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

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

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

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

Hint

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

Practice

1. Why does advanced search improve user experience in Elasticsearch?

easy

A. It helps users find more precise and relevant results quickly.

B. It slows down the search process to check more data.

C. It shows all data without filtering to avoid missing anything.

D. It removes all search filters to simplify the interface.

Solution

1. Step 1: Understand the purpose of advanced search

   Advanced search uses multiple conditions to narrow down results, making them more relevant.

2. Step 2: Connect relevance to user experience

   More precise results mean users find what they want faster, improving satisfaction.

3. Final Answer:

   It helps users find more precise and relevant results quickly. -> Option A

4. Quick Check:

   Advanced search = precise results = better experience [OK]

Hint: Advanced search narrows results for faster, better matches [OK]

Common Mistakes:

• Thinking advanced search slows down results
• Believing it shows all data without filtering
• Assuming it removes filters to simplify

2. Which Elasticsearch query syntax correctly uses multiple conditions for advanced search?

easy

A. {"query": {"match": "title:book price<20"}}

B. {"query": {"bool": {"should": [{"match": {"title": "book"}}, {"range": {"price": {"gt": 20}}}]}}}

C. {"query": {"filter": "title=book AND price<20"}}

D. {"query": {"bool": {"must": [{"match": {"title": "book"}}, {"range": {"price": {"lt": 20}}}]}}}

Solution

1. Step 1: Identify correct JSON structure for multiple conditions

   {"query": {"bool": {"must": [{"match": {"title": "book"}}, {"range": {"price": {"lt": 20}}}]}}} uses a bool query with must array, combining match and range correctly.

2. Step 2: Check other options for syntax errors or wrong logic

   Options A and C have invalid syntax; D uses should with price greater than 20, which is different logic.

3. Final Answer:

   {"query": {"bool": {"must": [{"match": {"title": "book"}}, {"range": {"price": {"lt": 20}}}]}}} -> Option D

4. Quick Check:

   Bool must with match and range = correct syntax [OK]

Hint: Use bool must with arrays for multiple conditions [OK]

Common Mistakes:

• Using invalid JSON syntax
• Confusing should with must for filtering
• Writing filters as plain strings

3. What will be the result count of this Elasticsearch query if the index has 5 documents with prices 10, 15, 25, 30, 5?

{"query": {"bool": {"must": [{"range": {"price": {"lt": 20}}}]}}}

medium

A. 0

B. 2

C. 3

D. 5

Solution

1. Step 1: Identify documents matching price less than 20

   Prices 10, 15, and 5 are less than 20, so 3 documents match.

2. Step 2: Confirm query logic

   The bool must with range lt 20 filters only those documents with price below 20.

3. Final Answer:

   3 -> Option C

4. Quick Check:

   Prices < 20 count = 3 [OK]

Hint: Count items matching range lt 20 to find result count [OK]

Common Mistakes:

• Counting prices equal to 20
• Including prices greater than 20
• Misreading the range operator

4. Identify the error in this Elasticsearch query that aims to find documents with status 'active' and score above 50:

{"query": {"bool": {"must": [{"match": {"status": "active"}}, {"range": {"score": {"gt": 50}}}]}}

medium

A. Using 'match' instead of 'term' for exact status match.

B. Missing closing braces for the JSON object.

C. Range query should use 'gte' instead of 'gt'.

D. Must clause should be replaced with should.

Solution

1. Step 1: Check JSON syntax completeness

   The query JSON is missing closing braces at the end, causing syntax error.

2. Step 2: Validate other parts

   Using match for status is acceptable; range gt 50 is valid; must is correct for AND logic.

3. Final Answer:

   Missing closing braces for the JSON object. -> Option B

4. Quick Check:

   JSON syntax error = missing braces [OK]

Hint: Count opening and closing braces to spot JSON errors [OK]

Common Mistakes:

• Ignoring missing braces causing parse errors
• Confusing match and term queries
• Changing must to should incorrectly

5. You want to improve user experience by filtering products that are either in category 'electronics' or have a rating above 4.5, but not both. Which Elasticsearch query achieves this advanced search?

hard

A. {"query": {"bool": {"should": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}], "minimum_should_match": 1, "must_not": [{"bool": {"must": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}]}}]}}}

B. {"query": {"bool": {"must": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}]}}}

C. {"query": {"bool": {"should": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}], "minimum_should_match": 1}}}

D. {"query": {"bool": {"filter": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}]}}}

Solution

1. Step 1: Understand the requirement for exclusive OR (XOR)

   The query must match either category electronics or rating > 4.5, but not both.

2. Step 2: Analyze options for XOR logic

   {"query": {"bool": {"should": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}], "minimum_should_match": 1, "must_not": [{"bool": {"must": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}]}}]}}} uses should with minimum_should_match 1 and excludes documents matching both conditions using must_not with must inside, implementing XOR.

3. Step 3: Verify other options

   {"query": {"bool": {"should": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}], "minimum_should_match": 1}}} matches either or both (OR), B matches both (AND), D filters both (AND). Only C excludes both.

4. Final Answer:

   {"query": {"bool": {"should": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}], "minimum_should_match": 1, "must_not": [{"bool": {"must": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}]}}]}} -> Option A

5. Quick Check:

   XOR = should + must_not both = {"query": {"bool": {"should": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}], "minimum_should_match": 1, "must_not": [{"bool": {"must": [{"term": {"category": "electronics"}}, {"range": {"rating": {"gt": 4.5}}}]}}]}}} [OK]

Hint: Use must_not with must inside should for XOR logic [OK]

Common Mistakes:

• Using must instead of should for OR
• Not excluding both conditions for XOR
• Confusing filter with must or should