6.1 Aggregation framework overview

A call to the aggregation framework defines a pipeline , the aggregation pipeline, where the output from each step in the pipeline provides input to the next step. Each step executes a single operation on the input documents to transform the input and generate output documents.

  • $project: specify fields to be placed in the output document
  • $match
  • $limit
  • $skip
  • $unwind
  • $group
  • $sort
  • $geoNear:Select documents near a geospatial location
  • $out
  • $redact: Control access to certain data

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  1. db.products.aggregate([ {$match: …}, {$group: …}, {$sort: …} ] )

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a detailed comparison of SQL commands to the aggregation framework operators
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6.2 E-commerce aggregation example

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6.2.1 Products, categories, and reviews

an example of counting the number of reviews for a given product using this query:

  1. product = db.products.findOne({'slug': 'wheelbarrow-9092'})
  2. reviews_count = db.reviews.count({'product_id': product['_id']})

how to do this using the aggregation framework

  1. db.reviews.aggregate([
  2.   {$group : { _id:'$product_id',        // Group the input documents by product_id
  3.               count:{$sum:1} }}            // Count the number of reviews for each product
  4. ]);

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add one more operator to your pipline so that you select only the one product you want to get a count for:

  1. product = db.products.findOne({'slug': 'wheelbarrow-9092'})
  3. ratingSummary = db.reviews.aggregate([
  4.   {$match : { product_id: product['_id']} },        // Select only a single product
  5.   {$group : { _id:'$product_id',                                
  6.               count:{$sum:1} }}
  7. ]).next();                                                                            // Return the first document in the results

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Calculating the average review

  1. product = db.products.findOne({'slug': 'wheelbarrow-9092'})
  3. ratingSummary = db.reviews.aggregate([
  4.   {$match : {'product_id': product['_id']}},
  5.   {$group : { _id:'$product_id',
  6.               average:{$avg:'$rating'},            // Calculate the average rating for a product
  7.               count: {$sum:1}}}
  8. ]).next();

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Counting reviews by rating

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  1. countsByRating = db.reviews.aggregate([
  2.     {$match : {'product_id': product['_id']}},        // Select product
  3.     {$group : { _id:'$rating',                                        // Group by value of rating: '$rating'
  4.           count:{$sum:1}}}                                                // Count number of reviews for each rating
  5. ]).toArray();                                                                            // Convert resulting cursor to an array

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Joining collections

  1. db.mainCategorySummary.remove({});        // Remove existing documents from mainCategorySummary collection
  3. db.products.aggregate([
  4.   {$group : { _id:'$main_cat_id',
  5.               count:{$sum:1}}}
  6.   ]).forEach(function(doc){
  7.           var category = db.categories.findOne({_id:doc._id});              // Read category for a result
  8.           if (category !== null) {                                                                        // You aren't guaranteed the category actually exists!
  9.               doc.category_name = category.name;
  10.           }
  11.           else {
  12.               doc.category_name = 'not found';
  13.           }
  14.           db.mainCategorySummary.insert(doc);            // Insert cominned result into your summary collection
  15. })

$out and $project

With the $out operator, you can automatically save the output from a pipeline into a collection. 

  1. db.products.aggregate([
  2.   {$group : { _id:'$main_cat_id',
  3.               count:{$sum:1}}},
  4.   {$out : 'mainCategorySummary'}        // Save pipeline results to collection mainCategorySummary
  5.  ])

The $project operator allows you to filter which fields will be passed to the next stage of the pipeline.
Although $match allows you to limit how much data is passed to the next stage by limiting the number of documents passed, $project can be used to limit the size of each document passed to the next stage.

The following is an example of a $project operator that limits the output documents to just the list of category IDs used for each product: 

  1. db.products.aggregate([
  2.  {$project : {category_ids:1}}
  3. ]);

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Faster joins with $unwind

  1. db.products.aggregate([
  2.   {$project : {category_ids:1}},
  3.   {$unwind : '$category_ids'},                // Create an output document for every array entry in category_ids
  4.   {$group : { _id:'$category_ids',
  5.               count:{$sum:1}}},
  6.   {$out : 'countsByCategory'}
  7. ]);

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6.2.2 User and order