


How to get all documents in an array that contain another document using MongoDB?
To do this, just use dot notation and find() in MongoDB. Let us create a collection containing documents -
> db.demo465.insertOne( ... { ... id: 101, ... details: [{ ... Name: "Chris", ... Info: { ... Subject: "MongoDB", ... Marks:67 ... } ... }, { ... Name: "David", ... Info: { ... Subject: "MySQL", ... Marks:78 ... } ... }] ... } ... ); { "acknowledged" : true, "insertedId" : ObjectId("5e80421bb0f3fa88e2279061") } > > db.demo465.insertOne( ... { ... id: 102, ... details: [{ ... Name: "Bob", ... Info: { ... Subject: "Java", ... Marks:45 ... } ... }, { ... Name: "Carol", ... Info: { ... Subject: "C", ... Marks:67 ... } ... }] ... } ... ); { "acknowledged" : true, "insertedId" : ObjectId("5e80421cb0f3fa88e2279062") }
Display all the documents in the collection with the help of find() method-
> db.demo465.find();
This will produce the following output-
{ "_id" : ObjectId("5e80421bb0f3fa88e2279061"), "id" : 101, "details" : [ { "Name" : "Chris", "Info" : { "Subject" : "MongoDB", "Marks" : 67 } }, { "Name" : "David", "Info" : { "Subject" : "MySQL", "Marks" : 78 } } ] } { "_id" : ObjectId("5e80421cb0f3fa88e2279062"), "id" : 102, "details" : [ { "Name" : "Bob", "Info" : { "Subject" : "Java", "Marks" : 45 } }, { "Name" : "Carol", "Info" : { "Subject" : "C", "Marks" : 67 } } ] }
The following is Query to get all documents in an array that contain another document -
> db.demo465.find({"details.Name":"Bob"});
This will produce the following output -
{ "_id" : ObjectId("5e80421cb0f3fa88e2279062"), "id" : 102, "details" : [ { "Name" : "Bob", "Info" : { "Subject" : "Java", "Marks" : 45 } }, { "Name" : "Carol", "Info" : { "Subject" : "C", "Marks" : 67 } } ] }
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MongoDB's scalability and performance considerations include horizontal scaling, vertical scaling, and performance optimization. 1. Horizontal expansion is achieved through sharding technology to improve system capacity. 2. Vertical expansion improves performance by increasing hardware resources. 3. Performance optimization is achieved through rational design of indexes and optimized query strategies.

MongoDB is a NoSQL database because of its flexibility and scalability are very important in modern data management. It uses document storage, is suitable for processing large-scale, variable data, and provides powerful query and indexing capabilities.

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Deploying a MongoDB cluster is divided into five steps: deploying the primary node, deploying the secondary node, adding the secondary node, configuring replication, and verifying the cluster. Including installing MongoDB software, creating data directories, starting MongoDB instances, initializing replication sets, adding secondary nodes, enabling replica set features, configuring voting rights, and verifying cluster status and data replication.

MongoDB is widely used in the following scenarios: Document storage: manages structured and unstructured data such as user information, content, product catalogs, etc. Real-time analysis: Quickly query and analyze real-time data such as logs, monitoring dashboard displays, etc. Social Media: Manage user relationship maps, activity streams, and messaging. Internet of Things: Process massive time series data such as device monitoring, data collection and remote management. Mobile applications: As a backend database, synchronize mobile device data, provide offline storage, etc. Other areas: diversified scenarios such as e-commerce, healthcare, financial services and game development.


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