Data Block Alignment for Storage Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In Elastic Cloud Service (ECS) storage systems, the arbitrary offset of data blocks during storage leads to issues with data validation after garbage collection, where parts of the storage unit become garbage data, making it impossible to validate subsequent data blocks effectively.
Innovation Solution
Aligning data blocks to the boundary of a tracking unit of a predefined size, such as 2 MB, ensures that data validation can be performed and minimizes waste in storage space by using identical metadata for split data blocks, allowing for efficient garbage collection and storage management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data blocks are stored at arbitrary offsets without alignment, then storage space utilization is maximized, but data validation fails after garbage collection because tracking units cannot properly validate aligned data boundaries
Solution Approach 1:
The storage system segments data blocks into fixed-size units that align with tracking unit boundaries. Each data block is divided or padded to ensure its size is a multiple of the tracking unit size, allowing garbage collection to validate data integrity at clear boundaries without crossing into adjacent tracking units.
Solution Approach 2:
The system changes the size parameter of data blocks to be multiples of the tracking unit size. By adjusting block sizes to align with predefined tracking unit boundaries, the system enables reliable validation during garbage collection while maintaining efficient storage management through standardized block dimensions.
2Reliability
If data blocks are aligned to tracking unit boundaries, then data validation during garbage collection becomes reliable, but storage space waste increases due to padding requirements
Solution Approach 1:
The system segments the storage space into tracking units of fixed size and aligns data blocks to these boundaries. When data blocks need to be stored, they are segmented or padded to fit exactly within tracking unit boundaries, ensuring that garbage collection can validate each tracking unit independently without risking data from adjacent units.
Solution Approach 2:
The system modifies the data block size parameter to be a multiple of the tracking unit size. This parameter change ensures that aligned storage is achieved while minimizing padding waste, as blocks are sized to fit efficiently within the tracking unit structure rather than using excessive alignment margins.
3Reliability
If garbage collection validates entire tracking units, then data integrity is ensured, but validation efficiency decreases when data blocks cross tracking unit boundaries
Solution Approach 1:
The system segments data into blocks that align with tracking unit boundaries, ensuring that each data block fits entirely within one or more complete tracking units. This segmentation allows garbage collection to validate entire tracking units independently, improving validation efficiency by avoiding the need to check for partial data blocks that would cross boundaries.
Solution Approach 2:
The system changes the data block size to be a multiple of the tracking unit size, which ensures that data blocks align with tracking unit boundaries. This parameter adjustment enables efficient validation during garbage collection, as the system can validate complete tracking units without worrying about data blocks spilling into adjacent units, thereby improving productivity.
Data Source
AI summary
Embodiments of the present disclosure provide a method and device for storing data. The method comprises: generating a data block corresponding to data to be stored; aligning the data block to a boundary of a tracking unit of a predefined size for validating the data; and storing the aligned data block in at least one storage unit of a storage space, the at least one storage unit having an identical size. The method according to embodiments of the present disclosure can align the data block so as to minimize the waste of storage space and avoid the situation where the rest data cannot be validated due to disappearance of partial data.