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Mongodb join8/11/2023 ![]() Remember that one of the key advantages of MongoDb is faster performance with unstructured data.the irony. Remember that a $lookup operation comes with the cost of performing a JOIN operation on your collections. While it's good that $lookup exists in MongoDb, it goes against every reason why you would use MongoDB vs another relational datastore (MySQL). Remember that $lookup can be used for both equality checks (first example) as well as more complex sub-queries (second example).ĭepending on which type of query you run, $lookup will take slightly different parameters (let, pipeline vs localField, foreignField).įor more on the aggregation pipeline, be sure to check out this 5 minute guide to the MongoDB aggregation framework. You've now seen two examples of using $lookup in the aggregation pipeline. This query adds an additional condition for returning comments whose likes count is greater than the corresponding post's likes.īy running this query, we now know if any posts have comments with more likes than the post itself :). Like the first example, this query returns the comments whose postTitle matches the title field for each post. We reference fields in the foreign collection with a single $. ![]() Notice how we use $$ to refer to the variables we defined in let. ![]() The examples are based on this sample data. We'll provide an example of each scenario. $lookup supports both basic equality matches as well as uncorrelated sub-queries. $lookup works by returning documents from a "joined" collection as a sub-array of the original collection. $lookup allows you to perform joins on collections in the same database. Joins can be a tough topic to wrap your mind around so we hope that this tutorial helped you understand how to do joins in MongoDB and apply it to your specific application.Preface: New to the aggregation pipeline? Check out our 5 minute explanation before diving into these $lookup examples.Īlso be sure to understand indexing and it's performance implications before reviewing these examples. We were able to join our users collection and with our comments collection with an aggregation method that resulted in a set that showed us every comment made by every user. ![]() In this tutorial we joined two collections in MongoDB that had a many-to-one relationship. You’ll notice that Al our user with userId = 1, has two comments in the combined field which means this kind of join works on many-to-one relationships. I enjoyed reading your website."Īs you can see we were returned our initial users collection but it now has a combined field which contains every comment made by the user. "comment" : "Hi, I'm Al and I love comments." Use the aggregate() method with the $lookup stage. As you can see in our dataset there is a common field userId on both collections which allows us to match up each user with their comments. ![]()
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