Aggregation Builder

Overview

Sutido provides full support for MongoDB's aggregation framework, allowing you to write complex data processing pipelines directly in the query editor.

Writing Aggregation Pipelines

Use the standard aggregate() method with an array of pipeline stages:

db.orders.aggregate([
  { $match: { status: "completed" } },
  { $group: {
    _id: "$customerId",
    totalSpent: { $sum: "$amount" },
    orderCount: { $sum: 1 }
  }},
  { $sort: { totalSpent: -1 } },
  { $limit: 10 }
])

Common Pipeline Stages

$match

Filter documents, similar to find():

{ $match: { status: "active", amount: { $gt: 100 } } }

$project

Reshape documents, include or exclude fields:

{ $project: {
  name: 1,
  email: 1,
  fullName: { $concat: ["$firstName", " ", "$lastName"] }
}}

$group

Group documents and perform aggregations:

{ $group: {
  _id: "$category",
  count: { $sum: 1 },
  avgPrice: { $avg: "$price" },
  maxPrice: { $max: "$price" }
}}

$sort

Order the results:

{ $sort: { createdAt: -1 } }  // Descending
{ $sort: { name: 1 } }        // Ascending

$limit and $skip

Pagination:

{ $skip: 20 },
{ $limit: 10 }

$unwind

Flatten arrays into individual documents:

{ $unwind: "$items" }

// Preserve documents with empty/missing arrays
{ $unwind: { path: "$items", preserveNullAndEmptyArrays: true } }

$lookup

Join with another collection:

{ $lookup: {
  from: "products",
  localField: "productId",
  foreignField: "_id",
  as: "productDetails"
}}

Advanced Lookup with Pipeline

For more complex joins, use the pipeline form:

{ $lookup: {
  from: "inventory",
  let: { productId: "$_id" },
  pipeline: [
    { $match: {
      $expr: { $eq: ["$productId", "$$productId"] },
      inStock: true
    }},
    { $project: { quantity: 1, warehouse: 1 } }
  ],
  as: "stockInfo"
}}

$facet for Multiple Aggregations

Run multiple pipelines in parallel on the same input:

db.orders.aggregate([
  { $facet: {
    "totalRevenue": [
      { $group: { _id: null, sum: { $sum: "$total" } } }
    ],
    "byStatus": [
      { $group: { _id: "$status", count: { $sum: 1 } } }
    ],
    "recentOrders": [
      { $sort: { createdAt: -1 } },
      { $limit: 5 },
      { $project: { _id: 1, total: 1, createdAt: 1 } }
    ]
  }}
])

$bucket for Histograms

Group documents into ranges:

{ $bucket: {
  groupBy: "$price",
  boundaries: [0, 50, 100, 200, 500],
  default: "500+",
  output: {
    count: { $sum: 1 },
    products: { $push: "$name" }
  }
}}

Aggregation Options

Pass options as the second argument:

db.orders.aggregate(
  [
    { $match: { status: "completed" } },
    { $group: { _id: "$customerId", total: { $sum: "$amount" } } }
  ],
  {
    allowDiskUse: true,  // For large sorts
    maxTimeMS: 60000     // Timeout in milliseconds
  }
)

Autocomplete Support

The IntelliShell editor provides autocomplete for aggregation operators and field paths. Start typing $ inside a pipeline stage to see available operators.

Viewing Results

Aggregation results appear in the same result panel as regular queries. Use Table, JSON, or Tree view to inspect the output. The Document Inspector works with aggregation results too.

Next Steps

Learn about importing and exporting data.