Dictionary for Data Deduplication Using Dual-Hash Keys
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Solution Overview
Problem
Current data deduplication mechanisms face challenges in efficiently managing and storing large amounts of data, with existing dictionaries being limited in computation and storage needs, leading to inefficiencies in resource utilization and data redundancy.
Innovation Solution
The implementation of a dual-hash key system, using a weak hash key in the dictionary and a strong hash key with the deduplicated data, balances uniqueness and space savings, with weak hash values stored in the dictionary and strong hash values stored as metadata, allowing for efficient identification and storage of identical data segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a strong hash key is used in the dictionary to ensure uniqueness, then data integrity is improved, but dictionary size and storage requirements increase significantly
Solution Approach 1:
The hash key is segmented into two parts: a weak hash key stored in the dictionary for quick lookup, and a strong hash key stored with the actual data for verification. This segmentation allows the dictionary to remain compact while still ensuring data integrity through the strong hash key.
Solution Approach 2:
The weak hash key acts as an intermediary in the dictionary that points to the actual data location. Instead of storing strong hash keys throughout the system, the weak hash key serves as a mediator that enables efficient lookup while the strong hash key is only stored where needed for verification.
2Quantity of substance
If a weak hash key is used in the dictionary to reduce storage needs, then space efficiency is improved, but uniqueness guarantee and data integrity are compromised
Solution Approach 1:
The hash key functionality is segmented between weak and strong hash keys. The weak hash key handles the high-frequency operation of dictionary lookup with minimal storage, while the strong hash key handles the critical function of uniqueness verification at the data storage level.
Solution Approach 2:
The weak hash key provides partial hashing functionality sufficient for dictionary lookup operations, while the full strong hash key is applied only when needed for data verification. This partial action approach optimizes performance for common operations while maintaining integrity for critical operations.
3Quantity of substance
If comprehensive data deduplication is implemented to eliminate all duplicates, then storage efficiency is improved, but computation time and processing overhead increase
Solution Approach 1:
The deduplication process is segmented into two stages: first using weak hash keys for rapid initial filtering and identification of potential duplicates, then using strong hash keys only for verification of identified candidates. This segmentation dramatically reduces computation time by avoiding full strong hash computations for all data segments.
Solution Approach 2:
The system skips the computationally expensive strong hash computation for data segments that don't match on the weak hash key level. By rushing through the filtering stage with weak hashes, the system efficiently eliminates non-duplicates without performing full verification on every segment.
Data Source
AI summary
Mechanisms are provided for efficiently improving a dictionary used for data deduplication. Dictionaries are used to hold hash key and location pairs for deduplicated data. Strong hash keys prevent collisions but weak hash keys are more computation and storage efficient. Mechanisms are provided to use both a weak hash key and a strong hash key. Weak hash keys and corresponding location pairs are stored in an improved dictionary while strong hash keys are maintained with the deduplicated data itself. The need for having uniqueness from a strong hash function is balanced with the deduplication dictionary space savings from a weak hash function.