Datastream Engine for Backup Storage Efficiency
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Solution Overview
Problem
Traditional data backup methods suffer from significant disk overhead and inefficiency due to redundant data storage and the fragmented nature of deduplicated data, especially when dealing with large datasets like those on tape storage systems, which leads to high costs and resource wastage.
Innovation Solution
The datastream engine organizes deduplicated data into a self-contained format with file headers, metadata, and blocks, minimizing the need for multiple reads and allowing for efficient storage and retrieval by maintaining all necessary components in a single datastream, reducing redundancy and disk overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If deduplicated data is stored in a fragmented manner in traditional backup systems, then storage capacity is optimized by removing redundancy, but disk overhead and access time increase due to the need to search across multiple locations
Solution Approach 1:
The patent combines scattered deduplicated data blocks into a single sequential datastream format. Instead of storing blocks分散ly across storage media, the system merges all data blocks, metadata, and file headers into one continuous sequential stream, eliminating the need to search multiple locations and reducing access time while maintaining storage efficiency.
Solution Approach 2:
The system performs preliminary organization of data into a self-contained datastream format during the backup process. By pre-organizing all data blocks, metadata, and file headers into a single sequential structure before storage, the system eliminates the need for subsequent searching and random access operations, reducing both disk overhead and access time.
2Productivity
If traditional backup methods store redundant copies of data, then data retrieval is simpler and faster, but storage capacity is wasted due to duplicate data
Solution Approach 1:
The patent segments data into unique blocks and assigns each block a signature, storing only one copy of each unique block. This segmentation approach eliminates redundant storage while maintaining the ability to efficiently retrieve data by reconstructing files from the unique blocks using the stored metadata and file headers.
3Ease of operation
If searching techniques are used to find data blocks in a database, then data can be located, but the search becomes less efficient as the database size grows
Solution Approach 1:
The system performs preliminary organization of data into a self-contained datastream with embedded metadata and file headers during the backup process. This pre-organization eliminates the need for subsequent searching operations, as all data blocks and their locations are already arranged in sequential order with accompanying metadata, making data location immediate and efficient regardless of data size.
Data Source
AI summary
A method, article of manufacture, and apparatus for efficiently restoring information is disclosed. In an embodiment, this comprises receiving a self-contained datastream and analyzing the self-contained datastream for file headers, corresponding file metadata and corresponding file blocks. Data is then reconstructed based on analyzing the self-contained datastream into reconstructed data, and the reconstructed data is then stored in a storage device. File headers are used to indicate the start of a new file in the self contained datastream. File blocks contain the information necessary to reconstruct the files in the datastream. File metadata describes how to reconstruct the file, such as which file blocks are required for the file, and the location of each file block in the self contained datastream, among others. In an embodiment, the reconstructed data may contain deduped data.