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* [ML][Data frame] fixing failure state transitions and race condition (#45627) There is a small window for a race condition while we are flagging a task as failed. Here are the steps where the race condition occurs: 1. A failure occurs 2. Before `AsyncTwoPhaseIndexer` calls the `onFailure` handler it does the following: a. `finishAndSetState()` which sets the IndexerState to STARTED b. `doSaveState(...)` which attempts to save the current state of the indexer 3. Another trigger is fired BEFORE `onFailure` can fire, but AFTER `finishAndSetState()` occurs. The trick here is that we will eventually set the indexer to failed, but possibly not before another trigger had the opportunity to fire. This could obviously cause some weird state interactions. To combat this, I have put in some predicates to verify the state before taking actions. This is so if state is indeed marked failed, the "second trigger" stops ASAP. Additionally, I move the task state checks INTO the `start` and `stop` methods, which will now require a `force` parameter. `start`, `stop`, `trigger` and `markAsFailed` are all `synchronized`. This should gives us some guarantees that one will not switch states out from underneath another. I also flag the task as `failed` BEFORE we successfully write it to cluster state, this is to allow us to make the task fail more quickly. But, this does add the behavior where the task is "failed" but the cluster state does not indicate as much. Adding the checks in `start` and `stop` will handle this "real state vs cluster state" race condition. This has always been a problem for `_stop` as it is not a master node action and doesn’t always have the latest cluster state. closes #45609 Relates to #45562 * [ML][Data Frame] moves failure state transition for MT safety (#45676) * [ML][Data Frame] moves failure state transition for MT safety * removing unused imports