ES|QL DATE_TRUNC function
Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud. Availability This functionality is generally available and ready for production usage. Serverless interfaces and procedures might differ from classic Elastic Stack deployments. The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats. Availability This functionality is generally available and ready for production usage. Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments. This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.
Serverless
Generally available
Stack
Generally available
Rounds down a date to the closest interval.
interval- Interval; time span (DATE_PERIOD or TIME_DURATION).
date-
Date expression
Rounds down a date to the closest interval since epoch, which starts at 0001-01-01T00:00:00Z.
| interval | date | result |
|---|---|---|
| date_period | date | date |
| date_period | date_nanos | date_nanos |
| time_duration | date | date |
| time_duration | date_nanos | date_nanos |
FROM employees
| KEEP first_name, last_name, hire_date
| EVAL year_hired = DATE_TRUNC(1 year, hire_date)
| first_name:keyword | last_name:keyword | hire_date:date | year_hired:date |
|---|---|---|---|
| Alejandro | McAlpine | 1991-06-26T00:00:00.000Z | 1991-01-01T00:00:00.000Z |
| Amabile | Gomatam | 1992-11-18T00:00:00.000Z | 1992-01-01T00:00:00.000Z |
| Anneke | Preusig | 1989-06-02T00:00:00.000Z | 1989-01-01T00:00:00.000Z |
Combine DATE_TRUNC with STATS to create date histograms. For example, the number of hires per year:
FROM employees
| EVAL year = DATE_TRUNC(1 year, hire_date)
| STATS hires = COUNT(emp_no) BY year
| SORT year
| hires:long | year:date |
|---|---|
| 11 | 1985-01-01T00:00:00.000Z |
| 11 | 1986-01-01T00:00:00.000Z |
| 15 | 1987-01-01T00:00:00.000Z |
| 9 | 1988-01-01T00:00:00.000Z |
| 13 | 1989-01-01T00:00:00.000Z |
| 12 | 1990-01-01T00:00:00.000Z |
| 6 | 1991-01-01T00:00:00.000Z |
| 8 | 1992-01-01T00:00:00.000Z |
| 3 | 1993-01-01T00:00:00.000Z |
| 4 | 1994-01-01T00:00:00.000Z |
| 5 | 1995-01-01T00:00:00.000Z |
| 1 | 1996-01-01T00:00:00.000Z |
| 1 | 1997-01-01T00:00:00.000Z |
| 1 | 1999-01-01T00:00:00.000Z |
Or an hourly error rate:
FROM sample_data
| EVAL error = CASE(message LIKE "*error*", 1, 0)
| EVAL hour = DATE_TRUNC(1 hour, @timestamp)
| STATS error_rate = AVG(error) by hour
| SORT hour
| error_rate:double | hour:date |
|---|---|
| 0.0 | 2023-10-23T12:00:00.000Z |
| 0.6 | 2023-10-23T13:00:00.000Z |