Why aggregations summarize data in Elasticsearch - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a terms aggregation on the field 'category'.

Elasticsearch

{
  "aggs": {
    "categories": {
      "terms": { "field": "[1]" }
    }
  }
}

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

Auser

Bprice

Cdate

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using a numeric field like 'price' instead of a categorical field.

Misspelling the field name.

The terms aggregation groups documents by the values in the 'category' field.

2fill in blank

medium

Complete the code to calculate the average price using an aggregation.

Elasticsearch

{
  "aggs": {
    "average_price": {
      "[1]": { "field": "price" }
    }
  }
}

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

Aavg

Bsum

Cmax

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'sum' instead of 'avg' for average calculation.

Using 'max' or 'min' which find extremes, not averages.

The 'avg' aggregation calculates the average value of the specified field.

3fill in blank

hard

Fix the error in the aggregation that tries to get the maximum value of 'rating'.

Elasticsearch

{
  "aggs": {
    "max_rating": {
      "max": { "field": "[1]" }
    }
  }
}

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

Arating

Bratings

Crate

Drank

Attempts:

3 left

💡 Hint

Common Mistakes

Using a wrong field name like 'ratings' or 'rate'.

Typos in the field name.

The field name must exactly match the field in the index, which is 'rating'.

4fill in blank

hard

Fill both blanks to create a date histogram aggregation on the 'timestamp' field with daily intervals.

Elasticsearch

{
  "aggs": {
    "daily_sales": {
      "date_histogram": {
        "field": "[1]",
        "interval": "[2]"
      }
    }
  }
}

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

Atimestamp

Bday

Chourly

Ddate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'date' instead of 'timestamp' for the field.

Using 'hourly' instead of 'day' when daily grouping is needed.

The 'date_histogram' aggregation groups data by dates. The field is 'timestamp' and the interval is 'day' for day-by-day grouping.

5fill in blank

hard

Fill all three blanks to create a nested aggregation that groups by 'category', then calculates the average 'price' for each category, only including categories with at least 5 documents.

Elasticsearch

{
  "aggs": {
    "categories": {
      "terms": {
        "field": "[1]",
        "min_doc_count": [2]
      },
      "aggs": {
        "average_price": {
          "[3]": { "field": "price" }
        }
      }
    }
  }
}

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

Acategory

B5

Cavg

Dprice

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong field names for grouping or average calculation.

Setting 'min_doc_count' to a string instead of a number.

This nested aggregation groups documents by 'category', filters out categories with fewer than 5 documents using 'min_doc_count', and calculates the average 'price' per category.

Practice

1. What is the main purpose of aggregations in Elasticsearch?

easy

A. To delete documents from the index

B. To summarize data like totals, averages, and counts

C. To update the mapping of fields

D. To create new indexes

Solution

1. Step 1: Understand what aggregations do

   Aggregations are used to get summaries such as totals, averages, and counts from data.

2. Step 2: Compare with other options

   Deleting documents, updating mappings, and creating indexes are not related to summarizing data.

3. Final Answer:

   To summarize data like totals, averages, and counts -> Option B

4. Quick Check:

   Aggregations summarize data = A [OK]

Hint: Aggregations summarize data, not modify it [OK]

Common Mistakes:

• Confusing aggregations with data deletion
• Thinking aggregations change index structure
• Mixing aggregations with indexing operations

2. Which part of an Elasticsearch query contains aggregations?

easy

A. aggs

B. query

C. filter

D. sort

Solution

1. Step 1: Identify the query structure

   Elasticsearch queries have different parts like query, aggs, filter, and sort.

2. Step 2: Locate where aggregations go

   Aggregations are always written inside the aggs section to summarize data.

3. Final Answer:

   aggs -> Option A

4. Quick Check:

   Aggregations inside aggs = A [OK]

Hint: Aggregations live inside the aggs section [OK]

Common Mistakes:

• Putting aggregations inside query or filter
• Confusing aggs with sort
• Missing the aggs keyword

3. Given this aggregation query snippet, what does it calculate?

{"aggs": {"total_sales": {"sum": {"field": "price"}}}}

medium

A. Sums all values in the price field

B. Calculates the average price

C. Finds the maximum price

D. Counts the number of documents

Solution

1. Step 1: Read the aggregation type

   The aggregation uses sum on the field price.

2. Step 2: Understand what sum does

   Sum adds all values in the specified field across documents.

3. Final Answer:

   Sums all values in the price field -> Option A

4. Quick Check:

   sum aggregation = D [OK]

Hint: Sum adds all values in a field [OK]

Common Mistakes:

• Confusing sum with count or average
• Thinking sum finds max value
• Ignoring the field name

4. This aggregation query returns an error. What is the mistake?

{"aggs": {"avg_price": {"average": {"field": "price"}}}}

medium

A. The aggs keyword is misspelled

B. The field name 'price' is invalid

C. Aggregations cannot use numeric fields

D. The aggregation type should be 'avg', not 'average'

Solution

1. Step 1: Check aggregation type spelling

   The correct aggregation for average is avg, not average.

2. Step 2: Validate other parts

   The field name and aggs keyword are correct, and numeric fields are allowed.

3. Final Answer:

   The aggregation type should be 'avg', not 'average' -> Option D

4. Quick Check:

   Use 'avg' for average aggregation = C [OK]

Hint: Use 'avg' keyword, not 'average' [OK]

Common Mistakes:

• Using 'average' instead of 'avg'
• Assuming field name causes error
• Thinking aggs is misspelled

5. You want to find the average price of products but only for those with stock greater than 10. Which aggregation setup is correct?

hard

A. {"aggs": {"avg_price": {"avg": {"field": "price", "gt": 10}}}}

B. {"query": {"term": {"stock": 10}}, "aggs": {"avg_price": {"avg": {"field": "price"}}}}

C. {"query": {"range": {"stock": {"gt": 10}}}, "aggs": {"avg_price": {"avg": {"field": "price"}}}}

D. {"aggs": {"avg_price": {"avg": {"field": "price"}}}, "filter": {"range": {"stock": {"gt": 10}}}}

Solution

1. Step 1: Understand filtering before aggregation

   To filter documents before aggregation, use a query with a range filter on stock > 10.

2. Step 2: Check aggregation syntax

   The aggregation should be inside aggs with avg on the price field.

3. Step 3: Evaluate options

   {"query": {"range": {"stock": {"gt": 10}}}, "aggs": {"avg_price": {"avg": {"field": "price"}}}} correctly filters with query and then aggregates. {"aggs": {"avg_price": {"avg": {"field": "price", "gt": 10}}}} wrongly puts filter inside aggregation. {"query": {"term": {"stock": 10}}, "aggs": {"avg_price": {"avg": {"field": "price"}}}} filters exact stock=10, not greater. {"aggs": {"avg_price": {"avg": {"field": "price"}}}, "filter": {"range": {"stock": {"gt": 10}}}} misplaces filter outside query.

4. Final Answer:

   {"query": {"range": {"stock": {"gt": 10}}}, "aggs": {"avg_price": {"avg": {"field": "price"}}}} -> Option C

5. Quick Check:

   Filter in query, aggregation in aggs = B [OK]

Hint: Filter in query, aggregate in aggs section [OK]

Common Mistakes:

• Putting filters inside aggregation incorrectly
• Using term filter instead of range for greater than
• Placing filter outside query block