![MongoDB
{
By:
[
“Shirish Kulkarni”,
“Sagar Pol”
]
}](https://image.slidesharecdn.com/mongodbppt-230404172647-98b88135/85/MongoDB_ppt-pptx-1-320.jpg)
![Example of Document
> db.user.findOne({age:39})
{
"_id" : ObjectId("5114e0bd42…"),
"first" : "John",
"last" : "Doe",
"age" : 39,
"interests" : [
"Reading",
"Mountain Biking ]
"favorites": {
"color": "Blue",
"sport": "Soccer"}
}](https://image.slidesharecdn.com/mongodbppt-230404172647-98b88135/85/MongoDB_ppt-pptx-12-320.jpg)
![Aggregation Syntax
Basic syntax of aggregate() method is as follows −
db.COLLECTION_NAME.aggregate(AGGREGATE_OPERATION)
Example:
db.collection.aggregate([ {stage1}, {stage2}, {stage3}...])
• There is a set of possible stages and each of those is taken as a set of documents
as an input and produces a resulting set of documents (or the final resulting JSON
document at the end of the pipeline)](https://image.slidesharecdn.com/mongodbppt-230404172647-98b88135/85/MongoDB_ppt-pptx-17-320.jpg)
MongoDB_ppt.pptx
- 2. Why MongoDB? • MongoDB is a NoSQL (Not only SQL) database that stores large volumes of data in the form of documents. • MongoDB removes the concept of "rows" of conventional and relational data models by introducing “documents”. • MongoDB is more flexible and ensures high and diverse data availability.
- 3. When to use MongoDB? • You have lots of unstructured data. MongoDB (and NoSQL databases in general) has no storable data type limits. • You have schema issues. If you have an unstable or undefined schema, use MongoDB.
- 4. Features of MongoDB • Document-Oriented storage • Full Index Support • Replication & High Availability • Auto-Sharding • Querying Scalable
- 5. Document-oriented storage: • MongoDB is a document-oriented NoSQL database. It is used for storing massive volumes of data. Unlike a traditional SQL relational database, MongoDB does not rely on tables and columns. Data is stored as collections and documents. • Data is stored in BSON format internally and over the network but retrieved as JSON.
- 6. • Index is a way to organize information so that the database engine can quickly find the relevant results. • Indexes in MongoDB are similar to indexes in other database systems. MongoDB defines indexes at the collection level and supports indexes on any field or sub- field of the documents in a MongoDB collection. Full-index support:
- 7. • Replication is performed in MongoDB to maintain data redundancy and high availability. It is performed by creating multiple copies of your data across multiple servers. Replication and high availability:
- 8. • Sharding is a method for distributing or partitioning data across multiple machines. • It is useful when no single machine can handle large modern-day workloads, by allowing you to scale horizontally. Auto-Sharding:
- 9. Querying: • MongoDB Query is a way to get the data from the MongoDB database. • MongoDB queries provide the simplicity in process of fetching data from the database. • MongoDB provides the function names as db.collection_name.find() to operate query operation on database. • Database: Newspaper • Collection: Article • Query: db.article.find() // returns all the documents in the Article collection
- 11. Comparison of MongoDB with RDBMS RDBMS MongoDB Database Database Table, View Collection Row Document (JSON, BSON) Column Field Index Index Join Embedded Document Foreign Key Reference
- 12. Example of Document > db.user.findOne({age:39}) { "_id" : ObjectId("5114e0bd42…"), "first" : "John", "last" : "Doe", "age" : 39, "interests" : [ "Reading", "Mountain Biking ] "favorites": { "color": "Blue", "sport": "Soccer"} }
- 13. CRUD Operations • Create • db.collection.insert( <document> ) • db.collection.save( <document> ) • db.collection.update( <query>, <update>, { upsert: true } ) • Read • db.collection.find( <query>, <projection> ) • db.collection.findOne( <query>, <projection> ) • Update • db.collection.update( <query>, <update>, <options> ) • Delete • db.collection.remove( <query>, <justOne> )
- 14. CRUD Operations Example > db.user.insert({ first: "John", last : "Doe", age: 39 }) > db.user.findOne( { "_id" : ObjectId("51…"), }) > db.user.update( {"_id" : ObjectId("51…")}, { $set: { age: 40, salary: 7000} } ) > db.user.deleteOne({ “_id”: ObjectId(“6382er...”) })
- 15. Aggregation Functions • Aggregation operations process the data records/documents and return computed results. • It collects values from various documents and groups them together and then performs different types of operations on that grouped data like sum, average, minimum, maximum, etc to return a computed result. • the aggregation pipeline consists of stages and each stage transforms the document.
- 17. Aggregation Syntax Basic syntax of aggregate() method is as follows − db.COLLECTION_NAME.aggregate(AGGREGATE_OPERATION) Example: db.collection.aggregate([ {stage1}, {stage2}, {stage3}...]) • There is a set of possible stages and each of those is taken as a set of documents as an input and produces a resulting set of documents (or the final resulting JSON document at the end of the pipeline)
- 18. Stages Stages: Each stage starts from stage operators which are: •$match: It is used for filtering the documents can reduce the amount of documents that are given as input to the next stage. •$project: It is used to select some specific fields from a collection. •$sort: It is used to sort the document that is rearranging them •$limit: It is used to pass first n number of documents thus limiting them
- 20. THANK YOU