[ML] Use disk storage for forecasting large models#36
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hendrikmuhs wants to merge 10 commits intoelastic:masterfrom
hendrikmuhs:forecast-scale-rebase
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[ML] Use disk storage for forecasting large models#36hendrikmuhs wants to merge 10 commits intoelastic:masterfrom hendrikmuhs:forecast-scale-rebase
hendrikmuhs wants to merge 10 commits intoelastic:masterfrom
hendrikmuhs:forecast-scale-rebase
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added 8 commits
April 5, 2018 11:24
Re-factor minimumSeasonalVarianceScale to make it available as method. This is required in order to restore models from a file stream, more precisely it is required as a parameter for maths::CModelParams which is required for maths::SModelRestoreParams
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Moving into a feature branch, replaced by #59 |
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This implements the C++ side of forecast persistence. An additional parameter allows the forecast runner to persist models on disk for temporary purposes. Models are loaded back into memory one by one.
For models smaller than the current limit of 20MB nothing changes.
X-Pack part: elastic/x-pack-elasticsearch#4134
replaces #22
Only formating changes after #15, no logical changes compared to #22