Deduplication Bit Array Partition for Zero False Positives
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Solution Overview
Problem
Current data deduplication methods, such as those using bloom filters, are resource-intensive and prone to false positives due to collisions, leading to inefficiencies in storage and processing.
Innovation Solution
The creation of deduplication bit array partitions that track data items using sequential numeric identifiers, allowing for efficient identification and deletion of duplicates, reducing memory usage and eliminating false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bloom filter with multiple hash operations is used for data deduplication, then collision prevention is improved, but storage space requirement increases
Solution Approach 1:
The patent divides the deduplication tracking into multiple independent bit array partitions, where each partition handles a specific range of data item identifiers. This segmentation allows the system to use smaller, more memory-efficient structures while maintaining comprehensive coverage of all data items through ordered processing across partitions.
Solution Approach 2:
The patent changes the fundamental parameter of the deduplication structure from hash-based bloom filter bits to direct-addressing bit array partitions. Each partition uses sequential bit positions that directly correspond to data item identifiers, eliminating the need for multiple hash operations and reducing false positives to zero while maintaining linear memory growth.
2Reliability
If bloom filter with multiple hash operations is used for data deduplication, then false positive rate is reduced, but processing complexity increases
Solution Approach 1:
The patent segments the data stream into ordered partitions based on identifier ranges, processing each partition sequentially. This eliminates the need for multiple hash operations per data item, reducing processing complexity to simple bit array lookups while achieving zero false positives through direct addressing.
Solution Approach 2:
The patent creates a simplified copy of the deduplication mechanism that uses direct bit array indexing instead of hash-based bloom filters. This copying approach replaces complex hash computation with simple integer-to-index mapping, dramatically reducing processing complexity while maintaining accuracy.
3Reliability
If conventional deduplication methods are used, then data accuracy is maintained, but resource consumption increases
Solution Approach 1:
The patent segments the deduplication process into ordered bit array partitions that process data items in identifier sequence. This segmentation enables efficient memory utilization and reduces the computational overhead per data item, lowering resource consumption while maintaining complete accuracy through direct addressing.
Solution Approach 2:
The patent replaces the mechanical hash computation system with a direct-addressing bit array system. Instead of performing multiple hash operations for each data item, the system directly computes the bit array index from the data item identifier, substituting complex computational mechanics with simple arithmetic indexing to reduce resource consumption.
Data Source
AI summary
Efficient data deduplication is described herein. A deduplication bit array partition can be created that corresponds to a number of data items in an expected dataset. The deduplication bit array partition can track whether the data items have been received. When a data item in the expected dataset is received, a bit in the deduplication bit array partition corresponding to the received data item can be accessed to determine, based on the value of the bit, if the received data item has already been received. When the value of the bit indicates that the received data item has not already been received, the value can be changed to indicate that the data item has now been received. When the value of the bit indicates that the received data item has already been received, the data item can be deleted or ignored.