Could Someone help me out with the Guidance on MongoDB Aggregation Framework for Complex Queries?

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Hello there,

As I’m currently on a project that heavily relies on MongoDB as our primary database solution. While I have managed to get a grip on the basics of MongoDB querying, I have hit a bit of a roadblock when it comes to executing more intricate queries using the Aggregation Framework.

My main challenge lies in aggregating data from multiple collections, applying diverse stages like $lookup, $match, $group, and $project, and then performing calculations based on this aggregated data.

https://stackoverflow.com/questions/21818162/need-some-help-guidance-on-mongodb-aggregation-mapreduce-queriesinfo

I am reaching out to kindly ask if anyone here could offer some guidance or perhaps share examples on how to tackle these complex queries effectively using the Aggregation Framework.

I’m particularly interested in learning about best practices for optimizing performance and efficiency, especially with handling large datasets.

Also, if anyone could point me towards recommended resources, tutorials, or documentation that delve deeper into advanced MongoDB aggregation techniques, I would be grateful.

Thankyou in advance.

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Start at https://learn.mongodb.com/

and

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Try to avoid lookups if possible. Try to do as much of a match in your first stage and make sure that you are hitting an index with that match. Avoid $or queries in favor of $in queries. Run explain early to make sure your index is being used and try to reduce the amount of documents scanned so your scan:return ratio is low.

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Hi Elija,

Thanks for posting here. I’ve been looking at your question (and the answers) in Stack Overflow and I think the last one is quite good.

I’ll add that in your data you store Latitudes and Longitudes but it’ll be better to store them as GeoJSON Points. You can use an aggregation pipeline to transform your data and then use $merge to write the data back to a collection with a different name than the original one. Then you can check the data and see if it’s what you need. Finally, you can delete the old collection and rename the new one.

In terms of resources, the main three ones are:

Hope this helps!