Bucket aggregations (terms, histogram) in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a terms aggregation on the field "user.keyword".

Elasticsearch

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

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

Auser

Buser.keyword

Ckeyword.user

Dusers.keyword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the analyzed field "user" instead of the keyword subfield.

Swapping the order of "keyword" and "user" in the field name.

The terms aggregation requires the exact field, usually the keyword subfield like "user.keyword" for aggregations.

2fill in blank

medium

Complete the code to create a histogram aggregation on the field "price" with interval 50.

Elasticsearch

{
  "aggs": {
    "price_ranges": {
      "histogram": {
        "field": "price",
        "[1]": 50
      }
    }
  }
}

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

Arange

Bbucket_size

Cinterval

Dstep

Attempts:

3 left

💡 Hint

Common Mistakes

Using "range" instead of "interval" for histogram buckets.

Using "step" or "bucket_size" which are not valid parameters.

The histogram aggregation uses the "interval" parameter to define bucket size.

3fill in blank

hard

Fix the error in the terms aggregation by completing the missing parameter to limit the number of buckets to 5.

Elasticsearch

{
  "aggs": {
    "top_users": {
      "terms": {
        "field": "user.keyword",
        "[1]": 5
      }
    }
  }
}

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

Amax_buckets

Blimit

Ccount

Dsize

Attempts:

3 left

💡 Hint

Common Mistakes

Using "limit" or "count" which are not valid parameters for terms aggregation.

Using "max_buckets" which is a cluster setting, not an aggregation parameter.

The "size" parameter limits the number of buckets returned in a terms aggregation.

4fill in blank

hard

Fill both blanks to create a histogram aggregation on "age" with interval 10 and include only buckets with doc_count greater than 5.

Elasticsearch

{
  "aggs": {
    "age_histogram": {
      "histogram": {
        "field": "age",
        "[1]": 10
      },
      "aggs": {
        "filtered_buckets": {
          "bucket_selector": {
            "buckets_path": {
              "count": "_count"
            },
            "script": "params.count [2] 5"
          }
        }
      }
    }
  }
}

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

Ainterval

B>

C<

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using "range" instead of "interval" for histogram.

Using "<" or "==" in the script which would filter incorrectly.

The histogram interval is set with "interval" and the bucket_selector script uses ">" to filter buckets with doc_count greater than 5.

5fill in blank

hard

Fill all three blanks to create a nested aggregation: a terms aggregation on "category.keyword", with a sub-aggregation histogram on "price" with interval 20, and limit the terms buckets to 3.

Elasticsearch

{
  "aggs": {
    "categories": {
      "terms": {
        "field": "[1]",
        "[2]": 3
      },
      "aggs": {
        "price_ranges": {
          "histogram": {
            "field": "price",
            "[3]": 20
          }
        }
      }
    }
  }
}

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

Acategory.keyword

Bsize

Cinterval

Dprice.keyword

Attempts:

3 left

💡 Hint

Common Mistakes

Using "price.keyword" for histogram field instead of "price".

Using "limit" instead of "size" to limit terms buckets.

The terms aggregation uses "category.keyword" field with "size" 3 to limit buckets, and the histogram uses "interval" 20 on "price" field.

Practice

1.

What does the terms aggregation do in Elasticsearch?

easy

A. Sorts documents by date in ascending order

B. Groups documents by unique values of a field and counts them

C. Filters documents based on a numeric range

D. Calculates the average value of a numeric field

Solution

1. Step 1: Understand the purpose of terms aggregation

   The terms aggregation groups documents by unique values of a specified field.

2. Step 2: Recognize the output of terms aggregation

   It counts how many documents fall into each unique value group.

3. Final Answer:

   Groups documents by unique values of a field and counts them -> Option B

4. Quick Check:

   terms aggregation = grouping by unique values [OK]

Hint: Remember: terms = group by unique values and count [OK]

Common Mistakes:

• Confusing terms with filtering
• Thinking terms sorts documents
• Mixing terms with metric aggregations

2.

Which of the following is the correct syntax for a histogram aggregation on a field named price with interval 50?

{
  "aggs": {
    "price_ranges": {
      "histogram": {
        "field": "price",
        "interval": 50
      }
    }
  }
}

easy

A. Correct as shown

B. Use "interval": "50" (string instead of number)

C. Use "terms" instead of "histogram"

D. Place "interval" outside "histogram" block

Solution

1. Step 1: Check the structure of histogram aggregation

   The histogram aggregation requires a field and a numeric interval inside its block.

2. Step 2: Verify the given JSON syntax

   The example correctly places field and interval inside the histogram object with interval as a number.

3. Final Answer:

   Correct as shown -> Option A

4. Quick Check:

   Histogram syntax with numeric interval = correct [OK]

Hint: Interval must be a number inside histogram block [OK]

Common Mistakes:

• Using string instead of number for interval
• Confusing terms and histogram aggregations
• Placing interval outside histogram object

3.

Given this aggregation query:

{
  "aggs": {
    "by_category": {
      "terms": { "field": "category.keyword" }
    }
  }
}

What will the aggregation return?

medium

A. The average value of the category field

B. A histogram of categories grouped by numeric ranges

C. A list of unique categories with document counts for each

D. A filtered list of documents matching category.keyword

Solution

1. Step 1: Identify the aggregation type and field

   The query uses a terms aggregation on the category.keyword field, which groups by unique values.

2. Step 2: Understand the output of terms aggregation

   It returns buckets for each unique category with counts of documents in each bucket.

3. Final Answer:

   A list of unique categories with document counts for each -> Option C

4. Quick Check:

   Terms aggregation output = unique value buckets with counts [OK]

Hint: Terms aggregation returns unique values with counts [OK]

Common Mistakes:

• Thinking histogram groups string fields
• Expecting average instead of counts
• Confusing filtering with aggregation

4.

Identify the error in this aggregation query:

{
  "aggs": {
    "price_buckets": {
      "histogram": {
        "field": "price",
        "interval": "100"
      }
    }
  }
}

medium

A. The field name "price" is invalid

B. Missing "size" parameter for histogram

C. Histogram aggregation cannot be nested inside aggs

D. The interval value should be a number, not a string

Solution

1. Step 1: Check the type of the interval parameter

   The interval must be a numeric value, but here it is given as a string "100".

2. Step 2: Understand impact of wrong interval type

   Using a string instead of a number causes a syntax error or unexpected behavior in Elasticsearch.

3. Final Answer:

   The interval value should be a number, not a string -> Option D

4. Quick Check:

   Interval must be numeric, not string [OK]

Hint: Interval must be numeric, not quoted string [OK]

Common Mistakes:

• Using string instead of number for interval
• Assuming field name is wrong without checking
• Thinking histogram can't be inside aggs

5.

You want to group sales data by price ranges of 100 units and then within each price range, group by product category. Which aggregation structure should you use?

hard

A. { "aggs": { "price_ranges": { "histogram": { "field": "price", "interval": 100 }, "aggs": { "by_category": { "terms": { "field": "category.keyword" } } } } } }

B. { "aggs": { "by_category": { "terms": { "field": "category.keyword" }, "aggs": { "price_ranges": { "histogram": { "field": "price", "interval": 100 } } } } } }

C. { "aggs": { "price_ranges": { "terms": { "field": "price" }, "aggs": { "by_category": { "histogram": { "field": "category.keyword", "interval": 100 } } } } } }

D. { "aggs": { "by_category": { "histogram": { "field": "category.keyword", "interval": 100 }, "aggs": { "price_ranges": { "terms": { "field": "price" } } } } } }

Solution

1. Step 1: Identify the primary grouping by price ranges

   The outer aggregation should be a histogram on the price field with interval 100 to group sales by price ranges.

2. Step 2: Nest the category grouping inside each price range bucket

   Inside each price range bucket, use a terms aggregation on category.keyword to group by product category.

3. Final Answer:

   Aggregation with histogram on price and nested terms on category -> Option A

4. Quick Check:

   Histogram outer, terms nested = correct structure [OK]

Hint: Nest terms inside histogram for grouped sub-buckets [OK]

Common Mistakes:

• Reversing the order of aggregations
• Using terms for numeric price instead of histogram
• Using histogram on keyword fields