What is the impact of the presence of an index in the query?
There is a particular scenario where n has a large dataset in a table named is “products” and the column has “product_category” which has many rows with the value of “electronics”. What is the importance of using an index on the “product category’’ column, especially during the process of querying all products belonging to the electronics category? How can the presence of an index impact the performance of a query?
In the context of Python programming language, if you have a scenario where a column like “product category” has many similar values, such as “electronics” the utilization of an index can surely enhance the performance of Query.
From SQLAlchemy import create_engine, select, Table, MetaData
# Create an SQLAlchemy engine
Engine = create_engine(‘your_database_connection_string’)
# Reflect the existing table
Metadata = MetaData()
Products_table = Table(‘products’, metadata, autoload_with=engine)
# Define the product category you’re interested in (e.g., “electronics”)
Desired_category = ‘electronics’
# to Build a select statement with a WHERE clause filtering by product category
Query = select([products_table]).where(products_table.c.product_category == desired_category)
# Execute the query
Result = engine.execute(query)
# Fetch and print the results
For row in result:
Print(row)Creating an index
The CREATE INDEX statement refers to creating an index named “idx product category” on the column of “product category”. This would help in optimizing the searches of a database based on the column “product category”
Querying with index
Then the subsequent statement of SELECT would fetch all rows from the table of “products” where the “product category” is electronic. This would speed up the query because the database can effectively locate the rows within the specified category.