3results about How to "Reduce space overhead" patented technology

The embodiment of the invention provides a database fault recovery method and device, equipment, a medium and a program product. The database system comprises a main database and a standby database, the method is applied to the main database, and the method comprises the following steps: in response to a fault recovery request from the standby database, based on a target Bloom filter, determining a changed target data block in a data file corresponding to the target Bloom filter; the target Bloom filter is used for representing that data blocks in the data file change; and sending the target data block to the standby database to enable the standby database to perform fault recovery based on the target data block. The method is used for reducing resource waste of database fault recovery.

The application discloses a kind of program dependence cluster detection methods based on binary set, method is: with binary set form data structure definition dependent set, and input general set operation interface based on bit operation, obtain new dependent set data storage to each instruction node of general set operation interface program, and traverse each instruction node of program;Dependency relationship between instructions is calculated using general set operation interface, and dependency analysis data of each instruction node is obtained;According to the set content in the new set data, the dependency analysis results obtained are reorganized and classified, and the corrected dependency analysis results are obtained to correctly detect the program dependence cluster in program source code.The application defines set data structure with binary set, defines operation interface according to data structure, calculates dependence by calling interface, corrects dependence result, saves the correction result, thereby significantly reduces the space overhead problem during analysis.

This invention relates to a range-filtering nearest neighbor search method, electronic devices, readable storage media, and program products for timely knowledge retrieval of large language models, encompassing computer data retrieval, vector databases, and high-dimensional similarity search technologies. It addresses the challenge of existing technologies in large language model retrieval enhancement scenarios, where handling vector retrieval with ordered attributes makes it difficult to simultaneously balance index size and query efficiency. The method includes database index construction and query phases. By constructing a segmented nearest neighbor graph index based on ordered attribute values ​​and combining it with user-given attribute ranges for efficient vector similarity search and filtering, the timeliness and accuracy of retrieval during the query phase are improved. This invention is primarily used to retrieve external knowledge applied to large language models.