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Indexing in MongoDB using Python

  • Last Updated : 10 Jul, 2020

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 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 : string used for naming index, it can be one or more than one
  • direction : can be one or many directions, it has to be one of these directions- descending, ascending, hashed, geosphere, geohaystack, geo2d or text

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 compund 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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