For very large (over 10GB) .cub and .feeder files, the time to load, save or process them could be substantially reduced were they partitioned and processed in parallel. For servers with 40 cores, the time savings can be significant.
The obvious use case is to partition by the Time dimension since historical time series data is generally static with only the current and future time periods changing.
During server startup, multiple partitions would be loaded in parallel, respecting the MTQ setting, for both cubes and feeders, even conditional feeders.
During a SAVEDATAALL, only the cube and feeder partitions that had changed would be saved and those would also be saved in parallel respecting the MTQ setting.
During a CubeProcessFeeders operation, the user would have the ability to specify the partitions to generate, or take the default option of ALL.
The benefits to customers is (1) increased application availability, (2) decreased load on network bandwidth during load/save/process feeder operations, and (3) opportunity to adjust the data backup/restore strategy to backup and recover only those partitions of interest.
|Who would benefit from this IDEA?||As a customer, I want to maximize application availability by minimizing the time to save data and rebuild feeders.|
How should it work?
|Priority Justification||High value change to customers to improve application availability. This is a standard RDBMS feature that should already be available in Planning Analytics.|
|Client Name||Werner Co.|
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