78 lines
2.6 KiB
ReStructuredText
78 lines
2.6 KiB
ReStructuredText
Aggregation Examples
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====================
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There are several methods of performing aggregations in MongoDB. These
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examples cover the new aggregation framework, using map reduce and using the
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group method.
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.. testsetup::
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from pymongo import MongoClient
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client = MongoClient()
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client.drop_database('aggregation_example')
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Setup
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-----
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To start, we'll insert some example data which we can perform
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aggregations on:
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.. doctest::
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>>> from pymongo import MongoClient
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>>> db = MongoClient().aggregation_example
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>>> result = db.things.insert_many([{"x": 1, "tags": ["dog", "cat"]},
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... {"x": 2, "tags": ["cat"]},
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... {"x": 2, "tags": ["mouse", "cat", "dog"]},
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... {"x": 3, "tags": []}])
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>>> result.inserted_ids
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[ObjectId('...'), ObjectId('...'), ObjectId('...'), ObjectId('...')]
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.. _aggregate-examples:
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Aggregation Framework
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---------------------
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This example shows how to use the
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:meth:`~pymongo.collection.Collection.aggregate` method to use the aggregation
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framework. We'll perform a simple aggregation to count the number of
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occurrences for each tag in the ``tags`` array, across the entire collection.
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To achieve this we need to pass in three operations to the pipeline.
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First, we need to unwind the ``tags`` array, then group by the tags and
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sum them up, finally we sort by count.
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As python dictionaries don't maintain order you should use :class:`~bson.son.SON`
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or :class:`collections.OrderedDict` where explicit ordering is required
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eg "$sort":
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.. note::
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aggregate requires server version **>= 2.1.0**.
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.. doctest::
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>>> from bson.son import SON
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>>> pipeline = [
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... {"$unwind": "$tags"},
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... {"$group": {"_id": "$tags", "count": {"$sum": 1}}},
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... {"$sort": SON([("count", -1), ("_id", -1)])}
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... ]
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>>> import pprint
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>>> pprint.pprint(list(db.things.aggregate(pipeline)))
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[{'_id': 'cat', 'count': 3},
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{'_id': 'dog', 'count': 2},
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{'_id': 'mouse', 'count': 1}]
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To run an explain plan for this aggregation use the
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:meth:`~pymongo.database.Database.command` method::
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>>> db.command('aggregate', 'things', pipeline=pipeline, explain=True)
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{'ok': 1.0, 'stages': [...]}
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As well as simple aggregations the aggregation framework provides projection
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capabilities to reshape the returned data. Using projections and aggregation,
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you can add computed fields, create new virtual sub-objects, and extract
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sub-fields into the top-level of results.
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.. seealso:: The full documentation for MongoDB's `aggregation framework
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<http://mongodb.com/docs/manual/applications/aggregation>`_
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