Object and nested types in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this Elasticsearch query?

Given the following Elasticsearch mapping and query, what will be the result count?

Elasticsearch

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

POST /users/_search
{
  "query": {
    "bool": {
      "must": [
        { "term": { "user.name": "alice" } },
        { "range": { "user.age": { "gte": 30 } } }
      ]
    }
  }
}

A Returns documents where user.age is 30 or more but ignores user.name filter

B Returns documents where user.name contains 'alice' anywhere and user.age is exactly 30

C Returns documents where user.name is 'alice' but ignores user.age filter

D Returns all documents where user.name is exactly 'alice' and user.age is 30 or more

💡 Hint

Remember that term queries match exact values and range queries filter by numeric ranges.

The term query matches exact values for user.name. The range query filters user.age to be greater than or equal to 30. Both conditions must be true because of the bool must clause.

🧠 Conceptual

intermediate

Why use nested type instead of object type in Elasticsearch?

Choose the best reason to use nested type instead of object type for a field containing arrays of objects.

A Nested type allows querying each object in the array independently, preserving relationships between fields inside each object.

B Nested type stores data in a separate index, improving write speed.

C Nested type automatically flattens all objects into a single document for faster search.

D Nested type disables indexing of the field to save storage space.

💡 Hint

Think about how Elasticsearch matches fields inside arrays of objects.

The nested type stores each object in the array as a separate hidden document, allowing queries to match fields within the same object. The object type flattens all fields, which can cause incorrect matches across different objects.

🔧 Debug

advanced

Why does this nested query return zero results?

Given this mapping and query, why does the query return no results?

Elasticsearch

{
  "mappings": {
    "properties": {
      "comments": {
        "type": "nested",
        "properties": {
          "author": { "type": "keyword" },
          "message": { "type": "text" }
        }
      }
    }
  }
}

POST /posts/_search
{
  "query": {
    "bool": {
      "must": [
        { "term": { "comments.author": "john" } },
        { "match": { "comments.message": "great" } }
      ]
    }
  }
}

A The mapping is incorrect; nested type is not supported for comments.

B The term query is case-sensitive and 'john' does not match the stored value.

C The query does not use a nested query wrapper, so it treats comments as flat fields causing no matches.

D The match query cannot be used on nested fields.

💡 Hint

Check how nested fields must be queried in Elasticsearch.

When querying nested fields, you must use a nested query to scope the conditions inside the nested documents. Without it, the query treats nested fields as flat, causing no matches.

📝 Syntax

advanced

Identify the syntax error in this nested mapping definition

Which option contains the correct syntax for defining a nested field items with properties product (keyword) and quantity (integer)?

A

{
  "items": {
    "type": "object",
    "nested": true,
    "properties": {
      "product": { "type": "keyword" },
      "quantity": { "type": "integer" }
    }
  }
}

B

{
  "items": {
    "type": "nested",
    "properties": {
      "product": { "type": "keyword" },
      "quantity": { "type": "integer" }
    }
  }
}

C

{
  "items": {
    "type": "nested",
    "fields": {
      "product": { "type": "keyword" },
      "quantity": { "type": "integer" }
    }
  }
}

D

{
  "items": {
    "nested": true,
    "properties": {
      "product": { "type": "keyword" },
      "quantity": { "type": "integer" }
    }
  }
}

💡 Hint

Check the correct keyword to specify nested type in Elasticsearch mappings.

The correct way to define a nested field is to set type to nested and then define properties. Options A, B, and D use invalid or unsupported keywords.

🚀 Application

expert

How many documents are returned by this nested aggregation?

Given this mapping and data, what is the count of unique authors returned by the nested aggregation?

Elasticsearch

{
  "mappings": {
    "properties": {
      "reviews": {
        "type": "nested",
        "properties": {
          "author": { "type": "keyword" },
          "rating": { "type": "integer" }
        }
      }
    }
  }
}

Data example:
{
  "reviews": [
    {"author": "alice", "rating": 5},
    {"author": "bob", "rating": 4},
    {"author": "alice", "rating": 3}
  ]
}

Aggregation query:
{
  "aggs": {
    "nested_reviews": {
      "nested": { "path": "reviews" },
      "aggs": {
        "unique_authors": {
          "cardinality": { "field": "reviews.author" }
        }
      }
    }
  }
}

A 2

B 3

C 0

D 1

💡 Hint

Count distinct authors inside the nested reviews array.

The nested aggregation counts unique authors inside the nested reviews field. The authors are 'alice' and 'bob', so the count is 2.