Cardinality aggregation in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the cardinality aggregation field.

Elasticsearch

{
  "aggs": {
    "unique_users": {
      "cardinality": {
        "field": "[1]"
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Auser_id

Btimestamp

Cmessage

Dstatus

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-unique field like 'message' or 'status' instead of 'user_id'.

The cardinality aggregation counts unique values of the specified field. Here, user_id is the correct field to count unique users.

2fill in blank

medium

Complete the code to set the precision threshold for the cardinality aggregation.

Elasticsearch

{
  "aggs": {
    "unique_users": {
      "cardinality": {
        "field": "user_id",
        "[1]": 1000
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Ashard_size

Bprecision_threshold

Cmin_doc_count

Dmax_doc_count

Attempts:

3 left

💡 Hint

Common Mistakes

Using unrelated parameters like 'max_doc_count' or 'min_doc_count'.

The precision_threshold controls the accuracy of the cardinality aggregation. Higher values increase accuracy but use more memory.

3fill in blank

hard

Fix the error in the aggregation type to correctly perform cardinality aggregation.

Elasticsearch

{
  "aggs": {
    "unique_users": {
      "[1]": {
        "field": "user_id"
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Aterms

Bavg

Cstats

Dcardinality

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'terms' aggregation which groups by terms but does not count unique values directly.

The aggregation type must be cardinality to count unique values. Other types like terms or avg do different aggregations.

4fill in blank

hard

Fill both blanks to create a cardinality aggregation with a custom name and field.

Elasticsearch

{
  "aggs": {
    "[1]": {
      "cardinality": {
        "field": "[2]"
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Aunique_visitors

Buser_id

Ctimestamp

Dunique_sessions

Attempts:

3 left

💡 Hint

Common Mistakes

Using a field like 'timestamp' which is not suitable for unique user counts.

The aggregation is named unique_visitors and counts unique values in the user_id field.

5fill in blank

hard

Fill all three blanks to create a cardinality aggregation with a name, field, and precision threshold.

Elasticsearch

{
  "aggs": {
    "[1]": {
      "cardinality": {
        "field": "[2]",
        "[3]": 2000
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Aunique_customers

Bcustomer_id

Cprecision_threshold

Dmax_precision

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect parameter names like 'max_precision' instead of 'precision_threshold'.

The aggregation is named unique_customers, counts unique customer_id values, and sets precision_threshold to 2000 for accuracy.

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