How to Leverage Enriched Queries with MongoDB 6.0

MongoDB introduces useful new functions and features with every release, and MongoDB 6.0, released this summer, offers many notable improvements, including deeper insights from enriched queries via the MongoDB Query API.

This set of query enhancements was announced at MongoDB World 2022 by senior product manager Katya Kamenieva. You can watch her presentation below.

Users can now use upgraded operators and change stream features. In this post, we’ll look at several of these updates, along with examples of how you can put them to use.

Top N accumulators

With this new feature, users can compute top items in each group based on the sort criteria ($topN, $bottomN), current order of documents ($firstN, $lastN), or value of a field ($manX, $minN).

This functionality would be useful, for example, if you have a collection of restaurants with ratings, and you want to see the top three highest-rated restaurants based on the type of cuisine. You can group by cuisine and use $topN to return the top three restaurants by rating.

Ability to sort arrays

The ability to sort an array allows users to sort elements in the array. For example, suppose you have posted content with hundreds of user comments, and you want to sort the comments based on how many likes they received. In this case, $sortArray can pull those comments and prioritize them to the top of the comments list.

Densification and gap-filling

These new additions to the aggregation framework help to build out time series data more completely. When attempting to create histograms of data over time, the new stages, $denisfy and $fill, allow you to fill gaps in that data to create smoother and more complete graphs using linear interpolation, last/next observed value carried forward, or a constant value.

This capability can be helpful, for example, if you want to create a graph that shows the amount of inventory in a warehouse every day for a year, but the inventory was only recorded once a week. The $densify expression will fill the gaps in the timeline, while $fill will produce values for the inventory data based on the previous observation.

Joining sharded collections

With this new feature, when joining collections using $lookup or performing recursive search with $graphLookup, collections on both sides can be sharded. Before 6.0, only the originating collection could be sharded.

An example use case is enriching records in the “accounts” collection with the list of the corresponding orders that are stored in the “orders” collection. In the past, only “accounts” collections could be sharded. Starting with 6.0, both “accounts” and “orders” collections can be sharded.

Change streams pre- and post-images

Change streams now offer point-in-time (PIT) pre- and post-image capabilities, allowing users to include the state of the document before and after changes in the output of the change stream.

This functionality can be useful in many situations. For example, suppose a company is tracking flight times. If a flight is delayed, the system can compare the value of the departure and arrival times both before and after that delay and trigger an automatic rewrite of the schedule for the new flight timeline, including schedules for the entire crew.

Atlas Search across multiple collections

This improvement to MongoDB Atlas Search allows users to search across multiple collections with a single query using $search inside the $unionWith or $lookup stages. $search can provide these results quickly, using only one query.

Enriched queries are not the only improvements in MongoDB 6.0. Read about the 7 reasons to upgrade to MongoDB 6.0 and discover the possibilities.