Gap Filter Sorting for Dataset Summary Metadata
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Solution Overview
Problem
Existing sorting techniques and summary information methods are computationally expensive and require large amounts of storage, leading to inefficiencies in determining whether a particular value is present in a dataset.
Innovation Solution
The use of a gap filter, which represents a sorted set of unique values with gaps, allowing for efficient determination of value presence through a compressed representation that balances compressibility and false positive results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sorting techniques are used to create summary information, then the accuracy of determining value presence is improved, but the computational cost and time consumption increase
Solution Approach 1:
The patent applies preliminary action by pre-sorting the dataset once to create summary information (min, max, and gap filter) before queries are executed. This preliminary sorting enables rapid query evaluation without requiring repeated sorting operations, thus resolving the contradiction between accurate value presence determination and time consumption.
Solution Approach 2:
The patent extracts only the essential sorting results needed for query evaluation - specifically the minimum value, maximum value, and gap information - rather than maintaining fully sorted data. This extraction approach provides sufficient accuracy for determining value presence while significantly reducing the computational burden compared to complete sorting.
2Measurement precision
If detailed summary information is created to reduce false positives, then the precision of value presence determination is improved, but the storage requirements increase
Solution Approach 1:
The patent applies local quality by creating a gap filter that focuses storage resources on capturing only the critical gap information between consecutive sorted values, rather than storing all individual data points. This localized approach to storing difference information achieves high precision in value presence determination while minimizing storage requirements.
Solution Approach 2:
The patent transforms the storage representation from storing all individual data values to storing derived parameters (gaps between consecutive values). This parameter transformation reduces the quantity of stored information while maintaining or improving the precision of value presence determination, as the gap structure efficiently encodes the distribution characteristics of the data.
3Productivity
If comprehensive summary information is maintained for all datasets, then the ability to answer queries efficiently is improved, but the overhead for creating and maintaining summary information increases
Solution Approach 1:
The patent employs cheap short-living objects by using lightweight gap filter structures that require minimal computational resources to create and maintain. These simplified summary information structures can be quickly generated and updated, making them suitable for datasets where full sorting would be prohibitively expensive, thus improving query evaluation efficiency without excessive overhead.
Data Source
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AI summary
The present disclosure provides techniques and solutions for sorting data. In a particular implementation, a sorting technique is provided that places values in a sorted order by adding an offset value to values that are not in a sorted order. The resulting sorted set of values is not truly sorted, in that the set of modified values is sorted, but the underlying data itself is not sorted. In another implementation, a sorting technique can use multiple streams or sets. When an out of order element is encountered, it can be added to a new stream, if such a stream is available. The sorting techniques can be used for a variety of purposes, including provided sorted data for use in generating summary data, or for providing sorted data to be used in determining an intersection between two datasets.