[ML] Restore data counts on resuming data frame analytics #67937
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Now that data frame analytics jobs can be resumed straight into the inference phase, we need to ensure data counts are persisted at the end of the analysis step and restored when the job is started again. This commit removes the need for storing the progress on start as a task parameter. Instead, when the task gets assigned we now restore all stats by making a call to the get stats API. Additionally, we now ensure that an allocated task that hasn't had its `StatsHolder` restored yet is treated as a stopped task from the get stats API, which means we will report the stored stats. Relates elastic#67623
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Pinging @elastic/ml-core (:ml) |
benwtrent
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dimitris-athanasiou
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dimitris-athanasiou
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… (#67979) Now that data frame analytics jobs can be resumed straight into the inference phase, we need to ensure data counts are persisted at the end of the analysis step and restored when the job is started again. This commit removes the need for storing the progress on start as a task parameter. Instead, when the task gets assigned we now restore all stats by making a call to the get stats API. Additionally, we now ensure that an allocated task that hasn't had its `StatsHolder` restored yet is treated as a stopped task from the get stats API, which means we will report the stored stats. Relates #67623 Backport of #67937
dimitris-athanasiou
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Now that data frame analytics jobs can be resumed straight into
the inference phase, we need to ensure data counts are persisted
at the end of the analysis step and restored when the job is
started again.
This commit removes the need for storing the progress on start
as a task parameter. Instead, when the task gets assigned we now
restore all stats by making a call to the get stats API. Additionally,
we now ensure that an allocated task that hasn't had its
StatsHolderrestored yet is treated as a stopped task from the get stats API, which
means we will report the stored stats.
Relates #67623