81results about How to "Improve indexing efficiency" patented technology

The invention relates to a method for making real-time roaming and zooming operations on a vector map in the mobile navigation equipment. Aiming at the defect of the prior art that the vector map can not be roamed and zoomed in real time, the invention provides a method for making real-time roaming and zooming operations on the vector map in the mobile navigation equipment. The key points of the technical proposal include: a, the vector map is pre-treated; b, according to geometrical characteristics of essential objects in the vector map, a model is built; c, according to different importance of the essential objects, display grading is divided; d, a quad tree index system structure is established, wherein the structure includes a first grade index file and a second grade index file; e, by utilizing the first grade index file, the province-level map file and the second grade index file are indexed, and by the second grade index file, the external storage address of the map data in the vector map file is obtained; and f, according to the external storage address in the vector map file, the map data are found and loaded to display. The method has the advantages of making the roaming and zooming operations on the vector map in real time.

The invention discloses a multi-scale road flow visual analysis method based on taxi GPS data. The method comprises the following steps: 1, taking an overview, i.e., first of all, extracting GPS data of a taxi, and analyzing road flow information; 2, performing filtering selection from different scales; and 3, performing detail presentation, wherein this step specifically comprises a Road Over View, a road bidirectional Line Chart and a visualization assembly describing a specific road flow speed.

The invention discloses a safe context organizing structure and a maintaining method in broadband wireless metropolitan area network base station medium accessed to a control system. The organizing structure comprises a connection identifiers hashtable which is used for managing the context of authorization keys and a safety association identifying hashtable which is used for managing the context of communication secret keys. The maintaining method operates on the connection identifiers hashtable and the safety association identifying hashtable respectively when can authenticate the expandable authentication agreement to terminals, when in the process of safety association-communication encryption secret key shaking hands and when terminals distributes secret keys and create service flow. The invention can realize the organization and maintenance of safety context and high-speed searching. When terminals are in large number and the data amount is large, the maintaining efficiency of data can be improved to a large extent.

The invention relates to a data retrieving and ordering method for an electrical power system. The data retrieving and ordering method comprises the following steps: (1) storing data by virtue of a distributed file system; (2) establishing a professional knowledge relevant synonym participle lexicon; (3) establishing full-text index for data; (4) carrying out retrieving and ordering in a parallelization manner; and (5) realizing the fuzzy matching of multiple retrieved fields. According to the method, the storing, retrieving and ordering of the data are realized in a parallel computing manner, so that the rapid retrieving is realized; by defining a professional word segmentation system, the indexing efficiency is improved; by virtue of a full-text retrieval manner and a distributed retrieval manner, the retrieval speed of a non-standard text is increased; by retrieving self-learning and synonym definition of a keyword, the fuzzy retrieval is realized; and the synonym lexicon is utilized for intelligently identifying situations of abbreviation of terms, nonstandard filling and the like, so that the business Integrity of a retrieval result is guaranteed. The method is simple and practical, the data of a relation database can be directly imported, and the distributed storage and the data index can be automatically established, so that rapid deployment and multi-scene application are realized.

An embodiment of the invention provides a database indexing method and device. The method comprises receiving a database operation requirement through a database, performing indexing operation on key values to be operated in the database according to the database operation requirement, wherein the database is in a T-Tree data structure, each node in the T-Tree stores the key values through a binary tree structure, and accordingly, indexing can be performed according to the T-Tree data structure, the binary tree structure of each node in the T-Tree when indexing is performed on the key values to be operated in the database, and the indexing efficiency in the database is improved.

The embodiment of the invention discloses a video frame storage management method, a related device and a related communication system. The video frame storage management method can include the steps that a video server receives a fist video data packet, searching is conducted to find out whether an index record used for identifying the mapping relation between a first video frame and a storage address is stored in an index storage region or not,, and the first video data packet is written in a first storage space to which the first storage address contained in the first index record points if the index record used for identifying the mapping relation between the first video frame and the storage address is found out to be stored in the index storage region, wherein the first video data packet belongs to the first video frame, the first storage space belongs to the video data storage region. According to the technical scheme, the improvement of the efficiency of the storage address of the index video frame is facilitated.

The invention belongs to the technical field of scientific research data management. The invention discloses a scientific research data management control system and method based on a block chain technology. The scientific research data management control system based on the blockchain technology comprises a scientific research data acquisition module, a data splitting and cleaning module, a datacalibration module, a data statistics module, a data classification module, a data feature extraction module, a data analysis module, a data block chain construction module, a block index module, a web crawler management module, a data storage module and a display module. By means of the block index module, operation resources and time can be saved and the scientific research data block index updating efficiency is improved; after the block is packaged, the block head information of the block is broadcasted to the block chain network through the block chain storage module, and the content of the whole block is not broadcasted, so that the broadcast content is reduced, and the network transmission pressure is reduced; and the block information is stored by using the distributed storage network, so that the storage pressure of a single node is reduced.

The invention discloses an ElasticSearch-based data indexing method and a device, computer equipment and a storage medium. The method comprises the steps: setting a main fragment based on a distributed search engine ElasticSearch, and writing data into the main fragment; aiming at the data of each main fragment, respectively creating an index task, importing the corresponding index fragment into the main fragment according to the type of the index task, and creating an index; if a data query request instruction is detected, performing index query on the index fragments through each node serverto obtain the index data volume of each node server; combining the index data volume of each node server to obtain a total index data volume; and if it is detected that the total index data volume exceeds a preset numerical value, indexing in a preset mode. The invention also relates to the blockchain technology. Index data is stored in the blockchain. According to the method, the data indexing efficiency is improved for mass data of hundreds of T or above.

The invention discloses a method for indexing data in a storage engine and a related device. Target affairs are indexed by acquiring indication data. Determining a first index table in a first storageengine according to the target transaction; determining at least one second index table configured in a second storage engine according to the first index table; and determining index data corresponding to the data index condition in the first storage engine from the second index table. Therefore, the cross-storage-engine data indexing process is achieved, due to the fact that the development complexity introduced by a new storage engine is reduced, code reuse of multiple storage engines is achieved, and the indexing efficiency of a database is improved.

The invention provides a data coding unification method for a hospital heterogeneous system, which comprises the following steps of: creating an index library, importing standard data, setting standard codes in the standard data, and creating an index library corresponding to the standard data; importing the source data of the hospital heterogeneous system, wherein to-be-unified codes are arranged in the source data; unifying the codes, wherein the source data matches with the index library to establish a mapping relation between the standard codes and the codes to be unified. The invention relates to a data coding unification system of a hospital heterogeneous system, electronic device and a readable storage medium. According to the method, the source data codes of the heterogeneous systems can be compared with the unified standard codes, the heterogeneous data codes are converted into the unified standard codes to be stored and applied, data mapping can be rapidly positioned and completed, the indexing efficiency is high, information exchange between the heterogeneous systems is achieved, and high-efficiency operation management of hospitals is facilitated.

The invention discloses a data sharing platform based on a block chain. The data sharing platform comprises a block chain data sharing platform, a node management unit and a plurality of node servers,the plurality of node servers are in interactive communication connection with the blockchain number sharing platform through a node management unit; the node server comprises a data real-time accessmodule and a data subscription access unit. The real-time access module is used for sending a data access request to the node management unit in real time. Data customization access sharing is achieved, a subscription mechanism is determined through a user, asynchronous data service is conducted, detection statistics is conducted on service node data flow, data access is conducted in the smooth data flow time period to obtain data and cache the data, then the data is fed back to the user when the user needs, the data flow access peak value is reduced, the efficiency of real-time data access sharing is improved, and efficient and extensible information acquisition of a user is realized.

The invention provides touch control equipment and a display control method and device of a 3D rotary plate. The method includes the steps of detecting a touch point position of a touch operation, converting a displacement vector of the touch point of the touch operation in a screen coordinate system into a displacement vector in a work coordinate system, determining the turning direction and the rotation speed of the 3D rotary plate according to a direction parameter and the displacement vector in the world coordinate system, wherein the direction parameter is determined according to the relationship of the touch operation and the focus point of the 3D rotary plate, and controlling rotation display of the 3D rotary plate on a screen according to the determined rotation direction and the rotation speed of the 3D rotary plate. Based on the method, a user can achieve rotation control of the 3D rotary plate at any position, and good man-machine interaction experience is achieved.

The invention provides a dictionary indexing method for implementing space optimization through 16-bit Trie trees. The method comprises the following steps: generating a dictionary index of the 16-bitTrie tree; inputting a to-be-operated keyword key according to a user; and indexing according to the current state of the keyword key. Dictionary data of the 16-bit Trie tree is constructed under a mapping table structure, it can be ensured that the complexity is not changed basically while the space of the Trie tree is optimized, the speed of construction and indexing of a dictionary and the speed of modifying and deleting are increased, the keyword key can be searched quickly, moreover, the dictionary indexing of the 16-bit Trie tree is realized with the aid of the mapping table, and the problems that a common double-array Trie tree dictionary index is constructed complicatedly, and a dictionary cannot be modified at any time and cannot be traversed can be solved. By the dictionary algorithm, the dictionary can be modified and traversed at any time, sequencing can be implemented while construction, and after specific optimization, the dictionary algorithm can be used as an index fora file system or photos.

The invention provides a data block processing method, device and equipment, and a storage medium. A target storage unit corresponding to a target logic address is determined through the target logicaddress of a to-be-processed target data block, the target storage unit comprises bitmap information, and the bitmap information is used for representing whether a data block corresponding to each logic address in a plurality of logic addresses corresponding to the target storage unit is a repeated data block or not. Furthermore, a target physical address corresponding to the target logic addressis determined according to a flag bit corresponding to the target logic address in the bitmap information, the flag bit is used for representing whether the target data block is a repeated data blockor not, and the target data block is processed according to the target physical address. Under the condition of storing a large amount of data, the indexing efficiency of the target data block can beeffectively improved, so that the application of a deduplication technology in a large-capacity storage system is promoted.

The invention discloses a spatial range query method based on an extensible learning index, and the method comprises the following steps: 1) performing data preprocessing: sorting spatial objects according to Hilbert coded values of coordinates, and extracting the Hilbert coded value of each piece of data and the position of the data as training data; 2) constructing an extensible multi-layer space learning index, training a multi-layer model, learning data distribution of a space object, and adding a cache region for data insertion and update operation; 3) performing a spatial range query operation based on the extensible multilayer learning index; after the data is sorted according to the Hilbert coding values, dividing the query range into a plurality of subareas according to the characteristics of the Hilbert curve; for each subarea, predicting the position of the data through the multi-layer learning index, traversing the corresponding cache region, and searching the data fallingin the query range. According to the method, machine learning and a space filling curve are fused into a space index, and an effective space range query method is designed according to a data distribution rule.

The invention discloses a MapReduce and inverted Thiessen polygon-based large-scale neighbor query method, belongs to the field of cloud computation and big data, and aims at improving index efficiency of existing data query method. The method comprises the following steps of: S1, constructing a MapReduce-based inverted Voronoi index; and S2, partitioning a data set R and a data set S by using theinverted Voronoi index, and carrying out distributed kNN query by using MapReduce-based IVKNN. The method has the effects of improving the algorithm index efficiency and enabling MapReduce to be notinfluenced by space and time.

The invention provides a FLASH memory and a storage file management method. The FLASH memory is used for writing, reading or deleting files. The FLASH memory includes a FLASH memory area, which is divided into a plurality of pages starting from a number 0 in the smallest unit of FLASH erasing. The FLASH memory area includes a boot area for describing information of the FLASH memory; a storage pagevolume comprising a plurality of items, wherein the address order stored by each item corresponds to the item number, each item is used for storing the page number of the next storage page of file data, and the item numbers correspond to the page numbers of the corresponding storage pages one by one; a file description volume used to describe the information of a storage file, wherein the information of the storage file includes: file information and the starting page number of the file; and a file data storage area used to store the file data. The FLASH memory and the storage file managementmethod provided by the invention can reduce the storage space required for the storage page volume and improve the index efficiency.

The invention discloses a large-scale neighbor query system based on MapReduce and an inverted Thiessen polygon and belongs to the fields of cloud computing and big data. The system is used for improving indexing efficiency of existing data query methods. The system is technically characterized in that multiple instructions are stored in the system, and the instructions are suitable for being loaded and executed in a processor, wherein inverted Voronoi indexes based on MapReduce are constructed; the inverted Voronoi indexes are used to perform partitioning on a dataset R and a dataset S; and an IVKNN based on MapReduce is used to perform distributed kNN query. The system has the advantages that algorithm indexing efficiency can be improved, and MapReduce is no longer influenced by space and time.

The invention provides a multi-level index method and device for data of an audio fingerprint database in order to solve the technical problems that in the prior art, the searching performance of massive audio fingerprint databases is low, and the number of calculation times is larger during comparison searching. The method comprises the steps that the value data bit of each audio fingerprint in the data of the fingerprint database is segmented into an index part and a fingerprint data part, and the index part is a multi-level index; all levels in the index parts point to the next level through a pointer; the pointer at the final level of the index parts is pointed to the fingerprint data parts. The device comprises a device body used for segmenting the value data bit of each audio fingerprint in the data of the audio fingerprint database into the index part and the fingerprint data part, a device body used for pointing all the levels in the index parts to the next level through the pointer and a device body used for pointing the pointer at the final level of the index parts to the fingerprint data parts, wherein the index parts are the multi-level indexes.

The invention discloses an indexing method and device for large-scale point cloud data, terminal equipment and a medium. The indexing method comprises the following steps: reading point cloud data from a local hard disk, wherein the point cloud data is that a spatial feature data structure of a target file is stored in a local hard disk by taking a file name form as an entry of an index; calculating a minimum bounding box vertex of the point cloud data to obtain X-axis, Y-axis and Z-axis coordinates of the maximum bounding box and the minimum bounding box; constructing a file index table according to the coordinates; and directionally extracting target point cloud data from the file index table, the target point cloud data being that the processing pressure of a computer memory can be reduced, and the indexing efficiency of large-scale point cloud data is improved.