The orchestration

ML sequences all of these pieces together when an ML job is configured to run. A simplified version of this process is shown in the following diagram:

In general, the preceding procedures are done once per bucket_span—however, additional optimizations are done to minimize I/O. Those details are beyond the scope of this book. The key takeaway, however, is that this orchestration enables ML to be online (that is, not offline/batch) and constantly learning on newly ingested data. This process is also automatically handled by ML so that the user doesn't have to worry about the complex logistics required to make it all happen.