Object and nested types in Elasticsearch

Introduction

Object and nested types help you store and search complex data with multiple layers inside Elasticsearch.

When you want to store a group of related fields together, like an address with street, city, and zip code.

When you have lists of objects, like multiple comments on a blog post, and want to search each comment separately.

When you need to keep the relationship between fields inside an object, so searches don't mix data from different objects.

When you want to organize data clearly to make queries easier and more accurate.

Syntax

Elasticsearch

PUT /my_index
{
  "mappings": {
    "properties": {
      "user": {
        "type": "object",
        "properties": {
          "name": { "type": "text" },
          "age": { "type": "integer" }
        }
      },
      "comments": {
        "type": "nested",
        "properties": {
          "author": { "type": "text" },
          "message": { "type": "text" }
        }
      }
    }
  }
}

Object type stores data as a single JSON object inside a document.

Nested type stores arrays of objects separately to keep each object's fields linked during searches.

Examples

This example creates an object type for a book with title and author fields.

Elasticsearch

PUT /library
{
  "mappings": {
    "properties": {
      "book": {
        "type": "object",
        "properties": {
          "title": { "type": "text" },
          "author": { "type": "text" }
        }
      }
    }
  }
}

This example uses nested type for comments so each comment is treated separately in searches.

Elasticsearch

PUT /blog
{
  "mappings": {
    "properties": {
      "comments": {
        "type": "nested",
        "properties": {
          "user": { "type": "text" },
          "comment": { "type": "text" }
        }
      }
    }
  }
}

Sample Program

This program creates an index with object and nested types, adds a document, and searches for comments by author 'Bob'.

Elasticsearch

PUT /my_index
{
  "mappings": {
    "properties": {
      "user": {
        "type": "object",
        "properties": {
          "name": { "type": "text" },
          "age": { "type": "integer" }
        }
      },
      "comments": {
        "type": "nested",
        "properties": {
          "author": { "type": "text" },
          "message": { "type": "text" }
        }
      }
    }
  }
}

POST /my_index/_doc/1
{
  "user": {
    "name": "Alice",
    "age": 30
  },
  "comments": [
    { "author": "Bob", "message": "Great post!" },
    { "author": "Carol", "message": "Thanks for sharing." }
  ]
}

GET /my_index/_search
{
  "query": {
    "nested": {
      "path": "comments",
      "query": {
        "match": { "comments.author": "Bob" }
      }
    }
  }
}

Important Notes

Use object type for simple nested data without needing separate queries.

Use nested type when you want to search inside arrays of objects without mixing fields from different objects.

Remember to use nested queries when searching nested fields to get correct results.

Summary

Object type stores grouped fields as one JSON object inside a document.

Nested type stores arrays of objects separately to keep their fields linked during searches.

Use nested queries to search inside nested fields correctly.

Practice

1. What is the main difference between object and nested types in Elasticsearch?

easy

A. Both types store data the same way but nested type is faster.

B. Object type stores arrays of objects separately, while nested type stores grouped fields as one JSON object.

C. Nested type is used only for numeric fields, object type for text fields.

D. Nested type stores arrays of objects separately to keep their fields linked during searches, while object type stores grouped fields as one JSON object.

Solution

1. Step 1: Understand object type storage

   Object type stores grouped fields as a single JSON object inside a document, meaning all fields are flattened and stored together.

2. Step 2: Understand nested type storage

   Nested type stores arrays of objects separately to maintain the relationship between fields within each object during searches.

3. Final Answer:

   Nested type stores arrays of objects separately to keep their fields linked during searches, while object type stores grouped fields as one JSON object. -> Option D

4. Quick Check:

   Nested keeps object fields linked = C [OK]

Hint: Nested keeps object arrays linked; object flattens fields [OK]

Common Mistakes:

• Confusing object and nested storage behavior
• Thinking nested is only for numeric fields
• Assuming both types store data the same way

2. Which of the following is the correct way to define a nested type field in an Elasticsearch mapping?

easy

A. "comments": { "type": "object" }

B. "comments": { "type": "keyword" }

C. "comments": { "type": "nested" }

D. "comments": { "type": "text" }

Solution

1. Step 1: Recall nested type syntax

   To define a nested field, the type must be explicitly set to "nested" in the mapping.

2. Step 2: Check options

   "comments": { "type": "nested" } correctly sets "comments" field type to "nested". Other options use incorrect types for nested data.

3. Final Answer:

   "comments": { "type": "nested" } -> Option C

4. Quick Check:

   Nested type requires "type": "nested" [OK]

Hint: Use "type": "nested" to define nested fields [OK]

Common Mistakes:

• Using "object" instead of "nested" for nested arrays
• Confusing text or keyword types with nested
• Omitting the type field

3. Given this mapping with a nested field comments and this document:

{"title": "Post", "comments": [{"user": "alice", "message": "Hi"}, {"user": "bob", "message": "Hello"}]}

Which query will correctly find documents where comments.user is "alice" and comments.message is "Hello" in the same comment object?

medium

A. { "query": { "nested": { "path": "comments", "query": { "bool": { "must": [ { "match": { "comments.user": "alice" } }, { "match": { "comments.message": "Hello" } } ] } } } } }

B. { "query": { "bool": { "must": [ { "match": { "comments.user": "alice" } }, { "match": { "comments.message": "Hello" } } ] } } }

C. { "query": { "term": { "comments.user": "alice" } } }

D. { "query": { "nested": { "path": "comments", "query": { "term": { "comments.message": "Hi" } } } } }

Solution

1. Step 1: Understand nested query usage

   To search inside nested fields and keep field relationships, use a nested query with the correct path and combined conditions inside it.

2. Step 2: Analyze options

   { "query": { "nested": { "path": "comments", "query": { "bool": { "must": [ { "match": { "comments.user": "alice" } }, { "match": { "comments.message": "Hello" } } ] } } } } } uses a nested query on "comments" with a bool must for both user "alice" and message "Hello" in the same nested object. { "query": { "bool": { "must": [ { "match": { "comments.user": "alice" } }, { "match": { "comments.message": "Hello" } } ] } } } searches flattened fields, losing the link. { "query": { "term": { "comments.user": "alice" } } } only matches user. { "query": { "nested": { "path": "comments", "query": { "term": { "comments.message": "Hi" } } } } } searches for message "Hi" only.

3. Final Answer:

   Uses nested query to match both conditions in the same nested object. -> Option A

4. Quick Check:

   Nested query with bool must inside = A [OK]

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

Common Mistakes:

• Using bool query without nested for nested fields
• Searching fields separately losing object linkage
• Using term query without nested path

4. You wrote this mapping for a nested field:

{ "properties": { "tags": { "type": "nested", "properties": { "name": { "type": "keyword" } } } } }

But your nested query returns no results even though documents have matching tags. What is the likely mistake?

medium

A. You forgot to use a nested query; used a regular bool query instead.

B. You defined tags as object type instead of nested.

C. You used match query on keyword field instead of term query.

D. You indexed tags as text instead of keyword.

Solution

1. Step 1: Check mapping correctness

   The mapping correctly defines "tags" as nested with keyword "name" field, so mapping is fine.

2. Step 2: Identify query mistake

   If nested query returns no results, often the cause is using a regular bool query instead of a nested query to search nested fields, losing the link between nested objects.

3. Final Answer:

   You forgot to use a nested query; used a regular bool query instead. -> Option A

4. Quick Check:

   Nested fields require nested queries [OK]

Hint: Always use nested query for nested fields [OK]

Common Mistakes:

• Using bool query without nested for nested fields
• Confusing object and nested types in mapping
• Using match query on keyword fields

5. You have documents with a nested field orders containing product and quantity. You want to find documents where there is an order with product "apple" and quantity greater than 10, but also an order with product "banana" and quantity less than 5. Which query structure correctly finds such documents?

hard

A. { "query": { "nested": { "path": "orders", "query": { "bool": { "must": [ { "term": { "orders.product": "apple" } }, { "range": { "orders.quantity": { "gt": 10 } } }, { "term": { "orders.product": "banana" } }, { "range": { "orders.quantity": { "lt": 5 } } } ] } } } }

B. { "query": { "bool": { "must": [ { "nested": { "path": "orders", "query": { "bool": { "must": [ { "term": { "orders.product": "apple" } }, { "range": { "orders.quantity": { "gt": 10 } } } ] } } } }, { "nested": { "path": "orders", "query": { "bool": { "must": [ { "term": { "orders.product": "banana" } }, { "range": { "orders.quantity": { "lt": 5 } } } ] } } } } ] } } }

C. { "query": { "bool": { "must": [ { "term": { "orders.product": "apple" } }, { "range": { "orders.quantity": { "gt": 10 } } }, { "term": { "orders.product": "banana" } }, { "range": { "orders.quantity": { "lt": 5 } } } ] } } }

D. { "query": { "nested": { "path": "orders", "query": { "term": { "orders.product": "apple" } } } } }

Solution

1. Step 1: Understand nested query for multiple conditions

   Each nested object must be queried separately to keep conditions linked inside the same nested object.

2. Step 2: Analyze query options

   { "query": { "bool": { "must": [ { "nested": { "path": "orders", "query": { "bool": { "must": [ { "term": { "orders.product": "apple" } }, { "range": { "orders.quantity": { "gt": 10 } } } ] } } } }, { "nested": { "path": "orders", "query": { "bool": { "must": [ { "term": { "orders.product": "banana" } }, { "range": { "orders.quantity": { "lt": 5 } } } ] } } } } ] } } } uses two nested queries combined with bool must, one for "apple" orders with quantity > 10, another for "banana" orders with quantity < 5, correctly matching documents with both conditions in different nested objects.

3. Step 3: Identify incorrect options

   { "query": { "nested": { "path": "orders", "query": { "bool": { "must": [ { "term": { "orders.product": "apple" } }, { "range": { "orders.quantity": { "gt": 10 } } }, { "term": { "orders.product": "banana" } }, { "range": { "orders.quantity": { "lt": 5 } } } ] } } } } tries to combine all conditions in one nested query, which requires all conditions in the same nested object (impossible for different products). { "query": { "bool": { "must": [ { "term": { "orders.product": "apple" } }, { "range": { "orders.quantity": { "gt": 10 } } }, { "term": { "orders.product": "banana" } }, { "range": { "orders.quantity": { "lt": 5 } } } ] } } } ignores nested queries, losing object linkage. { "query": { "nested": { "path": "orders", "query": { "term": { "orders.product": "apple" } } } } } only queries for "apple" product.

4. Final Answer:

   Uses separate nested queries for each product condition. -> Option B

5. Quick Check:

   Separate nested queries for each condition = A [OK]

Hint: Use separate nested queries for different nested object conditions [OK]

Common Mistakes:

• Combining multiple product conditions in one nested query
• Not using nested queries for nested fields
• Assuming all conditions apply to the same nested object