Date histogram in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a date histogram aggregation with a daily interval.

Elasticsearch

{
  "aggs": {
    "sales_over_time": {
      "date_histogram": {
        "field": "sale_date",
        "calendar_interval": "[1]"
      }
    }
  }
}

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

Aday

Bhour

Cweek

Dmonth

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'interval' instead of 'calendar_interval'.

Choosing 'hour' when day grouping is needed.

The calendar_interval set to day groups documents by each day.

2fill in blank

medium

Complete the code to set the time zone to 'UTC' in the date histogram aggregation.

Elasticsearch

{
  "aggs": {
    "sales_over_time": {
      "date_histogram": {
        "field": "sale_date",
        "calendar_interval": "day",
        "[1]": "UTC"
      }
    }
  }
}

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

Azone

Btimezone

Ctime_zone

DtimeZone

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'timezone' or 'timeZone' instead of 'time_zone'.

Omitting the time zone key entirely.

The correct key to specify the time zone in a date histogram is time_zone.

3fill in blank

hard

Fix the error in the date histogram aggregation by completing the missing key for minimum document count.

Elasticsearch

{
  "aggs": {
    "sales_over_time": {
      "date_histogram": {
        "field": "sale_date",
        "calendar_interval": "month",
        "[1]": 0
      }
    }
  }
}

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

Amin_document_count

Bmin_doc_count

Cmin_count

Dminimum_doc_count

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'min_document_count' which is invalid.

Using 'min_count' or 'minimum_doc_count' which do not exist.

The correct key to include empty buckets is min_doc_count set to 0.

4fill in blank

hard

Fill both blanks to create a date histogram aggregation with a weekly interval.

Elasticsearch

{
  "aggs": {
    "weekly_sales": {
      "date_histogram": {
        "field": "sale_date",
        "[1]": "[2]"
      }
    }
  }
}

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

Acalendar_interval

Btime_zone

Cweek

DAmerica/New_York

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing 'interval' with 'calendar_interval'.

Using 'weekly' instead of 'week'.

The first blank is the key calendar_interval to set the interval, and the second blank is the value week for weekly grouping.

5fill in blank

hard

Fill all three blanks to create a date histogram aggregation with a monthly interval, time zone 'UTC', and minimum document count 0.

Elasticsearch

{
  "aggs": {
    "monthly_sales": {
      "date_histogram": {
        "[1]": "[2]",
        "[3]": "UTC",
        "min_doc_count": 0
      }
    }
  }
}

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

Acalendar_interval

Binterval

Cmonth

Dtime_zone

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'interval' instead of 'calendar_interval'.

Using 'timezone' instead of 'time_zone'.

The first blank is the key calendar_interval, the second blank is the value month, and the third blank is the key time_zone.

Practice

1. What is the primary purpose of a date_histogram aggregation in Elasticsearch?

easy

A. To group documents into buckets based on time intervals

B. To sort documents by date in ascending order

C. To filter documents by a specific date range

D. To count the total number of documents in the index

Solution

1. Step 1: Understand the function of date_histogram

   The date_histogram aggregation groups documents into buckets based on specified time intervals like days or months.

2. Step 2: Compare with other options

   Sorting, filtering, and counting are different operations; only grouping by time intervals matches date_histogram.

3. Final Answer:

   To group documents into buckets based on time intervals -> Option A

4. Quick Check:

   date_histogram = group by time [OK]

Hint: Remember: date_histogram groups data by time intervals [OK]

Common Mistakes:

• Confusing date_histogram with sorting
• Thinking it filters documents
• Assuming it counts all documents without grouping

2. Which of the following is the correct syntax to create a date_histogram aggregation on the field timestamp with a daily interval?

easy

A. "date_histogram": { "field": "timestamp", "interval": "day" }

B. "date_histogram": { "field": "timestamp", "interval": "daily" }

C. "date_histogram": { "field": "timestamp", "interval": "1day" }

D. "date_histogram": { "field": "timestamp", "interval": "days" }

Solution

1. Step 1: Check valid interval values

   Elasticsearch expects intervals like "day", "week", "month" as strings without plural or numeric prefixes.

2. Step 2: Validate each option

   "date_histogram": { "field": "timestamp", "interval": "day" } uses "day" which is correct. Options B, C, and D use invalid interval formats.

3. Final Answer:

   "date_histogram": { "field": "timestamp", "interval": "day" } -> Option A

4. Quick Check:

   Use singular interval names like "day" [OK]

Hint: Use singular interval names like "day", not "daily" or "days" [OK]

Common Mistakes:

• Using plural interval names like "days"
• Using malformed numeric prefixes like "1day"
• Using incorrect interval strings like "daily"

3. Given this Elasticsearch aggregation query snippet:

{
  "aggs": {
    "sales_over_time": {
      "date_histogram": {
        "field": "sale_date",
        "calendar_interval": "month"
      }
    }
  }
}

What will be the result of this aggregation?

medium

A. Buckets grouping sales by each day based on sale_date

B. Buckets grouping sales by each month based on sale_date

C. A syntax error due to missing interval

D. Buckets grouping sales by year ignoring months

Solution

1. Step 1: Identify the interval type

   The query uses calendar_interval": "month", which groups data by calendar months.

2. Step 2: Understand the effect on buckets

   Each bucket will contain documents with sale_date in the same month.

3. Final Answer:

   Buckets grouping sales by each month based on sale_date -> Option B

4. Quick Check:

   calendar_interval month = monthly buckets [OK]

Hint: calendar_interval "month" means monthly buckets [OK]

Common Mistakes:

• Confusing calendar_interval with fixed_interval
• Assuming daily buckets instead of monthly
• Thinking missing interval causes syntax error

4. You wrote this date_histogram aggregation:

{
  "aggs": {
    "by_week": {
      "date_histogram": {
        "field": "created_at",
        "interval": "week"
      }
    }
  }
}

But Elasticsearch returns an error. What is the likely cause?

medium

A. Missing "time_zone" parameter causes error

B. Field "created_at" is missing from the index

C. Using deprecated "interval" instead of "calendar_interval" or "fixed_interval"

D. The interval value "week" is invalid

Solution

1. Step 1: Check interval parameter usage

   Since Elasticsearch 7.2, "interval" is deprecated; use "calendar_interval" or "fixed_interval" instead.

2. Step 2: Identify error cause

   Using "interval" causes an error; other options are less likely or cause different errors.

3. Final Answer:

   Using deprecated "interval" instead of "calendar_interval" or "fixed_interval" -> Option C

4. Quick Check:

   Use calendar_interval or fixed_interval, not interval [OK]

Hint: Replace deprecated "interval" with "calendar_interval" or "fixed_interval" [OK]

Common Mistakes:

• Ignoring deprecation and using "interval"
• Assuming missing field causes this specific error
• Thinking "week" is invalid interval

5. You want to create a date_histogram aggregation that groups documents by week but aligns weeks to start on Monday instead of Sunday. Which parameter should you add to your aggregation?

hard

A. "calendar_interval": "week"

B. "time_zone": "UTC"

C. "week_start": "monday"

D. "offset": "1d"

Solution

1. Step 1: Understand week alignment in date_histogram

   Elasticsearch weeks start on Sunday by default; to shift start day, use the "offset" parameter.

2. Step 2: Identify correct parameter

   Setting "offset": "1d" shifts buckets by one day, making weeks start on Monday.

3. Step 3: Check other options

   "time_zone" adjusts time zones, "week_start" is not a valid parameter, and "calendar_interval" defines interval but not start day.

4. Final Answer:

   "offset": "1d" -> Option D

5. Quick Check:

   Use offset to shift week start day [OK]

Hint: Use offset "1d" to start weeks on Monday [OK]

Common Mistakes:

• Trying to use non-existent "week_start" parameter
• Assuming time_zone changes week start day
• Not using offset to shift buckets