Aggregation

Analogy

Aggregation operations function similarly to car factories with assembly lines. The assembly lines have stations with specialized tools to perform specific tasks. For example, when building a car, the assembly line begins with the frame. Then, as the car frame moves through the assembly line, each station assembles a separate part. The result is a transformed final product, the finished car.

The assembly line represents the aggregation pipeline, the individual stations represent the aggregation stages, the specialized tools represent the expression operators, and the finished product represents the aggregated result.

Age Insights by Genre

The following example calculates the average, minimum, and maximum age of users interested in each genre.

The aggregation pipeline contains the following stages:

• An $unwind stage to separate each array entry in the genre_interests field into a new document.

• A $group stage to group documents by the value of the genre_interests field. This stage finds the average, minimum, and maximum user age by using the $avg, $min, and $max operators.

let age_pipeline = vec![
    doc! { "$unwind": doc! { "path": "$genre_interests" } },
    doc! { "$group": doc! {
        "_id": "$genre_interests",
        "avg_age": doc! { "$avg": "$age" },
        "min_age": doc! { "$min": "$age" },
        "max_age": doc! { "$max": "$age" }
    } }
];
let mut results = my_coll.aggregate(age_pipeline).await?;
while let Some(result) = results.try_next().await? {
    println!("* {:?}", result);
}

* { "_id": "memoir", "avg_age": 25.8, "min_age": 18, "max_age": 39 }
* { "_id": "sci-fi", "avg_age": 42, "min_age": 18, "max_age": 66 }
* { "_id": "fiction", "avg_age": 33.333333333333336, "min_age": 16, "max_age": 66 }
* { "_id": "nonfiction", "avg_age": 53.5, "min_age": 31, "max_age": 76 }
* { "_id": "self help", "avg_age": 56, "min_age": 56, "max_age": 56 }
* { "_id": "poetry", "avg_age": 39, "min_age": 39, "max_age": 39 }
* { "_id": "literary", "avg_age": 49.5, "min_age": 21, "max_age": 76 }
* { "_id": "fantasy", "avg_age": 34.666666666666664, "min_age": 18, "max_age": 66 }
* { "_id": "mystery", "avg_age": 24.666666666666668, "min_age": 20, "max_age": 31 }
* { "_id": "theory", "avg_age": 33, "min_age": 21, "max_age": 45 }
* { "_id": "art", "avg_age": 39, "min_age": 39, "max_age": 39 }
* { "_id": "sports", "avg_age": 22.5, "min_age": 16, "max_age": 29 }

Group by Time Component

The following example finds how many users were last active in each month.

The aggregation pipeline contains the following stages:

• $project stage to extract the month from the last_active field as a number into the month_last_active field

• $group stage to group documents by the month_last_active field and count the number of documents for each month

• $sort stage to set an ascending sort on the month

let last_active_pipeline = vec![
    doc! { "$project": { "month_last_active" : doc! { "$month" : "$last_active" } } },
    doc! { "$group": doc! { "_id" : doc! {"month_last_active": "$month_last_active"} ,
    "number" : doc! { "$sum" : 1 } } },
    doc! { "$sort": { "_id.month_last_active" : 1 } }
];
let mut results = my_coll.aggregate(last_active_pipeline).await?;
while let Some(result) = results.try_next().await? {
    println!("* {:?}", result);
}

* { "_id": { "month_last_active": 1 }, "number": 3 }
* { "_id": { "month_last_active": 5 }, "number": 4 }
* { "_id": { "month_last_active": 6 }, "number": 1 }
* { "_id": { "month_last_active": 7 }, "number": 1 }
* { "_id": { "month_last_active": 8 }, "number": 2 }
* { "_id": { "month_last_active": 11 }, "number": 1 }

Calculate Popular Genres

The following example finds the three most popular genres based on how often they appear in users' interests.

The aggregation pipeline contains the following stages:

• $unwind stage to separate each array entry in the genre_interests field into a new document

• $group stage to group documents by the genre_interests field and count the number of documents for each genre

• $sort stage to set a descending sort on the genre popularity

• $limit stage to show only the first three genres

let popularity_pipeline = vec![
    doc! { "$unwind" : "$genre_interests" },
    doc! { "$group" : doc! { "_id" : "$genre_interests" , "number" : doc! { "$sum" : 1 } } },
    doc! { "$sort" : doc! { "number" : -1 } },
    doc! { "$limit": 3 }
];
let mut results = my_coll.aggregate(popularity_pipeline).await?;
while let Some(result) = results.try_next().await? {
    println!("* {:?}", result);
}

* { "_id": "fiction", "number": 6 }
* { "_id": "memoir", "number": 5 }
* { "_id": "literary", "number": 4 }

API Documentation

To learn more about the methods and types mentioned in this guide, see the following API documentation:

• aggregate()

• AggregateOptions