Become MongoDB Certified with updated Associate-Data-Modeler exam questions and correct answers
When designing a MongoDB schema for an application that tracks user activities and their corresponding locations, which approach best facilitates efficient data retrieval and updates?
In MongoDB, how should the analysis of query and analytics patterns influence the decision on indexing strategies, particularly with respect to the operational context of queries being part of a transaction?
In a blogging application, the main entity Article contains text, a title, and metadata. Each article can have multiple comments made by users. The application frequently retrieves an article along with all its comments for display. How should the developer optimize the schema for read performance?
A data modeler is tasked with enhancing query efficiency for the salesRecords collection. Considering the queries:
db.salesRecords.find({"productId": 15}).sort({"saleDate": -1, "quantity": 1})
and
db.salesRecords.find({"saleDate": {"$gte": ISODate("2023-06-01")}}).sort({"productId": 1, "quantity": -1})
which indexing strategy would be most effective in improving response times for both queries?
In a MongoDB database, the events collection stores documents related to various events with fields like eventId, title, location, and date. The schema needs to be updated to support a new tags array field, which will store keywords related to each event. What is the most effective way to introduce this change, ensuring backward compatibility and minimal disruption to the existing application?
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