Deduplicated Data Restructuring for Sequential Storage Access
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data deduplication in storage environments leads to non-sequential data writing, causing increased resource usage and performance issues due to the need for storage devices to frequently seek and read data from disparate locations, which reduces the benefits of deduplication and can result in slowdowns, especially in mechanical drives.
Innovation Solution
Applying analytics to restructure deduplicated data into a more sequential pattern based on read patterns, data movement characteristics, and block move counts, while avoiding unnecessary data movement and disk thrashing, and excluding solid-state drives from these mechanisms to maintain optimal performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is heavily deduplicated with pointers to retained duplicate information, then storage space is significantly reduced, but the storage device must expend additional resources finding, accessing, and reading the information
Solution Approach 1:
The patent applies analytics to deduplicated data blocks to identify candidates for restructuring before actual read operations occur. By pre-analyzing read patterns, data movement characteristics, and block move counts, the system proactively restructures data into more sequential arrangements, eliminating the need for random access during actual reads and thereby improving access speed while maintaining storage efficiency
Solution Approach 2:
The patent dynamically adjusts the restructuring decisions based on observed data characteristics. Analytics continuously monitor read patterns, data movement, and block move counts to determine which deduplicated blocks should be restructured. This dynamic approach allows the system to adapt to changing access patterns and optimize the balance between storage efficiency and access performance in real-time
2Productivity
If analytics are applied to restructure deduplicated data into sequential patterns, then read performance is improved, but unnecessary data movement and disk thrashing may occur
Solution Approach 1:
The patent applies analytics selectively to only those deduplicated data blocks that meet specific criteria indicating they would benefit from restructuring. By using thresholds on read patterns, data movement characteristics, and block move counts, the system avoids applying restructuring to all blocks, thereby reducing unnecessary data movement and resource consumption while still achieving performance improvements for the most beneficial blocks
Solution Approach 2:
The system uses analytics to continuously monitor data access patterns and restructuring effectiveness. By tracking read patterns, data movement, and block move counts, the system receives feedback on which restructure operations are actually improving performance versus those that are causing thrashing. This feedback mechanism allows the system to adjust its restructuring decisions and avoid wasteful operations
3Speed
If data is written sequentially to storage devices, then access performance is optimized, but deduplication creates non-sequential data patterns that require additional seeking
Solution Approach 1:
The patent performs preliminary analysis of deduplicated data blocks to identify candidates for restructuring before read operations occur. By pre-processing the data to identify blocks with beneficial access patterns, the system can proactively restructure them into sequential arrangements, eliminating the need for random seeking during actual reads and thereby restoring the performance benefits of sequential access
Solution Approach 2:
The patent changes the physical arrangement parameter of deduplicated data blocks from random/non-sequential positions to sequential positions on storage devices. By modifying this spatial parameter based on analytics of read patterns and data movement characteristics, the system transforms the data organization from a complex non-sequential structure into a simpler sequential structure that optimizes access speed
Data Source
AI summary
Various embodiments for enhancing storage of deduplicated data in a computing storage environment. Analytics are applied to at least one data storage characteristic observed in the computing storage environment to restructure the deduplicated data in a more sequential manner so as to enhance performance of the computing storage environment. A type of storage device associated with the deduplicated data is monitored, and the analytics are withheld from application when the type of storage device is determined to be a solid-state device. The restructuring of the deduplicated data in the sequential manner is performed by comparing the at least one data storage characteristic against at least one predetermined thresholds, one of the at least one predetermined thresholds prohibiting a particular block of the deduplicated data from being restructured when the particular block of deduplicated data has been previously moved in the computing storage environment within a predefined timeframe.