Dynamic vs explicit mapping in Elasticsearch - Practice Questions

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this dynamic mapping example?

Given the following Elasticsearch mapping and document indexing, what will be the type of the age field in the index?

{
  "mappings": {
    "dynamic": true
  }
}

Document:
{
  "name": "Alice",
  "age": 30
}

A The document will fail to index due to missing explicit mapping.

B "age" will be mapped as a <code>text</code> type by default.

C "age" will be mapped as a <code>long</code> type automatically.

D "age" will be mapped as a <code>keyword</code> type automatically.

💡 Hint

Dynamic mapping tries to guess the field type based on the value.

With dynamic mapping enabled, Elasticsearch detects the age field as a number and maps it as long automatically.

❓ Predict Output

intermediate

What happens when explicit mapping conflicts with dynamic mapping?

Given this explicit mapping and a document, what will be the type of the price field?

{
  "mappings": {
    "properties": {
      "price": { "type": "keyword" }
    },
    "dynamic": true
  }
}

Document:
{
  "price": 19.99
}

A "price" will be mapped as <code>text</code> by dynamic mapping.

B "price" will be mapped as <code>keyword</code> as per explicit mapping, ignoring dynamic mapping.

C "price" will be mapped as <code>float</code> because the document value is a number.

D The document will fail to index due to type conflict.

💡 Hint

Explicit mappings override dynamic mapping for specified fields.

Explicit mapping for price as keyword takes precedence, so dynamic mapping does not change it.

🔧 Debug

advanced

Why does this dynamic mapping cause a runtime error?

Consider this mapping and document indexing attempt:

{
  "mappings": {
    "dynamic": "strict"
  }
}

Document:
{
  "title": "Book",
  "pages": 250
}

What error will Elasticsearch raise when indexing this document?

A Elasticsearch will raise a <code>strict_dynamic_mapping_exception</code> because <code>pages</code> is not defined in mapping.

B Elasticsearch will index the document successfully with dynamic mapping.

C Elasticsearch will ignore the <code>pages</code> field silently.

D Elasticsearch will raise a <code>mapper_parsing_exception</code> due to invalid field type.

💡 Hint

Strict dynamic mapping forbids new fields not defined explicitly.

With dynamic": "strict", Elasticsearch rejects documents with fields not in the mapping, raising strict_dynamic_mapping_exception.

🧠 Conceptual

advanced

How does explicit mapping improve search performance compared to dynamic mapping?

Which of the following best explains why explicit mapping can improve Elasticsearch search performance?

A Explicit mapping forces Elasticsearch to reindex data on every search.

B Explicit mapping disables indexing, so searches are faster.

C Explicit mapping automatically caches all fields, speeding up searches.

D Explicit mapping defines field types and analyzers upfront, allowing optimized indexing and queries.

💡 Hint

Think about how knowing field types helps Elasticsearch.

Explicit mapping lets Elasticsearch know field types and analyzers in advance, so it can index and search more efficiently.

❓ Predict Output

expert

What is the number of fields indexed with this mixed mapping?

Given this mapping and document, how many fields will be indexed?

{
  "mappings": {
    "dynamic": false,
    "properties": {
      "user": { "type": "keyword" },
      "message": { "type": "text" }
    }
  }
}

Document:
{
  "user": "bob",
  "message": "Hello world",
  "timestamp": "2024-06-01T12:00:00Z"
}

A 2 fields will be indexed: <code>user</code> and <code>message</code> only.

B 3 fields will be indexed including <code>timestamp</code>.

C Only 1 field will be indexed because <code>dynamic</code> is false.

D No fields will be indexed due to <code>dynamic</code> false.

💡 Hint

Dynamic false disables indexing of fields not explicitly mapped.

With dynamic": false, only explicitly mapped fields (user and message) are indexed; timestamp is ignored.