary (in case the write has an associated write concern). In particular, we will discuss the techniques MongoDB uses to ensure correct write ordering on secondaries while still keeping up with the primary and servicing client reads as well. This is an advanced session intended for those who possess a basic understanding of MongoDB and general programming concepts.

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The Weather of the Century Part 3: Visualization

MongoDB natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. In this presentation, learn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.

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The Weather of the Century Part 1: Design Overview

The weather is everywhere and always. That makes for a lot of data. This talk will walk you through how you can use MongoDB to store and analyze worldwide weather data from the entire 20th century in a graphical application. We’ll discuss loading and indexing terabytes of data in a sharded cluster, and optimizing the schema design for interactive exploration.

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