19 results about "Heapsort" patented technology

The invention relates to a database technology, in particular to a data sorting method, a storage medium and equipment. The data sorting method comprises the steps that to-be-sorted elements and a pre-constructed data structure are obtained, and the data structure comprises a heap structure and a linked list with heap nodes in the heap structure as linked list nodes; based on the first sorting key of the to-be-sorted element, judging whether the to-be-sorted element meets the condition of adding the to-be-sorted element into the linked list or not; and if yes, adding the to-be-sorted elements into the linked list. According to the data sorting method, on the basis of the first sorting key of the to-be-sorted elements, the to-be-sorted elements meeting the conditions can be temporarily stored in the linked list with the heap nodes in the heap structure as the linked list nodes, and the problem that the execution efficiency is low due to the fact that repeated replacement operation is executed on the heap top nodes in the heap sorting process is solved; the node replacement operation in the heap sorting process is reduced, so that the overall sorting execution efficiency is improved, and the performance of a database system is improved.

An apparatus includes interface circuitry, machine readable instructions, and programmable circuitry to at least one of execute or instantiate the machine readable instructions to quantize an input vector having a first precision to generate a quantized vector having a second precision that is lower than the first precision, index the quantized vector using vector clustering, and perform a vector search query for an input query using the quantized vector, the vector search utilizing enhanced heap sorting.

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 invention relates to a database technology, in particular to a data processing method, a storage medium and equipment. The data processing method comprises the steps of obtaining a to-be-sorted data set and a pre-constructed heap structure; each piece of data in the to-be-sorted data set is marked, and different pieces of data correspond to different to-be-sorted marks; recording to-be-sorted marks of all data meeting the condition of adding the heap structure in the to-be-sorted data set; and copying the recorded data corresponding to the to-be-sorted marks. According to the data processing method, the corresponding to-be-sorted mark is set for each piece of to-be-sorted data, the to-be-sorted mark meeting the heap sorting condition is recorded, and only the data corresponding to the recorded to-be-sorted mark is copied, so that the problem of CPU resource waste caused by copying all data in the to-be-sorted data set is avoided, and the data processing efficiency is improved. The copying operation in the heap sorting process is reduced, so that the overall sorting execution efficiency is improved, and the performance of a database system is improved.

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 present invention relates to database technology, and particularly to a data sorting method, a storage medium and a device. The data sorting method includes: obtaining elements to be sorted and a pre-constructed data structure, wherein the data structure includes a heap structure and a linked list with heap nodes in the heap structure as linked list nodes; based on the first sorting key of the elements to be sorted, determining whether the elements to be sorted meet the condition for joining the linked list; if so, adding the elements to be sorted to the linked list. The data sorting method of the present invention can, based on the first sorting key of the elements to be sorted, temporarily store the elements to be sorted that meet the conditions in a linked list with heap nodes in the heap structure as linked list nodes, avoiding the problem of low execution efficiency caused by repeatedly replacing the top node of the heap during the heap sorting process, reducing the node replacement operation during the heap sorting process, thereby improving the overall sorting execution efficiency, and further enhancing the performance of the database system.

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.

The invention discloses a grouped data processing method and equipment based on a distributed database KaiwuDB and a medium, belongs to the technical field of databases, and aims to solve the technical problem of how to increase the data processing capacity of a database and improve the data processing efficiency. According to the technical scheme, a grouped window function is nested in an orderdAggregate by utilizing an execution process of orderdAggregate r, and the data processing efficiency is improved; the method comprises the following steps of: grouping data in a data row by using a window number, replacing a value of a grouping column of the data row by using a window number before executing actual grouping by using an orderdAggregate, performing grouping by using an orderdAggregate grouping characteristic after the value of the grouping column in the row data is replaced by the window number, sorting according to a time column in each node where table data is distributed, and performing heap sorting on the sorted data at a gateway node, a row of data can be sent to an upper layer ordedAggregate by each row of data, and the ordedAggregate is used for carrying out grouping window function calculation on the input ordered data.

The present invention discloses a method and system for scanning data in a time series database sorted by time, which belongs to the field of data scanning technology. The technical problem to be solved is how to optimize the data scanning method and improve the latest and oldest N data in the time series database sorted by time. The method includes the following steps: data storage: for streaming data, partition storage is performed according to timestamps; data query: when querying data, initialize the timestamp ts called, filter the qualified data from the storage partition according to the timestamp ts, and perform bulk sorting on the filtered data.

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 invention discloses a method for realizing a grouping window function timewindow based on a distributed database KaiwDB, belongs to the technical field of databases, and aims to solve the technical problem of how to realize a time window grouping function in the distributed database KaiwDB. According to the technical scheme, sorting is performed according to a time column in three nodes of no de1, node2 and node3 of table data distribution; and performing heap sorting on the sorted data at a gateway node, sending a row of data to an upper orderdAggregate through gRPC in each row of data, and performing grouping window function calculation on the input ordered data by the orderdAggregate.

The present invention discloses a method, system, device and medium for spatiotemporal coding of geographic entities in a real-life three-dimensional system, which belongs to the field of three-dimensional scene technology. The technical problem to be solved by the present invention is how to quickly and accurately perform spatiotemporal positioning and coding of geographic entities in a real-life three-dimensional system, thereby improving the efficiency and accuracy of data processing. The technical solution is as follows: multi-level network division and unique identifier: based on the GeoSOT model, the earth's surface is divided into multi-level and multi-scale grids, and the GB / T 40087-2021 earth space grid coding rules are followed. The grid level is determined by calculating the bounding box size of the geographic entity, and a coordinate binary left shift operation is performed at the coordinates of the entity center point. Combined with Morton code conversion and quaternary conversion technology, a unique grid code containing markers for the northern and southern hemispheres and the eastern and western hemispheres is generated; BTC Beidou segmentation time code; spatiotemporal embedding model; combining Morton code and binary tree coding to optimize spatial data coding; and sorting the spatiotemporal codes through a heap sorting algorithm.

The invention relates to the technical field of data management, and discloses a data encryption method and an encryption query method, comprising encryption uploading at a client and query at a cloud server. The method comprises the following steps: creating a key pair by using a homomorphic encryption method, encrypting data, constructing a security index based on an SAR-Tree structure by taking the encrypted data as a node, and sending the security index to a cloud server for storage. During query, obtaining an encrypted query request, calculating a loose score corresponding to each non-leaf node in the security index, descending by using heap sorting, obtaining a corresponding descending heap, further calculating an accurate score, trimming the descending heap, and obtaining a target encryption result set; and adding each node in the target encryption result set to a preset noise component to obtain a noise vector and an encryption interference point, decrypting the encryption interference point by using a private key to obtain decrypted data, and sending the decrypted data to a client to restore original data. According to the invention, the query efficiency is improved, and the data query security is guaranteed.

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.

The invention discloses a method and system for extracting a support resistance data coal cutting circulation demarcation point, and relates to the technical field of coal mining safety. Comprising the steps of collecting real-time data of a hydraulic support; processing to ensure the integrity and accuracy of the data; fitting the processed data by using a least square method to obtain a fitting function; gaussian filtering processing is adopted to obtain a smooth data function; and traversing a difference value array of the filtering smoothing function and the original fitting function through a heap sorting algorithm, and finding out the first k maximum and non-adjacent difference values and corresponding positions thereof, thereby accurately determining the coal cutting circulation demarcation point. The method effectively solves the problems of poor extraction precision and poor timeliness due to the fact that manual input modes such as frame moving actions are mostly adopted in a traditional method. In addition, the method improves the automation degree of identification of the initial supporting force and the circulating end resistance of the roof in the recovery process, and further promotes the improvement of the intelligent level of roof prevention and control.