Shape · Time series

Sessionize

Groups events into sessions: a new session starts when the gap since the last event is longer than you set, such as 30 minutes.

Also known as: Clickstream sessions

How it works

Pick, usually, a Group by column such as the user id so sessions are numbered per user, and the Timestamp column. The Inactivity gap is a whole number of seconds, minutes, hours or days, 30 minutes by default. Within each group the rows are ordered by time and a new session starts when the time since the previous event is longer than the gap; a gap exactly equal to it stays in the session. The node appends session_id, counting 1, 2, 3 per group, and with Add session_seq also the event's 1-based position in its session. Rows with a NULL timestamp get NULL ids.

Inputs and outputs

Settings

{
  timestampColumn: string
  partitionBy?: string[]
  gapValue: number
  gapUnit: "seconds"|"minutes"|"hours"|"days"
  includeSeq?: boolean
}

Example

Web events per visitor with a 30-minute timeout: group by user_id, timestamp column ts, gap 30 minutes, session_seq on.

More in Time series

• Shift / Lag — Copies a value from N rows earlier or later onto each row, so you can compare a row with the one before it. For example, last month's sales next to this month's.
• Diff / Pct Change — Compares each row with the one N periods earlier and writes the difference or percent change. For example, month-over-month growth per store.
• Rolling Window — Adds moving statistics over the last N rows: sum, average, standard deviation, min, max, count or median. For example, a 7-day moving average.
• Resample — Rolls a time series up into regular buckets, from minutes to years, with a total or other summary per bucket. Empty buckets can be left out, carried forward or set to zero.
• Exponential Weighted Mean — Smooths a number column so recent rows count more than older ones. Gives a weighted mean, standard deviation or variance.
• Forecast — Forecasts the next periods of a measure from a dated series, one forecast per group, with a lower and upper band. It can also backtest the recent past to show how accurate the forecast would have been.