Difference between revisions of "AGGREGATE examples"
| Line 1: | Line 1: | ||
| − | ==Introducing the | + | ==Introducing the <code>aggregate</code>== |
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> | ||
Revision as of 21:02, 1 April 2022
Introducing the aggregate
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
- _id - this determines the values to be grouped
- $continent and $population refers to keys 'continent' and 'population' available in each item
- $sum is a keyword
List the continents
db.world.aggregate(
{$group: {_id: "$continent"}, pop:{$sum:'$population'}}
);
$match performs queries in a similar way to find()
Show all the details for France
db.world.aggregate([
{$match: {name: "France"}}
]);
db.world.aggregate([{$match:{name:"France"}}]);
Return the first document
db.world.aggregate([
{$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
}}
]);