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Difference between revisions of "AGGREGATE examples"

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These examples introduce the aggregation framework and its operators. Again we will be using the '''world''' collection.
 
These examples introduce the aggregation framework and its operators. Again we will be using the '''world''' collection.
 
<div class='extra_space' style='width:1em; height:6em;'></div>
 
<div class='extra_space' style='width:1em; height:6em;'></div>
 +
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<div class="q" data-lang="mongo">
 +
'''$group''' allows you to collect group items that share common features
 +
<p class="strong">List the continents</p>
 +
<pre class="def"><nowiki>
 +
db.world.aggregate([
 +
    {$group: {_id: "$continent"}}
 +
]);</nowiki></pre>
 +
<pre class="ans"><nowiki>db.world.aggregate([{$group:{_id:"$continent"}}]);</nowiki></pre>
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</div>
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<div class="q" data-lang="mongo">
 
<div class="q" data-lang="mongo">

Revision as of 08:49, 14 May 2021

Introducing the aggregation framework

These examples introduce the aggregation framework and its operators. Again we will be using the world collection.

$group allows you to collect group items that share common features

List the continents

db.world.aggregate([
    {$group: {_id: "$continent"}}
]);
db.world.aggregate([{$group:{_id:"$continent"}}]);


$match performs queries in a similar way to find()

Show all the details for France

db.world.aggregate([
    {$match: {name: "France"}}
]);
db.world.aggregate([{$match:{name:"France"}}]);
$limit sets the amount of documents to be handed to the next stage in the pipeline.

Return the first document

db.world.aggregate([
    {$limit: 1}
]);
db.world.aggregate([{"$limit":1}]);

$project selects what fields to display.
It can also has the ability to create new fields and to compare fields against each other without using $where

Show the name and population density of all Asian countries. (population/area)

Note that "density" is a new field made from the result of dividing two existing fields, and that $divide is an aggregate function.

To avoid diving by 0 insert a $match to remove any countries with no area (Vatican City), then pipe these results through to $project
There is no need to check if values are null, MongoDB will ignore these documents.

db.world.aggregate([
    {$match: {area: {$ne: 0}, continent: "Asia"}},
    {$project: {
        _id: 0,
        name: 1,
        density: {$divide: ["$population", "$area"]}
    }}
]);
db.world.aggregate([{"$match":{"area":{"$ne":0},"continent":"Asia"}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}}]);

Because aggregate is a pipeline stages may be repeated, and stages don't have to be used in a specific order.

Show the name of Asian countries with a density that's over 500 people per km2. (population/area)

db.world.aggregate([
   {$match: {area: {$ne: 0}, continent: "Asia"}},
   {$project: {
       _id: 0,
       name: 1,
       density: {$divide: ["$population", "$area"]}
   }},
   {$match: {density: {$gt: 500}}}
]);
db.world.aggregate([{"$match":{"area":{"$ne":0},"continent":"Asia"}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}},{"$match":{"density":{"$gt":500}}}]);

$sort allows ordering of the results set, where 1 is ascending and -1 is descending.
Note that not including $match is the same as {"$match":{}}

Show the name of all countries in descending order.

db.world.aggregate([
    {"$project":{
        "_id":0,
        "name":1,
    }},
    {"$sort":{
        "name":-1
    }}  
]);
db.world.aggregate([{"$project":{"_id":0,"name":1,}},{"$sort":{"name":-1}}])

Grouping

Grouping provides accumulator operations such as $sum
All groups must have an _id. To see why this is useful imagine the following:

So far you've been using the world collection
As every country has a continent, it would make sense to have countries as a nested document inside continents: e.g:

[    
    {"name": "Africa",
     "countries": [
         {"name": "Algeria",     "capital": "Algiers",    ...},
         {"name": "Angola",      "capital": "Luanda",     ...},
         {"name": "Benin",       "capital": "Porto-Novo", ...}.
         {...},
         ...
    ]},
    {"name": "Asia",
     "countries": [
         {"name": "Afghanistan", "capital": "Kabul",  ...},
         {"name": "Azerbaijan",  "capital": "Baku",   ...},
         {"name": "Bahrain",     "capital": "Manama", ...},
         {...},
         ...
    ]},
    {...},
    ...
]

The world collection isn't like this however. It uses the following structure, which has a redundancy where continent is repeated for each country.

[ 
    {"name": "Afghanistan", "capital": "Kabul",   "continent": "Asia",   ...},
    {"name": "Albania",     "capital": "Tirana",  "continent": "Europe",  ...},
    {"name": "Algeria",     "capital": "Algiers", "contiennt": "Africa", ...},
    {...},
    ...
]

The code to group by continent is "_id":"$continent"
If instead the question was to group by country the code would be "_id": "$name".
To operate over the whole document (which would have the same effect as "_id": "$name") "_id": "null" or "_id": None can be used.

group operators

$max and $min can be used to get the largest and smallest values in a group.

Get the smallest and largest GDPs of each continent.

db.world.aggregate([
    {$group: {
        _id: '$continent',
        min: {$min: "$gdp"},
        max: {$max: "$gdp"}
    }},
    {$project: {
        _id: 1,
        min: 1,
        max: 1
    }}
]);
db.world.aggregate([{"$group":{'_id':'$continent','min':{"$min":"$gdp"},'max':{"$max":"$gdp"}}},{"$project":{"_id":1,"min":1,"max":1}}]);

Some other useful aggregate functions to know are $sum and average: $avg
The example below combines previous example material.

Order the continents in descending order by total GDP, Include the average GDP for each country.

db.world.aggregate([
    {$match: {}},
    {$group: {
        _id:"$continent",
        "Total GDP": {"$sum": "$gdp"},
        "Average GDP": {"$avg": "$gdp"}
    }},
    {$sort: {
        "Total GDP":-1
    }},
    {$project:{
        "Area": "$_id",
        "Total GDP": 1,
        "Average GDP": 1,
        _id: 0
    }}
]);
db.world.aggregate([{"$group":{"_id":"$continent","Total GDP":{"$sum":"$gdp"},"Average GDP":{"$avg":"$gdp"}}},{"$sort":{"Total GDP":-1}},{"$project":{"Area":"$_id","Total GDP":1,"Average GDP":1,"_id":0}}]);

Using Conditions

$cond is similar to a CASE statement in other languages.
It has the form "$cond": [{<comparison>: [<field or value>, <field or value>]}, <true case>, <false case>]

db.world.aggregate([
    {$group: {
        _id: {
            $cond: [{"$eq": ["$continent", "Eurasia"]}, "Europe", "$continent"]
        },
        area: {$sum: "$area"}
    }},
    {$sort: {
        area: -1
    }},
    {$project: {
        _id: 1,
        area: 1
    }}
]);