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website/versioned_docs/version-v1.14/aggregation-operations/_category_.yml
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| --- | ||
| label: Aggregation Operations | ||
| position: 6 | ||
| link: | ||
| type: generated-index | ||
| slug: /aggregation-operations/ | ||
| description: > | ||
| This section details aggregation operations in FerretDB, including aggregation commands, stages, and operators |
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..._docs/version-v1.14/aggregation-operations/aggregation-pipeline-and-commands.md
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| --- | ||
| sidebar_position: 1 | ||
| --- | ||
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| # Aggregation pipeline and commands | ||
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| Aggregation operations involve performing various operations on a large number of data records, such as data grouping, sorting, restructuring, or modifying. | ||
| These operations pass through one or more stages, which make up a pipeline. | ||
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|  | ||
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| Each stage acts upon the returned documents of the previous stage, starting with the input documents. | ||
| As shown above, the documents pass through the pipeline with the result of the previous stage acting as input for the next stage, going from `$match` => `$group` => `$sort` stage. | ||
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| For example, insert the following documents in a `sales` collection: | ||
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| ```js | ||
| db.sales.insertMany([ | ||
| { _id: 1, category: 'Electronics', price: 1000 }, | ||
| { _id: 2, category: 'Electronics', price: 800 }, | ||
| { _id: 3, category: 'Clothing', price: 30 }, | ||
| { _id: 4, category: 'Clothing', price: 50 }, | ||
| { _id: 5, category: 'Home', price: 1500 }, | ||
| { _id: 6, category: 'Home', price: 1200 }, | ||
| { _id: 7, category: 'Books', price: 20 }, | ||
| { _id: 8, category: 'Books', price: 40 } | ||
| ]) | ||
| ``` | ||
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| A typical aggregation pipeline would look like this: | ||
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| ```js | ||
| db.sales.aggregate([ | ||
| { $match: { category: { $ne: 'Electronics' } } }, | ||
| { | ||
| $group: { | ||
| _id: '$category', | ||
| totalPrice: { $sum: '$price' }, | ||
| productCount: { $sum: 1 } | ||
| } | ||
| }, | ||
| { $sort: { totalPrice: -1 } } | ||
| ]) | ||
| ``` | ||
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| In the pipeline, the complex query is broken down into separate stages where the record goes through a series of transformations until it finally produces the desired result. | ||
| First, the `$match` stage filters out all documents where the `category` field is not `Electronics`. | ||
| Then, the `$group` stage groups the documents by their `category` and calculates the total price and product count for each of those category. | ||
| Finally, the `$sort` stage sorts the documents by the `totalPrice` field in descending order. | ||
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| So the above aggregation pipeline operation would return the following result: | ||
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| ```json5 | ||
| [ | ||
| { _id: 'Home', totalPrice: 2700, productCount: 2 }, | ||
| { _id: 'Clothing', totalPrice: 80, productCount: 2 }, | ||
| { _id: 'Books', totalPrice: 60, productCount: 2 } | ||
| ] | ||
| ``` | ||
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| This section of the documentation will focus on [`aggregate` command](#aggregate-command), [aggregation stages](aggregation-stages.md), and aggregation operators. | ||
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| ## `aggregate` command | ||
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| The aggregation command `aggregate` is a top-level command used for aggregating data across various pipeline stages. | ||
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| The command is used for performing aggregation operations on a collection and lets you specify aggregation operations in a pipeline consisting of one or more stages and operators for transforming and analyzing data, such as grouping, filtering, sorting, projecting, and calculating aggregates. | ||
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| ```js | ||
| // Aggregation pipeline to perform aggregation operations on a collection | ||
| db.collection.aggregate([ | ||
| // Stage 1: Matching documents based on a specific field and value | ||
| { $match: { field: value } }, | ||
| // Stage 2: Grouping documents by the "category" field and calculating the sum of the "quantity" field | ||
| { $group: { _id: '$category', total: { $sum: '$quantity' } } } | ||
| ]) | ||
| ``` |
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website/versioned_docs/version-v1.14/aggregation-operations/aggregation-stages.md
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| --- | ||
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| --- | ||
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| # Aggregation stages | ||
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| Aggregation stages are a series of one or more processes in a pipeline that acts upon the returned result of the previous stage, starting with the input documents. | ||
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| | Supported aggregation stages | Description | | ||
| | ---------------------------- | ----------------------------------------------------------------------------------------------------- | | ||
| | `$count` | Returns the count of all matched documents in a specified query | | ||
| | `$group` | Groups documents based on specific value or expression and returns a single document for each group | | ||
| | `$limit` | Limits specific documents and passes the rest to the next stage | | ||
| | `$match` | Acts as a `find` operation by only returning documents that match a specified query to the next stage | | ||
| | `$project` | Specifies the fields in a document to pass to the next stage in the pipeline | | ||
| | `$skip` | Skips a specified `n` number of documents and passes the rest to the next stage | | ||
| | `$sort` | Sorts and returns all the documents based on a specified order | | ||
| | `$unset` | Specifies the fields to be removed/excluded from a document | | ||
| | `$unwind` | Deconstructs and returns a document for every element in an array field | |
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website/versioned_docs/version-v1.14/basic-operations/_category_.yml
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| --- | ||
| label: Basic CRUD Operations | ||
| position: 4 | ||
| link: | ||
| type: generated-index | ||
| slug: /basic-operations/ | ||
| description: > | ||
| Perform basic CRUD operations using FerretDB |
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website/versioned_docs/version-v1.14/basic-operations/create.md
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| --- | ||
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| # Insert operation | ||
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| The insert operation adds a new document to a collection. | ||
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| ## Insert a single document | ||
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| The `insertOne()` command is used to add a single document into a collection, using this syntax format: | ||
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| ```js | ||
| db.collection.insertOne({field1: value1, field2: value2,.... fieldN: valueN}) | ||
| ``` | ||
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| The example below depicts how a single document can be added to a collection. | ||
| If a collection does not exist, the insert command automatically creates one. | ||
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| ```js | ||
| db.scientists.insertOne({ | ||
| name: { | ||
| firstname: 'Thomas', | ||
| lastname: 'Edison' | ||
| }, | ||
| born: 1847, | ||
| invention: 'lightbulb' | ||
| }) | ||
| ``` | ||
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| If the operation is successful, you will get a response with acknowledged set to true, and the autogenerated ObjectId of the document that looks like this: | ||
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| ```js | ||
| { | ||
| acknowledged: true, | ||
| insertedId: ObjectId("6346fcafd7a4a1b0b38eb2db") | ||
| } | ||
| ``` | ||
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| ## Insert multiple documents at once | ||
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| A collection can contain multiple documents. | ||
| Using the `insertMany()` command, you can add multiple documents to a collection at once. | ||
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| ```js | ||
| db.collection_name.insertMany([{ document1 }, { document2 }, ...{ documentN }]) | ||
| ``` | ||
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| The following example shows how to insert multiple documents into a collection: | ||
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| ```js | ||
| db.scientists.insertMany([ | ||
| { | ||
| name: { | ||
| firstname: 'Alan', | ||
| lastname: 'Turing' | ||
| }, | ||
| born: 1912, | ||
| invention: 'Turing Machine' | ||
| }, | ||
| { | ||
| name: { | ||
| firstname: 'Graham', | ||
| lastname: 'Bell' | ||
| }, | ||
| born: 1847, | ||
| invention: 'telephone' | ||
| }, | ||
| { | ||
| name: { | ||
| firstname: 'Ada', | ||
| lastname: 'Lovelace' | ||
| }, | ||
| born: 1815, | ||
| invention: 'computer programming' | ||
| } | ||
| ]) | ||
| ``` | ||
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| You can retrieve all the documents in the collection with this command: `db.scientists.find({})` |
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website/versioned_docs/version-v1.14/basic-operations/delete.md
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| --- | ||
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| --- | ||
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| # Delete operation | ||
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| The delete operation removes a document from the database when a given query is met. | ||
| Two methods for deleting documents in a collection include `deleteOne()` and `deleteMany()`. | ||
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| ## Delete a single document | ||
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| The `deleteOne()` method removes a single document (the first document that matches the query parameter) completely from the collection. | ||
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| ```js | ||
| db.collection.deleteOne({<query_params>}) | ||
| ``` | ||
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| Insert the following list of documents: | ||
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| ```js | ||
| db.scientists.insertMany([ | ||
| { | ||
| firstname: 'Thomas', | ||
| lastname: 'Edison', | ||
| born: 1847, | ||
| invention: 'LightBulb', | ||
| nobel: true | ||
| }, | ||
| { | ||
| firstname: 'Graham', | ||
| lastname: 'Bell', | ||
| born: 1847, | ||
| invention: 'telephone', | ||
| nobel: false | ||
| }, | ||
| { | ||
| firstname: 'Nikola', | ||
| lastname: 'Tesla', | ||
| born: 1856, | ||
| invention: 'Tesla coil', | ||
| nobel: false | ||
| }, | ||
| { | ||
| firstname: 'Ada', | ||
| lastname: 'Lovelace', | ||
| born: 1815, | ||
| invention: 'Computer programming', | ||
| nobel: false | ||
| } | ||
| ]) | ||
| ``` | ||
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| This operation returns a response showing `acknowledged` as `true` and the `ObjectId` of the four inserted documents: | ||
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| ```js | ||
| { | ||
| acknowledged: true, | ||
| insertedIds: { | ||
| '0': ObjectId("63470121d7a4a1b0b38eb2df"), | ||
| '1': ObjectId("63470121d7a4a1b0b38eb2e0"), | ||
| '2': ObjectId("63470121d7a4a1b0b38eb2e1"), | ||
| '3': ObjectId("63470121d7a4a1b0b38eb2e2") | ||
| } | ||
| } | ||
| ``` | ||
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| Next, delete a document from the collection where the field `nobel` is set to false. | ||
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| ```js | ||
| db.scientists.deleteOne({ nobel: false }) | ||
| ``` | ||
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| This operation returns a response that shows that a single document was deleted from the collection. | ||
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| ```js | ||
| { acknowledged: true, deletedCount: 1 } | ||
| ``` | ||
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| ## Deletes multiple documents | ||
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| To delete multiple documents at once, use the `deleteMany()` method. | ||
| Using the same record from earlier, let's delete all the documents with `nobel` set to false. | ||
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| ```js | ||
| db.scientists.deleteMany({ nobel: false }) | ||
| ``` | ||
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| This command removes all the documents in the collection that matches the query. |
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