Composite Data Store Indexing with Speed-Up Filtering
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Solution Overview
Problem
Traditional search engines require significant processing power when searching large datasets and often need to filter results across multiple repositories, leading to inefficiencies in data retrieval, especially in environments with limited resources like handheld devices.
Innovation Solution
Implementing a composite data store with a speed-up data structure that eliminates unnecessary comparisons by using a multi-level bit reduction structure or offset correlation table to efficiently filter and search data across selected repositories, allowing for targeted searches within specific data stores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional search engines use Boolean searching with indexes to search for records containing multiple terms, then search functionality is achieved, but processing power requirements increase significantly when index entries are dense
Solution Approach 1:
The patent divides the search process into two distinct phases: a filtering phase that operates on index entries to identify candidate records, and a verification phase that checks actual record contents. This segmentation allows the system to perform preliminary filtering with lower processing power while reserving intensive verification for only the necessary records, thereby reducing overall processing power requirements while maintaining search functionality.
Solution Approach 2:
The patent performs preliminary filtering actions by first processing index entries to identify candidate records before actually verifying their contents. The system pre-processes the index structure to determine which records might contain the search terms, allowing the more resource-intensive verification step to be applied only to a subset of records rather than all records, thus reducing total processing power consumption.
2Adaptability or versatility
If traditional search engines search across multiple repositories as a composite repository and filter results based on selected repositories, then comprehensive search capability is achieved, but additional filtering operations increase processing requirements
Solution Approach 1:
The patent segments the search operation by repository by maintaining separate index entries for each repository while using a unified search interface. The system processes index entries individually for each selected repository, allowing comprehensive multi-repository search capability while managing processing power through selective processing of only the repositories the user has chosen to search.
Solution Approach 2:
The patent performs preliminary identification of which repositories to search based on user selections before executing the full search. By determining the scope of search across multiple repositories in advance, the system can allocate processing resources more efficiently, focusing computational power only on the selected repositories rather than processing all repositories uniformly.
3Productivity
If a composite data store combines multiple data stores sequentially with address ranges, then efficient data storage is achieved, but determining which data stores to search requires additional comparisons
Solution Approach 1:
The patent performs preliminary processing of the composite data store structure by pre-establishing the sequential address ranges and index entries for each constituent data store. This preliminary organization allows the search system to quickly identify which data stores need to be searched without performing extensive comparisons during the actual search operation, reducing search time while maintaining efficient storage.
Solution Approach 2:
The patent adds an index dimension to the composite data store structure, organizing data not only by sequential address ranges but also by creating index entries that map search terms to specific data stores and record positions. This dimensional addition allows the system to navigate the composite structure more efficiently, reducing the number of comparisons needed to determine which data stores to search while preserving the sequential storage efficiency.
Data Source
AI summary
Data stores are combined into a composite data store. A method includes referencing a first index entry for a user specified first parameter pattern. The first index entry includes references to record addresses for records in the composite data store which include the first parameter pattern. A first beginning composite data store address of a first selected data store is referenced. A determination is made that the first beginning composite data store address is at or above an address at or above a predetermined threshold above the first record address. Based on determining that the first beginning composite data store address is at or above a predetermined threshold above the first record address, a speed-up data structure is used to eliminate one or more comparisons of record entries in the first index entry between the first record address and the first beginning composite data store address.