Skip to main content

Group or Aggregate Operators

Aggregating (group-by) functions evaluate messages and place them into groups. The group operator is used in conjunction with group-by functions.

Only search results that have been aggregated using a group or aggregate operator can be placed on a dashboard panel. See Chart Search Results for information about charting.

Overview

When using any grouping function, the word by is sufficient for representing the group operator. The typical construction when using group-by functions is:

grouping_function by <fieldname>
info

The withtimemost_recent, and least_recent operators are not considered standalone operators; they are designed to only be used as an alternative to the first and last operators in Live Dashboards or any continuous query where first and last are not supported.

By default, the ordering is not defined inside of groups created using a group-by expression. To order your results, use the sort operator.

Syntax

... | group_by_function <field_to_operate_on> group by <field_to_group_by>[, <field2>, ...]

You can use by instead of group by so count group by user is equivalent to count by user.

Rules

  • Cannot be used with the LogReduce operator.
  • When parsing and naming (aliasing) fields, avoid using the names of grouping functions or other operators as field names.
  • When using count, or any grouping function, remember to include the underscore before the field name (sort by _count).
  • Multiple aggregation functions can be on the same line, but you can't include another function, such as a math function, on the same line of a query.

For example, you can't use:

... | avg(x + y) as average, sum(x+y) as total

You would need to do that in two separate steps, such as:

... | x + y as z | avg(z) as average, sum(z) as total

In another example, you can't use:

avg(abs_latency)/1000/60 as avg_latency_min

Instead, you'd need to use two separate lines:

avg(abs_latency_ms) as avg_latency_ms
| avg_latency_ms / 1000 / 60 as avg_latency_min

Examples

Sort by _count and limit to 10 results
* | parse "GET * " as url 
| count by url 
| sort by _count 
| limit 10
Count by user
status AND down 
| parse regex "user=(?<user>.*?)"
| parse regex "host=(?<msg_host>.*?)"
| count by user
Count by the Source IP address
_sourceCategory=apache 
| parse "* " as src_ip
| parse "GET *" as url
| count by src_ip
| sort by _count
Group by multiple fields
| count(field1), avg(field2) group by field1, _timeslice
Use multiple aggregate operators
| max(amount) as amount_max, count(datetime) as datetime_count, sum(_size) as messages_size_sum, last(query) as last_query

All Sumo Logic system-generated fields begin with an underscore (_). Group-by functions always create a Sumo Logic field named with a combination of an underscore (_) and the function name. Using the function count inserts a field into the pipeline called _count. The function count_distinct inserts a field into the pipeline called _count_distinct.

Guide Contents

In this section, we'll introduce the following concepts:

icon

avg

Calculates the avg value of a numerical field being evaluated.

icon

count, count_distinct, count_frequent

Use with a group operator and field name.

icon

first, last

Return the first or last result relative to the sort order.

icon

median

Calculates the median value for a particular field.

icon

min, max

Use these functions to find the smallest or largest value in a set of values.

icon

most_recent, least_recent

Select the most or least recent value within a group.

icon

pct

Finds the specified percentiles of a given field.

icon

pct_sampling

Finds the percentile of a given field.

icon

stddev

Finds the standard deviation for numerical values within a time range.

icon

sum

Adds values of a numerical field being evaluated within a time range.

icon

values

Provides all the distinct values of a field.


Legal
Privacy Statement
Terms of Use

Copyright © 2024 by Sumo Logic, Inc.