A storage method, device, equipment and storage medium for polymorphic natural resource big data

Abstract

The present application discloses a storage method, device, equipment and storage medium for polymorphic natural resource big data. The method includes: establishing a natural resource polymorphic data object; converting an existing storage form data set in the natural resource polymorphic data object into a data set of other storage forms with consistent information; storing the polymorphic storage data in corresponding storage areas according to different stages of natural resource data business flow and application scenarios; the storage area includes a collection area, a resource area and a service area. The method performs object-oriented management on the natural resource polymorphic data set, and each natural resource polymorphic data object is converted into a corresponding storage form according to the scene requirements, and the consistency and coexistence of data can be maintained between different forms. The formulated data access strategy and method are used to access the objectified natural resource data through a unified interface and structured query language, so that the storage method of the present invention supports distributed queries and non-distributed queries.

Description

Technical Field

[0001] The present application relates to the technical field of natural resource data storage, and in particular to a storage method, device, equipment and storage medium for polymorphic natural resource big data. Background Art

[0002] One of the current technical methods for natural resource polymorphic storage is to integrate natural resource data from different sources and structures and convert them into single-state data storage under a unified model. However, this technical method not only faces the problem of efficiency bottleneck when processing large-scale natural resource polymorphic data, but also cannot fully meet the specific storage requirements of diversified scenarios such as management, computing and visualization.

[0003] Another existing natural resource polymorphic storage technology combines the advantages of multiple storage technologies, designs data models based on the characteristics of various types of data, selects appropriate storage forms, and achieves integrated management of natural resource polymorphic data through unified metadata management. However, each type of natural resource data is still stored in a single form, which may make it impossible to simultaneously meet multiple requirements such as high performance, high concurrency, and high throughput when dealing with diverse application scenarios.

[0004] At the same time, natural resource polymorphic storage technology only realizes the storage of multiple data forms from a data perspective, and fails to combine natural resource data storage with different stages of business processes and application scenarios. There is an unclear division of natural resource data functional areas, resulting in insufficient utilization of polymorphic storage capabilities.

[0005] The above contents are only used to assist in understanding the technical method of this application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0006] The main purpose of this application is to provide a storage method, device, equipment and storage medium for polymorphic natural resource big data, aiming to solve the technical problem that the existing methods can neither effectively meet the needs of rapid use of natural resource big data resources, nor meet the different storage requirements of diversified natural resource scenarios.

[0007] To achieve the above objectives, the present application proposes a storage method for polymorphic natural resource big data, the storage method for polymorphic natural resource big data comprising:

[0008] Establish natural resource polymorphic data objects;

[0009] Converting the existing storage form of the natural resource data set in the natural resource polymorphic data object into another storage form of the natural resource data set with consistent information in the object;

[0010] According to different stages of natural resource data business flow and production application scenarios, data sets in various storage forms are stored in corresponding storage areas respectively; the storage areas include collection areas, resource areas and service areas.

[0011] In one embodiment, the step of establishing a natural resource polymorphic data object includes:

[0012] Create natural resource dataset information from raw natural resource data;

[0013] A natural resource polymorphic data object is established according to the natural resource data set information.

[0014] In one embodiment, the step of converting the existing storage form in the natural resource polymorphic data object into polymorphic storage data includes:

[0015] Obtaining a first conversion method;

[0016] The first conversion method is used to convert the existing storage form in the natural resource polymorphic data object into data with other different storage forms and consistent information.

[0017] In one embodiment, the step of storing data sets in various storage forms into corresponding storage areas respectively according to different stages of natural resource data business flows and application scenarios includes:

[0018] Collect raw natural resource data to create raw natural resource data set information;

[0019] Collecting the natural resource data set information to create a natural resource polymorphic data object set 1;

[0020] When the data in the original natural resource data set information is in file form, copying the data to natural resource polymorphic data object set 1;

[0021] When the data in the original natural resource data set information is in a non-file form, recording data connection information of the data in the collection area;

[0022] The natural resource polymorphic data object set is stored in the collection area.

[0023] In one embodiment, the step of storing data sets in various storage forms into corresponding storage areas respectively according to different stages of natural resource data business flows and application scenarios includes:

[0024] The processed data obtained by screening and merging the natural resource polymorphic data object set in the collection area;

[0025] When the processed data is a relational database, copying the processed data to data object set 2;

[0026] When the processed data is a non-relational database, converting the processed data into a relational database by using the first conversion method;

[0027] The data object set 2 is stored in the resource area.

[0028] In one embodiment, the step of storing data sets in various storage forms into corresponding storage areas respectively according to different stages of natural resource data business flows and application scenarios includes:

[0029] Dividing the data object set in the resource area into two blocks, slicing and analyzing to obtain a data object set three of the relational database;

[0030] The data object set three is stored in the service area.

[0031] In one embodiment, after the step of storing the data sets in the plurality of storage forms into the corresponding storage areas according to the different storage forms, the method further comprises:

[0032] Obtain the natural resource application scenarios of the data that needs to be queried;

[0033] Acquire a first data access method according to the natural resource application scenario;

[0034] The data to be queried is acquired from the collection area, the resource area and the service area through the first data access method.

[0035] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage device for polymorphic natural resource big data, the storage device for polymorphic natural resource big data comprising:

[0036] An object creation module is used to create natural resource polymorphic data objects;

[0037] An object storage form conversion module, used to convert an existing storage form data set in the natural resource polymorphic data object into a data set of other storage forms with consistent information;

[0038] The data storage module is used to store data sets in various storage forms into corresponding storage areas according to different stages of natural resource data business flow and application scenarios; the storage areas include collection areas, resource areas and service areas.

[0039] In addition, to achieve the above-mentioned objectives, the present application also proposes a storage device for polymorphic natural resource big data, the device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the storage method for polymorphic natural resource big data as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the storage method for polymorphic natural resource big data as described above are implemented.

[0041] The present application discloses a storage method, device, equipment and storage medium for polymorphic natural resource big data, and relates to the technical field of natural resource data storage. A storage method for polymorphic natural resource big data: establish a natural resource polymorphic data object; convert the existing storage form data set in the natural resource polymorphic data object into a data set of other storage forms with consistent information, so that the same natural resource data can be stored in multiple forms and coexist; according to the different stages of the natural resource data production and application scenario, the data sets of multiple storage forms are respectively stored in corresponding storage areas; the storage areas include collection areas, resource areas and service areas. The method performs object-oriented management on the natural resource polymorphic data set, and each natural resource polymorphic data object is converted into a corresponding storage form according to the scene requirements, and the consistency and coexistence of data can be maintained between different forms. The formulated data access strategy and method are used to access the objectified natural resource data through a unified interface and structured query language, so that the storage method of the present invention supports distributed queries and non-distributed queries. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical methods in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 A flowchart diagram of the first embodiment of the storage method for polymorphic natural resource big data provided by the present application;

[0045] Figure 2 A structural diagram provided for Embodiment 1 of the storage method for polymorphic natural resource big data of the present application;

[0046] Figure 3 A flowchart diagram of Embodiment 2 of the storage method for polymorphic natural resource big data provided by the present application;

[0047] Figure 4A flowchart diagram of Embodiment 3 of the storage method for polymorphic natural resource big data provided by the present application;

[0048] Figure 5 This is a schematic diagram of the module structure of a storage device for polymorphic natural resource big data according to an embodiment of the present application;

[0049] Figure 6 A schematic diagram of the structure of a storage device for polymorphic natural resource big data in the hardware operating environment involved in the storage method for polymorphic natural resource big data in the embodiment of the present application.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical methods of the present application and are not used to limit the present application.

[0052] In order to better understand the technical method of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] Problem 1: One of the current natural resource polymorphic storage technology methods integrates natural resource data from different sources and structures and converts them into single-state data storage under a unified model. However, this technology not only faces performance bottlenecks when processing large-scale natural resource polymorphic data, but also cannot fully meet the specific storage requirements of diverse scenarios such as management, computing, and visualization.

[0054] Question 2: Another existing natural resource polymorphic storage technology combines the advantages of multiple storage technologies, designs data models based on the characteristics of various types of data, selects appropriate storage forms, and achieves integrated management of natural resource polymorphic data through unified metadata management. However, each type of natural resource data is still stored in a single form, which may make it impossible to simultaneously meet multiple requirements such as high performance, high concurrency, and high throughput when dealing with diverse application scenarios.

[0055] Question 3: The polymorphic storage technology mentioned in Questions 1 and 2 requires that the original data of natural resources be converted into a specific data storage model and saved using the corresponding storage technology. This results in the problem that all original data of natural resources must be converted into the target data model and storage form in advance before they can be used, which to some extent limits the immediacy of data use.

[0056] Question 4: Existing natural resource polymorphic storage technology only realizes the storage of multiple data forms from the data perspective, but does not consider the scenarios of natural resource data collection, processing, service, analysis, and visualization. This leads to a weak integration of natural resource data and scenario-based storage, as well as insufficient utilization of polymorphic storage technology.

[0057] This application aims to solve the following problems with similar existing technologies or products:

[0058] Regarding questions 1 and 2: By adopting a unified metadata model, object-based management of natural resource datasets can be achieved, where each object supports multiple storage forms.

[0059] Regarding question 3: In order to meet the storage format requirements of different scenarios, the natural resource dataset object can realize instant conversion between multi-format data to adapt to various needs.

[0060] For questions 3 and 4: By building three core areas, namely data collection area, data resource area and service area, the collection area will be responsible for collecting raw data; the resource area will focus on building a data database; and the service area will provide data services. At the same time, in order to achieve unified data conversion, a distributed structured query language is built to effectively convert data of various forms and formats in the three areas.

[0061] Regarding question 4: From the perspective of natural resource data collection, processing, service, analysis, and visualization, the storage needs of natural resource data can be scenario-based to fully unleash the capabilities of polymorphic storage.

[0062] The present application provides a technical method, the storage method for polymorphic natural resource big data includes: establishing a natural resource polymorphic data object; converting the existing storage form data set in the natural resource polymorphic data object into a data set of other storage forms with consistent information; according to the different stages of the natural resource data application scenario, storing the data sets of various storage forms in corresponding storage areas respectively; the storage areas include collection areas, resource areas, and service areas. The method performs object-oriented management of natural resource polymorphic data sets, and each natural resource polymorphic data object is converted into a corresponding storage form according to the scene requirements, and the consistency and coexistence of data can be maintained between different forms. The formulated data access strategy and method are used to access the objectified natural resource data through a unified interface and structured query language, so that the storage method of the present invention supports distributed queries and non-distributed queries.

[0063] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a storage device for polymorphic natural resource big data that can realize the above functions, etc. The controller is taken as an example to illustrate this embodiment and the following embodiments.

[0064] Based on this, the present application embodiment provides a storage method for polymorphic natural resource big data, referring to Figure 1 and Figure 2 , Figure 1 This is a flow chart of the first embodiment of the storage method for polymorphic natural resource big data of this application. Figure 2 This is a flow chart of the first embodiment of the storage method for polymorphic natural resource big data of the present application.

[0065] In this embodiment, the storage method for polymorphic natural resource big data includes the following steps:

[0066] Step S10: Create a natural resource polymorphic data object.

[0067] It is understandable that natural resource polymorphic data is an important concept in natural resource management, which involves the integration and management of data from multiple forms, multiple attributes and multiple sources of natural resources. Natural resource data comes from multiple different channels and departments, such as land, ocean, forestry, surveying and mapping departments, and the data of these departments differ in format, standard, accuracy and other aspects. Natural resource data includes multiple types such as spatial data, attribute data, image data, etc. Each type of data has its specific structure and expression. The same natural resource entity may show different forms and attributes under different classification systems or utilization methods. For example, a pond may belong to both water system elements and wetland elements, which are stored in file form and relational database form respectively.

[0068] It should be noted that the above-mentioned natural resource polymorphic data is original data, and step S10 includes the following steps S201 and S202.

[0069] Step S201: Create natural resource data set information based on original natural resource data.

[0070] It should be noted that the natural resource dataset information is represented as D i (id i , e i , p i , s i , mi , v i , t i ) ,in, id i A unique identifier for a polymorphic data object; e i Represents storage form and storage format / model information; p i Indicates the current storage form information; s i It is the original source information of data, mainly referring to the original data information from outside; m i It is metadata information, including scope information, field information, etc. v i The version information of the current data provides support for consistency between subsequent different data; t i The time when the data was created or last updated.

[0071] Understandably, m i Metadata is data that describes other data. It encapsulates different attributes, history, source, version, and other information of data assets. e i Storage form mainly refers to the specific method and structure of data storage; the original data is detected, classified, sliced ​​and identified to obtain natural resource data set information. D i .

[0072] Step S202: establishing a natural resource polymorphic data object according to the natural resource dataset information.

[0073] It should be noted that the natural resource polymorphic data object is represented as O i (id i ,M i ,(f, D a ), (r, D b ), (n, D c ),t i ) ,in id i A unique identifier for a polymorphic data object; M iMetadata information for polymorphic data objects, mainly including spatial range information and attribute field information; (f, D a ) Represents the file storage form, f represents the file form, D a Refers to the natural resource dataset information in this form; (r, D b ) represents the storage form of relational database, r represents the type of relational database, D b Refers to the natural resource dataset information in this form; (n,D c ) Represents the non-relational database storage form, n represents the non-relational database type, D c Refers to the natural resource dataset information in this form. D a , D b and D c Refers to the same natural resource data set stored in different forms.

[0074] Specifically, for D a , D b and D c The natural resource dataset model is represented as D i (id i , e i , p i , s i , m i , v i , t i ) .

[0075] Step S20: converting the existing natural resource data set in the storage form in the natural resource polymorphic data object into a natural resource data set in another storage form with consistent information in the object.

[0076] It should be noted that the storage form mainly refers to the specific method and structure of data storage, and common storage forms include file form, relational database type form and non-relational database form. Step S20 includes step S203 and step S204.

[0077] Step S203: Obtain a first conversion method.

[0078] It should be noted that the first conversion method is F 1 (O i , T, M, P) ,exist F 1 specifies the spatiotemporal model, spatiotemporal index, and spatiotemporal calculation functions of natural resource data in memory, so that the required information can be retrieved from polymorphic data through structured query statements. O i Represents spatiotemporal data objects; T Refers to the target storage form of the conversion (by default, T means O i all storage forms that do not yet exist in the ); M Determines whether data acquisition is full or partial. M To select partial retrieval, you need to use structured query conditions P To extract data, through the first transformation method F 1 The new dataset obtained is O i If the dataset in the source is different, then the extracted natural resource dataset needs to be created into a new object O j , and by default is stored as O j The file format in .

[0079] Specifically, the space-time model is a four-dimensional (X,Y,Z,T) or (S, T) information systems, including (X,Y,Z) or （S） represents the space system, （T） Represents time. This is a system with spatiotemporal composite analysis functions and multidimensional information visualization. It mainly studies spatiotemporal data models, that is, the representation, storage, operation, query, update, spatiotemporal analysis and visualization of spatiotemporal data. Spatiotemporal index is a data structure used to accelerate spatiotemporal queries. It combines the characteristics of spatial index and time index, and can efficiently process queries containing spatial and temporal dimensions. Spatiotemporal calculation functions are functions used to process and analyze spatiotemporal data. They can capture and represent the changing patterns of geographical phenomena over time, and provide powerful tools for spatiotemporal analysis and decision support. The first conversion method encapsulates the spatiotemporal model, spatiotemporal index and spatiotemporal calculation function, so that the required information can be retrieved from polymorphic data through structured query statements.

[0080] Step S204: using the first conversion method, the existing storage form in the natural resource polymorphic data object is converted into data with other different storage forms and consistent information.

[0081] It is understood that the first transformation method F 1. Polymorphic data objects of natural resources can be O i Conversion between file form, relational database type form and non-relational database form, if the polymorphic data object of natural resources O i In file form, through the first conversion method F 1Can be converted to relational database type form O n .

[0082] Step S30: According to different stages of natural resource data business flow and production application scenarios, data sets in various storage forms are stored in corresponding storage areas; the storage areas include a collection area, a resource area, and a service area.

[0083] It should be noted that the above steps are methods for creating natural resource polymorphic data objects and converting between polymorphic data, which solves the problems of object-based storage management, query and conversion of natural resource data sets. However, in order to further improve the storage and management efficiency of natural resource polymorphic data, it is necessary to divide the data storage into collection areas, resource areas and service areas from the phased perspective of natural resource data business flow and application scenarios.

[0084] In this embodiment, mainly based on polymorphic storage technology, an object-oriented method is used to manage polymorphic data of natural resources, which can realize mutual conversion and coexistence between forms and provide a unified access interface. The original data has multiple forms, attributes and sources. By adopting a unified metadata model, the object-oriented management of the natural resource data set is realized, where each object supports multiple storage forms. In order to meet the requirements of storage forms in different scenarios, the natural resource data set object can realize instant conversion between polymorphic data through the first conversion method to adapt to various needs.

[0085] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , Figure 3 A flow chart of the second embodiment of the storage method for polymorphic natural resource big data provided in this application.

[0086] Polymorphic natural resource big data has the characteristics of diversity and complexity, so it is necessary to select a suitable storage strategy. According to the characteristics and access requirements of polymorphic natural resource big data, this application selects a combination of file form, relational database type form and non-relational database form to achieve high-performance, scalability and disaster-tolerant storage.

[0087] In step S30, the storage method for polymorphic natural resource big data includes:

[0088] Step S301: Collect original natural resource data to create original natural resource data set information.

[0089] It is understood that the collection area is used to collect raw natural resource data sets from multiple sources. {d m , d m+1 , ... , d n } .

[0090] It should be noted that multi-source heterogeneity means that on the same system or platform, there are data and information from different sources and of different types. These data and information may have different formats, structures, semantics and granularity, and may also come from different data sources, databases, file systems and networks.

[0091] Step S302: Collect the natural resource data set information to create a natural resource polymorphic data object set 1.

[0092] It should be noted that, in the collection area, a natural resource polymorphic data object set is created. {O m , O m+1 , ... , O n } .

[0093] Step S303: When the data in the original natural resource data set information is in file format, copy the data to natural resource polymorphic data object set 1.

[0094] It should be noted that if d j If it is in file form, copy it to O j Storage in the form of files.

[0095] Step S304: When the data in the original natural resource data set information is in a non-file format, data connection information of the data is recorded in the collection area.

[0096] It should be noted that if d j If it is in non-file form, only the data connection information is obtained and recorded in the file form information, and the method is used when the data is needed F 1Instantly extract the data into files through parameters.

[0097] Step S305: storing the natural resource polymorphic data object set 1 into the collection area.

[0098] It should be noted that step S30 also includes steps S306 to S311, which are not marked in the figure.

[0099] Step S306: Screening and merging the natural resource polymorphic data object set in the collection area to obtain processed data.

[0100] Step S307: when the processed data is a relational database, copy the processed data to data object set 2.

[0101] It can be understood that the resource area is used to store a polymorphic data object set from an object data set in the collection area. {O m , O m+1 , ... , O n } Data object set 2 obtained by screening, merging, etc. {O b , O b+1 , ... , O b+n } , and the default storage form of data object set 2 is a relational database, which is mainly used for natural resource data management.

[0102] Step S308: when the processed data is a non-relational database, convert the processed data into a relational database using the first conversion method.

[0103] It is understandable that if {O b , O b+1 , ... , O b+n } Object O b+i Only through {O m , O m+1 , ... , O n } An object Om+j Only the form is converted, and the data set information does not change. b+i =O m+j , that is, O b+i In A and B coexist; if O b+i Not just from {O m , O m+1 , ... , O n } If a certain data is transformed into a certain form, it is a newly created object.

[0104] Step S309: storing the data object set 2 into the resource area.

[0105] Step S310: Divide the data object set in the resource area into two blocks 、 Slicing and analysis processing obtains data object set 3 of relational database.

[0106] It can be understood that the service area is used to store the polymorphic data object set from the collection area object data set. {O b , O b+1 , ... , O b+n } The data object set obtained by block, slice, analysis, etc. {O c , O c+1 , ... , O c+n } The default storage form of data object set 3 is a non-relational database, which is mainly used for natural resource data service sharing and visualization. {O b , O b+1 , ... , O b+n } After calculation analysis, data slicing and other methods, we can get {O c , O c+1 , ... , O c+n } Basically a newly created object.

[0107] Step S311: storing the data object set three into the service area.

[0108] In this embodiment, by constructing three core areas, namely, data collection area, data resource area and service area, the collection area will be responsible for collecting raw data; the resource area will focus on building a data database; and the service area will provide data services. At the same time, in order to achieve unified data conversion, a distributed structured query language is constructed to effectively convert data of various forms and formats in the three areas.

[0109] Based on the first embodiment and / or the second embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those of the above-mentioned first and second embodiments can refer to the above introduction, and will not be repeated later. Figure 4 , Figure 4 A flowchart diagram is provided for Example 3 of the storage method for polymorphic natural resource big data of this application.

[0110] Step S401: Obtain the natural resource application scenario of the data to be queried.

[0111] It is understandable that the application scenarios of natural resources are S(id, priority, create, tmp, driver) ,in id Identifies a specific scene. priority Specifies the priority order for reading information from different data forms, including six strategies: f→r→n, f→n→r, r→f→n, r→n→f, n→f→r, n→r→f}, representing the file form ( f ), relational database form ( r ) and non-relational database forms ( n ) different combinations; when the data form with higher priority does not exist, create The instructions allow the conversion of lower priority data forms into higher priority forms and the execution of query operations; tmp The parameter determines whether the query results need to be cached; driver The parameters involve whether to use a third-party structured query driver, such as JDBC, so as to expand the data source through a third-party driver, making data development and expansion more flexible and convenient.

[0112] It should be noted that JDBC (Java Database Connectivity) is a Java API that allows Java applications to connect and interact with databases.

[0113] Specifically, through the storage requirements of natural resource scenarios and the experience statistics during use, the data access strategies for each scenario are formulated, including the strategy for integrating scenarios. S(id = 1, f→r→n, true, true, null) The strategy for data processing scenarios is S(id = 2, f→r→n, false, true, null) The strategy for data service scenarios is S(id = 3, r→n, false, false, jdbc) The strategy for analyzing the scenario is S(id = 4, r, true, false, jdbc) , S(id = 5, f, true, false, null) The strategy for visualizing the scene is S(id = 6, n, false, false, jdbc) In use, data acquisition can be achieved by calling existing strategies, and data acquisition strategies can be further expanded according to needs.

[0114] Step S402: Acquire a first data access method according to the natural resource application scenario.

[0115] It should be noted that the first data access method F(O i , S, P) , covering the integration, processing, service, analysis, visualization and other aspects of natural resources. In this strategy, O i Refers to the multi-form data objects of natural resources and the application scenarios of natural resources S(id, priority, create, tmp, driver) Defines the specific operating environment, P It is a structured query condition.

[0116] Step S403: Acquire the data to be queried from the collection area, the resource area and the service area through the first data access method.

[0117] Understandably, users need to query the plant coverage of the pond area, and can customize the natural resource application scenario of vegetation coverage monitoring S , through the first data access method F(O i , S, P) Query ecological monitoring data.

[0118] In this embodiment, the present invention also formulates corresponding data access strategies and methods from the perspective of natural resource data business flow and application scenarios to improve the storage, management and application efficiency of natural resource data. From the perspective of natural resource data collection, processing, service, analysis, visualization and other scenarios, the storage requirements of natural resource data are scenario-based.

[0119] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the storage method of the present application for polymorphic natural resource big data. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0120] This application also provides a storage device for polymorphic natural resource big data, please refer to Figure 5 , the storage device for polymorphic natural resource big data includes:

[0121] The object creation module 10 is used to create natural resource polymorphic data objects.

[0122] The object conversion module 20 is used to convert the existing storage form data set in the natural resource polymorphic data object into another storage form data set with consistent information.

[0123] The data storage module 30 is used to store data sets in various storage forms into corresponding storage areas according to different stages of natural resource data business flow and production application scenarios; the storage areas include collection areas, resource areas and service areas.

[0124] The storage device for polymorphic natural resource big data provided by the present application adopts the storage method for polymorphic natural resource big data in the above-mentioned embodiment, which can solve the technical problem that the existing method can neither effectively meet the demand for rapid use of natural resource big data resources nor meet the different storage requirements of diversified natural resource scenarios. Compared with the prior art, the beneficial effects of the storage device for polymorphic natural resource big data provided by the present application are the same as the beneficial effects of the storage method for polymorphic natural resource big data provided by the above-mentioned embodiment, and the other technical features of the storage device for polymorphic natural resource big data are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0125] The present application provides a storage device for polymorphic natural resource big data, and the storage device for polymorphic natural resource big data includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the storage method for polymorphic natural resource big data in the above-mentioned embodiment one.

[0126] Reference below Figure 6 , which shows a schematic diagram of the structure of a storage device for polymorphic natural resource big data suitable for implementing the embodiment of the present application. The storage device for polymorphic natural resource big data in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The storage device for polymorphic natural resource big data shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0127] like Figure 6As shown, the storage device for polymorphic natural resource big data may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the storage device for polymorphic natural resource big data are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the storage device for polymorphic natural resource big data to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a storage device for polymorphic natural resource big data with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0128] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0129] The storage device for polymorphic natural resource big data provided by the present application adopts the storage method for polymorphic natural resource big data in the above embodiment, which can solve the technical problem of mechanical fatigue imbalance of the dual motor spindle. Compared with the prior art, the beneficial effects of the storage device for polymorphic natural resource big data provided by the present application are the same as the beneficial effects of the storage method for polymorphic natural resource big data provided by the above embodiment, and the other technical features of the storage device for polymorphic natural resource big data are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0130] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0131] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0132] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the storage method for polymorphic natural resource big data in the above-mentioned embodiment.

[0133] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0134] The above-mentioned computer-readable storage medium may be included in the storage device for polymorphic natural resource big data; or it may exist independently without being assembled into the storage device for polymorphic natural resource big data.

[0135] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0136] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0137] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0138] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned storage method for polymorphic natural resource big data, which can solve the technical problem that the existing methods can neither effectively meet the demand for rapid use of natural resource big data resources nor meet the different storage requirements of diversified natural resource scenarios. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the storage method for polymorphic natural resource big data provided in the above-mentioned embodiments, and will not be repeated here.

[0139] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A storage method for polymorphic natural resource big data, characterized in that: The method comprises: Create natural resource data set information Di (idi, ei, pi, si, mi, vi, ti) according to the original natural resource data; wherein idi is the unique identifier of the natural resource polymorphic data object, ei is the storage form and storage format information of the natural resource data set information, pi is the current storage form information of the natural resource data set information, si is the source information of the original natural resource data, mi is the metadata information of the natural resource data set information, vi is the version information, and ti is the creation or last update time of the natural resource data set information; A natural resource polymorphic data object Oi(idi, Mi, (f, Da), (r, Db), (n, Dc), ti) is established according to the natural resource data set information; wherein idi is the unique identifier of the natural resource polymorphic data object, Mi is the metadata information of the natural resource polymorphic data object, including spatial range information and attribute field information, (f, Da) is the file storage form, f represents the file form, Da is the natural resource data set information in the file form, (r, Db) is the relational database storage form, r represents the relational database type, Db is the natural resource data set information in the relational database type form, (n, Dc) represents the non-relational database storage form, n represents the non-relational database type, Dc is the natural resource data set information in the non-relational database type form, and ti is the creation or last update time of the natural resource polymorphic data object; Obtain a first conversion method F1 (Oi, T, M, P), wherein T refers to the target storage form of the conversion, M determines whether to obtain all or part of the natural resource polymorphic data object, and P is a structured query condition; The existing storage form in the natural resource polymorphic data object is converted into data with other different storage forms and consistent information through the first conversion method; the storage forms include file forms, relational database type forms and non-relational database forms; According to different stages of natural resource data business flow and application scenarios, data sets in various storage forms are stored in corresponding storage areas; the storage areas include collection areas, resource areas and service areas; Get the natural resource application scenario S (id, priority, create, tmp, driver) of the data to be queried; id identifies a specific scenario, priority specifies the priority order of reading information from different data forms, create means allowing the data form with a lower priority to be converted to a high priority form and perform the query operation, tmp determines whether the query results need to be cached, and driver involves whether to use a third-party structured query driver; Acquire a first data access method F(Oi, S, P) according to the natural resource application scenario; The data to be queried is acquired from the collection area, the resource area and the service area through the first data access method.

2. The storage method for polymorphic natural resource big data according to claim 1, characterized in that: The step of storing data sets of various storage forms into corresponding storage areas respectively according to different stages of natural resource data business flow and application scenarios includes: Collect raw natural resource data to create raw natural resource data set information; Collecting the natural resource data set information to create a natural resource polymorphic data object set 1; When the data in the original natural resource data set information is in file form, copying the data to natural resource polymorphic data object set 1; When the data in the original natural resource data set information is in a non-file form, recording data connection information of the data in the collection area; The natural resource polymorphic data object set is stored in the collection area.

3. The storage method for polymorphic natural resource big data according to claim 2, characterized in that: The step of storing data sets of various storage forms into corresponding storage areas respectively according to different stages of natural resource data business flow and application scenarios includes: The processed data obtained by screening and merging the natural resource polymorphic data object set in the collection area; When the processed data is a relational database, copying the processed data to data object set 2; When the processed data is a non-relational database, converting the processed data into a relational database by using the first conversion method; The data object set 2 is stored in the resource area.

4. The storage method for polymorphic natural resource big data according to claim 3, characterized in that: The step of storing data sets of various storage forms into corresponding storage areas respectively according to different stages of natural resource data business flow and application scenarios includes: Divide the data object set in the resource area into two blocks 、 Slicing and analyzing the data object set 3 of the relational database is obtained; The data object set three is stored in the service area.

5. A storage device for polymorphic natural resource big data, characterized in that: The device comprises: An information establishment module is used to create natural resource data set information Di (idi, ei, pi, si, mi, vi, ti) according to the original natural resource data; wherein idi is the unique identifier of the natural resource polymorphic data object, ei is the storage form and storage format information of the natural resource data set information, pi is the current storage form information of the natural resource data set information, si is the source information of the original natural resource data, mi is the metadata information of the natural resource data set information, vi is the version information, and ti is the time when the natural resource data set information is created or last updated; An object creation module is used to create a natural resource polymorphic data object Oi(idi,Mi,(f, Da), (r, Db), (n,Dc),ti) according to the natural resource data set information; wherein idi is the unique identifier of the natural resource polymorphic data object, Mi is the metadata information of the natural resource polymorphic data object, including spatial range information and attribute field information, (f, Da) is the file storage form, f represents the file form, Da is the natural resource data set information in the file form, (r,Db) is the relational database storage form, r represents the relational database type, Db is the natural resource data set information in the relational database type form, (n,Dc) represents the non-relational database storage form, n represents the non-relational database type, Dc is the natural resource data set information in the non-relational database type form, and ti is the time when the natural resource polymorphic data object is created or last updated; The conversion method module is used to obtain the first conversion method F1 (Oi, T, M, P), wherein T refers to the target storage form of the conversion, M determines whether to obtain the full or partial amount of the natural resource polymorphic data object, and P is a structured query condition; A conversion module, used to convert the existing storage form in the natural resource polymorphic data object into data with other different storage forms and consistent information through the first conversion method; the storage forms include file forms, relational database type forms and non-relational database forms; A data storage module, used to store data sets in various storage forms into corresponding storage areas according to different stages of natural resource data business flows and application scenarios; the storage areas include a collection area, a resource area, and a service area; The scenario building module is used to obtain the natural resource application scenario S (id, priority, create, tmp, driver) of the data to be queried; among them, id identifies a specific scenario, priority specifies the priority order of reading information from different data forms, create means allowing the data form with a lower priority to be converted to a high priority form and executing the query operation, tmp determines whether the query result needs to be cached, and driver involves whether to use a third-party structured query driver; A query method module, used to obtain a first data access method F(Oi, S, P) according to the natural resource application scenario; The data query module is used to obtain the data to be queried from the collection area, the resource area and the service area through the first data access method.

6. A storage device for polymorphic natural resource big data, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the storage method for polymorphic natural resource big data as described in any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the storage method for polymorphic natural resource big data as described in any one of claims 1 to 4 are implemented.

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