Celestial object retrieval methods, devices, electronic equipment, and storage media

Abstract

This application provides a method, apparatus, electronic device, and storage medium for astronomical data retrieval. The astronomical data retrieval method may include: obtaining the number of grid cells in the initial retrieval; determining the number of grid cells in the initial retrieval to obtain the current grid cell count; merging the current grid cells when a shrinkage condition is met to obtain the number of grid cells at the upper N level after shrinkage, until the number of grid cells at the upper N level does not exceed a grid threshold; expanding the current grid cells when an expansion condition is met to obtain the number of sub-grid cells at the lower M level after expansion, and removing sub-grid cells at the lower M level that do not contain retrieval results to obtain the effective grid cell count, until the number of grid cells at the lower M level equals the grid threshold; and retrieving celestial bodies corresponding to the unique identifier of the current grid cell in the database according to the unique identifier of the current grid cell, and presenting the celestial bodies.

Description

Technical Field

[0001] This invention relates to the field of computer simulation technology, and in particular to a celestial object retrieval method, apparatus, electronic device, and storage medium. Background Technology

[0002] Currently, celestial cone retrieval defines the search area using the celestial coordinates of the celestial body, determines the center point using right ascension (RA) and declination (DEC), and then delineates the range using a specified search radius (SR), thereby retrieving celestial target information within the cone-shaped area.

[0003] In related technologies, a certain level, such as level 10, is pre-established for celestial bodies. Users know the level number of the celestial body. By inputting the celestial body and its level number, all numbers within that level are determined for retrieval. Specifically, the healpix unique identifier of the celestial body and its celestial coordinates (right ascension (ra) and declination (dec)) are calculated. Based on the celestial body and its level number, a grid unique identifier is calculated. Finally, a search is performed in the database to identify the celestial body corresponding to the grid unique identifier and present it to the user.

[0004] However, if the grid unique identifier exceeds the grid threshold for star retrieval input, the index becomes invalid and retrieval cannot be performed. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for celestial object retrieval.

[0006] This application provides a method for retrieval of astronomical data, including:

[0007] A preliminary search is performed based on the specified celestial body and the specified search radius input by the user, to obtain the number of grid cells in the preliminary search.

[0008] The number of grid cells retrieved in the initial search is determined to obtain the current number of grid cells.

[0009] If the number of grids in the current grid reaches the shrinkage condition, multiple consecutive grids in the current grid are merged to obtain the number of grids at the next higher level after the current grid is shrunk, until the number of grids at the next higher level does not exceed the grid threshold.

[0010] If the current grid size reaches the expansion condition, the current grid is further divided to obtain the number of sub-grids at the next M level after the current grid is expanded. Sub-grids that do not contain search results are removed from the number of sub-grids at the next M level to obtain the effective number of grids, until the number of sub-grids at the next M level is equal to the grid threshold; the sub-grids at the next M level are multiple consecutive grids.

[0011] Based on the unique identifiers after the current grid is expanded and / or shrunk, a search is performed in the database to obtain the celestial bodies corresponding to the unique identifiers of the current grid, and then they are presented.

[0012] Furthermore, the step of further dividing the current grid to obtain the number of sub-grids at the next M level after the current grid is expanded includes: further dividing the current grid in a direction from the edges of all preliminary search grids to the centers of all preliminary search grids to obtain the number of sub-grids at the next M level after the current grid is expanded.

[0013] And / or,

[0014] The step of merging multiple consecutive grids of the current grid to obtain the number of grids at the upper N level after shrinking the current grid includes: merging multiple consecutive grids of the current grid in a direction from the center of all initially retrieved grids to the edge of all initially retrieved grids to obtain the number of grids at the upper N level after shrinking the current grid;

[0015] And / or,

[0016] The unique identifier after the current grid is expanded and / or shrunk includes the unique identifier of each grid level; the step of retrieving the celestial body corresponding to the current grid unique identifier in the database according to the unique identifier after the current grid is expanded and / or shrunk, and then presenting it, includes: performing multi-level indexing in the database according to the unique identifier of each level, associating the celestial body corresponding to the unique identifier of each level, and then presenting it.

[0017] Furthermore, the shrinkage condition includes a difference between the number of grids initially retrieved and the grid threshold that satisfies a reduction level difference value;

[0018] The method further includes:

[0019] Based on the difference value of the reduction level, determine the total number of reduction levels N; the N 1; The difference in the reduction level is positively correlated with N;

[0020] Based on the total number of reduction levels N, determine the Nth power of the number of single contractions as the number of the multiple consecutive grids;

[0021] The step of merging multiple consecutive grids in the current grid to obtain the number of grids at the next higher level after the current grid is shrunk includes:

[0022] The number of consecutive grids in the current grid is merged according to the Nth power of the single merging number, resulting in the number of grids at the Nth level above the current grid after shrinking.

[0023] Furthermore, the expansion condition includes a difference between the number of grids initially retrieved and the grid threshold that satisfies an increased level of difference.

[0024] The method further includes:

[0025] Based on the difference value of the elevation level, the total number of elevation levels M is determined; the M 1; The difference in the level of elevation is positively correlated with M;

[0026] Based on the total number of levels M of the elevation level, determine the power of M of the number of single expansions as the number of the multiple consecutive grids;

[0027] The step of further subdividing the current grid to obtain the number of lower M-level subgrids after the current grid expansion includes:

[0028] The current grid is further divided into multiple continuous grids according to the M-th power of the single expansion number, to obtain the number of M-level sub-grids after the current grid is expanded.

[0029] Furthermore, the current grid's grid size reaches the shrinkage condition, including the initial search's grid size exceeding the grid threshold input for celestial body retrieval; when N is 1, correspondingly, merging multiple consecutive grids of the current grid to obtain the number of grids at the next higher level after shrinkage, until the number of grids at the next higher level does not exceed the grid threshold, includes:

[0030] Merge multiple consecutive grids in the current grid to obtain the number of grids in the previous level after shrinking the current grid;

[0031] Based on the number of the previous level grid after the current grid shrinkage, determine whether the number of the current grid after shrinkage does not exceed the grid threshold;

[0032] If the number of grids exceeds the grid threshold, then return to the previous step of merging multiple consecutive grids of the current grid to obtain the number of grids in the next higher level after the current grid is shrunk, until the number of grids in the current grid after shrinking does not exceed the grid threshold.

[0033] Furthermore, the current grid's grid count reaches the expansion condition, including the initial search grid count being lower than the grid threshold for celestial body search input; when M is 1, correspondingly, the current grid is further divided to obtain the number of sub-grids at the next M level after the current grid expansion, and sub-grids without search results are removed from the number of sub-grids at the next M level to obtain the effective grid count, until the number of sub-grids at the next M level equals the grid threshold, including:

[0034] The current grid is further divided to obtain the number of sub-grids at the next level after the current grid is expanded;

[0035] Based on the number of sub-grids at the next level after the current grid expansion, determine whether the number of grids after the current grid expansion is equal to the grid threshold;

[0036] If not equal, return to the step of further dividing the current grid to obtain the number of sub-grids at the next level after the current grid is expanded, and remove the sub-grids that do not contain search results from the number of sub-grids at the next level to obtain the number of valid grids, until the number of grids after the current grid is expanded is equal to the grid threshold.

[0037] Furthermore, the step of retrieving the celestial body corresponding to the current grid's unique identifier in the database according to the unique identifier after the current grid expansion and / or contraction includes: indexing the databases of multiple storage nodes in the distributed storage according to the unique identifier after the current grid expansion and / or contraction to obtain the celestial body corresponding to the current grid's unique identifier;

[0038] And / or,

[0039] The preliminary search based on the specified celestial body and the specified search radius input by the user, to obtain the number of grid cells for the preliminary search, includes: converting the specified celestial body input by the user into celestial coordinates; and performing a preliminary search based on the celestial coordinates of the specified celestial body and the specified search radius to obtain the number of grid cells for the preliminary search.

[0040] This application provides a celestial object retrieval device, comprising:

[0041] The preliminary search module is used to perform a preliminary search based on the specified celestial body and the specified search radius input by the user, and to obtain the number of grids in the preliminary search.

[0042] The current grid cell count acquisition module is used to determine the number of cells in the initial search and obtain the current grid cell count.

[0043] The grid shrinking module is used to merge multiple consecutive grids of the current grid when the number of grids in the current grid reaches the shrinking condition, to obtain the number of grids at the next higher level after the current grid is shrunk, until the number of grids at the next higher level does not exceed the grid threshold.

[0044] The grid expansion module is used to further divide the current grid when the number of grids in the current grid reaches the expansion condition, to obtain the number of sub-grids at the next M level after the current grid is expanded, and to remove sub-grids that do not contain search results from the number of sub-grids at the next M level to obtain the effective number of grids, until the number of sub-grids at the next M level is equal to the grid threshold; the sub-grids at the next M level are multiple consecutive grids.

[0045] The celestial body retrieval output module is used to search the database according to the unique identifier after the current grid is expanded and / or shrunk, and to obtain the celestial bodies corresponding to the unique identifier of the current grid for presentation.

[0046] This application provides an electronic device including one or more processors for implementing the method described in any of the preceding claims.

[0047] This application provides a computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the method described in any of the preceding claims.

[0048] This application provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the method described in any of the preceding claims.

[0049] In some embodiments, the astronomical data retrieval method of this application determines the number of grid cells in the initial retrieval. When the number of grid cells in the initial retrieval exceeds the grid cell threshold input for celestial body retrieval, multiple consecutive grid cells in the initial retrieval grid are merged to obtain the number of grid cells at the next higher level for the current grid. This process continues until the number of grid cells at the next higher level does not exceed the grid cell threshold input for celestial body retrieval, thereby reducing the number of grid cells by shrinking the grid. In this way, the grid cells are merged and shrunk to be equal to or lower than the grid cell threshold input for celestial body retrieval, satisfying the grid requirements of the celestial body retrieval input and completing the celestial body retrieval.

[0050] Furthermore, when the initial search grid count falls below the grid threshold for celestial body retrieval, the initial search grid is further divided to obtain the number of sub-grids at the next M-level after grid expansion. Sub-grids without search results are removed from this expanded M-level sub-grid count to obtain the effective grid count, thus increasing the overall grid count through expansion. Removing sub-grids without search results results in fewer effective searches, faster retrieval, and more accurate search results. Attached Figure Description

[0051] Figure 1 The diagram shown illustrates spatial retrieval segmentation at different pixel levels in the astronomical data retrieval method of this application embodiment.

[0052] Figure 2 The diagram shown is a flowchart of the astronomical data retrieval method provided in an embodiment of this application;

[0053] Figure 3a As shown Figure 2 The user input and search result display interface for the astronomical data retrieval method shown;

[0054] Figure 3b As shown Figure 2 The astronomical data retrieval method shown is based on distributed storage using healpix ID;

[0055] Figure 4 As shown Figure 3a A schematic diagram illustrating the preliminary retrieval process of the astronomical data retrieval method shown;

[0056] Figure 5 As shown Figure 3a The diagram illustrates the segmented retrieval method used in astronomical data retrieval.

[0057] Figure 6 As shown Figure 2 A schematic diagram of grid shrinkage in the astronomical data retrieval method shown;

[0058] Figure 7 As shown Figure 2 A schematic diagram of grid expansion in the astronomical data retrieval method shown;

[0059] Figure 8 As shown Figure 1 The search results for astronomical data are shown below;

[0060] Figure 9 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this application. Detailed Implementation

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of this specification. Rather, they are merely examples of apparatuses and methods consistent with some aspects of one or more embodiments of this specification as detailed in the appended claims.

[0062] It should be noted that the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification in other embodiments. In some other embodiments, the methods may include more or fewer steps than described in this specification. Furthermore, a single step described in this specification may be broken down into multiple steps in other embodiments; and multiple steps described in this specification may be combined into a single step in other embodiments.

[0063] With the development of science and technology, astronomy has entered a new era of data explosion and information abundance. Multi-band data is growing rapidly, with observations conducted across gamma rays, X-rays, ultraviolet, optical, infrared, and radio bands. The volume of astronomical data is enormous, reaching the petabyte (PB) level. Therefore, efficient retrieval of astronomical data has become a pressing issue in the field of astronomy.

[0064] Currently, celestial data retrieval can be achieved through celestial region retrieval. Celestial region retrieval can be exemplified by celestial cone retrieval. This celestial cone retrieval defines the search area using the celestial coordinates of celestial bodies, determines the center point using right ascension (RA) and declination (DEC), and then delineates the range using a specified search radius (SR), thereby retrieving celestial target information within that cone-shaped region.

[0065] In related technologies, a certain level, such as level 10, is pre-established for celestial bodies. Users know the level number of the celestial body. By inputting the celestial body and its level number, all numbers within that level are determined for retrieval. Specifically, the healpix unique identifier of the celestial body and its celestial coordinates (right ascension (ra) and declination (dec)) are calculated. Based on the celestial body and its level number, a grid unique identifier is calculated. Finally, a search is performed in the database to identify the celestial body corresponding to the grid unique identifier and present it to the user.

[0066] However, if the unique identifier of the grid exceeds the grid threshold for celestial body retrieval input, the index becomes invalid, and retrieval cannot be performed. Furthermore, the retrieval results provided by searching the grid using the celestial coordinates of the celestial body and a specified search radius in related technologies are inaccurate.

[0067] To address the technical problems of index failure and inaccurate search results provided by the search grid in the aforementioned related technologies, this application provides an astronomical data retrieval method. By judging the number of grids in the initial search, when the number of grids in the initial search exceeds the grid threshold input for celestial body retrieval, multiple consecutive grids in the initial search grid are merged to obtain the number of grids at the next higher level. This process continues until the number of grids at the next higher level does not exceed the grid threshold input for celestial body retrieval, thereby reducing the number of grids through grid shrinking. In this way, by merging and shrinking the grids to a value equal to or lower than the grid threshold input for celestial body retrieval, the grid requirements for celestial body retrieval are met, thus completing the retrieval of celestial bodies.

[0068] Furthermore, when the initial search grid count falls below the grid threshold for celestial body retrieval, the initial search grid is further divided to obtain the number of sub-grids at the next M-level after grid expansion. Sub-grids without search results are removed from this expanded M-level sub-grid count to obtain the effective grid count, thus increasing the overall grid count through expansion. Removing sub-grids without search results results in fewer effective searches, faster retrieval, and more accurate search results.

[0069] Figure 1 The diagram shows spatial retrieval segmentation at different pixel levels in the astronomical data retrieval method of this application embodiment.

[0070] like Figure 1 As shown, Healpix (Hierarchical Equal Area isoLatitude Pixelization) is a spherical mesh generation scheme applied in astronomy, which efficiently and uniformly divides a sphere into meshes of equal area. Healpix refines the mesh level by level through recursive splitting, forming a hierarchical structure. For example, the hierarchical structure may include 16 levels. Level 0 has the lowest resolution (12 meshes), while level 1 has a higher resolution (12 meshes). There are 4 grids, and so on, with level 15 being the highest resolution, totaling 1,288,491,888 grids. For example... Figure 1 The Healpix segmentation at different pixel levels is shown. Under Healpix's Nested (Nested OrderingScheme) mode, the number of grids at each resolution level increases according to the following formula:

[0071]

[0072] in, This refers to the resolution level of Healpix, also known as the level. The number of grids at each resolution level and the total number of grids at each level of each hierarchy are shown in Table 1 below:

[0073]

[0074] For numbering the grids in Table 1 above, Healpix uses two main grid numbering methods: Nested mode and Ring (Ring Ordering Scheme) mode. Nested mode recursively arranges the grids in a tree structure, facilitating quick access and neighbor pixel lookup. The Nested numbering rule is illustrated using grid numbering at level 0 as an example; the initial 12 basic pixels are numbered from 0 to 11.

[0075] Based on the above content, the level number increases from 2 to 15. The upgrade after the current grid expansion in this application is based on the current grid level in Table 1 above, i.e., the level number increases, also known as down 1 level or down M levels. The downgrade after the current grid contraction refers to the downgrade based on the current grid level in Table 1 above, i.e., the level number decreases, also known as up 1 level or up N levels. Please refer to the following text for details on upgrades and downgrades.

[0076] Figure 2 The diagram shown is a flowchart of the astronomical data retrieval method provided in an embodiment of this application.

[0077] like Figure 2 As shown, this astronomical data retrieval method may include, but is not limited to, the following steps 110 to 150:

[0078] Step 110: Perform a preliminary search based on the specified celestial body and the specified search radius input by the user to obtain the number of grid cells for the preliminary search.

[0079] The retrieval methods described in this article may include, but are not limited to, at least one of the following: Cone Search and Square Search. Cone Search is an astronomical data query method used to retrieve celestial object data within a specific sky region. This method returns celestial object information within that region based on user-provided specified celestial objects (typically right ascension RA and declination Dec) and the search radius. Cone Search is applied to large-scale astronomical databases such as SDSS (Sloan Digital Sky Survey), Gaia (Global Astrometric Interferometer for Astrophysics), and 2MASS (Two Micron All-Sky Survey) to support the selection, cross-matching, and statistical analysis of specified celestial objects in astronomical research.

[0080] The aforementioned designated celestial body can be referred to as the target celestial body, and is used to retrieve information about celestial bodies within a radius around this target celestial body.

[0081] Step 120: Determine the number of grids initially retrieved to obtain the current number of grids.

[0082] Step 130: When the number of grids in the current grid reaches the shrinkage condition, merge multiple consecutive grids in the current grid to obtain the number of grids at the next higher level after shrinkage, until the number of grids at the next higher level does not exceed the grid threshold, so as to perform downgrading after shrinkage of the current grid.

[0083] The shrinkage condition in this paper indicates that the current grid has a large number of grid cells (i.e., exceeding the grid threshold or far exceeding the grid threshold), and grid cells need to be merged to reduce the number of grid cells. Here, "far exceeding" means that the difference between the current grid cell number and the grid threshold (also known as the difference value) is relatively large, and the current grid cell number is much greater than the grid threshold.

[0084] Where N represents the number of contraction levels, and N is a value greater than or equal to 1. In this specification, merging can be performed based on the number of single contractions. For example, the number of single contractions can be, but is not limited to, containing 4, multiples of 4, etc. N and (integer multiples of 4) N At least one of the following. Thus, every 4 adjacent consecutive grids are merged, or every multiple of 4 adjacent consecutive grids are merged, or every 4 adjacent consecutive grids at each level (also called per level) are merged, or every 4 adjacent consecutive grids at each level are merged.

[0085] The above N-level subgrids can include the 1st-order subgrid of the current grid, the 2nd-order subgrid of the current grid, the 3rd-order subgrid of the current grid, and so on. They will not be listed one by one here.

[0086] The aforementioned grid threshold refers to the threshold at which the number of grid cells reaches the required number for retrieval after grid shrinking and / or expanding. This grid threshold can be a value set according to user requirements, or it can be a threshold determined through multiple trials.

[0087] Step 140: If the number of grids in the current grid reaches the expansion condition, the current grid is further divided to obtain the number of sub-grids at the next M level after the current grid is expanded. Sub-grids that do not contain search results are removed from the number of sub-grids at the next M level to obtain the effective number of grids, until the number of sub-grids at the next M level is equal to the grid threshold. The sub-grids at the next M level are multiple continuous grids to upgrade the current grid after expansion.

[0088] The expansion condition in this paper is used to indicate that the current grid has a small number of grid cells (i.e., below or far below the grid threshold), and further grid division is needed to increase the number of grid cells. Here, "far below" means that the difference between the grid threshold and the current grid cell number (also called the difference value) is relatively large, and the current grid cell number is much smaller than the grid threshold.

[0089] Where M represents the number of expansion levels, and M is a value greater than or equal to 1. The implementation of further subdividing the current mesh in step 140 can be: one implementation is to further subdivide one mesh in the current mesh; another implementation is to further subdivide multiple meshes simultaneously.

[0090] The aforementioned M-level subgrids can include the 1st-order subgrid of the current grid, the 2nd-order subgrid of the current grid, the 3rd-order subgrid of the current grid, and so on, which will not be listed here.

[0091] Of course, there is no limitation on the order of execution of steps 130 and 140 in this application. Step 130 can be executed before or after step 140.

[0092] Step 150: Search the database according to the unique identifier after the current grid is expanded and / or shrunk to obtain the star corresponding to the unique identifier of the current grid for presentation.

[0093] In step 150, the search can be further performed in the database according to the unique identifier after the current grid is expanded and / or shrunk, to obtain the star corresponding to the unique identifier of the current grid, which is called the grid star; and for the distance between each grid star and the specified star (also known as the great circle distance calculation), the grid stars within the search radius with the specified star as the center are selected and presented.

[0094] Among them, great circle distance calculation can refer to calculating the distance between every two stars in the grid.

[0095] The unique identifier in this article is used to indicate the uniqueness of the grid, and can refer to a unique number, such as id.

[0096] Step 150 may further include indexing the database of multiple storage nodes in the distributed storage according to the unique identifier after the current grid expansion and / or contraction, to obtain the star corresponding to the unique identifier of the current grid.

[0097] Based on the shrinking in step 130 above, step 150 includes retrieving the celestial body corresponding to the unique identifier of the current grid after shrinking from the database, and then presenting it. And / or, based on the expansion in step 140 above, step 150 includes retrieving the celestial body corresponding to the unique identifier of the current grid after expansion from the database, and then presenting it.

[0098] Combination Figure 3a The interface shown depicts the user's search input and the display of search results. For example... Figure 3a As shown, the search radius is converted from the input of a specified celestial body, such as M76, and the input angle of 1 degree. The default level is 10.

[0099] Because astronomical star catalogs are generally quite large, often exceeding one billion entries, single-table storage is difficult to implement and suffers from single-machine performance bottlenecks. This application's embodiment employs a distributed storage solution, which can resolve this single-machine performance bottleneck issue.

[0100] Combination Figure 3a and Figure 3b As shown, firstly, for each row of celestial data, multiple healpix IDs (also called grid IDs, auxiliary indexes, with only one column) are calculated based on its right ascension (ra) and declination (dec). These represent the grid position number of each row of celestial data at different resolutions. Referring to Table 1, this paper can store levels 3 to 15, where levels 3 to 15 refer to levels 3 to 15 for each celestial body. Then, using the 10-level healpix ID as the distribution key, the star catalog data, such as the global table, is distributed as evenly as possible to different storage nodes, such as host 1, host 2, and host 3, etc. Sharding is based on grid identifiers. For example, grid data with the same ID are uniformly distributed to the same host. That is, grid ID 1 is uniformly distributed to one host, and grid ID 2 is uniformly distributed to another host.

[0101] For example, the above distribution key may initially be around 1 degree, and may eventually output stars within a grid of 1 degree.

[0102] In this embodiment, by judging the number of grids in the initial search, when the number of grids in the initial search exceeds the grid threshold input for celestial body retrieval, multiple consecutive grids in the initial search are merged to obtain the number of grids at the next higher level, until the number of grids at the next higher level does not exceed the grid threshold input for celestial body retrieval, thereby reducing the number of grids by shrinking the grids. In this way, the grids are merged and shrunk to be equal to or lower than the grid threshold input for celestial body retrieval, satisfying the grid requirements input for celestial body retrieval and completing the celestial body retrieval.

[0103] Figure 4 As shown Figure 3a The diagram illustrates the preliminary retrieval process of the astronomical data retrieval method.

[0104] like Figure 4 As shown, step 110 above may further include, but is not limited to, converting the specified celestial body into celestial coordinates based on the specified celestial body input by the user; performing a preliminary search based on the celestial coordinates of the specified celestial body and the specified search radius to obtain the number of grids for the preliminary search.

[0105] The specified search radius is used to determine the range of the celestial sphere search. This specified search radius is expressed in degrees, and the search can generally start from degrees 10.

[0106] In this embodiment of the application, the preliminary search can determine a preliminary search range, and further searches can be carried out by judging the number of grids in the preliminary search.

[0107] Continue as Figure 4 The preliminary search shown is also called the pre-filtering operation. During the search, a pre-filtering operation is first performed. Within a specified search radius and point coordinates (the sphere radius is specified as 100m or 100km (degrees), all grid IDs that might include search results are pre-calculated (the initial screening process is similar). Here, the point coordinates and search radius are variable. Specifically, based on the specified search radius, a spherical disk is drawn, spanning multiple grids. All grid IDs touched by the spherical disk are collected. All other celestial bodies within the specified search radius from the designated celestial body will fall within the grids touched by the spherical disk; that is, the collected grid IDs contain all search results. Specifically, as shown... Figure 4 As shown, the target is a circle, the celestial body (also called a star) is the circle's radius, and the celestial body's coordinates and distance (i.e., the search radius) are also shown. This may result in omissions or additions.

[0108] Figure 5 As shown Figure 3a The diagram illustrates the segmented retrieval method for astronomical data retrieval.

[0109] like Figure 5 The sharded search shown is as follows: shards include shard 1, shard 2, ..., shard n. n represents the total number of shards, determined by the grid data. After pre-filtering, the grid IDs containing all search results are filtered out. Therefore, subsequent searches (such as steps 130 to 150) only need to be performed within the grid IDs of the search results, i.e., searching across different shards, greatly narrowing the search scope and improving search speed.

[0110] When the initial search grid count is lower than the grid threshold for celestial body retrieval, the initial search grid is further divided into expanded Level 1 sub-grids to increase the total number of grids. Level 1 sub-grids that do not contain search results are then removed, resulting in the effective number of grids. This process of removing Level 1 sub-grids without search results reduces the number of effective searches, leading to faster and more accurate retrieval results.

[0111] Theoretically, during retrieval, a higher grid resolution results in a finer division of the celestial sphere (also known as celestial bodies), leading to a smaller area of ​​all possible grids containing results. This means a more precise retrieval range and therefore faster retrieval speed. However, in practice, the list of values ​​for the `IN` clause in a query is finite and cannot be expanded indefinitely. Therefore, the adaptive retrieval method is as follows: 1. First, a baseline resolution is selected. For most searches, the number of grids used in the retrieval results will not exceed the limit. 2. If the number of grids in the retrieval results exceeds the limit, a grid scaling operation is performed to constrain it within the grid limit. 3. If there is a significant difference between the number of grids in the retrieval results and the grid threshold, a grid expansion operation is performed to progressively bring it closer to the grid threshold.

[0112] To address this, the following grid shrinking or further grid merging can be performed: When the number of grids is too small after cross-level merging, or when the number of grids is too small during the initial search, grid expansion (i.e., further dividing the grid) can be used to increase the number of grids to an appropriate level to improve search accuracy. When the number of grids is too large after cross-level expansion, or when the number of grids is too large during the initial search, grid shrinking (i.e., merging grids) can be used to reduce the number of grids to an appropriate level to improve search feasibility. See below for details.

[0113] Figure 6 As shown Figure 2 A schematic diagram of grid shrinkage in the astronomical data retrieval method shown.

[0114] like Figure 2 and Figure 6As shown, step 130 above can adopt at least one of the following optional embodiments to merge multiple consecutive grids of the current grid to obtain the number of grids at the next higher level after the current grid is shrunk:

[0115] In a first optional embodiment of step 130, multiple consecutive grids of the current grid are merged in a direction from the center of all preliminary search grids to the edge of all preliminary search grids to obtain the number of grids at the upper N level after the current grid is shrunk.

[0116] Here, the aforementioned edge refers to the outermost edge of the initial search grid. This edge can include at least any one of the four diagonal edges, or at least any one of the two lateral edges. Of course, the aforementioned edge can be at the default edge position, or it can be at a randomly selected edge position.

[0117] Continue as Figure 6 As illustrated, the aforementioned edge can start from the bottom right corner for merging, merging 4 grids at a time. Specifically, when the number of grids in the search results exceeds the grid threshold, a grid shrinking method needs to be used to reduce the number of grids to within the threshold range. A greedy strategy is used: every 4 small grids are shrunk to a larger grid at the next higher resolution level. If, after shrinking at the current resolution level, the result is still not constrained to the threshold range, the process continues recursively to the next higher resolution level until the search requirements are met.

[0118] In this embodiment, the merging process proceeds outward from the center to the edge. Since the center contains adjacent grids in all directions, these adjacent grids can be considered as continuous grids. Therefore, the continuous grids to be merged can be obtained more effectively and quickly, and the merging can be achieved.

[0119] Related technologies use fixed-level grids for retrieval. Due to the large number of grids, such as over ten thousand, the system cannot execute, resulting in errors and excessive resolution. In contrast, this embodiment reduces the resolution by shrinking the current grid and decreasing its number. Furthermore, the shrinking process during grid merging reduces the number of grids being retrieved, thereby reducing the number of "in" clauses (maximum 3000) in the SQL (Structured Query Language) clauses that prevents SQL statement execution. Here, "in" is a keyword used to determine if a value exists in a specified set.

[0120] See also Figure 6As shown, the shrinkage conditions in this paper may include, but are not limited to, the difference between the number of grids initially retrieved and the grid threshold satisfying a reduction level difference value.

[0121] The difference between the number of grid cells initially retrieved and the grid threshold refers to the degree of difference between the two. The difference is positively correlated with N. For example, a larger difference leads to a larger N, and a smaller difference leads to a smaller N.

[0122] The aforementioned shrinkage conditions may also include, but are not limited to, the difference between the number of grids during further retrieval (also known as the number of grids in the retrieval results) and the grid threshold satisfying a reduction level difference value. The reduction level may include, but is not limited to, downgrading to adjacent levels (also known as skipping levels) or upgrading to multiple levels (also known as crossing levels).

[0123] The method of this application embodiment can be executed cyclically from step 130 to step 150 until the desired celestial body is retrieved.

[0124] Accordingly, the above method may also include, but is not limited to, the following steps (1) to (2):

[0125] (1) Determine the total number of reduction levels N based on the difference value of the reduction level; the N 1; The difference value of the reduced level is positively correlated with N.

[0126] The difference value for the aforementioned reduction level refers to the difference between the number of grids being higher than the grid threshold.

[0127] (2) Determine the number of single contractions to the power of N according to the total number of reduction levels N, which is the number of the multiple continuous grids.

[0128] In this article, the number of single shrinkages refers to the number of consecutive grids merged each time.

[0129] Based on this, in the second optional embodiment of step 130, multiple consecutive grids of the current grid are merged according to the Nth power of the number of merges in a single merge, to obtain the number of grids at the upper N level after the current grid is shrunk.

[0130] Since the initial search count is too large to handle, and to avoid situations where execution is impossible, the initial search count is compared to a grid threshold to determine the degree of difference between the two. When the difference is significant, cross-level merging can be selected. This improves merging efficiency.

[0131] Of course, in this process, it is possible to skip one level or two levels (including two) or more. The specific number of grids retrieved initially is related to the difference between the grid threshold and the value of the difference.

[0132] In a second optional embodiment of step 130 above, the size of the cross-level can be adaptively determined according to the degree of difference between the number of grids initially retrieved and the grid threshold, so as to perform grid merging, thereby reducing the number of grids retrieved more effectively and quickly.

[0133] like Figure 6 As shown, in one embodiment, the current grid number reaches the shrinkage condition, including the number of grids initially retrieved exceeding the grid threshold of the star retrieval input; when N is 1, the corresponding step 130 above may include, but is not limited to, the following steps [1] to [4]:

[0134] [1] Merge multiple consecutive grids in the current grid to obtain the number of grids in the previous level after the current grid is shrunk;

[0135] [2] Based on the number of the previous level grid after the current grid shrinkage, determine whether the number of the current grid after shrinkage does not exceed the grid threshold;

[0136] [3] If the grid threshold is exceeded, return to the step of merging multiple consecutive grids of the current grid to obtain the number of grids of the next higher level after the current grid is shrunk, until the number of grids after the current grid is shrunk does not exceed the grid threshold.

[0137] [4] If equal, then perform the next step 150 to retrieve the star corresponding to the current grid unique identifier in the database according to the unique identifier of the current grid and present it.

[0138] Figure 7 As shown Figure 2 A schematic diagram of grid expansion for the astronomical data retrieval method shown.

[0139] like Figure 2 and Figure 7 As shown in step 140 above, at least one of the following optional embodiments can be used to further divide the current mesh to obtain the number of lower M-level sub-mesh after the current mesh expansion:

[0140] In a first optional embodiment of step 140, the current grid is further divided in a direction from the edges of all preliminary search grids toward the center of all preliminary search grids to obtain the number of lower M-level subgrids after the current grid is expanded.

[0141] Continue as Figure 7As illustrated, the aforementioned edge can start from the bottom right corner for further subdivision, dividing into 4 grids at a time. Specifically, when the number of grids in the search results is far below the grid threshold, a grid expansion operation is required to subdivide large grids, making the grid range of the search results more precise and smaller, thereby significantly improving search speed. Specifically: 1. Sort the grids in descending order according to the number of celestial bodies within each grid. 2. Expand the grids sequentially, dividing a large grid into four smaller grids, while removing smaller grids containing no results. 3. If, after step 2, the number of grids still differs significantly from the grid threshold, continue expanding to the next resolution level.

[0142] In this embodiment, since the edges are more likely to contain no search results, expanding from the edges makes it easier to remove grids that do not contain search results. This makes it faster to reduce the number of searches, obtain the amount of data to be searched more effectively, and improve the search speed more efficiently.

[0143] Continue as Figure 7 As shown, the expansion condition includes a difference between the number of grids initially retrieved and the grid threshold that satisfies an escalation level difference. Furthermore, the expansion condition may also include, but is not limited to, a difference between the number of grids in further retrieval (also known as the number of grids in the retrieval results) and the grid threshold that satisfies an escalation level difference. This escalation level may include, but is not limited to, upgrading from adjacent levels (also known as skipping levels) or upgrading from multiple levels (also known as crossing levels).

[0144] This method may also include, but is not limited to, the following steps 1) to 2):

[0145] 1) Determine the total number of elevation levels M based on the difference values ​​of the elevation levels; the M 1; The difference in the level of elevation is positively correlated with M.

[0146] The difference value for the aforementioned increase level refers to the difference when the number of grids is less than the grid threshold.

[0147] 2) Determine the number of expansions to the power of M based on the total number of the elevation levels M.

[0148] In this article, the number of single expansions refers to the number of consecutive grid cells added each time.

[0149] Based on this, in the second optional embodiment of step 140, the multiple consecutive grids of the current grid are further divided according to the M-th power of the single expansion number to obtain the number of sub-grids of the next M level after the current grid is expanded.

[0150] In this embodiment, the number of grids increases by 1,000 or 2,000 each time the level changes. The number of grids varies depending on the level (9, 10, 11) and the distance. The greater the distance, the fewer grids are needed to index the data and satisfy the index input.

[0151] In a second optional embodiment of step 140 above, the size of the cross-level can be adaptively determined according to the degree of difference between the number of grids initially retrieved and the grid threshold, so as to further divide the grid and thus improve the accuracy of retrieval more effectively and quickly.

[0152] like Figure 7 As shown, in one embodiment, the current grid number reaches the expansion condition, including the initial search grid number being lower than the grid threshold of the star search input; when M is 1, the above step 140 may further include, but is not limited to, the following steps 1] to 4]:

[0153] 1] Further divide the current grid to obtain the number of sub-grids at the next level after the current grid is expanded;

[0154] 2] Based on the number of sub-grids at the next level after the current grid expansion, determine whether the number of grids after the current grid expansion is equal to the grid threshold;

[0155] 3] If not equal, return to the step of further dividing the current grid to obtain the number of sub-grids at the next level after the current grid is expanded, and remove the sub-grids that do not contain search results from the number of sub-grids at the next level to obtain the number of valid grids, until the number of grids after the current grid is expanded is equal to the grid threshold.

[0156] 4] If equal, then proceed to the next step 150, which involves retrieving the celestial body corresponding to the current grid's unique identifier from the database and presenting it.

[0157] Figure 2 , Figure 6 and Figure 7 As shown, the unique identifier after the current grid expansion and / or contraction includes the unique identifier of each level of the grid; the above step 150 may include, but is not limited to, performing multi-level indexing in the database according to the unique identifier of each level of each grid, associating the celestial bodies corresponding to the unique identifier of each level of the grid, and presenting them.

[0158] Each celestial body has a corresponding number at each level, enabling the association between each level and the celestial body. This allows for indexing across multiple levels (i.e., multi-level indexing) using a celestial body and its unique grid identifier. Therefore, compared to the slower and less accurate single-index search of related technologies, this application is more convenient and efficient.

[0159] Thus, since each level has a unique grid identifier, indexing can begin at each level independently, rather than starting from the first level and indexing level by level. This improves indexing efficiency and allows for the rapid retrieval of celestial bodies corresponding to unique identifiers.

[0160] Figure 8 As shown Figure 1 The search results for astronomical data retrieval are shown below.

[0161] like Figure 8 As shown, the performance of the retrieval method was evaluated on the Gaia DR3 dataset (a total of 181,093,017 celestial objects). The dataset was partitioned based on HEALPix level 10 IDs and distributed across 5 computing nodes. In the initial 12 large grids, 10 celestial objects were randomly selected from each large grid, for a total of 120 objects, for cone search, with a search radius of 1 degree. SELECT LIMIT and SELECT COUNT queries were executed during the evaluation, and the average value was used for analysis. From... Figure 8 The search time was significantly improved, and the statistical results show that the search speed was significantly improved after optimization.

[0162] Based on the same inventive concept as the above method, this application also provides an astronomical data retrieval device, which may include the following modules:

[0163] The preliminary search module is used to perform a preliminary search based on the specified celestial body and the specified search radius input by the user, and to obtain the number of grids in the preliminary search.

[0164] The current grid cell count acquisition module is used to determine the number of cells in the initial search and obtain the current grid cell count.

[0165] The grid shrinking module is used to merge multiple consecutive grids of the current grid when the number of grids in the current grid reaches the shrinking condition, to obtain the number of grids at the next higher level after the current grid is shrunk, until the number of grids at the next higher level does not exceed the grid threshold.

[0166] The grid expansion module is used to further divide the current grid when the number of grids in the current grid reaches the expansion condition, to obtain the number of sub-grids at the next M level after the current grid is expanded, and to remove sub-grids that do not contain search results from the number of sub-grids at the next M level to obtain the effective number of grids, until the number of sub-grids at the next M level is equal to the grid threshold; the sub-grids at the next M level are multiple consecutive grids.

[0167] The celestial body retrieval output module is used to search the database according to the unique identifier after the current grid is expanded and / or shrunk, and to obtain the celestial bodies corresponding to the unique identifier of the current grid for presentation.

[0168] As one embodiment, the astronomical data retrieval device further includes:

[0169] The shrinkage condition includes a difference between the number of grids initially retrieved and the grid threshold that satisfies the difference value of the reduction level;

[0170] The device further includes:

[0171] The downgrade level determination module is used to determine the total number of downgrade levels N based on the difference value of the downgrade levels; the N 1; The difference in the reduction level is positively correlated with N;

[0172] The contraction quantity determination module is used to determine the Nth power of the single contraction quantity according to the total number of reduction levels N, which is the number of the multiple consecutive grids;

[0173] The grid shrinking module includes a grid shrinking submodule, which is used to merge multiple consecutive grids of the current grid according to the Nth power of the single merging quantity, to obtain the number of grids at the Nth level after the current grid is shrunk.

[0174] As one embodiment, the astronomical data retrieval device further includes: the expansion condition includes a difference value between the number of grids initially retrieved and the grid threshold that satisfies an increased level of difference value;

[0175] The device further includes:

[0176] The escalation level determination module is used to determine the total number of escalation levels M based on the difference value of the escalation levels; the M 1; The difference in the level of elevation is positively correlated with M;

[0177] An expansion quantity determination module is used to determine the M-th power of the single expansion quantity according to the total number of the elevation levels M, as the number of the multiple consecutive grids;

[0178] The grid shrinking module includes a grid shrinking submodule, which is used to merge multiple consecutive grids of the current grid according to the M-th power of the single merging quantity, to obtain the number of grids at the upper M level after the current grid is expanded.

[0179] Each module / submodule of the above-mentioned device corresponds to the steps of the above-mentioned method. The specific implementation process of the function and role of each module / submodule in the above-mentioned device can be found in the implementation process of the corresponding steps in the above-mentioned method, which can achieve the same technical effect, and will not be repeated here.

[0180] This application provides an electronic device, including the astronomical data retrieval device described above.

[0181] The astronomical data retrieval method of this application embodiment is applied to an electronic device. The aforementioned electronic device can be a PC (Personal Computer) device. The PC device can include, but is not limited to, desktop computers, tablet computers, or laptop computers.

[0182] Figure 9 The diagram shown is a structural schematic of the electronic device 90 provided in an embodiment of this application.

[0183] like Figure 9 As shown, the electronic device 90 includes one or more processors 91 for implementing the astronomical data retrieval method described above.

[0184] In some embodiments, electronic device 90 may include storage medium 99. For example, a computer-readable storage medium may store a program that can be invoked by processor 91, and may include non-volatile storage medium. In some embodiments, electronic device 90 may include memory 98 and interface 97. In some embodiments, electronic device 90 may also include other hardware depending on the specific application.

[0185] The computer-readable storage medium of this application embodiment stores a program that, when executed by processor 91, is used to implement the astronomical data retrieval method described above.

[0186] This application provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the method described in any of the preceding claims.

[0187] This application also provides a computer program stored in a computer-readable storage medium, for example... Figure 9 The storage medium 99, and when the processor executes the computer program, causes the processor 91 to perform the method described above.

[0188] This application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented using any method or technology. Information may be computer-readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include, but are not limited to: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0189] The above description is merely a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of protection of this specification.

[0190] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element qualified by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A celestial object search method characterized by comprising: The method comprises the following steps: performing a preliminary search according to a specified celestial body input by a user and a specified search radius, to obtain a preliminary search grid quantity; judging the preliminary search grid quantity, to obtain a current grid quantity; in a case where the current grid quantity reaches a contraction condition, merging a plurality of continuous grids of the current grid in a direction from the center of all the preliminary search grids to the edge of all the preliminary search grids, to obtain an upper N-level grid quantity of the current grid after contraction, until the upper N-level grid quantity is not more than a grid threshold value; in a case where the current grid quantity reaches an expansion condition, further dividing the current grid in a direction from the edge of all the preliminary search grids to the center of all the preliminary search grids, to obtain a lower M-level sub-grid quantity of the current grid after expansion, and removing sub-grids without search results from the lower M-level sub-grid quantity, to obtain an effective grid quantity, until the lower M-level grid quantity is equal to the grid threshold value; the lower M-level sub-grid is a plurality of continuous grids; performing a search in a database according to a unique identifier of the current grid after expansion and / or contraction, to obtain a celestial body corresponding to the unique identifier of the current grid, and presenting the celestial body. The method comprises the following steps: performing a multi-level indexing in the database according to a unique identifier of a grid of each level, to associate a celestial body corresponding to the unique identifier of the grid of each level, and presenting the celestial body; the unique identifier of the current grid after expansion and / or contraction comprises the unique identifier of the grid of each level.

2. The celestial body search method according to claim 1, wherein the contraction condition comprises a difference value between the preliminary search grid quantity and the grid threshold value satisfying a difference value of a reduced level; According to the difference value of the reduced level, a total number N of reduced levels is determined; the N 1; the difference value of the reduced level is positively correlated with the N; the method further comprises the following steps: determining Nth power of a single contraction quantity as the quantity of the plurality of continuous grids according to a total level number N of the reduced level; the step of merging the plurality of continuous grids of the current grid, to obtain the upper N-level grid quantity of the current grid after contraction, comprises the following step:

3. The celestial object retrieval method of claim 1, wherein, merging the plurality of continuous grids of the current grid according to Nth power of the single contraction quantity, to obtain the upper N-level grid quantity of the current grid after contraction. the expansion condition comprises a difference value between the preliminary search grid quantity and the grid threshold value satisfying a difference value of a raised level; According to the difference value of the promotion level, a total number M of promotion levels is determined; the M 1; the difference value of the promotion level is positively correlated with the M; the method further comprises the following steps: determining Mth power of a single expansion quantity as the quantity of the plurality of continuous grids according to a total level number M of the raised level; the step of further dividing the current grid, to obtain the lower M-level sub-grid quantity of the current grid after expansion, comprises the following step:

4. The celestial object retrieval method of claim 1, wherein, further dividing the plurality of continuous grids of the current grid according to Mth power of the single expansion quantity, to obtain the lower M-level sub-grid quantity of the current grid after expansion. the current grid quantity reaching the contraction condition comprises the preliminary search grid quantity exceeding a grid threshold value input by a celestial body search; when the N is 1, the step of merging the plurality of continuous grids of the current grid, to obtain the upper N-level grid quantity of the current grid after contraction, until the upper N-level grid quantity is not more than the grid threshold value, comprises the following step: Merging a plurality of continuous grids of the current grid to obtain a grid quantity of a next level after the current grid is shrunk; Judging whether the grid quantity after the current grid is shrunk exceeds the grid threshold based on the grid quantity of the next level after the current grid is shrunk; If the grid quantity after the current grid is shrunk exceeds the grid threshold, returning to execute the step of merging a plurality of continuous grids of the current grid to obtain a grid quantity of a next level after the current grid is shrunk until the grid quantity after the current grid is shrunk does not exceed the grid threshold.

5. The celestial object retrieval method of claim 1, wherein, The grid quantity of the current grid reaches an expansion condition, including that a preliminary search grid quantity is lower than a grid threshold input by a star search; when the M is 1, corresponding to the step of further dividing the current grid to obtain a grid quantity of a next level after the current grid is expanded, and removing a sub-grid without a search result from the grid quantity of the next level after the current grid is expanded to obtain an effective grid quantity until the grid quantity of the next level after the current grid is expanded is equal to the grid threshold, including: Further dividing the current grid to obtain a grid quantity of a next level after the current grid is expanded; Judging whether the grid quantity after the current grid is expanded is equal to the grid threshold based on the grid quantity of the next level after the current grid is expanded; If the grid quantity after the current grid is expanded is not equal to the grid threshold, returning to execute the step of further dividing the current grid to obtain a grid quantity of a next level after the current grid is expanded, and removing a sub-grid without a search result from the grid quantity of the next level after the current grid is expanded to obtain an effective grid quantity until the grid quantity after the current grid is expanded is equal to the grid threshold.

6. The celestial object retrieval method of claim 1, wherein, The step of searching in the database according to the unique identifier after the current grid is expanded and / or shrunk to obtain a star corresponding to the unique identifier of the current grid, including: indexing in the databases of a plurality of storage nodes stored in a distributed manner according to the unique identifier after the current grid is expanded and / or shrunk to obtain the star corresponding to the unique identifier of the current grid.

7. The celestial object retrieval method of claim 1, wherein, The step of performing preliminary search according to a specified star input by a user and a specified search radius to obtain a preliminary search grid quantity, including: converting the specified star into a celestial coordinate of the specified star according to the specified star input by the user; performing preliminary search based on the celestial coordinate of the specified star and the specified search radius to obtain the preliminary search grid quantity.

8. An astronomical object search device characterized by comprising: Including: A preliminary search module, configured to perform preliminary search according to a specified star input by a user and a specified search radius to obtain a preliminary search grid quantity; A current grid quantity obtaining module, configured to judge the preliminary search grid quantity to obtain a grid quantity of a current grid; A grid shrinking module, configured to, in a case where the grid quantity of the current grid reaches a shrinking condition, merge a plurality of continuous grids of the current grid in a direction from a center of all preliminary search grids to edges of the all preliminary search grids to obtain a grid quantity of a next N level after the current grid is shrunk until the grid quantity of the next N level does not exceed a grid threshold; a grid expansion module, configured to, when the number of grids of a current grid reaches an expansion condition, further divide the current grid according to a direction from edges of all preliminary search grids to centers of the all preliminary search grids, to obtain a number of M-level sub-grids after expansion of the current grid, and remove sub-grids without search results from the number of M-level sub-grids to obtain a number of effective grids, until the number of M-level sub-grids is equal to the grid threshold; the M-level sub-grids are a plurality of continuous grids; a celestial body search output module, configured to search in a database according to a unique identifier after expansion and / or contraction of a current grid to obtain a celestial body corresponding to the unique identifier of the current grid, and present the celestial body; the method further includes: performing multi-level indexing in the database according to the unique identifier of each grid at each level, and associating a celestial body corresponding to the unique identifier of each grid at each level to present the celestial body; the unique identifier after expansion and / or contraction of the current grid includes the unique identifier of each grid at each level.

9. An electronic device, comprising: The one or more processors are configured to implement the celestial body search method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The program is stored on the computer-readable storage medium and is executed by the processor to implement the celestial body search method according to any one of claims 1 to 7.

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