Dynamic vs explicit mapping in Elasticsearch - Visual Side-by-Side Comparison

Concept Flow - Dynamic vs explicit mapping

Start: Indexing document

↓

Check mapping type

↓

Dynamic mapping

↓

Infer field types

↓

Add fields to mapping

↓

Store document in index

↓

End

When a document is indexed, Elasticsearch either infers field types dynamically or uses explicit predefined mappings before storing the document.

Execution Sample

Elasticsearch

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

// Index document with fields name and age

This example shows explicit mapping where field types are defined before indexing documents.

Execution Table

Step	Action	Mapping Type	Field Processed	Mapping Update	Result
1	Index document {"name": "Alice", "age": 30}	Explicit	name	Exists as text	Field accepted as text
2	Index document {"name": "Alice", "age": 30}	Explicit	age	Exists as integer	Field accepted as integer
3	Index document {"city": "Paris"}	Explicit	city	Not in mapping	Rejected or error (depends on settings)
4	Index document {"name": "Bob", "age": 25, "city": "Paris"}	Dynamic	name	Exists as text	Field accepted as text
5	Index document {"name": "Bob", "age": 25, "city": "Paris"}	Dynamic	age	Exists as integer	Field accepted as integer
6	Index document {"name": "Bob", "age": 25, "city": "Paris"}	Dynamic	city	Inferred as text	Field added dynamically
7	Index document {"name": "Charlie", "age": "thirty"}	Dynamic	age	Inferred as integer before	Type conflict error or dynamic mapping update
8	Stop	-	-	-	No more documents to index

💡 Execution stops when no more documents are indexed or mapping conflicts occur.

Variable Tracker

Variable	Start	After 1	After 2	After 3	After 4	After 5	After 6	Final
Mapping fields	{}	{"name": "text"}	{"name": "text", "age": "integer"}	{"name": "text", "age": "integer"}	{"name": "text", "age": "integer", "city": "text"}	{"name": "text", "age": "integer", "city": "text"}	{"name": "text", "age": "integer", "city": "text"}	{"name": "text", "age": "integer", "city": "text"}
Document indexed	None	{"name": "Alice", "age": 30}	{"name": "Alice", "age": 30}	{"city": "Paris"} (rejected in explicit)	{"name": "Bob", "age": 25, "city": "Paris"}	{"name": "Bob", "age": 25, "city": "Paris"}	{"name": "Charlie", "age": "thirty"} (conflict)	Stopped

Key Moments - 3 Insights

Why does indexing a new field fail in explicit mapping?

In explicit mapping, only predefined fields are accepted. As shown in step 3 of the execution_table, the 'city' field is not defined, so Elasticsearch rejects it.

How does dynamic mapping add new fields?

Dynamic mapping infers the field type from the document and adds it automatically to the mapping, as seen in steps 4-6 where 'city' is added dynamically.

What happens if a field's type conflicts with previous mapping?

If a new document has a field with a different type than previously mapped, Elasticsearch raises a type conflict error, as in step 7 with 'age' field.

Visual Quiz - 3 Questions

Look at the execution_table, at which step is a new field added dynamically?

A Step 4

B Step 3

C Step 2

D Step 1

💡 Hint

Check the 'Mapping Update' column for when 'city' is added dynamically.

According to variable_tracker, what fields exist after step 2 in explicit mapping?

A Only 'name'

B 'name', 'age', and 'city'

C 'name' and 'age'

D No fields

💡 Hint

Look at the 'Mapping fields' row after 'After 2' column.

If explicit mapping allowed unknown fields, how would step 3 change?

A Field 'city' would be rejected

B Field 'city' would be accepted without error

C Field 'city' would be added dynamically

D Mapping would be deleted

💡 Hint

Refer to the difference between explicit and dynamic mapping in the execution_table steps 3 and 4.

Concept Snapshot

Dynamic vs explicit mapping in Elasticsearch:
- Explicit mapping: define fields and types before indexing
- Dynamic mapping: Elasticsearch infers and adds fields automatically
- Explicit rejects unknown fields unless updated
- Dynamic can cause type conflicts if data changes
- Choose explicit for control, dynamic for flexibility

Full Transcript

When you add data to Elasticsearch, it needs to know what type each field is, like text or number. You can tell it exactly by making an explicit mapping before adding data. Then, only those fields are allowed. If you try to add a new field not in the mapping, it will reject it. Or, you can let Elasticsearch guess the types by using dynamic mapping. It looks at your data and adds new fields automatically. But if later you add a field with a different type, it causes an error. This example showed how explicit mapping accepts only known fields and dynamic mapping adds new fields on the fly. Understanding this helps you decide how to organize your data in Elasticsearch.