Database Cache File System for Query Acceleration
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Solution Overview
Problem
Large digital information databases, especially those in semantic markup languages like XML, require full parsing and processing to retrieve specific information, which is time-consuming and resource-intensive, affecting software and system performance.
Innovation Solution
Implementing a cache file system that stores subsets of database information along with associated query expressions, allowing software agents to quickly check the cache for requested data using XPath or XQuery expressions, thereby reducing the need to parse the entire database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire database file is parsed and processed to locate and retrieve specific information, then complete and accurate information retrieval is ensured, but time consumption and computer system resource usage increase significantly
Solution Approach 1:
The patent segments the large database file into multiple smaller partition files. Each partition contains a subset of the database records and can be independently processed. This segmentation allows the system to search only relevant partitions rather than the entire database, reducing retrieval time while maintaining complete information coverage through coordinated partition searches.
Solution Approach 2:
The patent creates index files in advance that contain summaries or key information from each partition. These pre-computed indexes enable rapid location of relevant data without parsing the entire database file during query execution. The preliminary indexing action significantly reduces retrieval time while ensuring accurate information location through the pre-organized structure.
2Measurement precision
If the entire database file is parsed and processed to locate and retrieve specific information, then complete and accurate information retrieval is ensured, but computer system resource consumption increases
Solution Approach 1:
The database is divided into multiple partition files that can be processed independently and in parallel. This segmentation reduces the memory and CPU resources required for each individual parsing operation, as the system only needs to load and process relevant partitions rather than the entire database file into memory simultaneously.
Solution Approach 2:
The system performs partial parsing by processing only the necessary partition files based on query criteria, rather than parsing the entire database file. This partial action approach consumes fewer computational resources while still ensuring complete and accurate information retrieval by selectively processing only relevant data subsets.
3Speed
If a cache file system is implemented to store subsets of database information, then information retrieval speed is improved, but device complexity and memory usage increase
Solution Approach 1:
The cache system is segmented into multiple cache files, each corresponding to specific partition files. This segmentation allows the cache structure to mirror the database partitioning, simplifying the caching logic by establishing direct mappings between database partitions and cache files. The segmented approach reduces overall system complexity compared to a monolithic cache while maintaining fast retrieval speeds through targeted cache access.
4Speed
If a cache file system is implemented to store subsets of database information, then information retrieval speed is improved, but memory usage increases
Solution Approach 1:
Database information is divided into multiple partition files, and corresponding cache files store subsets of this partitioned data. This segmentation allows the system to load only the necessary cache partitions into memory based on query requirements, rather than loading entire database or cache files. The memory usage is optimized by processing partitions in manageable chunks while maintaining fast retrieval through cached subset data.
Data Source
AI summary
Embodiments for caching database information are disclosed. A query may specify a set of information to be retrieved from a database file. The database file may be parsed according to the query to retrieve the set of information. The query and the corresponding set of information retrieved from the database file may be stored in a cache file. The cache file may be searched for the query, which may enable the set of information to be retrieved from the cache file. Searching the cache file and retrieving the set of information from the cache file may be faster than searching the database file to retrieve the set of information. The cache file may be associated with a currency token which may indicate whether the cache file is current. The currency token may indicate whether the database file has been updated since being parsed according to the query.