Metric aggregations (avg, sum, min, max) in Elasticsearch - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of metric aggregations in Elasticsearch?

Metric aggregations calculate numeric summaries like average, sum, minimum, and maximum values from your data.

beginner

How do you calculate the average value of a field using Elasticsearch aggregations?

Use the avg aggregation with the field name specified, for example:

{ "aggs": { "average_price": { "avg": { "field": "price" } } } }

beginner

What is the difference between sum and avg aggregations?

sum adds all values of a field together, while avg calculates the average value by dividing the sum by the number of values.

beginner

How do you find the minimum and maximum values of a field in Elasticsearch?

Use the min and max aggregations with the field name, for example:

{ "aggs": { "min_price": { "min": { "field": "price" } }, "max_price": { "max": { "field": "price" } } } }

intermediate

Can you combine multiple metric aggregations in one Elasticsearch query?

Yes, you can include multiple metric aggregations inside the aggs object to get several summaries in one query.

Which aggregation calculates the average value of a numeric field in Elasticsearch?

A sum

B min

C avg

D max

The avg aggregation calculates the average value of a numeric field.

What does the sum aggregation do?

A Finds the smallest value

B Finds the largest value

C Calculates the average

D Adds all values together

The sum aggregation adds all numeric values of a field.

How do you specify the field to aggregate in Elasticsearch metric aggregations?

A Using the <code>field</code> parameter

B Using the <code>index</code> parameter

C Using the <code>type</code> parameter

D Using the <code>value</code> parameter

The field parameter tells Elasticsearch which field to use for aggregation.

Which aggregation would you use to find the highest value in a field?

A avg

B max

C min

D sum

The max aggregation finds the highest value in a numeric field.

Can you run multiple metric aggregations in a single Elasticsearch query?

A Yes, by nesting them inside <code>aggs</code>

B Only if they are the same type

C No, only one aggregation per query

D Only if they use different fields

Multiple metric aggregations can be combined inside the aggs object in one query.

Explain how to use Elasticsearch metric aggregations to find average, sum, minimum, and maximum values of a numeric field.

Think about how you specify the field and how you combine multiple aggregations.

Describe the difference between the sum and average metric aggregations in Elasticsearch.

Consider what each aggregation calculates from the data.

Practice

1. What does the avg metric aggregation calculate in an Elasticsearch query?

easy

A. The average value of a numeric field across documents

B. The total count of documents matching the query

C. The maximum value of a numeric field

D. The minimum value of a numeric field

Solution

1. Step 1: Understand the purpose of avg aggregation

   The avg aggregation calculates the average (mean) of values in a numeric field.

2. Step 2: Compare with other metric aggregations

   Other aggregations like sum, min, and max calculate total, minimum, and maximum respectively, not average.

3. Final Answer:

   The average value of a numeric field across documents -> Option A

4. Quick Check:

   avg = average value [OK]

Hint: avg means average value, not count or min/max [OK]

Common Mistakes:

• Confusing avg with sum or count
• Thinking avg returns min or max values
• Mixing avg with document count

2. Which of the following is the correct syntax to calculate the sum of the field price in an Elasticsearch aggregation?

easy

A. "aggs": { "total_price": { "sum": { "field": "price" } } }

B. "aggs": { "total_price": { "avg": { "field": "price" } } }

C. "aggs": { "total_price": { "max": { "field": "price" } } }

D. "aggs": { "total_price": { "min": { "field": "price" } } }

Solution

1. Step 1: Identify the aggregation type for sum

   The aggregation type to calculate sum is sum.

2. Step 2: Check the syntax structure

   The correct syntax uses "sum": { "field": "price" } inside aggs.

3. Final Answer:

   "aggs": { "total_price": { "sum": { "field": "price" } } } -> Option A

4. Quick Check:

   sum aggregation syntax = "aggs": { "total_price": { "sum": { "field": "price" } } } [OK]

Hint: sum uses "sum": { "field": "fieldname" } syntax [OK]

Common Mistakes:

• Using avg or max instead of sum
• Missing the field name inside sum
• Wrong nesting of aggregation keys

3. Given this Elasticsearch aggregation query snippet, what will be the output for the max_price aggregation?

{
  "aggs": {
    "max_price": {
      "max": { "field": "price" }
    }
  }
}

Assuming the documents have prices: 10, 25, 7, 30, 15.

medium

A. 25

B. 30

C. 15

D. 10

Solution

1. Step 1: Understand max aggregation

   The max aggregation returns the highest value of the specified field.

2. Step 2: Identify the maximum price from the list

   From the prices 10, 25, 7, 30, 15, the maximum is 30.

3. Final Answer:

   30 -> Option B

4. Quick Check:

   max price = 30 [OK]

Hint: max returns the highest number in the field values [OK]

Common Mistakes:

• Choosing the second highest value instead of max
• Confusing max with avg or sum
• Ignoring the actual field values

4. Identify the error in this Elasticsearch aggregation query that tries to calculate the minimum value of the field age:

{
  "aggs": {
    "min_age": {
      "min": "age"
    }
  }
}

medium

A. The query is missing a "query" section

B. The aggregation name "min_age" is invalid

C. The aggregation type should be "max" instead of "min"

D. The field name should be inside a nested object with key "field"

Solution

1. Step 1: Check the syntax for min aggregation

   The min aggregation requires the field name inside an object with key "field".

2. Step 2: Identify the error in the given query

   The query uses "min": "age" instead of "min": { "field": "age" } which is incorrect syntax.

3. Final Answer:

   The field name should be inside a nested object with key "field" -> Option D

4. Quick Check:

   min aggregation needs "field": "age" [OK]

Hint: Field must be inside { "field": "name" } for metric aggs [OK]

Common Mistakes:

• Passing field name as string directly without object
• Confusing aggregation type names
• Assuming query section is mandatory for aggregation

5. You want to find the average, sum, minimum, and maximum values of the field score using the avg, sum, min, and max aggregations in a single Elasticsearch query. Which aggregation structure correctly achieves this?

hard

A. { "aggs": { "score_metrics": { "metric": [ { "avg": { "field": "score" } }, { "sum": { "field": "score" } } ] } } }

B. { "aggs": { "score_stats": { "stats": { "field": "score" } } } }

C. { "aggs": { "avg_score": { "avg": { "field": "score" } }, "sum_score": { "sum": { "field": "score" } }, "min_score": { "min": { "field": "score" } }, "max_score": { "max": { "field": "score" } } } }

D. { "aggs": { "score": { "avg": { "field": "score" }, "sum": { "field": "score" }, "min": { "field": "score" }, "max": { "field": "score" } } } }

Solution

1. Step 1: Understand how to combine multiple metric aggregations

   Each metric aggregation must be a separate named aggregation inside aggs.

2. Step 2: Analyze each option's structure

   { "aggs": { "avg_score": { "avg": { "field": "score" } }, "sum_score": { "sum": { "field": "score" } }, "min_score": { "min": { "field": "score" } }, "max_score": { "max": { "field": "score" } } } } correctly defines four separate aggregations for avg, sum, min, and max on the field score. { "aggs": { "score_stats": { "stats": { "field": "score" } } } } uses stats which returns all metrics but is not separate aggregations. { "aggs": { "score_metrics": { "metric": [ { "avg": { "field": "score" } }, { "sum": { "field": "score" } } ] } } } and D have invalid syntax or unsupported structures.

3. Final Answer:

   Separate named aggregations for avg, sum, min, and max inside aggs -> Option C

4. Quick Check:

   Multiple metric aggs need separate keys inside aggs [OK]

Hint: Use separate named aggs for each metric under aggs [OK]

Common Mistakes:

• Trying to combine metrics inside one aggregation object
• Using unsupported array or metric keys
• Confusing stats aggregation with separate metric aggs