Why advanced search improves user experience in Elasticsearch - See It in Action

Why advanced search improves user experience

📖 Scenario: Imagine you run an online bookstore. Customers want to find books quickly and easily. Basic search only looks for exact words, but advanced search can find books even if customers type different words or want to filter by price or author.

🎯 Goal: You will create a simple Elasticsearch query that shows how advanced search features like filtering and matching multiple fields improve the search experience for users.

📋 What You'll Learn

Create an Elasticsearch index with sample book data

Add a filter to search only books cheaper than a certain price

Use a multi-match query to search both title and author fields

Print the final Elasticsearch query JSON

💡 Why This Matters

🌍 Real World

Online stores and libraries use advanced search to help users find products or books quickly by filtering and searching multiple fields.

💼 Career

Understanding how to build advanced search queries is important for roles in data engineering, backend development, and search engine optimization.

1

Create sample book data

Create a variable called books that holds a list of three dictionaries. Each dictionary should have these keys and values exactly: 'title': 'The Great Gatsby', 'author': 'F. Scott Fitzgerald', 'price': 10; 'title': '1984', 'author': 'George Orwell', 'price': 15; 'title': 'To Kill a Mockingbird', 'author': 'Harper Lee', 'price': 12.

Elasticsearch

# Create the list variable books with the exact three dictionaries
# Your code here

Need a hint?

Use a list with three dictionaries. Each dictionary has keys 'title', 'author', and 'price' with the exact values given.

2

Set a price filter

Create a variable called max_price and set it to 12. This will be used to filter books cheaper than or equal to this price.

Elasticsearch

books = [
    {'title': 'The Great Gatsby', 'author': 'F. Scott Fitzgerald', 'price': 10},
    {'title': '1984', 'author': 'George Orwell', 'price': 15},
    {'title': 'To Kill a Mockingbird', 'author': 'Harper Lee', 'price': 12}
]
# Create max_price variable and set it to 12
# Your code here

Need a hint?

Just create a variable named max_price and assign it the number 12.

3

Build the advanced search query

Create a variable called search_query that holds a dictionary representing an Elasticsearch query. Use a bool query with a filter for price less than or equal to max_price, and a multi_match query inside must that searches the text 'great' in both title and author fields.

Elasticsearch

books = [
    {'title': 'The Great Gatsby', 'author': 'F. Scott Fitzgerald', 'price': 10},
    {'title': '1984', 'author': 'George Orwell', 'price': 15},
    {'title': 'To Kill a Mockingbird', 'author': 'Harper Lee', 'price': 12}
]
max_price = 12
# Create search_query dictionary with bool filter and multi_match must
# Your code here

Need a hint?

Use a dictionary with 'query' key, inside it 'bool' with 'filter' for price range and 'must' for multi_match query on title and author.

4

Print the final search query

Write a print statement to display the search_query variable.

Elasticsearch

books = [
    {'title': 'The Great Gatsby', 'author': 'F. Scott Fitzgerald', 'price': 10},
    {'title': '1984', 'author': 'George Orwell', 'price': 15},
    {'title': 'To Kill a Mockingbird', 'author': 'Harper Lee', 'price': 12}
]
max_price = 12
search_query = {
    'query': {
        'bool': {
            'filter': [
                {
                    'range': {
                        'price': {'lte': max_price}
                    }
                }
            ],
            'must': [
                {
                    'multi_match': {
                        'query': 'great',
                        'fields': ['title', 'author']
                    }
                }
            ]
        }
    }
}
# Print the search_query variable
# Your code here

Need a hint?

Use print(search_query) to show the final query dictionary.