Index mappings overview in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

What is the output of this mapping query?

Given this Elasticsearch index mapping, what is the type of the field user.age?

Elasticsearch

{
  "mappings": {
    "properties": {
      "user": {
        "properties": {
          "name": { "type": "text" },
          "age": { "type": "integer" }
        }
      }
    }
  }
}

A "keyword"

B "text"

C "integer"

D "date"

💡 Hint

Look inside the nested properties under user.

The mapping defines user.age as an integer type, which means it stores whole numbers.

🧠 Conceptual

intermediate

Which statement about Elasticsearch mappings is true?

Choose the correct statement about index mappings in Elasticsearch.

A Mappings define how documents are indexed and stored in Elasticsearch.

B Mappings are only used to store the document data without any structure.

C Mappings automatically update field types when new data is indexed.

D Mappings are unrelated to search performance.

💡 Hint

Think about what controls the structure and data types in Elasticsearch.

Mappings tell Elasticsearch how to index and store each field, including data types and analyzers.

📝 Syntax

advanced

Which mapping snippet is syntactically correct for a date field with a custom format?

Select the valid Elasticsearch mapping snippet that defines a created_at field as a date with format yyyy-MM-dd HH:mm:ss.

A "created_at": { "type": "date", "format": "yyyy-MM-dd HH:mm:ss" }

B "created_at": { "type": "datetime", "format": "yyyy-MM-dd HH:mm:ss" }

C "created_at": { "type": "date", "format": "date_optional_time" }

D "created_at": { "type": "string", "format": "yyyy-MM-dd HH:mm:ss" }

💡 Hint

Check the valid type name for date fields in Elasticsearch.

The correct type for date fields is "date" and the format can be customized as shown in option A.

❓ optimization

advanced

Which mapping choice improves search performance for exact matches on a username?

You want to optimize search for exact username matches. Which mapping is best?

A "username": { "type": "text", "index": false }

B "username": { "type": "keyword" }

C "username": { "type": "text", "analyzer": "standard" }

D "username": { "type": "text" }

💡 Hint

Exact matches work best on fields that are not analyzed.

The "keyword" type stores the whole field as is, making exact match queries fast and efficient.

🔧 Debug

expert

What error occurs with this mapping snippet?

This mapping snippet is used to create an index. What error will Elasticsearch raise?

Elasticsearch

{
  "mappings": {
    "properties": {
      "price": { "type": "float" },
      "price": { "type": "integer" }
    }
  }
}

A IndexCreationException due to missing required fields

B No error, Elasticsearch merges the fields automatically

C SyntaxError due to invalid JSON format

D MappingConflictException due to duplicate field names with different types

💡 Hint

Check if you can define the same field twice with different types.

Elasticsearch does not allow duplicate field names with conflicting types in the same mapping, causing a MappingConflictException.