CN111931006A - Storage method of ocean lattice point data - Google Patents
Storage method of ocean lattice point data Download PDFInfo
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- CN111931006A CN111931006A CN202010744623.5A CN202010744623A CN111931006A CN 111931006 A CN111931006 A CN 111931006A CN 202010744623 A CN202010744623 A CN 202010744623A CN 111931006 A CN111931006 A CN 111931006A
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- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract
The invention discloses a storage method of ocean lattice point data, which comprises the following steps: formulating a numbering rule, wherein the numbers corresponding to grid points with different resolutions and different longitudes and latitudes meet the numbering rule, and the numbers comprise row numbers and column numbers; and formulating a partition storage rule, and dividing grid point network areas, wherein the grid points in the grid point network areas have the same resolution, and each grid point network area stores grid point data with the same magnitude. The method stores the lattice point data in the lattice point network area on the ocean according to different resolutions, and improves the storage efficiency of the data.
Description
Technical Field
The invention relates to the field of data application, in particular to a storage method of ocean lattice point data.
Background
The meteorological grid data is typical big data, has the characteristics of large data volume, high timeliness, rich data types and the like, and the data magnitude produced every day usually takes TB as a unit. The application of lattice point data on the sea is different from land, the requirement of the sea lattice point data on the resolution under different scales of open sea, offshore and offshore is gradually increased, and the data volume is increased explosively.
Disclosure of Invention
The invention aims to provide a method for storing ocean lattice point data, which aims to improve the storage efficiency of the data by storing the lattice point data in lattice point network areas on the ocean according to different resolutions aiming at the defects in the prior art.
Therefore, the invention adopts the following technical scheme:
a storage method of ocean lattice point data comprises the following steps:
formulating a numbering rule, wherein numbering corresponding to grid points with different resolutions and different longitudes and latitudes meets the numbering rule, and the numbering comprises a row number and a column number;
and formulating a partition storage rule, and dividing grid point network areas, wherein the grid points in the grid point network areas have the same resolution, and each grid point network area stores grid point data with the same magnitude.
Preferably, the longitude and latitude intervals of different resolutions are in a multiple relation.
Preferably, the numbering rule is as follows:
the row number: "R" + (grid longitude-start longitude) x minimum latitude and longitude interval x integer coefficient;
column number: "C" + (initial latitude-grid point latitude) x minimum latitude and longitude interval x integer coefficient.
Preferably, the number includes an identifier disposed at the forefront for identifying the resolution of the lattice point corresponding to the number.
Preferably, the first said number of said grid point network area is used as an identification.
Preferably, the partition range includes an equal number of the row numbers and the column numbers.
Based on the same inventive concept, the invention also provides a storage medium comprising a stored program, wherein the program executes the storage method of the ocean lattice point data.
Based on the same inventive concept, the invention also provides a processor, wherein the processor is used for running the program, and the program executes the storage method of the ocean lattice point data during running.
The technical scheme has the advantages that:
1. grid point network areas with different resolutions are divided, and the storage efficiency of grid point data is improved;
2. respectively identifying the resolution of the grid points and the grid point network area, wherein the identification of the grid point network area has uniqueness;
3. the longitude and latitude intervals of different resolutions are in a multiple relationship, so that conversion between the numbers and the longitude and latitude is convenient.
Drawings
FIG. 1 is a schematic diagram of grid point network regions of different resolutions.
Detailed Description
In order that the objects, features and advantages of the invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings, which are illustrated in detail in order to provide a thorough understanding of the invention, but which may be carried out in other ways than those described. Accordingly, the invention is not limited by the specific implementations disclosed below.
The embodiment provides a storage method of ocean lattice point data, which comprises the following steps:
and formulating a numbering rule. All grid points in the whole forecast area are numbered through the numbering rules, the numbering needs to be consistent, and the numbering of the grid points with different resolutions and different longitudes and latitudes meets the numbering rules. The numbers include row numbers and column numbers.
The row and column numbers and the longitude and latitude of the grid points with different resolutions can be converted with each other by using the numbering rule. Specifically, the row number and the longitude are converted to each other, and the column number and the latitude are converted to each other.
The top of the number is identified using the resolution L corresponding to the lattice point.
The numbering rules are as follows: the row number: "R" + (grid longitude-start longitude) x minimum latitude and longitude interval x integer coefficient;
column number: "C" + (initial latitude-grid point latitude) x minimum latitude and longitude interval x integer coefficient.
The rounding coefficient is determined according to the decimal point digit of the longitude and latitude, so that the number is an integer, and the lattice point is conveniently represented.
The latitude and longitude interval is inversely proportional to the resolution. The minimum longitude and latitude interval is the longitude and latitude interval when the resolution is maximum, and at the moment, the number of grid points in the same grid point network area is the largest. The density of grid points in a unit range is regulated and controlled by setting different longitude and latitude intervals under different scales of open sea, offshore and offshore to meet the storage requirement of grid point data.
For example, LR1000C1000 represents a grid point at 1000 th row and 1000 th column at L resolution, or grid point data of the grid point.
The longitude and latitude intervals of different resolutions are in a relationship of multiple. For example, the minimum longitude and latitude interval is k, the other two longitude and latitude intervals are n and m, and k, n and m are positive integers, wherein m is 5 × n; n is 9 × k; m is 45 × k.
And formulating a partition storage rule. The partition storage rule is defined on the basis of the minimum longitude and latitude interval and is used for meeting the storage of the grid point data under different resolutions.
And dividing the grid point network area, wherein the grid points in the grid point network area have the same resolution. And setting a storage magnitude according to the optimal solution of the data storage capacity and the read-write efficiency, and setting the number of the row and column numbers of each grid point network area to be equal.
Assuming that each grid point network area is I row and I column, the data magnitude of one grid point network area is I × I at k resolution, the data range in the area is I × k, and the row and column number of the first grid point of the area is used as a unique identifier to identify the area range of the partition.
By analogy, at n resolution, the data magnitude of a grid point network region is also I × I, but the data range in the region is I × n, i.e., I × k × 9, i.e., the data range covered by the region is 9 × 9 times that of the grid point network region at k resolution. Likewise, the row and column number of the first grid point of the area is used as the unique identifier.
By analogy, the data magnitude of a grid point network region is also I × I at m resolution, but the data range in the region is I × m, i.e., I × k × 45, i.e., the data range covered by the grid point network region is 45 × 45 times that at k resolution. Likewise, the row and column number of the first grid point of the area is used as the unique identifier.
The lattice point data is the most basic unit in our entire storage scheme, and corresponding lattice point data is stored on each lattice point. And combining the grid point network areas under different resolutions to form the whole forecast area range. As shown in fig. 1, the grid point network region is divided into regions near the taiwan strait, and grid points with different resolutions in the region form an irregular grid point network. And numbering each grid point to serve as an identifier, and storing grid point data with corresponding data magnitude in each grid point network area according to the storage requirement. The storage efficiency can be improved while the storage requirement is met, and the data magnitude in the area is prevented from being too large. Meanwhile, the query of the lattice data is facilitated.
The present embodiment also provides a storage medium on which a program is stored, the program implementing a storage method of ocean lattice data when executed by a processor.
The embodiment also provides a processor, wherein the processor is used for running the program, and the storage method of the ocean lattice point data is executed when the program runs.
Those skilled in the art will understand that all or part of the steps in the above method embodiments may be implemented by a program to instruct related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
While the above description shows and describes the preferred embodiments of the present invention, it is to be understood that the invention is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. A storage method of ocean lattice point data is characterized by comprising the following steps:
formulating a numbering rule, wherein numbering corresponding to grid points with different resolutions and different longitudes and latitudes meets the numbering rule, and the numbering comprises a row number and a column number;
and formulating a partition storage rule, and dividing grid point network areas, wherein the grid points in the grid point network areas have the same resolution, and each grid point network area stores grid point data with the same magnitude.
2. The method of claim 1, wherein the latitude and longitude intervals of different resolutions are in a multiple relationship.
3. The method for storing ocean lattice data according to claim 1, wherein the numbering rule is as follows:
the row number: "R" + (grid longitude-start longitude) x minimum latitude and longitude interval x integer coefficient;
column number: "C" + (initial latitude-grid point latitude) x minimum latitude and longitude interval x integer coefficient.
4. The method of claim 1, wherein the number comprises a top identifier for identifying the resolution of the lattice to which the number corresponds.
5. The method of storing ocean grid point data of claim 1 wherein the first of said numbers of said grid point network areas is used as a logo.
6. The method of storing ocean lattice data according to claim 1, wherein the range of divisions includes an equal number of the row numbers and the column numbers.
7. A storage medium comprising a stored program, wherein the program executes the method of storing ocean lattice data according to any one of claims 1 to 6.
8. A processor, characterized in that the processor is used for running a program, wherein the program executes the storage method of ocean lattice data according to any one of claims 1 to 6 during running.
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| JP2004286520A (en) * | 2003-03-20 | 2004-10-14 | Clarion Co Ltd | Navigation system |
| CN109885572A (en) * | 2019-02-20 | 2019-06-14 | 哈尔滨工程大学 | A kind of three-dimensional data coding and storage method for magnanimity marine environment data management |
| CN109918469A (en) * | 2019-03-27 | 2019-06-21 | 中国联合网络通信集团有限公司 | Gridding processing method and processing device |
| CN110399440A (en) * | 2019-06-28 | 2019-11-01 | 苏州浪潮智能科技有限公司 | A kind of longitude and latitude gridding coding method and device |
| CN110633282A (en) * | 2019-09-18 | 2019-12-31 | 四川九洲空管科技有限责任公司 | Airspace resource multistage three-dimensional gridding method and tool |
| CN110633262A (en) * | 2019-09-25 | 2019-12-31 | 重庆邮电大学 | Map intersection area calculation method and system based on Spark |
-
2020
- 2020-07-29 CN CN202010744623.5A patent/CN111931006A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004286520A (en) * | 2003-03-20 | 2004-10-14 | Clarion Co Ltd | Navigation system |
| CN109885572A (en) * | 2019-02-20 | 2019-06-14 | 哈尔滨工程大学 | A kind of three-dimensional data coding and storage method for magnanimity marine environment data management |
| CN109918469A (en) * | 2019-03-27 | 2019-06-21 | 中国联合网络通信集团有限公司 | Gridding processing method and processing device |
| CN110399440A (en) * | 2019-06-28 | 2019-11-01 | 苏州浪潮智能科技有限公司 | A kind of longitude and latitude gridding coding method and device |
| CN110633282A (en) * | 2019-09-18 | 2019-12-31 | 四川九洲空管科技有限责任公司 | Airspace resource multistage three-dimensional gridding method and tool |
| CN110633262A (en) * | 2019-09-25 | 2019-12-31 | 重庆邮电大学 | Map intersection area calculation method and system based on Spark |
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Application publication date: 20201113 |