yashmayya commented on code in PR #13657:
URL: https://github.com/apache/kafka/pull/13657#discussion_r1182756093
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docs/connect.html:
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@@ -301,7 +301,8 @@ <h4><a id="connect_rest" href="#connect_rest">REST
API</a></h4>
<li><code>GET /connectors/{name}/tasks</code> - get a list of tasks
currently running for a connector</li>
<li><code>GET /connectors/{name}/tasks/{taskid}/status</code> - get
current status of the task, including if it is running, failed, paused, etc.,
which worker it is assigned to, and error information if it has failed</li>
<li><code>PUT /connectors/{name}/pause</code> - pause the connector
and its tasks, which stops message processing until the connector is
resumed</li>
- <li><code>PUT /connectors/{name}/resume</code> - resume a paused
connector (or do nothing if the connector is not paused)</li>
+ <li><code>PUT /connectors/{name}/stop</code> - stop the connector and
its tasks, and also remove its tasks from the Connect cluster. This is
different from the paused state where the tasks aren't stopped and removed, but
only suspended.</li>
Review Comment:
> less resource-intensive than pausing the connector
This might be a little tricky to interpret considering that the stop API
triggers a group rebalance and shuts down tasks completely unlike the pause API
so it could be argued that the stop API is a more heavy-weight operation than
the pause API. I get that you meant "less resource-intensive" in terms of tasks
and their allocated resources not sticking around on the cluster unlike in a
paused state, but I'm wondering if there's better terminology we can use here.
What do you think about this instead:
`stop the connector and shut down its tasks, deallocating any resources
claimed by its tasks. This is more efficient from a resource usage standpoint
than pausing the connector, but can cause it to take longer to begin processing
data once resumed.`
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