Data Shaping for Multi-Tenant Database Memory Wear Reduction
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Solution Overview
Problem
Solid-state drives and other non-volatile memory devices experience degraded performance due to memory wear caused by repeated state transitions, such as erase-program cycles and read operations, which can lead to premature failure of memory cells, especially in multi-tenant database systems where these devices are used to maintain numerous datasets.
Innovation Solution
A symbol table is constructed based on entropy attributes of datasets to minimize the number of state transitions that cause memory wear by mapping subsets of data to symbols that are less likely to result in wear, using a minimization-maximization process that identifies optimal bit patterns and write patterns to reduce the impact of state transitions on memory cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If repeated state transitions are performed to maintain datasets on solid-state drives, then data storage and retrieval operations can be performed, but memory wear increases causing degraded operation over time
Solution Approach 1:
The patent changes the parameter of data representation by transforming datasets into alternative representations (such as run-length encoding, variable-length encoding, or reordering operations) that reduce the frequency of state transitions. This allows the same data to be stored and retrieved while minimizing wear on memory cells through parameter transformation of the data structure itself
Solution Approach 2:
The patent introduces dynamic data transformation techniques that adapt the representation of data based on access patterns and wear characteristics. The system dynamically adjusts encoding schemes and storage representations to optimize between retrieval efficiency and wear reduction, making the storage system adaptive to its operational environment
2Adaptability or versatility
If data is stored and retrieved frequently in multi-tenant database systems, then service functionality is maintained, but the number of erase-program cycles increases leading to memory degradation
Solution Approach 1:
The patent segments data into smaller units or blocks that can be independently transformed and stored. By dividing the data into manageable segments, the system can apply different encoding strategies to different segments, reducing overall state transitions while maintaining the flexibility needed for multi-tenant database operations
Solution Approach 2:
The patent performs preliminary data transformation and optimization before storage operations. By pre-processing data to create wear-efficient representations, the system reduces the impact of subsequent read-write cycles, effectively extending memory device lifetime while maintaining service functionality
Data Source
AI summary
A multi-tenant database may maintain a plurality of datasets on a memory device that is subject to degraded operation caused by a subset of possible state transitions within the device's memory cells. A storage engine may identify entropy characteristics of datasets, independently of other datasets hosted on the memory, and use the entropy to construct a symbol table that maps from data within the dataset to symbols that may be stored on the memory device with a minimized number of state transitions.