Cardinality aggregation in Elasticsearch - Mini Project: Build & Apply

Cardinality Aggregation in Elasticsearch

📖 Scenario: You work for an online store that wants to know how many unique customers have placed orders.

🎯 Goal: Build an Elasticsearch query using cardinality aggregation to find the count of unique customer IDs from the orders data.

📋 What You'll Learn

Create an Elasticsearch index named orders with sample order documents

Add a variable for the field name to aggregate on

Write a cardinality aggregation query using the field variable

Print the unique count of customers from the aggregation result

💡 Why This Matters

🌍 Real World

Counting unique customers helps businesses understand how many different people buy their products.

💼 Career

Knowing how to use cardinality aggregation is useful for data analysts and backend developers working with Elasticsearch.

1

Create the orders index with sample data

Create an Elasticsearch index called orders with these exact documents: {"order_id": 1, "customer_id": "C1"}, {"order_id": 2, "customer_id": "C2"}, {"order_id": 3, "customer_id": "C1"}, {"order_id": 4, "customer_id": "C3"}.

Elasticsearch

# Your code here

Hint

Use PUT /orders/_doc/{id} to add each document with the exact fields and values.

2

Set the field name for aggregation

Create a variable called field_name and set it to the string "customer_id".

Elasticsearch

PUT /orders/_doc/1
{
  "order_id": 1,
  "customer_id": "C1"
}

PUT /orders/_doc/2
{
  "order_id": 2,
  "customer_id": "C2"
}

PUT /orders/_doc/3
{
  "order_id": 3,
  "customer_id": "C1"
}

PUT /orders/_doc/4
{
  "order_id": 4,
  "customer_id": "C3"
}

field_name = "customer_id"  # Your code here

Hint

Just assign the string "customer_id" to the variable field_name.

3

Write the cardinality aggregation query

Write an Elasticsearch query using cardinality aggregation on the field stored in field_name. Use the aggregation name unique_customers.

Elasticsearch

PUT /orders/_doc/1
{
  "order_id": 1,
  "customer_id": "C1"
}

PUT /orders/_doc/2
{
  "order_id": 2,
  "customer_id": "C2"
}

PUT /orders/_doc/3
{
  "order_id": 3,
  "customer_id": "C1"
}

PUT /orders/_doc/4
{
  "order_id": 4,
  "customer_id": "C3"
}

field_name = "customer_id"

query = {
    "size": 0,
    "aggs": {
        "unique_customers": {
            "cardinality": {
                "field": field_name
            }
        }
    }
}  # Your code here

Hint

Use "aggs": { "unique_customers": { "cardinality": { "field": field_name }}} inside the query.

4

Print the unique customer count from the aggregation result

Print the unique customer count from the aggregation result using print(result['aggregations']['unique_customers']['value']).

Elasticsearch

PUT /orders/_doc/1
{
  "order_id": 1,
  "customer_id": "C1"
}

PUT /orders/_doc/2
{
  "order_id": 2,
  "customer_id": "C2"
}

PUT /orders/_doc/3
{
  "order_id": 3,
  "customer_id": "C1"
}

PUT /orders/_doc/4
{
  "order_id": 4,
  "customer_id": "C3"
}

field_name = "customer_id"

query = {
    "size": 0,
    "aggs": {
        "unique_customers": {
            "cardinality": {
                "field": field_name
            }
        }
    }
}

result = {
    "aggregations": {
        "unique_customers": {
            "value": 3
        }
    }
}

print(result['aggregations']['unique_customers']['value'])  # Your code here

Hint

Use the print statement to show the value inside result['aggregations']['unique_customers']['value'].

Practice

1.

What does the cardinality aggregation in Elasticsearch do?

easy

A. Calculates the sum of values in a field

B. Sorts documents by a field

C. Finds the average value of a field

D. Counts the number of unique values in a field

Solution

1. Step 1: Understand the purpose of cardinality aggregation

   Cardinality aggregation is designed to count unique values in a specified field.

2. Step 2: Compare with other aggregations

   Sum and average aggregations calculate totals and averages, not unique counts. Sorting is unrelated.

3. Final Answer:

   Counts the number of unique values in a field -> Option D

4. Quick Check:

   Cardinality = Unique count [OK]

Hint: Cardinality = count unique values fast [OK]

Common Mistakes:

• Confusing cardinality with sum or average
• Thinking it returns exact counts always
• Mixing it with sorting or filtering

2.

Which of the following is the correct syntax to define a cardinality aggregation on the field user_id in Elasticsearch?

{
  "aggs": {
    "unique_users": {
      "cardinality": {
        "field": "user_id"
      }
    }
  }
}

easy

A. { "aggs": { "unique_users": { "cardinality": { "field": "user_id" } } } }

B. { "aggs": { "unique_users": { "terms": { "field": "user_id" } } } }

C. { "aggs": { "unique_users": { "sum": { "field": "user_id" } } } }

D. { "aggs": { "unique_users": { "avg": { "field": "user_id" } } } }

Solution

1. Step 1: Identify the aggregation type for unique counts

   The cardinality aggregation is used to count unique values, so the key must be "cardinality".

2. Step 2: Check the field name and structure

   The field is correctly specified as "user_id" inside the cardinality object.

3. Final Answer:

   { "aggs": { "unique_users": { "cardinality": { "field": "user_id" } } } } -> Option A

4. Quick Check:

   Correct syntax uses "cardinality" with "field" [OK]

Hint: Cardinality uses "cardinality" key with "field" [OK]

Common Mistakes:

• Using terms aggregation instead of cardinality
• Using sum or avg aggregations for unique counts
• Incorrect JSON structure or missing braces

3.

Given the following Elasticsearch aggregation query:

{
  "aggs": {
    "unique_countries": {
      "cardinality": {
        "field": "country"
      }
    }
  }
}

If the indexed documents have countries: ["US", "US", "FR", "DE", "FR", "JP"], what is the expected approximate output value for unique_countries?

medium

A. 3

B. 4

C. 5

D. 6

Solution

1. Step 1: Identify unique countries in the list

   The countries are US, FR, DE, JP. Counting unique values gives 4.

2. Step 2: Understand cardinality output

   Cardinality aggregation returns approximate unique counts, which should be 4 here.

3. Final Answer:

   4 -> Option B

4. Quick Check:

   Unique countries count = 4 [OK]

Hint: Count distinct values in the field for cardinality [OK]

Common Mistakes:

• Counting duplicates as unique
• Confusing total documents with unique count
• Expecting exact count always (approximate)

4.

Identify the error in this cardinality aggregation query:

{
  "aggs": {
    "unique_users": {
      "cardinality": {
        "field_name": "user_id"
      }
    }
  }
}

medium

A. Aggregation name cannot be "unique_users"

B. Missing closing brace for "aggs"

C. "field_name" should be "field"

D. Cardinality aggregation requires a "size" parameter

Solution

1. Step 1: Check the field parameter name

   The correct key for specifying the field is "field", not "field_name".

2. Step 2: Verify JSON structure and parameters

   The braces are correctly closed, aggregation name is valid, and "size" is not required for cardinality.

3. Final Answer:

   "field_name" should be "field" -> Option C

4. Quick Check:

   Use "field" key for cardinality field [OK]

Hint: Use "field", not "field_name" in cardinality [OK]

Common Mistakes:

• Using wrong key "field_name" instead of "field"
• Adding unnecessary parameters like "size"
• Misnaming aggregation or missing braces

5.

You want to find the approximate number of unique products sold in each category using Elasticsearch. Which aggregation setup correctly combines terms and cardinality aggregations?

{
  "aggs": {
    "by_category": {
      "terms": { "field": "category" },
      "aggs": {
        "unique_products": {
          "cardinality": { "field": "product_id" }
        }
      }
    }
  }
}

hard

A. This setup groups by category and counts unique products per category

B. This setup counts unique categories per product

C. This setup sums product_id values per category

D. This setup finds average product_id per category

Solution

1. Step 1: Understand the terms aggregation

   "terms" groups documents by unique values in "category" field.

2. Step 2: Understand the nested cardinality aggregation

   Inside each category bucket, cardinality counts unique "product_id" values.

3. Final Answer:

   This setup groups by category and counts unique products per category -> Option A

4. Quick Check:

   Terms + cardinality = unique counts per group [OK]

Hint: Nest cardinality inside terms to count unique per group [OK]

Common Mistakes:

• Confusing aggregation order or nesting
• Using cardinality on category instead of product_id
• Expecting sum or average instead of unique count