9 results about "Heapsort" patented technology

This invention relates to the field of information processing technology, and in particular to a gridded interpolation method, apparatus, electronic device, and storage medium that integrates KNN search. It employs a KD-tree with contiguous memory storage and aggregated leaf node storage, which helps reduce memory usage and tree depth. Combined with an improved fast selection algorithm and iterative construction, it can increase tree construction speed and mitigate the risk of recursive stack overflow. By integrating KNN search with heap sort, the nearest neighbor is directly obtained during traversal. Compared to the two-stage method of querying first and then sorting, this reduces intermediate data storage and secondary sorting overhead. This invention improves interpolation speed and reduces memory usage when processing gridded interpolation of millions of scattered points. In typical browser scenarios, it can achieve millisecond-level response times, making it suitable for real-time visualization and rapid analysis in fields such as meteorology, oceanography, and the environment.

The present application relates to a kind of crowd-sourcing worker recommendation method based on ciphertext information.First, the similarity of each crowd-sourcing worker in crowd-sourcing worker set and crowd-sourcing task is calculated, and the crowd-sourcing worker with higher similarity with crowd-sourcing task is more suitable for the crowd-sourcing task;On this basis, we select the array of crowd-sourcing worker with higher similarity;Second, we find high worker ID from the array, and higher reputation value indicates that the crowd-sourcing worker performs well in historical tasks, and the worker with higher reputation value is selected as the final recommendation result by using heap sorting algorithm in the worker matching the requirements of crowd-sourcing task, which can help task requester to find suitable crowd-sourcing worker without revealing privacy.

This invention relates to the field of data management technology and discloses a data encryption method and an encrypted query method, including encrypted upload on the client side and query on the cloud server. A key pair is created using a homomorphic encryption method to encrypt the data. Using the encrypted data as nodes, a secure index based on a SAR-Tree structure is constructed and sent to the cloud server for storage. During querying, an encrypted query request is obtained, the loose score corresponding to each non-leaf node in the secure index is calculated, and heap sort is used to descend the order to obtain the corresponding descending heap. The precise score is further calculated to prune the descending heap, obtaining the target encrypted result set. Each node in the target encrypted result set is added to a preset noise component to obtain the noise vector and encryption interference points. The encryption interference points are decrypted using a private key to obtain the decrypted data, which is sent to the client to restore the original data. This invention improves query efficiency and ensures data query security.

The invention provides a data processing method of a database and a related product. The data processing method comprises the following steps: acquiring a to-be-processed data set, and determining a grouping column and a ranking sequence; grouping tuples of the data set according to the grouping key values of the grouping columns by using the hash table; sorting the tuples in each group by using a heap sorting structure, and taking a preset number of tuples at the sorting head in each group as target tuples; and forming a sorting array by the target tuples in each group to obtain a result set. According to the data processing method, on the premise of ensuring semantic equivalence, the sorting calculation amount and memory occupation in window function query are greatly reduced, the query execution performance and efficiency are improved, and the method is particularly suitable for a high-frequency Top-N scene.

The invention provides a multi-table connection processing method of a database and a related product. The multi-table connection processing method comprises the following steps: acquiring a plurality of tables to be connected; constructing a heap sorting structure; ranking the row data of the plurality of tables to be connected by using a heap ranking structure, and respectively forming candidate result subsets by using the row data with the same connection key value; and determining the candidate result subsets meeting a multi-table connection condition to obtain a multi-table connection result. According to the multi-table connection processing method, the memory and I / O consumption is reduced, the execution efficiency of large-scale data and complex query is remarkably improved, the optimization requirement of the connection sequence is eliminated, the query planning time is remarkably shortened, and the CPU and memory overhead is reduced.

The embodiment of the invention provides a large model service traffic scheduling method and system in a K8S environment, a storage medium and a computer program. According to the large model service traffic scheduling method in the K8S environment, firstly, a model reasoning request is submitted through a unified interface gateway, then target model information and authentication information of the request are extracted, and deployment instances of corresponding model services are automatically identified and matched by analyzing model names in the request. A priority queue algorithm based on the number of tasks is introduced to obtain a service instance with the minimum number of reasoning tasks in current execution in real time to serve as a target instance, the model reasoning request is preferentially allocated to the target instance to achieve concurrency control, and a heap sorting algorithm in a memory is adopted to dynamically maintain the current connection state of back-end model service. And identifying the GPU type of the node and intelligently distributing flow according to a preset flow distribution strategy. The stability, the resource utilization rate and the cost management capability of the large model service are remarkably improved.

Embodiments of the present disclosure provide an event queue scheduling method, device, equipment and medium. The method comprises: in response to an event enqueue request, determining a target bucket matching a target event to be enqueued in an event queue; the event queue is composed of one active bucket, no more than a preset number of alternative buckets, and one default bucket; inserting the target event into the target bucket, and performing heap sorting on events in the target bucket; and in response to an event dequeue request, taking a heap top event from the active bucket of the event queue. Through the above technical solution, the embodiments of the present disclosure reduce the event scheduling complexity based on the total number of events, and improve the scheduling efficiency of the event queue.

The application discloses a key value storage method based on a multi-log structure merge tree, and comprises the following steps: 1, when a read-write request is received by a multi-log structure merge tree (MLSMT), the hash value of a key in the request is used to determine the log structure merge tree (LSMT) to which the key belongs i , and read-write operation is performed on the LSMT i ; 2, when a scanning request is received by the MLSMT structure, a grouping iterator is established for a file in the log structure merge tree, parallel threads are used to perform a key positioning operation (Seek), and a heap sorting is used to find a next key, so that data is read out; 3, a compaction operation is processed by using parallel threads in the background, and data belonging to a current LSMT i is read out from an LSMT i split from the LSMT s and written into an SST file of the LSMT i . The application can realize accelerated writing and merging of data, reduce the number of layers of a single log structure merge tree, and thus improve the read-write performance of a system.

The invention discloses a test case generation method and device, equipment and a medium, and relates to the field of software testing. Comprising the steps of generating an adjacent matrix based on a plurality of functional test points; the adjacency matrix represents the relationship among the functional test points; constructing a test case generation engine by taking the adjacency matrix as a data basis and taking an improved depth-first search algorithm as computational logic; executing a test case generation engine to generate a test case based on a starting function test point and an ending function test point in the plurality of function test points and the constraint parameters; wherein the improved depth-first algorithm is obtained by taking a depth-first search algorithm as a basis, performing heap sorting based on weights among function test points, and adding necessary function test points and necessary function test points for improvement. Through the method provided by the invention, the problems of time consumption and resource exhaustion caused by many digraph nodes in a related test case generation method can be effectively solved.