Composite Hash Backup Storage with Localized Addresses
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Solution Overview
Problem
Conventional Content Addressed Storage (CAS) systems face performance issues during backup and restore operations due to the need for multiple seeks across various storage nodes to retrieve unique data elements, which increases the time required for data reconstruction.
Innovation Solution
The system localizes storage of data near corresponding composite or directory elements and records storage addresses with these elements, allowing for reduced seek operations by populating a cache with probabilistically unique identifiers and storage addresses, enabling contiguous retrieval of data during backup and restore processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAS systems store data elements distributed across multiple storage nodes, then data integrity and storage efficiency are improved, but restore performance deteriorates due to multiple seeks across storage nodes
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the storage addresses of all data elements referenced in a composite hash alongside the composite hash itself. This allows the system to prepare all necessary location information in advance, eliminating the need for multiple runtime seeks across storage nodes during restore operations, thus resolving the contradiction between distributed storage integrity and restore performance
2Measurement precision
If CAS systems perform multiple index seeks to retrieve storage addresses for data elements, then data can be located accurately, but backup and restore time increases
Solution Approach 1:
The patent merges the composite hash data structure with the storage address information by appending the addresses of all referenced data elements directly to the composite hash record. This combination eliminates the need for separate index seek operations, as all location information is immediately available with the hash itself, thereby resolving the contradiction between precise data location and time consumption
Data Source
AI summary
In one example, a method may include performance of a hash function on a digital sequence so as to generate a hash value that corresponds to the digital sequence. Next, the digital sequence may be broken into data pieces, and each data piece hashed to produce a corresponding hash value for each data piece. Then, a recipe may be produced that includes instructions which, when executed, may generate the digital sequence from the data pieces referenced by their corresponding hash values included in the recipe. Among other things, the hash values may enable reutilization of redundant data sequences by serving as pointers to the data pieces that the hash values respectively represent.