February 2019 Summaries

In MongoDB, the Subset Pattern is used to reduce the size of the working set by only bringing into memory a subset of the overall data. This is done by splitting large documents into smaller ones based on the most frequently accessed data. The idea is to store the most used part of the document in one collection and less frequently used data in another, allowing for shorter disk access times and reduced pressure on RAM capacities. By using this pattern, developers can improve performance and scalability of their applications.

The Computed Pattern` is a design pattern used to reduce CPU workload and increase application performance by computing values from data stored in a database, storing the results in a document, and avoiding redundant computations. It's particularly useful when there's a high read-to-write ratio and calculations need to be run against data, such as sums or time series data. By using this pattern, developers can optimize their applications and improve performance by offloading computations from the main application logic, allowing for faster page loads and improved user experience.

The Outlier Pattern is designed to prevent a few queries or documents from driving an application's solution towards one that would not be optimal for the majority of use cases. It involves adding a field to flag documents as outliers, allowing the application to handle them slightly differently, and leveraging MongoDB's flexible data model to optimize performance for typical documents or queries. This pattern is often used in situations where popularity is a factor, such as social network relationships, book sales, movie reviews, and video conferencing events, where large lists of attendees can be expected. The Outlier Pattern requires consideration of ad hoc queries and potential code maintenance over time.