next()
Applies to: ✅ Microsoft Fabric ✅ Azure Data Explorer ✅ Azure Monitor ✅ Microsoft Sentinel
Returns the value of a column in a row that is at some offset following the current row in a serialized row set.
Syntax
next(column, [ offset, default_value ])
Learn more about syntax conventions.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
| column | string |
✔️ | The column from which to get the values. |
| offset | int |
The amount of rows to move from the current row. Default is 1. | |
| default_value | scalar | The default value when there's no value in the next row. When no default value is specified, null is used. |
Examples
Filter data based on comparison between adjacent rows
The following query returns rows that show breaks longer than a quarter of a second between calls to sensor-9.
TransformedSensorsData
| where SensorName == 'sensor-9'
| sort by Timestamp asc
| extend timeDiffInMilliseconds = datetime_diff('millisecond', next(Timestamp, 1), Timestamp)
| where timeDiffInMilliseconds > 250
Output
| Timestamp | SensorName | Value | PublisherId | MachineId | timeDiff |
|---|---|---|---|---|---|
| 2022-04-13T00:58:53.048506Z | sensor-9 | 0.39217481975439894 | fdbd39ab-82ac-4ca0-99ed-2f83daf3f9bb | M100 | 251 |
| 2022-04-13T01:07:09.63713Z | sensor-9 | 0.46645392778288297 | e3ed081e-501b-4d59-8e60-8524633d9131 | M100 | 313 |
| 2022-04-13T01:07:10.858267Z | sensor-9 | 0.693091598493419 | 278ca033-2b5e-4f2c-b493-00319b275aea | M100 | 254 |
| 2022-04-13T01:07:11.203834Z | sensor-9 | 0.52415808840249778 | 4ea27181-392d-4947-b811-ad5af02a54bb | M100 | 331 |
| 2022-04-13T01:07:14.431908Z | sensor-9 | 0.35430645405452 | 0af415c2-59dc-4a50-89c3-9a18ae5d621f | M100 | 268 |
| ... | ... | ... | ... | ... | ... |
Perform aggregation based on comparison between adjacent rows
The following query calculates the average time difference in milliseconds between calls to sensor-9.
TransformedSensorsData
| where SensorName == 'sensor-9'
| sort by Timestamp asc
| extend timeDiffInMilliseconds = datetime_diff('millisecond', next(Timestamp, 1), Timestamp)
| summarize avg(timeDiffInMilliseconds)
Output
| avg_timeDiffInMilliseconds |
|---|
| 30.726900061254298 |
Extend row with data from the next row
In the following query, as part of the serialization done with the serialize operator, a new column next_session_type is added with data from the next row.
ConferenceSessions
| where conference == 'Build 2019'
| serialize next_session_type = next(session_type)
| project time_and_duration, session_title, session_type, next_session_type
Output
| time_and_duration | session_title | session_type | next_session_type |
|---|---|---|---|
| Mon, May 6, 8:30-10:00 am | Vision Keynote - Satya Nadella | Keynote | Expo Session |
| Mon, May 6, 1:20-1:40 pm | Azure Data Explorer: Advanced Time Series analysis | Expo Session | Breakout |
| Mon, May 6, 2:00-3:00 pm | Azure's Data Platform - Powering Modern Applications and Cloud Scale Analytics at Petabyte Scale | Breakout | Expo Session |
| Mon, May 6, 4:00-4:20 pm | How BASF is using Azure Data Services | Expo Session | Expo Session |
| Mon, May 6, 6:50 - 7:10 pm | Azure Data Explorer: Operationalize your ML models | Expo Session | Expo Session |
| ... | ... | ... | ... |