In ArcGIS Velocity, big data analytics run when you start the analytic. You can also schedule big data analytics to run periodically or at a recurring time. Scheduling big data analytics can be done when editing an analytic using the Schedule options.
The following configurations can be defined in Velocity big data analytics:
- Runs once—Analytic runs when you click Start.
- Run periodically
- Analytic runs every specified number of minutes or hours, for example, every 5 minutes.
- Analytic runs every specified number of minutes or hours within a time frame, for example, every 15 minutes between 8:00 a.m. and 5:00 p.m.
- Analytic runs every specified number of minutes or hours on the specified day (or days), for example, every 2 hours on weekdays.
- Analytic runs every specified number of minutes or hours on the specified day (or days) within a time frame, for example, every 20 minutes on weekends from 6:00 p.m. to 11:00 p.m.
- Runs at a recurring time—Analytic runs on a specified day (or days) around a specified time, for example, Mondays around 8:00 a.m.
Scheduling analytics is only supported when using the out-of-the-box scheduling options above. Running analytics on a schedule using external mechanisms such as ArcGIS Notebooks or third-party scheduling systems is not supported.
Schedule recurring analytics
To schedule recurring big data analytics that run periodically or at a recurring time, edit the big data analytic and click Schedule in the upper right. A scheduling pane appears where you can define a specific schedule for the big data analytic.
When scheduling recurring big data analytics, consider the following:
- The day and time are in UTC time.
- The big data analytic should finish running before the next run starts. For example, if the analytic takes approximately three minutes to complete, it is not recommended to configure the analytic to run every minute, as multiple runs will be skipped, and you will receive validation warnings.
- When updating and saving a big data analytic that is started, the next scheduled run of that analytic will use the latest saved configuration.
Use cases for recurring big data analytics
Several use cases exist for scheduling recurring big data analytics including when performing processing in near real-time or when performing analysis to generate analytic products for certain time ranges.
Perform processing in near real-time
One of the most common use cases for recurring big data analysis is to perform processing in near real time. This is when a big data analytic is configured to run every specified number of minutes or hours to process only the most recent features stored by a real-time analytic in that period of time.
For more information about performing near real-time analysis, see Perform near real-time analysis.
Perform analysis to generate analytic products for certain time ranges
You an perform repeated analysis on data collected within a certain time range. For example, an environmental organization with sensor data requires analytic products and outputs to be generated and archived each week, representing the past week of data collection. The analysis being performed remains the same; however, the data values being processed change week by week. To accomplish the analysis, you can configure a big data analytic to run once a week, for example, every Monday morning at 12:00 a.m.
For more information about how to perform and when to use a recurring analytic to generate informational products, see Generate up-to-date informational products.