Indexing in MongoDB using Python
Last Updated :
16 Jun, 2022
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By creating indexes in a MongoDB collection, query performance is enhanced because they store the information in such a manner that traversing it becomes easier and more efficient. There is no need for a full scan as MongoDB can search the query through indexes. Thus it restricts the number of documents that need to be checked for query criteria.
Syntax:create_index([(str1, direction), (str1, direction).......], optional)Parameters are:
- str : field to create index on.
- direction : can be one or many directions, it has to be one of these directions- descending, ascending, hashed, geosphere, geohaystack, geo2d or text
This function can accept either a key or a list of (key, direction) pairs.
Example 1:
from pymongo import MongoClient
# Create a pymongo client
client = MongoClient('localhost', 27017)
# database instance
db = client['GFG']
# collection instance
doc = db['Student']
# Creating a single field index
res = doc.create_index("index_created")
print(res)
Output:
index_created_1
Example 2:
from pymongo import MongoClient
# Create a pymongo client
client = MongoClient('localhost', 27017)
# database instance
db = client['GFG']
# collection instance
doc = db['Student']
# Creating a single field index in descending order
res = doc.create_index([ ("index_descending", -1) ])
print(res)
Output:
index_descending_-1
Example 3:
from pymongo import MongoClient,, ASCENDING, DESCENDING
# Create a pymongo client
client = MongoClient('localhost', 27017)
# database instance
db = client['GFG']
# collection instance
doc = db['Student']
# Creating a compound field index in descending order
res = doc.create_index(
[
("ascending_index", 1),
("second_descnding_indexed", DESCENDING)
]
)
print(res)
Output:
ascending_index_1 second_descnding_indexed_DESCENDING
