eventstats

`eventstats`

Use the eventstats command to obtain overall summary statistics, optionally grouped by fields, on properties of groups identified by any grouping command such as stats, link, or timestats. Its output will include one field for each aggregation.

Syntax

Note

The trend aggregate operator is not permitted with eventstats.

eventstats <stats_function> (<field_name>) [as <new_field_name>] [, <stats_function> (<field_name>) [as <new_field_name>]]* [by <field_name> [, <field_name>]*]

Parameters

The following table lists the parameters used with this command, along with their descriptions.

Parameter	Description
`field_name`	Use this parameter to specify the field according to which you want the results to be grouped.
`new_field_name`	Use this parameter to specify the new name for the field after applying the `stats` command.

For the supported functions, see Functions, Positional Functions, and Time Series Analysis Functions.

Functions

The following table lists the functions available with this command, along with their examples.

Function	Examples
Values Lists the first 10 values for a particular field with optional delimiter. Can be applied to any field data type.	`values(field_name)` `values(Label)` `values(Severity)` `values(‘Client Host City’)` `values(‘Client Host Country’)` `values(‘Client Host Continent’)`
Unique Lists the first 10 unique values for a particular field with optional delimiter. Can be applied to any field data type.	`unique(field_name)` `unique(Label)` `unique(Severity)` `unique(‘Client Host City’)` `unique(‘Client Host Country’)` `unique(‘Client Host Continent’)`
Earliest Return the eldest non-null value for the specified field. Null will be returned if field is completely empty for a particular queries results.	`earliest(field_name)` `earliest(‘OS Process ID’)`
Latest Return the most recent non-null value for the specified field. Null will be returned if field is completely empty for a particular queries results.	`latest(field_name)` `latest(‘Error ID’)`
Average Note: This function is supported only for numeric fields.	`avg(field_name)` `avg(‘Content Size’)`
Count Note: This function uses semantics similar to sql; that is, count returns the count for all rows; however, count(field) returns the count for all rows where field is not null.	`count(field_name)` `count(Source)`
Distinct Count	`distinctcount(field_name)` `distinctcount(Severity)`
Maximum Note: This function is supported only for numeric fields.	`max(field_name)` `max('Content Size')`
Median Note: This function is supported only for numeric fields.	`median(field_name)` `median('Content Size')`
Minimum Note: This function is supported only for numeric fields.	`min(field_name)` `min('Content Size')`
Percentage Note: This function is supported only for numeric fields.	`pct(field_name, n)` `pct('Content Size', 90)`
Sum Note: This function is supported only for numeric fields.	`sum(field_name)` `sum(‘Content Size’)`
Standard Deviation Note: This function is supported only for numeric fields.	`stddev(field_name)` `stddev(‘Content Size’)`

Positional Functions

The following table lists the functions that are unique to this command, along with their examples.

Function	Examples
first Retrieves property value from the first row, as defined by the current sort order, within the retrieved result.	Syntax: `first(field_name)` `\| eventstats first('Content Size')`
last Retrieves property value from the last row, as defined by the current sort order, within the retrieved result.	Syntax: `last(field_name)` `\| eventstats last('Content Size')`
nthval Retrieves property value from the nth row, as defined by the current sort order, within the retrieved result.	Syntax: `nthval(field_name, n)` `\| eventstats nthval('Content Size', 2)`
lag Retrieves property value from a row at a given offset prior to the current row. Default offset is 1.	Syntax: `lag(field_name)` `\| eventstats lag('Content Size')`
lead Retrieves property value from a row at a given offset after the current row. Default offset is 1.	Syntax: `lead(field_name)` `\| eventstats lead('Content Size')`
rownum Assigns a unique number sequentially, starting from 1, as defined by the current sort order to each row within the retrieved result.	Syntax: `rownum` `\| eventstats rownum`

Time Series Analysis Functions

The following table lists the functions for time series analysis, along with their examples.

Function	Examples
peak Retrieves property value with peak magnitude, within the retrieved result. A higher value of magnitude indicates larger absolute values.	Syntax: `peak` `\| eventstats peak('Content Size')`
peakscore Retrieves property value with normalized peak score between 0 and 1, within the retrieved result. The score can be used to compare the peaks, with the highest peak getting 1 as the score, and all other values between 0 and 1.	Syntax: `peakscore` `\| eventstats peakscore('Content Size')`
valley Retrieves property value with valley magnitude, within the retrieved result. A lower value of magnitude indicates smaller absolute values.	Syntax: `valley` `\| eventstats valley('Content Size')`
valleyscore Retrieves property value with normalized valley score between 0 and 1, within the retrieved result. The score can be used to compare the valleys, with the least valley getting 0 as the score, and all other values between 0 and 1.	Syntax: `valleyscore` `\| eventstats valleyscore('Content Size')`

Use the peak and peakscore functions to analyze sequential data in Link Visualization for peak magnitude and a normalized score between 0 and 1. For example, the following query highlights the highest peaks in user response time, using the Duration field from the Access Logs Log Source:

'Log Source' = 'OCI API Gateway Access Logs' 
| link span = 5minute Time, Server 
| stats avg(Duration) as 'Avg. Duration' 
| sort Server, 'Start Time' 
| eventstats peak('Avg. Duration')      as 'Peak Magnitude', 
             peakscore('Avg. Duration') as 'Peak Score' by Server 
| highlightgroups priority = high 
  [ * | where 'Peak Score' > 0.9 ] as 'High Response Time - Needs Attention'

This feature can be used for searching and grouping of time series data, like identifying all Out of Memory events that happened after a spike. A higher value for magnitude indicates larger absolute values. Score can be used to compare peaks, with the highest peak getting 1 as the score, and others a value between 0 and 1.

For examples of using eventstats command in typical scenarios, see:

Group all the fatal logs by transaction, and get the overall average elapsed time across all the groups:

severity = fatal | link 'Transaction ID' | stats avg('Elapsed Time (System)') as 'Average Elapsed Time' | eventstats avg('Average Elapsed Time') as 'Overall Average Elapsed Time'

severity = fatal | stats avg('Elapsed Time (system)') as 'Average Elapsed Time' | eventstats avg('Average elapsed time') as 'Overall Average elapsed time'

Group all the fatal logs by entity type and transaction, and get the overall average elapsed time across all the groups with the same entity type:

severity = fatal | link 'Entity Type', 'Transaction ID' | stats avg('Elapsed Time (System)') as 'Average Elapsed Time' | eventstats avg('Average Elapsed Time') as 'Overall Average Elapsed Time' by 'Entity Type'

severity = fatal | stats avg('Elapsed Time (System)') as 'Average Elapsed Time' by 'Entity Type', 'Transaction ID'  | eventstats avg('Average Elapsed Time') as 'Overall Average Elapsed Time' by 'Entity Type'

In the Link visualization, add a number to each row:

'Log Source' = 'Database Alert Logs' and Label != null and Entity = MyDB 
| rename Entity as Database
| link span = 1minute Time, Database, Label
| sort Database, 'Start Time'
| eventstats rownum as 'Row Number' by Database

Identify the last event using the row number:

'Log Source' = 'Database Alert Logs' and Label != null and Entity = MyDB
| rename Entity as Database
| link span = 1minute Time, Database, Label
| sort Database, 'Start Time'
| eventstats rownum as 'Row Number' by Database
| addfields
   [ * | where Label = 'Abnormal Termination'
       | eventstats last('Row Number') as 'Crash Row'
   ]

Identify the previous and next events of a selected event:

'Log Source' = 'Database Alert Logs' and Label != null and Entity = MyDB
| rename Entity as Database
| link span = 1minute Time, Database, Label
| sort Database, 'Start Time'
| addfields
   [ *
      | where Label != null
      | eventstats lag(Label) as 'Previous Event',
                   lead(Label) as 'Next Event'
   ]

Oracle Cloud Infrastructure Documentation