session_count plugin

Applies to: ✅ Azure Data Explorer

Calculates the session count based on the ID column over a timeline. The plugin is invoked with the evaluate operator.

Syntax

TabularExpression | evaluate session_count(IdColumn, TimelineColumn, Start, End, Bin, LookBackWindow [, dim1, dim2, ...])

Learn more about syntax conventions.

Parameters

Name	Type	Required	Description
TabularExpression	`string`	✔️	The tabular expression that serves as input.
IdColumn	`string`	✔️	The name of the column with ID values that represents user activity.
TimelineColumn	`string`	✔️	The name of the column that represents the timeline.
Start	scalar	✔️	The start of the analysis period.
End	scalar	✔️	The end of the analysis period.
Bin	scalar	✔️	The session's analysis step period.
LookBackWindow	scalar	✔️	The session lookback period. If the ID from `IdColumn` appears in a time window within `LookBackWindow`, the session is considered to be an existing one. If the ID doesn't appear, then the session is considered to be new.
dim1, dim2, ...	`string`		A list of the dimensions columns that slice the session count calculation.

Returns

Returns a table that has the session count values for each timeline period and for each existing dimensions combination.

Output table schema is:

TimelineColumn	dim1	..	dim_n	count_sessions
type: as of TimelineColumn	..	..	..	`long`

Examples

For this example, the data is deterministic, and we use a table with two columns:

Timeline: a running number from 1 to 10,000
Id: ID of the user from 1 to 50

Id appears at the specific Timeline slot if it's a divider of Timeline (Timeline % Id == 0).

An event with Id==1 will appear at any Timeline slot, an event with Id==2 at every second Timeline slot, and so on.

Here are 20 lines of the data:

Run the query

let _data = range Timeline from 1 to 10000 step 1
    | extend __key = 1
    | join kind=inner (range Id from 1 to 50 step 1 | extend __key=1) on __key
    | where Timeline % Id == 0
    | project Timeline, Id;
// Look on few lines of the data
_data
| order by Timeline asc, Id asc
| take 20

Output

Timeline	Id
1	1
2	1
2	2
3	1
3	3
4	1
4	2
4	4
5	1
5	5
6	1
6	2
6	3
6	6
7	1
7	7
8	1
8	2
8	4
8	8

Let's define a session in next terms: session considered to be active as long as user (Id) appears at least once at a timeframe of 100 time slots, while session look-back window is 41 time slots.

The next query shows the count of active sessions according to the above definition.