`TS`

Stack Planned Serverless Preview

Brief description

The TS source command is similar to the FROM source command, with the following key differences:

Targets only time series indices
Enables the use of time series aggregation functions inside the STATS command

Syntax

TS index_pattern [METADATA fields]

Parameters

index_pattern: A list of indices, data streams or aliases. Supports wildcards and date math.
fields: A comma-separated list of metadata fields to retrieve.

Description

The TS source command enables time series semantics and adds support for time series aggregation functions to the STATS command, such as AVG_OVER_TIME(), or RATE. These functions are implicitly evaluated per time series, then aggregated by group using a secondary aggregation function. For example:

		TS metrics
  | WHERE @timestamp >= now() - 1 hour
  | STATS SUM(RATE(search_requests)) BY TBUCKET(1 hour), host
		
	

This query calculates the total rate of search requests (tracked by the search_requests counter) per host and hour. The RATE() function is applied per time series in hourly buckets. These rates are summed for each host and hourly bucket (since each host can map to multiple time series).

This paradigm—a pair of aggregation functions—is standard for time series querying. For supported inner (time series) functions per metric type, refer to ES|QL time series aggregation functions. These functions also apply to downsampled data, with the same semantics as for raw data.

Note

If a query is missing an inner (time series) aggregation function, LAST_OVER_TIME() is assumed and used implicitly. For instance, the following two queries are equivalent, returning the average of the last memory usage values per time series:

		TS metrics | STATS AVG(memory_usage)

TS metrics | STATS AVG(LAST_OVER_TIME(memory_usage))

To calculate the average memory usage across per-time-series averages, use the following query:

TS metrics | STATS AVG(AVG_OVER_TIME(memory_usage))

Use regular (non-time-series) aggregation functions, such as SUM(), as outer aggregation functions. Using a time series aggregation in combination with an inner function causes an error. For example, the following query is invalid:

TS metrics | STATS AVG_OVER_TIME(RATE(memory_usage))

Note

A time series aggregation function must be wrapped inside a regular aggregation function. For instance, the following query is invalid:

TS metrics | STATS RATE(search_requests)

Best practices

Avoid aggregating multiple metrics in the same query when those metrics have different dimensional cardinalities. For example, in STATS max(rate(foo)) + rate(bar)), if foo and bar don't share the same dimension values, the rate for one metric will be null for some dimension combinations. Because the + operator returns null when either input is null, the entire result becomes null for those dimensions. Additionally, queries that aggregate a single metric can filter out null values more efficiently.
Use the TS command for aggregations on time series data, rather than FROM. The FROM command is still available (for example, for listing document contents), but it's not optimized for procesing time series data and may produce unexpected results.
The TS command can't be combined with certain operations (such as FORK) before the STATS command is applied. Once STATS is applied, you can process the tabular output with any applicable ES|QL operations.
Add a time range filter on @timestamp to limit the data volume scanned and improve query performance.

Examples

		TS metrics
| WHERE @timestamp >= now() - 1 day
| STATS SUM(AVG_OVER_TIME(memory_usage)) BY host, TBUCKET(1 hour)
		
	