CN113204592A - Data processing method, system and device under scene of Internet of things and storage medium - Google Patents
Data processing method, system and device under scene of Internet of things and storage medium Download PDFInfo
- Publication number
- CN113204592A CN113204592A CN202110551764.XA CN202110551764A CN113204592A CN 113204592 A CN113204592 A CN 113204592A CN 202110551764 A CN202110551764 A CN 202110551764A CN 113204592 A CN113204592 A CN 113204592A
- Authority
- CN
- China
- Prior art keywords
- database
- time sequence
- data
- operation instruction
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y20/00—Information sensed or collected by the things
- G16Y20/10—Information sensed or collected by the things relating to the environment, e.g. temperature; relating to location
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- General Health & Medical Sciences (AREA)
- Toxicology (AREA)
- Computing Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The application discloses a data processing method, a system, a device and a storage medium under the scene of the Internet of things, and relates to the technical field of the Internet of things. The method comprises the following steps: receiving a first operation instruction through a database access interface; the first operation instruction comprises at least one operation parameter; acquiring a target application scene; determining a target time sequence database according to a target application scene; mapping the attribute of the operation parameter to the corresponding attribute in the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operation instruction; issuing a second operation instruction to the target time sequence database, wherein the second operation instruction is used for indicating the target time sequence database to execute data processing operation corresponding to at least one operation parameter; and issuing a second operation instruction to the target time sequence database by the method, wherein the second operation instruction is used for indicating the target time sequence database to execute data processing operation corresponding to at least one operation parameter.
Description
Technical Field
The embodiment of the application relates to the technical field of the Internet of things, in particular to a data processing method, a data processing system, a data processing device and a storage medium in the scene of the Internet of things.
Background
With the large-scale popularization of the internet of things technology, the use scenes of the internet of things technology are gradually increased, and different requirements on the database are met in different application scenes.
In the related art, when accessing a database, a corresponding database is often deployed for a specific usage scenario to meet the requirements of different usage scenarios on the database.
However, in a multi-terminal scene of the internet of things, the database needs to be deployed at both the cloud and the edge device, and the specific database deployment cannot meet the requirements of the multi-terminal application scene, that is, the multi-terminal scene of the internet of things cannot be directly and effectively supported.
Disclosure of Invention
The embodiment of the application provides a data processing method, a system, a device and a storage medium under the scene of the internet of things, which can deploy different time sequence databases according to different application scenes in the multi-terminal scene of the internet of things, reduce the connection operation required when an upper layer application accesses the different time sequence databases, and improve the access efficiency of the upper layer application to the time sequence databases. The technical scheme is as follows:
in one aspect, a data processing method in an internet of things scene is provided, where the method includes:
receiving a first operation instruction through the database access interface; the first operation instruction comprises at least one operation parameter;
acquiring a target application scene; the target application scene is a use scene of an upper layer application which issues the data operation instruction;
determining a target time sequence database according to the target application scene, wherein the target time sequence database is one of the at least two time sequence databases and corresponds to the target application scene;
mapping the attribute of the operating parameter to the corresponding attribute in the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operating instruction;
and issuing the second operation instruction to the target time sequence database, wherein the second operation instruction is used for indicating the target time sequence database to execute the data processing operation corresponding to the at least one operation parameter.
In another aspect, a database management system is provided, which includes a management device and at least two time sequence databases; the data management system is externally provided with a database access interface;
the management device is used for receiving a data operation instruction of an upper application through the database access interface; the first operation instruction comprises at least one operation parameter;
acquiring a target application scene; the target application scene is a use scene of an upper layer application which issues the data operation instruction; determining a target time sequence database according to the target application scene, wherein the target time sequence database is one of the at least two time sequence databases and corresponds to the target application scene; mapping the attribute of the operating parameter to the attribute corresponding to the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operating instruction; issuing the second operation instruction to the target time sequence database;
and the target time sequence database is used for executing data processing operation corresponding to the at least one operation parameter.
On the other hand, a data processing apparatus under a scene of internet of things is provided, the apparatus is applied to a management device in a database management system, the database management system further includes at least two timing databases, the database management system is externally provided with a database access interface, and the apparatus includes:
the first operation instruction receiving module is used for receiving a first operation instruction through the database access interface; the first operation instruction comprises at least one operation parameter;
the target application scene acquisition module is used for acquiring a target application scene; the target application scene is a use scene of an upper layer application which issues the data operation instruction;
a target time sequence database determining module, configured to determine a target time sequence database according to the target application scenario, where the target time sequence database is a time sequence database corresponding to the target application scenario among the at least two time sequence databases;
a second operation instruction obtaining module, configured to map, based on a mapping relationship corresponding to the target time sequence database, an attribute of the operation parameter to a corresponding attribute in the target time sequence database, so as to obtain a second operation instruction;
and the second operation instruction issuing module is used for issuing the second operation instruction to the target time sequence database, and the second operation instruction is used for indicating the target time sequence database to execute the data processing operation corresponding to the at least one operation parameter.
In a possible implementation manner, the target application scenario obtaining module includes:
the deployment mode acquisition submodule is used for acquiring the deployment mode of the upper application;
and the target application scene determining submodule is used for determining the target application scene based on the deployment mode of the upper-layer application.
In one possible implementation, the attributes of the operating parameters include organization, station type, station, equipment, time, and corresponding values.
In a possible implementation manner, the second operation instruction obtaining module includes:
the first mapping submodule is used for mapping the organization into a database in the target time sequence database based on the mapping relation corresponding to the target time sequence database;
the second mapping submodule is used for mapping the measuring point types into a data table in the database;
a third mapping submodule for mapping the measurement points to metrics in the database;
a fourth mapping submodule, configured to map the device to a tag in the database;
a fifth mapping sub-module for mapping the time to a timestamp in the database;
a sixth mapping sub-module, configured to map the corresponding numerical value to a field value in the database;
and the second operation instruction obtaining submodule is used for obtaining the second operation instruction based on the database, the data table, the measurement, the tag, the timestamp and the field value.
In one possible implementation, the first operation instruction includes: one of a data add instruction, a data delete instruction, a data search instruction, and a data modify instruction.
In one possible implementation, the at least two time series databases are heterogeneous time series databases.
In another aspect, a computer device is provided, which includes a processor and a memory, where at least one instruction, at least one program, a set of codes, or a set of instructions is stored in the memory, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by the processor to implement the data processing method in the context of the internet of things as described in the above aspect.
In another aspect, a computer-readable storage medium is provided, in which at least one program code is stored, and the program code is loaded and executed by a processor to implement the data processing method in the context of the internet of things as described in the above aspect.
In another aspect, a computer program product or computer program is provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and executes the computer instruction, so that the computer device executes the data processing method in the internet of things scenario provided in the foregoing various optional implementations.
The technical scheme provided by the application can comprise the following beneficial effects:
by additionally arranging the database management system, a database access interface in the database management system receives a first operation instruction issued by an upper application, a management device in the database management system determines a target time sequence database acted by the first operation instruction based on a use scene of the upper application, and maps an operation parameter in the first operation instruction into a corresponding attribute in the target time sequence database, so that the first operation instruction is converted into a second operation instruction which can directly act on the target time sequence database, and data in the target time sequence database is correspondingly processed. Therefore, on the premise of realizing the deployment of the time sequence databases corresponding to the multi-terminal application scene of the Internet of things, the connection operation required when the upper-layer application accesses different time sequence databases is reduced, and the access efficiency of the upper-layer application to the time sequence databases is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
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 application.
FIG. 1 illustrates a schematic diagram of an environment for implementing the present application provided by an exemplary embodiment of the present application;
fig. 2 is a flowchart illustrating a data processing method in an internet of things scenario according to an exemplary embodiment of the present application;
fig. 3 is a flowchart illustrating a data processing method in an internet of things scenario according to an exemplary embodiment of the present application;
FIG. 4 is a diagram illustrating an Influx mapping process according to an exemplary embodiment of the present application;
FIG. 5 is a diagram illustrating OpenTSDB mapping processing in accordance with an illustrative embodiment of the present application;
FIG. 6 illustrates an architecture diagram of an upper level application accessing a time series database, according to an exemplary embodiment of the present application;
FIG. 7 illustrates a schematic diagram of a database management system shown in an exemplary embodiment of the present application;
fig. 8 is a block diagram illustrating a data processing apparatus in an internet of things scenario according to an exemplary embodiment of the present application;
FIG. 9 is a block diagram illustrating the structure of a computer device in accordance with an exemplary embodiment;
FIG. 10 is a block diagram illustrating the structure of a computer device according to an example embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
It is to be understood that reference herein to "a number" means one or more and "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
For ease of understanding, several terms referred to in this application are explained below.
1) Internet of Things (Internet of Things, IoT)
The internet of things is a network which enables all common objects capable of performing independent functions to realize interconnection and intercommunication based on information bearing bodies such as the internet and a traditional telecommunication network. The application fields of the method mainly comprise transportation, logistics, industrial manufacturing, health care, intelligent environments (families, offices and factories) and the like, and the method has very wide market prospect.
2) Time sequence Database (TSDB Time Series Database)
The time sequence database, which is called a time sequence database in all, is a specialized database for storing and managing time sequence data, and provides a distributed operation database service with high performance reading and writing and computation capabilities for the time sequence data, wherein the time sequence data refers to data with time tags (changed according to the sequence of time, namely time sequence).
The time sequence database is suitable for the monitoring of the Internet of things equipment and the monitoring scene of the Internet, and the time sequence data is mainly data collected and generated by various types of real-time monitoring, checking and analyzing equipment in the power industry, the chemical industry, the operation and maintenance technology, big data collection and the like. Typical characteristics of these industrial data are: the generation frequency is fast (each monitoring point can generate a plurality of pieces of data within one second), the collection time is seriously depended (each piece of data requires corresponding unique time), the multi-information quantity of the measuring points is large (a conventional real-time monitoring system has thousands of monitoring points which generate data every second and generate dozens of GB data quantity every day).
Fig. 1 is a schematic diagram illustrating an implementation environment of the present application provided by an exemplary embodiment of the present application, as shown in fig. 1, the implementation environment includes an IoT device 110, a timing database 120, and an operation terminal 130;
the IoT devices 110 are devices having a data acquisition function, and the acquired data is time series data, in one possible implementation manner, the IoT devices 110 may be new energy devices provided with sensors such as a wind speed detector, a temperature and humidity detector, and a photovoltaic sensor, for example, a wind power generator, a photovoltaic cell panel, and the like, as shown in fig. 1, a plurality of IoT devices 110 respectively acquire time series data of different data types, and send the acquired time series data to the time series database 120, and the time series database stores the devices acquired by the IoT.
In one possible application scenario, the IoT device 110 sends the timing data to the timing database 120 through a gateway device.
In one possible implementation, different IoT devices 110 correspond to different timing databases 120.
The IoT device 110 and the timing database 120 are connected via a communication network. Optionally, the communication network is a wired network or a wireless network.
Optionally, the wireless network or wired network described above uses standard communication techniques and/or protocols. The Network is typically the Internet, but may be any Network including, but not limited to, a Local Area Network (LAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a mobile, wireline or wireless Network, a private Network, or any combination of virtual private networks. In some embodiments, data exchanged over a network is represented using techniques and/or formats including Hypertext Mark-up Language (HTML), Extensible Markup Language (XML), and the like. All or some of the links may also be encrypted using conventional encryption techniques such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec). In other embodiments, custom and/or dedicated data communication techniques may also be used in place of, or in addition to, the data communication techniques described above. The application is not limited thereto.
The operation terminal 130 is a device having functions of querying, adding, deleting, and modifying data, and in a possible implementation manner, the operation terminal 130 sends a data operation instruction including an operation data parameter to each time series database 120 through a time series database access interface 121 provided outside each time series database 120, each time series database 120 determines target data in the time series database according to the operation parameter in the data operation instruction, and performs corresponding processing on the data, for example, the operation terminal 130 sends a data query instruction to the time series database 120, the time series database 120 acquires the target data based on the query parameter in the data query instruction, and feeds the target data back to the operation terminal 130, and the operation terminal 130 displays the target data, for example, displays the received target data in a graph form. The operation terminal 130 may be implemented as a personal computer, a smart phone, a tablet computer, or the like.
In the interaction between the time sequence database shown in fig. 1 and the operation terminal, the operation terminal needs to access the time sequence database access interfaces respectively corresponding to the time sequence databases to achieve the purpose of data interaction with the time sequence database. In the embodiment of the application, by arranging the database management system, when the operation terminal accesses the time sequence database in a multi-terminal scene of the internet of things, the corresponding database can be accessed through one database access interface based on different application scenes, so that the connection operation of the operation terminal to different time sequence databases during data access is reduced.
Fig. 2 shows a flowchart of a data processing method in the context of the internet of things, where the method may be executed by a computer device, where the computer device may be implemented as a management device in the data management system, the data management system further includes at least two timing databases, and the data management system is externally provided with a database access interface, as shown in fig. 2, the data processing method in the context of the internet of things includes the following steps:
In the embodiment of the application, a database access interface is defined, the database access interface is externally arranged in a database management system and is used for receiving an operation instruction sent by an operation terminal, and based on the database access interface, in a multi-terminal scene of the internet of things, an upper layer application only needs to access the database access interface and issue a corresponding operation instruction to realize corresponding data operation.
And step 230, determining a target time sequence database according to the target application scene, wherein the target time sequence database is one of at least two time sequence databases corresponding to the target application scene.
In a possible implementation manner, at least two time series databases included in the database management system are different time series databases, for example, the at least two time series databases may include a time series database supporting distribution, such as LinDB, infiux xdb, OpenTSDB, and the like, so as to meet the requirement in the scenario where the machine resources at the Cloud end (Cloud end) are more; a timing database supporting a single machine or an HA (High Availability) may be further included to meet the usage scenario due to machine resource constraints, such as only a single machine or two machines; or the at least two time sequence databases comprise a time sequence database with strong query capability so as to utilize the high-efficiency query performance of the time sequence database to meet the requirements of the analysis scene; the system can also comprise a time sequence database with high-efficiency compression capability so as to utilize the high-efficiency compression performance of the time sequence database, save more storage cost, meet the mass data scene and the like.
And 240, mapping the attribute of the operation parameter to the corresponding attribute in the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operation instruction.
Because different time sequence databases are all set with their own internal concepts (corresponding attributes in the instant sequence database) for describing data storage modes, these concepts are usually different from the attributes of the operation parameters in the internet of things devices, in order to establish the corresponding relationship between the attributes of the operation parameters and the attributes in the time sequence database, a mapping relationship corresponding to the time sequence database is set in the database management system, so as to correspond the attributes of the operation parameters to the concepts in the time sequence database, for example, the device types (AI, DI, PI) in the operation parameters are used to correspond to the data tables in the database, which is any one of the time sequence databases, thereby obtaining the second operation instruction directly corresponding to the time sequence database.
And 250, issuing a second operation instruction to the target time sequence database, wherein the second operation instruction is used for instructing the target time sequence database to execute data processing operation corresponding to at least one operation parameter.
To sum up, in the data processing method in the context of the internet of things provided by the embodiment of the application, by additionally providing the database management system, the database access interface in the database management system receives the first operation instruction issued by the upper application, the management device in the database management system determines the target time sequence database acted by the first operation instruction based on the usage context of the upper application, and maps the operation parameters in the first operation instruction to the corresponding attributes in the target time sequence database, so that the first operation instruction is converted into the second operation instruction capable of directly acting on the target time sequence database, and the data in the target time sequence database is correspondingly processed. Therefore, on the premise of realizing the deployment of the time sequence databases corresponding to the multi-terminal application scene of the Internet of things, the connection operation required when the upper-layer application accesses different time sequence databases is reduced, and the access efficiency of the upper-layer application to the time sequence databases is improved.
Fig. 3 is a flowchart illustrating a data processing method in an internet of things scenario, where the method may be executed by a computer device, where the computer device may be implemented as a management device in the data management system, the data management system further includes at least two timing databases, and the data management system is externally provided with a database access interface, as shown in fig. 3, the data processing method in the internet of things scenario includes the following steps:
In one possible implementation, the first operation instruction includes: one of a data add instruction, a data delete instruction, a data search instruction, and a data modify instruction.
The data adding instruction is used for indicating adding specified data in the target time sequence database; the data deleting instruction is used for indicating the deletion of the specified data in the target time sequence database; the data searching instruction is used for acquiring specified data in a target time sequence database; the data modification instruction is used for indicating the modification of the specified data in the target time sequence database.
In one possible implementation, the operation parameter has a corresponding attribute for indicating the source of the operation parameter and a corresponding operation value.
In one possible implementation, the attributes of the operating parameters include organization, station type, station, equipment, time, and corresponding values.
In the data adding instruction, the data deleting instruction, the data searching instruction and the data modifying instruction, the attribute of the operating parameter of the data adding instruction and the data modifying instruction needs to include at least one of organization, equipment, measuring point and time and a corresponding numerical value; the data deleting instruction and the data searching instruction need to include at least one of organization, equipment, measuring point and time. Taking a data increase instruction as an example, organizing a wind field, using a fan with the number of wtg001 in the wind field a as equipment, using a wind speed checking device with the number of windspeed on the fan as a measuring point, and using the time of 2020-10-1316: 56: the wind speed detected by the wind speed check means is 5 in m/s, i.e. the corresponding value is 5 m/s. When data is written, the upper layer application provides a certain organization, a certain device and a certain measuring point for the database access interface, and data can be written in at a certain time value; when data is inquired, a certain organization, a certain device, a certain measuring point and a certain time period are provided, and then corresponding values can be inquired.
In a possible implementation manner, the deployment manner of the upper layer application may be one of a privatized deployment, a publicized deployment, and a hybrid deployment. The number of devices covered by the privatization deployment is small, and the related application scenes are few; the number of devices covered by the commonized deployment and the hybrid deployment is large, and the related application scenes are also large.
In a possible implementation manner, a corresponding relationship between a deployment manner of an upper-layer application and an application scene is set in a database management system, for example, if the upper-layer application is deployed by using the deployment manner a, the application scene of the upper-layer application is determined to be the scene a; and if the upper-layer application is deployed in the deployment mode B, determining that the application scene of the upper-layer application is the scene B and the like. The corresponding relationship between the deployment mode of the upper layer application and the application scene can be set based on actual requirements.
In a possible implementation manner, the data management system may further establish a corresponding relationship between an application scenario and a data management requirement according to an actual requirement of a user on the time sequence database, for example, if the requirement of the upper layer application on data analysis is high, the application scenario of the upper layer application is determined to be a data analysis scenario; and if the requirement of the upper-layer application on data compression is high, determining that the application scene of the upper-layer application is a mass data scene and the like. The corresponding relation between the application scenes of the data management requirements can also be set based on actual requirements.
In a possible implementation manner, a corresponding relationship between an application scene and a time sequence database is preset in the data management system, that is, after an application scene (target application scene) of a current upper application is determined, the time sequence database (target time sequence database) corresponding to the application scene is determined according to the corresponding relationship, so that data obtained under the application scene is stored in the corresponding time sequence database, and when an operation instruction from the upper application is received, the data in the corresponding time sequence database is correspondingly processed.
Since different time-series databases are respectively corresponding to specific concepts, data in the target time-series database cannot be directly processed based on the attribute of the operation parameter in the first operation instruction, a mapping relation between the attribute of the operation parameter in the first operation instruction and the corresponding attribute (concept) in the target time-series database is established, the attribute of the operation parameter in the first operation instruction and the corresponding attribute in the target time-series database are corresponding based on the mapping relation, and a second operation instruction having the concept in the target time-series database is generated to process the data in the target time-series database.
In one possible implementation, the above process is implemented as:
mapping the organization into a database in the target time sequence database based on the mapping relation corresponding to the target time sequence database;
mapping the measuring point types into a data table in a database;
mapping the measurement points to metrics in a database;
mapping the device to a tag in a database;
mapping the time to a timestamp in a database;
mapping the corresponding numerical value to a field value in a database;
and obtaining a second operation instruction based on the database, the data table, the measurement, the tag, the timestamp and the field value.
In a possible implementation manner, names of databases, data tables, metrics, tags, timestamps, and Field values in different time sequence databases are different, for example, in infixdb, infixdb includes concepts such as Database, Retention Policy, measure (Measurement point), TimeStamp, Tag (Tag), and Field value, and the like, and can map an organization to Database, map different Measurement point types to Retention Policy, map a Measurement point to measure, map a device to a Tag, and convert a corresponding value to a Field. For another example, concepts such as Namespace, Table, Metric, TimeStamp, Tag, Value, Data point, etc. are included in OpenTSDB (Open Time Series Database), and the concepts such as Namespace, Table, Metric, TimeStamp, Tag, Value, Data point, etc. may be used to map an organization into Namespace, map different measurement point types into Table, map a measurement point into Metric, map a device into a kind of Tag, convert a corresponding Value into a kind of Value, and so on.
In one possible implementation, the database management system indicates physical isolation of data between different organizations. The physical isolation refers to that different organizations use different CPUs, memories, disks and the like, and the storage areas of data resources for storing respective data are isolated on hardware equipment, so that the data of the organizations are not interfered with each other.
In a possible implementation manner, the data types of different measuring points may be different, and the data of different measuring point types may be retained for different data durations, where the data types of the measuring points and the data retainable durations of the data of different measuring point types may be set by a user based on actual needs.
Based on the mapping process, the above object can be achieved through different attributes in a time sequence Database, taking infilux as an example, fig. 4 shows a schematic diagram of the infilux mapping process shown in an exemplary embodiment of the present application, as shown in fig. 4, taking a first operation instruction as an example of a data adding instruction, and the first operation instruction includes an AI type measuring point 410 and a DI type measuring point 420, where data corresponding to the AI type measuring point 410 is reserved for a first time period, such as 3 months, data corresponding to the DI type measuring point 420 is reserved for a second time period, such as 6 months, when the mapping process is performed, for the purpose of achieving physical isolation of data of different organizations, different measuring points may have different measuring point types, and different measuring point types are reserved for different data time periods, a management device labels different organizations through different databases (databases), and through different measurements (measuring points), marking different measuring points, marking measuring point types of different measuring points through different Retention policies, thereby realizing the distinction of data of different measuring points, and simultaneously adding corresponding data into field values (Filed) in a database in the Influx.
For another example, taking OpenTSDB (Open Time Series Database, development Time Series Database) as an example, fig. 5 shows a schematic diagram of OpenTSDB mapping processing shown in an exemplary embodiment of the present application, as shown in fig. 5, taking a first operation instruction as a data adding instruction, where the first operation instruction includes an AI type measuring point 510 and a DI type measuring point 520, where data corresponding to the AI type measuring point 510 is reserved for a first Time period, such as 3 months, data corresponding to the DI type measuring point 520 is reserved for a second Time period, such as 6 months, and when mapping processing is performed, for the purpose of achieving physical isolation of data of different organizations, different measuring points may have different measuring point types, and different measuring point types are reserved for different data Time periods, a management device labels different organizations through different namespaces, and different meters, the measuring point types of different measuring points are marked through different tables, so that the data of different measuring points are distinguished, and meanwhile, the corresponding data are added into a numerical Value (Value) in a database in the OpenTSDB.
In a possible implementation manner, when the attribute of at least one operation parameter in the first operation instruction is mapped to the corresponding attribute in the target time series database, the mapping relationship may be established based on the characteristic of the time series database engine, so as to meet the requirement in the scene of the internet of things, for example, the above-described characteristic that the Tag of the infiluxdb has an index may be fully utilized, and when querying different devices, the function of quickly searching by using the index is utilized, so as to improve the query efficiency.
And 360, issuing a second operation instruction to the target time sequence database, wherein the second operation instruction is used for indicating the target time sequence database to execute data processing operation corresponding to at least one operation parameter.
In a possible implementation manner, at least two databases included in the database management system are heterogeneous time-series databases, and during the connection process, the management device can implement access to the time-series databases across protocols of heterogeneous engines through Http/thread and the like. Fig. 6 shows an architecture diagram of accessing a time-series database by an upper layer application according to an exemplary embodiment of the present application, as shown in fig. 6, the upper layer application 610 issues a first operation instruction to a database management system, where the first operation instruction includes information such as an organization, a measurement point, and a device timestamp, the database management system receives the first operation instruction through a database access interface that is externally provided, the management device 620 maps an attribute of at least one operation parameter in the first operation instruction to a concept in the first time-series database 630 based on a usage scenario of the upper layer application 610 and an edge device application scenario of the upper layer application as an example, generates a second operation instruction, and sends the second operation instruction to the first time-series database 630 based on a protocol that can span a heterogeneous engine such as Http/thread, and the like, so as to implement access to the first time-series database 630, the data in the first time sequence database 630 corresponding to the at least one operation parameter is processed for operation based on the second operation instruction.
It should be noted that after the usage scenario of the upper layer application is determined, the time sequence database corresponding to the upper layer application is uniquely determined, that is, only one link in fig. 6 is passed through.
To sum up, in the data processing method in the context of the internet of things provided by the embodiment of the application, by additionally providing the database management system, the database access interface in the database management system receives the first operation instruction issued by the upper application, the management device in the database management system determines the target time sequence database acted by the first operation instruction based on the usage context of the upper application, and maps the operation parameters in the first operation instruction to the corresponding attributes in the target time sequence database, so that the first operation instruction is converted into the second operation instruction capable of directly acting on the target time sequence database, and the data in the target time sequence database is correspondingly processed. Therefore, on the premise of realizing the deployment of the time sequence databases corresponding to the multi-terminal application scene of the Internet of things, the connection operation required when the upper-layer application accesses different time sequence databases is reduced, and the access efficiency of the upper-layer application to the time sequence databases is improved.
Fig. 7 is a schematic diagram of a database management system according to an exemplary embodiment of the present application, and as shown in fig. 7, the data management system 700 includes a management device 710 and at least two timing databases 720; the data management system is externally provided with a database access interface;
the management device 710 is used for receiving a data operation instruction of an upper application through the database access interface; the first operation instruction comprises at least one operation parameter;
acquiring a target application scene; the target application scene is a use scene of an upper application for issuing a data operation instruction; determining a target timing database 721 according to the target application scenario, wherein the target timing database is a timing database corresponding to the target application scenario among the at least two timing databases 720; mapping the attribute of the operation parameter to the attribute corresponding to the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operation instruction; issuing a second operation instruction to the target time sequence database;
the target timing database 721 is used for performing data processing operations corresponding to at least one operation parameter.
To sum up, in the data processing method in the context of the internet of things provided by the embodiment of the application, by additionally providing the database management system, the database access interface in the database management system receives the first operation instruction issued by the upper application, the management device in the database management system determines the target time sequence database acted by the first operation instruction based on the usage context of the upper application, and maps the operation parameters in the first operation instruction to the corresponding attributes in the target time sequence database, so that the first operation instruction is converted into the second operation instruction capable of directly acting on the target time sequence database, and the data in the target time sequence database is correspondingly processed. Therefore, on the premise of realizing the deployment of the time sequence databases corresponding to the multi-terminal application scene of the Internet of things, the connection operation required when the upper-layer application accesses different time sequence databases is reduced, and the access efficiency of the upper-layer application to the time sequence databases is improved.
Fig. 8 is a block diagram of a data processing apparatus in an internet of things scenario, where the apparatus may be applied to a computer device, where the computer device may be implemented as a management device in the data management system, and the data management system further includes at least two timing databases, and the data management system is externally provided with a database access interface, as shown in fig. 8, the data processing apparatus in the internet of things scenario includes:
a first operation instruction receiving module 810, configured to receive a first operation instruction through a database access interface; the first operation instruction comprises at least one operation parameter;
a target application scene obtaining module 820, configured to obtain a target application scene; the target application scene is a use scene of an upper application for issuing a data operation instruction;
a target time sequence database determining module 830, configured to determine a target time sequence database according to a target application scenario, where the target time sequence database is a time sequence database corresponding to the target application scenario among at least two time sequence databases;
a second operation instruction obtaining module 840, configured to map, based on the mapping relationship corresponding to the target time sequence database, the attribute of the operation parameter to a corresponding attribute in the target time sequence database, so as to obtain a second operation instruction;
the second operation instruction issuing module 850 is configured to issue a second operation instruction to the target time sequence database, where the second operation instruction is used to instruct the target time sequence database to perform a data processing operation corresponding to at least one operation parameter.
In a possible implementation manner, the target application scenario obtaining module 820 includes:
the deployment mode acquisition submodule is used for acquiring the deployment mode of the upper application;
and the target application scene determining submodule is used for determining a target application scene based on the deployment mode of the upper application.
In one possible implementation, the attributes of the operating parameters include organization, station type, station, equipment, time, and corresponding values.
In a possible implementation manner, the second operation instruction obtaining module 840 includes:
the first mapping submodule is used for mapping the organization into a database in the target time sequence database based on the mapping relation corresponding to the target time sequence database;
the second mapping submodule is used for mapping the measuring point types into a data table in the database;
a third mapping submodule for mapping the measurement points to metrics in the database;
a fourth mapping submodule, configured to map the device to a tag in the database;
a fifth mapping submodule, configured to map the time to a timestamp in the database;
the sixth mapping submodule is used for mapping the corresponding numerical value into a record value in the database;
and the second operation instruction acquisition submodule is used for acquiring a second operation instruction based on the database, the tag, the data table, the timestamp and the record value.
In one possible implementation, the first operation instruction includes: one of a data add instruction, a data delete instruction, a data search instruction, and a data modify instruction.
In one possible implementation, the at least two time series databases are heterogeneous time series databases.
To sum up, in the data processing method in the context of the internet of things provided by the embodiment of the application, by additionally providing the database management system, the database access interface in the database management system receives the first operation instruction issued by the upper application, the management device in the database management system determines the target time sequence database acted by the first operation instruction based on the usage context of the upper application, and maps the operation parameters in the first operation instruction to the corresponding attributes in the target time sequence database, so that the first operation instruction is converted into the second operation instruction capable of directly acting on the target time sequence database, and the data in the target time sequence database is correspondingly processed. Therefore, on the premise of realizing the deployment of the time sequence databases corresponding to the multi-terminal application scene of the Internet of things, the connection operation required when the upper-layer application accesses different time sequence databases is reduced, and the access efficiency of the upper-layer application to the time sequence databases is improved.
Fig. 9 is a block diagram illustrating the structure of a computer device 900 according to an example embodiment. The computer device may be implemented as the management device in the above-mentioned aspect of the present application. The computer apparatus 900 includes a Central Processing Unit (CPU) 901, a system Memory 904 including a Random Access Memory (RAM) 902 and a Read-Only Memory (ROM) 903, and a system bus 905 connecting the system Memory 904 and the CPU 901. The computer device 900 also includes a basic Input/Output system (I/O system) 906, which facilitates the transfer of information between devices within the computer, and a mass storage device 907 for storing an operating system 913, application programs 914, and other program modules 915.
The basic input/output system 906 includes a display 908 for displaying information and an input device 909 such as a mouse, keyboard, etc. for user input of information. Wherein the display 908 and the input device 909 are connected to the central processing unit 901 through an input output controller 910 connected to the system bus 905. The basic input/output system 906 may also include an input/output controller 910 for receiving and processing input from a number of other devices, such as a keyboard, mouse, or electronic stylus. Similarly, input-output controller 910 also provides output to a display screen, a printer, or other type of output device.
The mass storage device 907 is connected to the central processing unit 901 through a mass storage controller (not shown) connected to the system bus 905. The mass storage device 907 and its associated computer-readable media provide non-volatile storage for the computer device 900. That is, the mass storage device 907 may include a computer-readable medium (not shown) such as a hard disk or Compact Disc-Only Memory (CD-ROM) drive.
Without loss of generality, the computer-readable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes RAM, ROM, Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), flash Memory or other solid state Memory technology, CD-ROM, Digital Versatile Disks (DVD), or other optical, magnetic, or other magnetic storage devices. Of course, those skilled in the art will appreciate that the computer storage media is not limited to the foregoing. The system memory 904 and mass storage device 907 described above may be collectively referred to as memory.
According to various embodiments of the present application, the computer device 900 may also operate as a remote computer connected to a network via a network, such as the Internet. That is, the computer device 900 may be connected to the network 912 through the network interface unit 911 coupled to the system bus 905, or the network interface unit 911 may be used to connect to other types of networks or remote computer systems (not shown).
The memory further includes one or more programs, the one or more programs are stored in the memory, and the central processor 901 implements all or part of the steps of the method shown in fig. 2 or fig. 3 by executing the one or more programs.
Fig. 10 is a block diagram illustrating the structure of a computer device 1000 according to an example embodiment. The computer device 1000 may be implemented as the above-mentioned operation terminal, such as a smart phone, a tablet computer or a desktop computer. The computer device 1000 may also be referred to by other names such as user equipment, portable terminal, laptop terminal, desktop terminal, and the like.
Generally, the computer device 1000 includes: a processor 1001 and a memory 1002.
In some embodiments, the computer device 1000 may further optionally include: a peripheral interface 1003 and at least one peripheral. The processor 1001, memory 1002 and peripheral interface 1003 may be connected by a bus or signal line. Various peripheral devices may be connected to peripheral interface 1003 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 1004, display screen 1005, camera assembly 1006, audio circuitry 1007, positioning assembly 1008, and power supply 1009.
In some embodiments, the computer device 1000 also includes one or more sensors 1010. The one or more sensors 1010 include, but are not limited to: acceleration sensor 1011, gyro sensor 1012, pressure sensor 1013, fingerprint sensor 1014, optical sensor 1015, and proximity sensor 1016.
Those skilled in the art will appreciate that the configuration shown in FIG. 10 is not intended to be limiting of the computer device 1000, and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components may be used.
Those skilled in the art will appreciate that in one or more of the examples described above, the functions described in the embodiments of the present application may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The disclosed embodiment also provides a computer device storage medium, which stores at least one program code, and the program code is loaded and executed by a processor to implement the program designed by all or part of the steps executed by the management device in the method as shown in fig. 2 or fig. 3.
According to an aspect of the present disclosure, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes all or part of the steps executed by the management device in the method shown in fig. 2 or fig. 3.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. A data processing method under the scene of the Internet of things is characterized in that the method is executed by management equipment in a database management system, the database management system also comprises at least two time sequence databases, and the database management system is externally provided with a database access interface, and the method comprises the following steps:
receiving a first operation instruction through the database access interface; the first operation instruction comprises at least one operation parameter;
acquiring a target application scene; the target application scene is a use scene of an upper layer application which issues the data operation instruction;
determining a target time sequence database according to the target application scene, wherein the target time sequence database is one of the at least two time sequence databases and corresponds to the target application scene;
mapping the attribute of the operating parameter to the corresponding attribute in the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operating instruction;
and issuing the second operation instruction to the target time sequence database, wherein the second operation instruction is used for indicating the target time sequence database to execute the data processing operation corresponding to the at least one operation parameter.
2. The method of claim 1, wherein the obtaining the target application scenario comprises:
acquiring a deployment mode of the upper application;
and determining the target application scene based on the deployment mode of the upper application.
3. A method according to any of claims 1 or 2, wherein the attributes of the operating parameters include organization, station type, station, equipment, time, and corresponding values.
4. The method according to claim 3, wherein the mapping the attribute of the operation parameter to the attribute corresponding to the target time-series database based on the mapping relationship corresponding to the target time-series database to obtain a second operation instruction comprises:
mapping the organization into a database in the target time sequence database based on a mapping relation corresponding to the target time sequence database;
mapping the measuring point types into a data table in the database;
mapping the measurement points to metrics in the database;
mapping the device to a tag in the database;
mapping the time to a timestamp in the database;
mapping the corresponding numerical value to a field value in the database;
obtaining the second operation instruction based on the database, the data table, the metric, the tag, the timestamp, and the field value.
5. The method of claim 1, wherein the first operation instruction comprises: one of a data add instruction, a data delete instruction, a data search instruction, and a data modify instruction.
6. The method of claim 1, wherein the at least two time series databases are heterogeneous time series databases.
7. A database management system is characterized in that the data management system comprises a management device and at least two time sequence databases; the data management system is externally provided with a database access interface;
the management device is used for receiving a data operation instruction of an upper application through the database access interface; the first operation instruction comprises at least one operation parameter;
acquiring a target application scene; the target application scene is a use scene of an upper layer application which issues the data operation instruction; determining a target time sequence database according to the target application scene, wherein the target time sequence database is one of the at least two time sequence databases and corresponds to the target application scene; mapping the attribute of the operating parameter to the attribute corresponding to the target time sequence database based on the mapping relation corresponding to the target time sequence database to obtain a second operating instruction; issuing the second operation instruction to the target time sequence database;
and the target time sequence database is used for executing data processing operation corresponding to the at least one operation parameter.
8. The data processing device under the scene of the internet of things is characterized in that the device is applied to management equipment in a database management system, the database management system further comprises at least two time sequence databases, the database management system is externally provided with a database access interface, and the device comprises:
the first operation instruction receiving module is used for receiving a first operation instruction through the database access interface; the first operation instruction comprises at least one operation parameter;
the target application scene acquisition module is used for acquiring a target application scene; the target application scene is a use scene of an upper layer application which issues the data operation instruction;
a target time sequence database determining module, configured to determine a target time sequence database according to the target application scenario, where the target time sequence database is a time sequence database corresponding to the target application scenario among the at least two time sequence databases;
a second operation instruction obtaining module, configured to map, based on a mapping relationship corresponding to the target time sequence database, an attribute of the operation parameter to a corresponding attribute in the target time sequence database, so as to obtain a second operation instruction;
and the second operation instruction issuing module is used for issuing the second operation instruction to the target time sequence database, and the second operation instruction is used for indicating the target time sequence database to execute the data processing operation corresponding to the at least one operation parameter.
9. A computer device, wherein the computer device comprises a processor and a memory; the memory stores at least one instruction, at least one program, a set of codes, or a set of instructions, which is loaded and executed by the processor to implement the data processing method in the context of the internet of things as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, wherein at least one program code is stored in the computer-readable storage medium, and the program code is loaded and executed by a processor to implement the data processing method in the context of the internet of things as claimed in any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110551764.XA CN113204592B (en) | 2021-05-20 | 2021-05-20 | Data processing method, system and device in Internet of things scene and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110551764.XA CN113204592B (en) | 2021-05-20 | 2021-05-20 | Data processing method, system and device in Internet of things scene and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113204592A true CN113204592A (en) | 2021-08-03 |
| CN113204592B CN113204592B (en) | 2023-07-21 |
Family
ID=77032188
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110551764.XA Active CN113204592B (en) | 2021-05-20 | 2021-05-20 | Data processing method, system and device in Internet of things scene and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113204592B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114595845A (en) * | 2022-03-10 | 2022-06-07 | 北京百度网讯科技有限公司 | Device information management method, device, electronic device and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104573115A (en) * | 2015-02-04 | 2015-04-29 | 新余兴邦信息产业有限公司 | Method and system for achieving integration interface supporting operation of multi-type databases |
| CN109614390A (en) * | 2018-12-06 | 2019-04-12 | 无锡华云数据技术服务有限公司 | Data base read-write separation method, device, service system, equipment and medium |
| CN109902103A (en) * | 2019-01-17 | 2019-06-18 | 平安城市建设科技(深圳)有限公司 | Service data management method, device, equipment and computer readable storage medium |
| CN110321004A (en) * | 2019-05-30 | 2019-10-11 | 努比亚技术有限公司 | A kind of gesture control method, terminal and computer readable storage medium |
| CN110749058A (en) * | 2019-10-31 | 2020-02-04 | 广东美的制冷设备有限公司 | Terminal control method and device, terminal, and air conditioner control method and device |
| CN111858765A (en) * | 2020-07-24 | 2020-10-30 | 中国工商银行股份有限公司 | Data processing method, device and system applied to database capacity expansion scene |
| CN112000444A (en) * | 2020-10-27 | 2020-11-27 | 财付通支付科技有限公司 | Database transaction processing method and device, storage medium and electronic equipment |
| CN112182634A (en) * | 2020-11-09 | 2021-01-05 | 安徽华典大数据科技有限公司 | Data encryption system and method for graph database |
-
2021
- 2021-05-20 CN CN202110551764.XA patent/CN113204592B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104573115A (en) * | 2015-02-04 | 2015-04-29 | 新余兴邦信息产业有限公司 | Method and system for achieving integration interface supporting operation of multi-type databases |
| CN109614390A (en) * | 2018-12-06 | 2019-04-12 | 无锡华云数据技术服务有限公司 | Data base read-write separation method, device, service system, equipment and medium |
| CN109902103A (en) * | 2019-01-17 | 2019-06-18 | 平安城市建设科技(深圳)有限公司 | Service data management method, device, equipment and computer readable storage medium |
| CN110321004A (en) * | 2019-05-30 | 2019-10-11 | 努比亚技术有限公司 | A kind of gesture control method, terminal and computer readable storage medium |
| CN110749058A (en) * | 2019-10-31 | 2020-02-04 | 广东美的制冷设备有限公司 | Terminal control method and device, terminal, and air conditioner control method and device |
| CN111858765A (en) * | 2020-07-24 | 2020-10-30 | 中国工商银行股份有限公司 | Data processing method, device and system applied to database capacity expansion scene |
| CN112000444A (en) * | 2020-10-27 | 2020-11-27 | 财付通支付科技有限公司 | Database transaction processing method and device, storage medium and electronic equipment |
| CN112182634A (en) * | 2020-11-09 | 2021-01-05 | 安徽华典大数据科技有限公司 | Data encryption system and method for graph database |
Non-Patent Citations (1)
| Title |
|---|
| 畅功民: "高新项目管理系统框架设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114595845A (en) * | 2022-03-10 | 2022-06-07 | 北京百度网讯科技有限公司 | Device information management method, device, electronic device and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113204592B (en) | 2023-07-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106980669B (en) | A kind of storage of data, acquisition methods and device | |
| US11870658B2 (en) | Method and apparatus for updating gateway resource, and IOT control platform | |
| CN111177400B (en) | Knowledge graph-based equipment, business and data associated display method and device | |
| CN102955977A (en) | Energy efficiency service method and energy efficiency service platform adopting same on basis of cloud technology | |
| CN110912782B (en) | Data acquisition method, device and storage medium | |
| CN111400393B (en) | Data processing method and device based on multi-application platform and storage medium | |
| CN109241096A (en) | Data processing method, device and system | |
| CN108958959A (en) | The method and apparatus for detecting hive tables of data | |
| US10671631B2 (en) | Method, apparatus, and computer-readable medium for non-structured data profiling | |
| WO2023138013A1 (en) | Method and system for computing power gridding in multi-cloud scene | |
| CN110046202A (en) | The integrated power system real time data releasing method of key value database based on memory | |
| CN111061802B (en) | Power data management processing method, device and storage medium | |
| CN113204592B (en) | Data processing method, system and device in Internet of things scene and storage medium | |
| CN115408546A (en) | Time sequence data management method, device, equipment and storage medium | |
| CN113934807A (en) | Territorial space planning system and method based on GIS | |
| CN109271453A (en) | A kind of determination method and apparatus of database volume | |
| CN107357919A (en) | User behaviors log inquiry system and method | |
| CN108205086A (en) | Monitoring method, device and system for power grid equipment | |
| CN103247087A (en) | City distribution network graphical intelligent anti-misoperation system and method of system | |
| CN113570464B (en) | Digital currency transaction community identification method, system, equipment and storage medium | |
| CN108683547A (en) | A kind of wireless sensor network configuration method of software definition | |
| CN115438812A (en) | Life-saving management method and device for power transmission equipment, computer equipment and storage medium | |
| CN109902067B (en) | File processing method and device, storage medium and computer equipment | |
| WO2019218677A1 (en) | Data storage method for power grid simulation analysis, device, and electronic apparatus | |
| Pan et al. | Quality monitoring and measuring for internet of services |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |