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Indexing in MongoDB using Python

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  • Last Updated : 16 Jun, 2022

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:

Python3




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: 

Python3




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: 

Python3




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

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