Indexes

Indexes are data structures used by a database to improve the performance of queries. They allow for faster data retrieval by creating a direct mapping between the values in a column and the corresponding rows in a table.

To understand indexes, let's consider an analogy of an index in a book. When you are looking for specific information in a book, you don't start reading from page one and go through every page. Instead, you refer to the index at the back of the book, which provides you with the page numbers where the information is located.

In a similar way, database indexes work by creating a lookup table that maps the values in a column to the corresponding rows in a table. When a query is executed, the database engine can use the index to quickly locate the relevant rows, instead of scanning the entire table.

Indexes can be created on one or more columns of a table, depending on the query patterns and the data access requirements. They are particularly useful for frequently used columns in WHERE or JOIN clauses.

Let's take a look at an example in Python:

1import pandas as pd
2
3# Create a sample DataFrame
4data = {
5    'Name': ['John', 'Jane', 'Mike', 'Emily'],
6    'Age': [25, 30, 35, 40]
7}
8df = pd.DataFrame(data)
9
10# Create an index on the 'Name' column
11df.set_index('Name', inplace=True)
12
13# Access data using the index
14print(df.loc['John'])
15print(df.loc['Mike'])

In this example, we create a DataFrame using the pandas library. We then set an index on the 'Name' column using the set_index method. This allows us to quickly access the data for a specific name using the loc method.

Indexes play a crucial role in optimizing database performance. By creating the appropriate indexes, you can significantly reduce the time it takes to retrieve data from a table, improving the overall responsiveness of your database queries.

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import pandas as pd

​

# Create a sample DataFrame

data = {

    'Name': ['John', 'Jane', 'Mike', 'Emily'],

    'Age': [25, 30, 35, 40]

}

df = pd.DataFrame(data)

​

# Create an index on the 'Name' column

df.set_index('Name', inplace=True)

​

# Access data using the index

print(df.loc['John'])

print(df.loc['Mike'])