AGGREGATE examples: Difference between revisions
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pp.pprint(list(db.world.aggregate([{"$match":{"area":{"$ne":0},"continent":"Asia"}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}}]))) | pp.pprint(list(db.world.aggregate([{"$match":{"area":{"$ne":0},"continent":"Asia"}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}}]))) | ||
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</div> | |||
<div class=q data-lang="py3"> | |||
<code>$sort</code> Allows us to choose how the results are displayed, where 1 is ascending and -1 is descending.<br/> | |||
<p class=strong>Show the name of all countries in descending order.</p>> | |||
</div> | |||
<pre class=def> | |||
pp.pprint(list( | |||
db.world.aggregate([ | |||
{"$project":{ | |||
"_id":0, | |||
"name":1, | |||
}}, | |||
("$sort":{ | |||
"name":1 | |||
}} | |||
]) | |||
)) | |||
</pre> | |||
<div class=ans> | |||
pp.pprint(list(db.world.aggregate([{"$project":{"_id":0,"name":1,}},("$sort":{"name":-1}}]))) | |||
</div> | </div> | ||
</div> | </div> |
Revision as of 16:04, 16 July 2015
#ENCODING import io import sys sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-16') #MONGO from pymongo import MongoClient client = MongoClient() client.progzoo.authenticate('scott','tiger') db = client['progzoo'] #PRETTY import pprint pp = pprint.PrettyPrinter(indent=4)
Introducing the aggregation framework
These examples introduce the aggregation framework and its operators. Again we will be using the collection world
$match
Allows us to perform queries in a similar way to find()
Show all the details for France
pp.pprint(list( db.world.aggregate([ {"$match":{"name":"France"}} ]) ))
pp.pprint(list(db.world.aggregate([{"$match":{"name":"France"}}])))
$project
Allows us to select what fields to display.
It can also has the ability to insert new fields and allows you 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 we do a $match
to remove any countries with negligible area, then pipe these results through to $project
pp.pprint(list( db.world.aggregate([ {"$match":{"area":{"$ne":0},"continent":"Asia"}}, {"$project":{ "_id":0, "name":1, "density": {"$divide": ["$population","$area"]} }} ]) ))
pp.pprint(list(db.world.aggregate([{"$match":{"area":{"$ne":0},"continent":"Asia"}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}}])))
$sort
Allows us to choose how the results are displayed, where 1 is ascending and -1 is descending.
Show the name of all countries in descending order.
>pp.pprint(list( db.world.aggregate([ {"$project":{ "_id":0, "name":1, }}, ("$sort":{ "name":1 }} ]) ))
pp.pprint(list(db.world.aggregate([{"$project":{"_id":0,"name":1,}},("$sort":{"name":-1}}])))