Abstract: Apparatus, method and storage medium for data query is disclosed. One or more domain-related question-answering pairs, files, and summary information of each file may be pre-stored in a vector database. When receiving the query request from the user, the question-answering system first obtains the associated data of the received query request from the vector database, and the associated data includes the associated question-answering pair and the associated summary information corresponding to the query request. Then, the question-answering system inputs the associated data and the query request into the large language model to obtain an intermediate query result. Finally, if there is summary information matching the intermediate query result in the associated summary information, the file corresponding to the matched summary information is added to the intermediate query result to obtain the query result corresponding to the query request.

Abstract: A retrieval apparatus, a method, and a storage medium are disclosed. The retrieval apparatus includes a memory and a processor, wherein the processor is configured to acquire a retrieval request, and the retrieval request includes the query vector; according to the query vector, generate and execute a first access request corresponding to the first memory according to the first graph index and the index node in the candidate pool; determine and process the data acquired by the first access request corresponding to the first memory, corresponding to the absence of redundant data in the previous storage pool, and store the result in the result pool; and output the data in the result pool corresponding to the candidate pool does not include unreachable index nodes. The retrieval apparatus improves the efficiency of the data reading process and further improves the efficiency of the retrieval process.

Abstract: Apparatus, method and storage medium for data query is disclosed. In the disclosure, the method is applied to a question-answering system including large language model. The question-answering system can store history query information to vector database, and store history query results corresponding to each history query information to scalar database. When receiving the current query request, the question-answering system may first match the current query request with the history query information. If the history query information contains target history query information matching the current query request, the query result of the current query request can be obtained based on the target history query result corresponding to the target history query information.

Abstract: An apparatus, a method, and a storage medium for database query. The apparatus, method, and storage medium are configured to: determine a syntax tree corresponding to an SQL query statement includes a preset subtree, wherein the preset subtree is used to indicate a query mode for querying vector data; determine a query mode according to the preset subtree and the SQL query statement; query data in a database based on the query mode to determine query results. By using an SQL query statement including a preset subtree to query a vector database, to realize an efficient approximate query, so as to avoid high access costs caused by accessing the database by using an API. Moreover, it can reduce user's understanding costs on unstructured query.

Abstract: A data backup method, a data recovery method, and an electronic device are disclosed. The data backup method includes: determining a data set to be backed up, performing a status update operation on a data block in the data set, determining the time points when the data block changes from the first phase to the second phase, and when the data block changes from the second phase to the third phase, and performing data backup on the data set to generate backup files. With this method, upon data seal time point, no fresh data can be reached in any data block, and the data block back-up persists, so that the time point of the data backup operation is more accurate, the cut point of which deleted data should be included in the back up is easy to locate, and the deleted data may be accurately processed.

Abstract: A data backup method, a data recovery method, and an electronic device are disclosed. The data backup method includes: determining a data set to be backed up, performing a status update operation on a data block in the data set, determining the time points when the data block changes from the first phase to the second phase, and when the data block changes from the second phase to the third phase, and performing data backup on the data set to generate backup files. With this method, upon data seal time point, no fresh data can be reached in any data block, and the data block back-up persists, so that the time point of the data backup operation is more accurate, the cut point of which deleted data should be included in the back up is easy to locate, and the deleted data may be accurately processed.

Abstract: The present disclosure relates to the field of computers, and provides an apparatus, a method, and a storage medium for database query, which are applied to a vector database, by acquiring a query request from a user, determining query parameters corresponding to each of multiple shards based on the query request using a preset neural network model, wherein the query parameters control query complexity by affecting a query range of database data of the query request for the corresponding shard; querying database data in each shard based on the query request and the query parameters to obtain a target query result. Accordingly, corresponding query parameters are adjusted for each shard, so that redundant queries are effectively avoided, and database performance is effectively improved.

Abstract: A data query apparatus, method, and storage medium include a database system that determines a data collection and a calculating model corresponding to a received query task request, according to the number of bytes occupied when the data collection or the calculating model is stored, or the number of bit widths occupied when the data collection or the calculating model is transmitted, the database system determines a transmission rate of the data collection or the calculating model. The query task request is transmitted to a model node or a data node with a lower transmission rate, and the data node or the model node with a higher transmission rate is dispatched to perform data calculation.