session_count 插件session_count plugin

• 09/30/2020
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针对某个时间线基于 ID 列计算会话计数。Calculates sessions count based on ID column over a timeline.

T | evaluate session_count(id, datetime_column, startofday(ago(30d)), startofday(now()), 1min, 30min, dim1, dim2, dim3)

语法Syntax

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

参数Arguments

• T ：输入表格表达式。T : The input tabular expression.
• IdColumn：列的名称，其 ID 值表示用户活动。IdColumn : The name of the column with ID values that represent user activity.
• TimelineColumn：表示时间线的列的名称。TimelineColumn : The name of the column that represents the timeline.
• 开始 ：带有分析开始时段值的标量。Start : Scalar with value of the analysis start period.
• End：带有分析结束时段值的标量。End : Scalar with value of the analysis end period.
• Bin ：会话分析步骤时间段的标量常数值。Bin : scalar constant value of session analysis step period.
• LookBackWindow ：表示会话回看期的标量常数值。LookBackWindow : scalar constant value representing session lookback period. 如果 IdColumn 中的 ID 在 LookBackWindow 之内的时间窗口中出现，则该会话被视为现有会话。If the ID from IdColumn appears in a time window within LookBackWindow, the session is considered to be an existing one. 如果该 ID 未出现，则该会话被视为新会话。If the ID doesn't appear, then the session is considered to be new.
• dim1 , dim2 , ...：（可选）维度列的列表，用于切分会话计数计算。dim1 , dim2 , ...: (optional) list of the dimensions columns that slice the session count calculation.

返回Returns

返回一个表，该表包含每个时间线期间的以及每个现有维度组合的会话计数值。Returns a table that has the session count values for each timeline period and for each existing dimensions combination.

输出表架构如下：Output table schema is:

示例Examples

对于此示例，数据是确定性的，并且我们使用具有两列的表：For this example, the data is deterministic, and we use a table with two columns:

• 时间线：一个 1 至 10,000 之间的顺序号Timeline: a running number from 1 to 10,000
• ID：1 至 50 之间的用户 IDId: Id of the user from 1 to 50

如果 Id 是 Timeline 的除数（时间线 % Id == 0），则该 ID 会出现在特定的 Timeline 时段。Id appears at the specific Timeline slot if it's a divider of Timeline (Timeline % Id == 0).

Id==1 的事件将出现在任何 Timeline 时段，Id==2 的事件将每隔一个 Timeline 时段出现，依此类推。An event with Id==1 will appear at any Timeline slot, an event with Id==2 at every second Timeline slot, and so on.

下面是很少的 20 行数据：Here are few 20 lines of the data:

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
| limit 20

我们换一种说法来定义会话：只要用户 (Id) 在 100 个时段的时间范围内出现至少一次，而会话回看窗口是 41 个时段，则会话被视为活跃。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.

下一个查询根据上述定义显示活跃会话的计数。The next query shows the count of active sessions according to the definition above.

let _data = range Timeline from 1 to 9999 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;
// End of data definition
_data
| evaluate session_count(Id, Timeline, 1, 10000, 100, 41)
| render linechart