MongoDB command

The MongoDB Command step allows you to execute any MongoDB command using the db.command method.

With this step, you can leverage the full power of MongoDB commands to interact with your MongoDB database. You can perform advanced operations, run aggregation pipelines, execute complex queries, and take advantage of specialized features specific to MongoDB.

Make sure to use MongoDB Extended JSON (v2) in your queries to prevent issues with complex data types (for example, UUID or Date).

MongoDB command example

To run a MongoDB command, you simply need to select it in the action selection dropdown and provide the necessary parameters. UI Bakery will then execute the command using the db.command method behind the scenes.

In the example below, the find command retrieves documents from the users collection where the age field is greater than or equal to 30. The projection parameter specifies that only the name and age fields should be included in the result.

{
  find: "users",
  filter: { age: { $gte: 30 } },
  projection: { name: 1, age: 1 }
}

The Command Parameters field in this action step provides a familiar code editor interface allowing you to conveniently interact with the user interface and write JavaScript code, for example:

const minAge = +{{ui.input.value}}

return {
  find: "users",
  filter: { age: { $gte: minAge } },
  projection: { name: 1, age: 1 }
}

Sample: Filter by Date

If the MongoDB Date property is of the BSON type, then in order to be able to filter by Date you should send not the date itself but rather an object with the key &date inside the &lt, &gt, &gte operators. Below is an example of the code you can use:

{
 find: "orders",
 filter: {
   "created_at": {
     $gte: {
       $date: "2022-08-11T04:00:00+0400"
     }
   }
 },
   limit: 1000
}

Sample: Aggregate

To perform data aggregation, you can use the aggregate operation with the following parameters:

{
  aggregate: "users",
  pipeline: [
    { $match: { age: { $gte: 30 } } },
    { $group: { _id: "$status", count: { $sum: 1 } } }
  ],
  cursor: { batchSize: 10 }
}

In this example, the aggregation pipeline consists of several stages:

• $match to filter documents based on the age field

• $group to group documents by the status field and calculate the count

Sample: Join and aggregate

You can also use the aggregate command in MongoDB to perform complex aggregations on your data by combining multiple stages in a pipeline:

{
  aggregate: "users",
  pipeline: [
    { $match: { age: { $gte: 30 } } },
    { $lookup: { from: "orders", localField: "_id", foreignField: "userId", as: "user_orders" } },
    { $unwind: "$user_orders" },
    { $group: { _id: "$_id", total_orders: { $sum: 1 }, total_amount: { $sum: "$user_orders.amount" } } },
    { $sort: { total_amount: -1 } },
    { $limit: 10 }
  ],
  cursor: { batchSize: 10 }
}

In this query, we're performing the following operations:

1. $match - Filters the documents to include only those where the age is greater than or equal to 30.

2. $lookup - Joins the users collection with the orders collection based on the _id field of users and the userId field of orders. This creates an array called user_orders containing the matching orders for each user.

3. $unwind - Deconstructs the user_orders array creating separate documents for each order associated with a user.

4. $group - Groups the documents by _id (which is the unique identifier of the user) and calculates the total number of orders (total_orders) and the total amount of orders (total_amount) by summing up the amount field from the user_orders array.

5. $sort - Sorts the resulting documents in descending order based on the total_amount field.

6. $limit - Limits the result to a maximum of 10 documents.

This query performs a join and aggregation operation to find users aged 30 or above, counts their total number of orders, calculates the total amount of their orders, and sorts the results by the total order amount in descending order. Finally, it limits the result to the top 10 users with the highest total order amount.

Sample: Insert multiple documents

To insert multiple documents into a collection, use the insertMany command:

{
  insert: "users",
  documents: [
    { name: "John", age: 30 },
    { name: "Jane", age: 25 }
  ],
  ordered: false
}

This example inserts two documents into the collection. Each document specifies the name and age fields.

The insert command allows you to insert one or more documents into a collection. The ordered option is set to false to continue inserting the remaining documents even if an error occurs for any individual document.

Sample: Update multiple documents

To update multiple documents in a collection, use the update command:

{
  update: "users",
  updates: [
    { q: { age: { $gte: 30 } }, u: { $set: { status: "inactive" } }, multi: true }
  ]
}

This example updates all documents in the collection where the age is greater or equal to 30. The $set operator is used to set the status field to inactive.

The update command allows you to update one or more documents in a collection. The updates array contains the update operations, where each operation has:

• the q field for the query/filter

• the u field for the update

• the multi field set to true to update multiple documents

Sample: Delete multiple documents

To delete multiple documents from a collection, use the delete command:

{
  delete: "users",
  deletes: [
    { q: { status: "inactive" }, limit: 0 }
  ]
}

This example deletes all documents from the collection where the status field is inactive.

The delete command allows you to delete one or more documents in a collection. The deletes array contains the delete operations, where each operation has:

• the q field for the query/filter

• the limit field set to 0 to delete all matching documents

Sample: Find one and modify

The findAndModify command allows you to find a single document in your collection based on a filter condition and update it:

{
  findAndModify: "users",
  query: { name: "John" },
  update: { $set: { name: "John Doe", age: 40 } },
  new: true
}

This operation will find a document in the "users" table with the name "John" and update its age to 40 and name to John Doe.

The findAndModify command is used to atomically find and modify a document in a collection:

• the query field specifies the filter for the document to find

• the update field specifies the replacement document

• the new option set to true returns the modified document

UI Bakery supports MongoDB Extended JSON v2, so you can use the$oid notation. For example, if you need to find one item by id, you can do it in the following way:

{find: 'orders', filter: { id: {$oid: 'required_id'}}}