Update documentation for Dataflow operators

[VladaZakharova]

This PR adds description about the way to update pipelines in Dataflow.

---

^ Add meaningful description above
Read the Pull Request Guidelines for more information.
In case of fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
In case of a new dependency, check compliance with the ASF 3rd Party License Policy.
In case of backwards incompatible changes please leave a note in a newsfragment file, named {pr_number}.significant.rst or {issue_number}.significant.rst, in newsfragments.

[sunank200]

Suggested change

	After being created, streaming pipeline can not be updated, because once a streaming job is running, its configuration
	is immutable. To apply any changes, you must modify the pipeline's definition (e.g., update your code or template)
	and then submit a new job. Essentially, you're creating a new instance of the pipeline with the desired updates.
	For batch pipelines, if the job is running and you want to update its configuration, you must cancel it because
	Dataflow jobs are immutable once they've started. Even though batch pipelines are designed to process finite data and
	eventually finish on their own, you cannot update a running job. If you decide to change any parameters or the
	pipeline logic while it's in progress, you need to cancel the current run and then launch a new job with the updated
	configuration.
	If the batch pipeline has already finished normally, then there's no running job to update—the new configuration
	would only apply to the next job submission.
	Once a streaming pipeline has been created and is running, its configuration cannot be changed because it is immutable. To make any modifications, you need to update the pipeline's definition (e.g., update your code or template), and then submit a new job.Essentially, you'll be creating a new instance of the pipeline with the desired updates.
	For batch pipelines, if a job is currently running and you want to update its configuration, you must cancel the job. This is because once a Dataflow job has started, it becomes immutable. Although batch pipelines are designed to process a finite amount of data and will eventually be completed on their own, you cannot update a job that is in progress. If you need to change any parameters or the pipeline logic while the job is running, you will have to cancel the current run and then launch a new job with the updated configuration.
	If the batch pipeline has already been completed successfully, then there is no running job to update; the new configuration will only be applied to the next job submission.