Wildcard and prefix queries in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this wildcard query?

Given the following Elasticsearch wildcard query, what documents will it match if the index contains documents with the field name having values: "apple", "application", "apply", "banana"?

Elasticsearch

{
  "query": {
    "wildcard": {
      "name": {
        "value": "app*"
      }
    }
  }
}

A ["apple", "banana"]

B ["apple", "application", "apply"]

C ["banana"]

D ["application", "banana"]

💡 Hint

The wildcard * matches zero or more characters after 'app'.

The wildcard query with value 'app*' matches any string starting with 'app'. So it matches 'apple', 'application', and 'apply', but not 'banana'.

❓ Predict Output

intermediate

What documents does this prefix query match?

Consider this Elasticsearch prefix query on the field title. Which documents will it match if the titles are: "Introduction to Elasticsearch", "Introductory Guide", "Installation Manual", "Integration Tips"?

Elasticsearch

{
  "query": {
    "prefix": {
      "title": "Intro"
    }
  }
}

A ["Installation Manual", "Integration Tips"]

B ["Introductory Guide", "Installation Manual"]

C ["Introduction to Elasticsearch", "Introductory Guide"]

D ["Integration Tips"]

💡 Hint

Prefix query matches documents where the field starts with the given prefix.

The prefix query with 'Intro' matches titles starting with 'Intro', so it matches 'Introduction to Elasticsearch' and 'Introductory Guide'.

🔧 Debug

advanced

Why does this wildcard query cause an error?

This wildcard query is intended to match any category starting with 'tech'. Why does it cause a syntax error?

Elasticsearch

{
  "query": {
    "wildcard": {
      "category": "tech*"
    }
  }
}

A Because the wildcard value must be inside a 'value' field, not directly as a string.

B Because the wildcard query does not support the '*' character.

C Because the field name 'category' is invalid in wildcard queries.

D Because the query must use 'prefix' instead of 'wildcard' for this pattern.

💡 Hint

Check the expected structure of a wildcard query in Elasticsearch.

The wildcard query requires the value to be specified inside a 'value' key. Writing the value directly as a string causes a syntax error.

❓ Predict Output

advanced

What is the result count of this prefix query?

If an Elasticsearch index has documents with the field username values: "john123", "johnny", "johanna", "jane", "jack", what is the number of documents matched by this prefix query?

Elasticsearch

{
  "query": {
    "prefix": {
      "username": "john"
    }
  }
}

A 4

B 1

C 3

D 2

💡 Hint

Count usernames starting exactly with 'john'.

The prefix 'john' matches 'john123' and 'johnny' because they start with 'john'. 'johanna' starts with 'joha', not 'john'. So the count is 2.

🧠 Conceptual

expert

Which option correctly explains the difference between wildcard and prefix queries?

Select the option that best describes the key difference between wildcard and prefix queries in Elasticsearch.

A Wildcard queries allow multiple wildcard characters anywhere in the term, while prefix queries only match terms starting with the given prefix without wildcards.

B Prefix queries support multiple wildcards in the middle of the term, but wildcard queries only support a single wildcard at the end.

C Wildcard queries are faster than prefix queries because they use inverted indices more efficiently.

D Prefix queries require the use of regular expressions, while wildcard queries do not.

💡 Hint

Think about where wildcards can appear in each query type.

Wildcard queries support '*' and '?' anywhere in the term, allowing flexible matching. Prefix queries only match terms starting with the given prefix and do not support wildcards.