Data processing method and device, equipment and medium

Abstract

The data processing method and device, the equipment and the medium provided by the embodiment of the invention comprise the steps that a data processing stream is constructed according to the data type of data received by a data acquisition system, and the data processing stream comprises a timed trigger task node, a data server node and a log printing node; the number of the data server nodes and the log printing nodes is the same as the number of data types received by the data acquisition system; in response to a received timed triggering task node triggered by the target object, configuring a triggering time interval of the timed triggering task node; acquiring a device address, a device port and a data IP address corresponding to the data received by the data server node, and performing connection configuration on the data server node according to the device address, the device port and the data IP address; and in response to the received point location information added by the target object, according to the point location information and the triggering time interval, obtaining the target data and printing the target data to the console, so that the data processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing and related technical fields, and specifically, to a data processing method, apparatus, device, and medium applicable to a data processing method, apparatus, device, and medium. Background Art

[0002] With the development of industrial automation, the collection and cleaning of data play an important role in intelligent manufacturing.

[0003] Sensors and devices in existing industrial sites usually generate high-frequency data streams. These data have strong real-time requirements and contain a large amount of noise and outliers. Traditional batch processing and cleaning methods are difficult to meet the real-time processing requirements of high-frequency data. Specifically, most existing high-frequency data collection and cleaning solutions adopt a batch processing mode, and cleaning and storage are performed after the data accumulates to a certain amount, which easily leads to insufficient real-time performance. At the same time, most existing cleaning rules are fixed configurations and are difficult to adapt to changes in different data sources and data characteristics, affecting the cleaning effect and accuracy.

[0004] To solve problems such as data loss, large latency, and low cleaning efficiency existing in the prior art when processing data, a data processing method is urgently needed. Summary of the Invention

[0005] The embodiments described herein provide a data processing method, apparatus, device, and medium to solve the problems existing in the prior art.

[0006] In a first aspect, according to the content of the present disclosure, a data processing method is provided, including:

[0007] Construct a data processing flow according to the data type of the data received by the data collection system, where the data processing flow includes a timed trigger task node, a data server node, and a log printing node, and the number of the data server nodes and the log printing nodes is the same as the number of data types of the data received by the data collection system;

[0008] In response to receiving a timed trigger task node triggered by a target object, configure the trigger time interval of the timed trigger task node;

[0009] Obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address;

[0010] In response to receiving the point information added by the target object, obtain the target data according to the point information and the trigger time interval, and print the target data to the console.

[0011] In some embodiments of the present disclosure, before constructing a data processing flow according to the data types received by the data acquisition system, it further includes:

[0012] Determine the attribute information of the data corresponding to different data types according to the frequencies of the data corresponding to different data types received by the data acquisition system;

[0013] Constructing a data processing flow according to the data types received by the data acquisition system includes:

[0014] Construct a data processing flow according to the data types received by the data acquisition system and the attribute information of the data corresponding to different data types received by the data acquisition system. Among them, the data processing flow includes a timed trigger task node, a data server node, and a log printing node. The number of timed trigger task nodes is related to the attribute information of the data corresponding to different data types received by the data acquisition system. The number of data server nodes and log printing nodes is the same as the number of data types received by the data acquisition system.

[0015] In some embodiments of the present disclosure, configuring the trigger time interval of the timed trigger task node in response to receiving a timed trigger task node triggered by a target object includes:

[0016] In response to receiving a target timed trigger task node triggered by a target object, configure the trigger time interval of the timed trigger task node according to the attribute information of the data corresponding to the target data type received by the target timed trigger task node.

[0017] In some embodiments of the present disclosure, obtaining the device address, device port, and data IP address corresponding to the data received by the data server node, and performing connection configuration on the data server node according to the device address, device port, and data IP address includes:

[0018] Determine the data server node according to the data type of the data received by the data acquisition system;

[0019] Obtain the device address, device port, and data IP address corresponding to the data received by the data server node according to the label identifier of the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address.

[0020] In some embodiments of the present disclosure, in response to receiving the point information added by the target object, obtaining target data according to the point information and the trigger time interval, and printing the target data to the console includes:

[0021] In response to receiving the point information added by the target object, obtain the data area, start address, and data label included in the point information;

[0022] According to the data area, start address, and data label, obtain the target data at the trigger time interval;

[0023] According to the trigger time interval, print the target data to the console.

[0024] In some embodiments of the present disclosure, before the step of responding to receiving the point information added by the target object, obtaining the target data according to the point information and the trigger time interval, and printing the target data to the console, further includes:

[0025] Obtain the data area, start address, and data label selected by the target object;

[0026] Generate point information to the data point table according to the data area, start address, and data label selected by the target object.

[0027] In some embodiments of the present disclosure, the data processing flow further includes a data cleaning node;

[0028] The step of obtaining the target data according to the point information and the trigger time interval, and printing the target data to the console includes:

[0029] Obtain the initial data according to the point information and the trigger time interval;

[0030] In response to receiving the target processing function selected by the target object, process the initial data to obtain the target data;

[0031] Print the target data to the console.

[0032] In a second aspect, according to the content of the present disclosure, a data processing device is provided, including:

[0033] A data processing flow construction module, configured to construct a data processing flow according to the data type of the data received by the data acquisition system, where the data processing flow includes a timing trigger task node, a data server node, and a log printing node, and the number of the data server nodes and the log printing nodes is the same as the number of data types of the data received by the data acquisition system;

[0034] A trigger time interval configuration module, configured to configure the trigger time interval of the timing trigger task node in response to receiving the timing trigger task node triggered by the target object;

[0035] A connection configuration module, configured to obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address;

[0036] A printing module, configured to, in response to receiving the point information added by the target object, obtain target data according to the point information and the trigger time interval, and print the target data to the console.

[0037] In a third aspect, according to the content of the present disclosure, a computer device is provided, including:

[0038] One or more processors;

[0039] A storage device, configured to store one or more programs,

[0040] When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of the first aspect.

[0041] In a fourth aspect, according to the content of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method according to any one of the first aspect is implemented.

[0042] The data processing method, device, and medium provided by the embodiments of the present disclosure first construct a data processing flow according to the data type of the data received by the data acquisition system. The data processing flow includes a timed trigger task node, a data server node, and a log printing node, and the number of data server nodes is the same as the number of data types of the data received by the data acquisition system. Then, in response to receiving the timed trigger task node triggered by the target object, configure the trigger time interval of the timed trigger task node; and obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address; in response to receiving the point information added by the target object, obtain target data according to the point information and the trigger time interval, and print the target data to the console. Since the data processing flow includes data server nodes corresponding to different data types, concurrent acquisition of data from different data sources can be realized, improving the data processing efficiency. In addition, during the process of acquiring target data according to the point information and the trigger time interval, the user can customize the configuration of the point information to realize the acquisition of different data, and by configuring the trigger time interval, the data acquisition efficiency can be changed, which has a certain degree of flexibility.

[0043] The above description is only an overview of the technical solutions of the embodiments of the present application. In order to better understand the technical means of the embodiments of the present application, it can be implemented according to the content of the description. Moreover, in order to make the above and other objects, features, and advantages of the embodiments of the present application more obvious and understandable, the following specifically illustrates the specific implementation manners of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly described below. It should be understood that the following described drawings only relate to some embodiments of the present disclosure and do not limit the present disclosure, where:

[0045] Figure 1 is a schematic flowchart of a data processing method provided by an embodiment of the present disclosure;

[0046] Figures 2A - 2D is a schematic diagram of the interface structure of a data processing method provided by an embodiment of the present disclosure;

[0047] Figure 3 is a schematic flowchart of another data processing method provided by an embodiment of the present disclosure;

[0048] Figure 3A is a schematic diagram of the interface structure of another data processing method provided by an embodiment of the present disclosure;

[0049] Figure 4 is a schematic flowchart of yet another data processing method provided by an embodiment of the present disclosure;

[0050] Figure 4A is a schematic diagram of the interface structure of yet another data processing method provided by an embodiment of the present disclosure;

[0051] Figure 5 is a schematic diagram of the structure of a data processing device provided by an embodiment of the present disclosure;

[0052] Figure 6 is a schematic diagram of the structure of a computer device provided by an embodiment of the present disclosure.

[0053] In the drawings, labels with the same last two digits correspond to the same elements. It should be noted that the elements in the drawings are schematic and not drawn to scale. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are some but not all of the embodiments of the present disclosure. All other embodiments obtained by those skilled in the art without creative efforts based on the described embodiments of the present disclosure also fall within the scope of protection of the present disclosure.

[0055] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the subject matter of the present disclosure pertains. Further, it will be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and the relevant art, and will not be interpreted in an idealized or overly formal manner unless expressly defined otherwise herein. As used herein, a statement that two or more parts are "connected" or "coupled" together shall mean that the parts are directly joined together or joined through one or more intermediate components.

[0056] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase "embodiments" appearing in various places in the specification does not necessarily refer to the same embodiment, nor are they independent or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0057] As used herein, the term "and / or" is merely a description of an association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: the existence of A, the simultaneous existence of A and B, and the existence of B. Additionally, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0058] In addition, in all embodiments of the present disclosure, terms such as "first" and "second" are only used to distinguish one component (or a part of a component) from another component (or another part of a component).

[0059] In the description of the present application, unless otherwise specified, the meaning of "a plurality" refers to two or more (including two). Similarly, "a plurality of groups" refers to two or more groups (including two groups).

[0060] To enable those skilled in the art of this technology to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0061] Based on the problems existing in the prior art, the embodiments of the present disclosure provide a data processing method.Figure 1 It is a schematic flowchart of a data processing method provided by an embodiment of the present disclosure. As Figure 1 shown, the data processing method includes:

[0062] S110. Construct a data processing flow according to the data type of the data received by the data acquisition system.

[0063] Among them, the data processing flow includes a timed trigger task node, a data server node, and a log printing node. The number of data server nodes and log printing nodes is the same as the number of data types of the data received by the data acquisition system.

[0064] In a specific implementation, the data acquisition system will receive data of multiple data types. For example, the data acquisition system collects sensor data, PLC data, database data, and API data. Since the data sources collected by the data acquisition system are different and the data types are different, by making the number of data server nodes and log printing nodes in the constructed data processing flow the same as the number of data types of the data received by the data acquisition system, the simultaneous reception and processing of data of different data types are realized.

[0065] Specifically, the constructed data processing flow includes a timed trigger task node, a data server node, and a log printing node. If the number of data types of the data received by the data acquisition system is two, the number of data server nodes and log printing nodes in the constructed data flow is two, as Figure 2A shown.

[0066] S120. In response to receiving a timed trigger task node triggered by a target object, configure the trigger time interval of the timed trigger task node.

[0067] After the data processing flow is constructed, the target object triggers and selects the timed trigger task node in the data processing flow to configure the trigger time interval of the timed trigger task node. By configuring the trigger time interval of the timed trigger task node, the data acquisition frequency of the data acquisition system can be changed. The shorter the configured trigger time interval of the timed trigger task node, the faster the data acquisition frequency of the data acquisition system, realizing the acquisition of high-frequency data.

[0068] As a specific implementation, configure the trigger time interval of the timed trigger task node to be the same as the efficiency of the time interval for the target object to expect to process data.

[0069] S130. Obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address.

[0070] After constructing the data processing flow and configuring the trigger time interval of the timed trigger task nodes in the data processing flow, it is necessary to configure the connection of the data server nodes to obtain data from different data sources through the data server nodes.

[0071] As a specific implementation, obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and configure the connection of the data server node according to the device address, device port, and data IP address, including: determining the data server node according to the data type of the data received by the data acquisition system; obtaining the device address, device port, and data IP address corresponding to the data received by the data server node according to the label identifier of the data server node, and configuring the connection of the data server node according to the device address, device port, and data IP address.

[0072] Specifically, first determine the data server node according to the data type of the data received by the data acquisition system and the number of data types of different received data, and then obtain the device address, device port, and data IP address corresponding to the label identifier according to the label identifier corresponding to the data server node, and configure the connection of the data server node through the device address, device port, and data IP address, so that the data server node can obtain data of the data type that the data server node can process from the IP address of the corresponding target device. Among them, during the process of the data server node collecting data of the data type that the data server node can process from the IP address of the target device, the data collection time interval is the same as the trigger time interval of the timed trigger task node.

[0073] As a specific example, if the data types of the data received by the data acquisition system include PLC data and API data, then select the data server corresponding to the PLC data and the data server corresponding to the API data according to the data types of the data received by the data acquisition system.

[0074] S140. In response to receiving the point information added by the target object, obtain the target data according to the point information and the trigger time interval, and print the target data to the console.

[0075] In a specific implementation, after the data server node obtains the data from the device, the obtained data is stored according to the point information, where the point information includes the data area, start address, and data label. As an example, the data stored in the data server node is as follows Figure 2BAs shown, the data stored at the points "4_0", "4_1", and "4_2" are 100, 200, and 300 respectively. Among them, F03 represents the data area, "4_0", "4_1", and "4_2" are data labels, 0 is the starting address of the point "4_0", 1 is the starting address of the point "4_1", and 2 is the starting address of the point "4_2".

[0076] Specifically, when the target object triggers the add button at the data server node and generates point information by adding data points, at this time, according to the point information added by the target object and the trigger time interval, the data corresponding to the point information is obtained according to the trigger time interval, and the data corresponding to the point information obtained according to the trigger time interval is printed to the console to achieve data acquisition.

[0077] As a specific implementable manner, in response to receiving the point information added by the target object, according to the point information and the trigger time interval, the target data is obtained and the target data is printed to the console, including: in response to receiving the point information added by the target object, obtaining the data area, starting address, and data label included in the point information; according to the data area, starting address, and data label, obtaining the target data according to the trigger time interval; printing the target data to the console according to the trigger time interval.

[0078] Specifically, after the data server node is connected and configured according to the device address, device port, and data IP address, the target object can trigger the add button, as Figure 2C shown, to display the configuration box for adding data points. The target object can select the data area, starting address, and data label in the configuration box for adding data points to generate point information in the data point table, as Figure 2D shown. At this time, the data server node obtains the target data from the corresponding position of the data server node according to the point information in the data point table according to the data area, starting address, and data label according to the trigger time interval, and prints the obtained target data to the console according to the trigger time interval to achieve data acquisition and printing, as Figure 2D shown.

[0079] The data processing method provided by the embodiments of the present disclosure first constructs a data processing flow according to the data types of the data received by the data acquisition system. The data processing flow includes a timed trigger task node, a data server node, and a log printing node, and the number of data server nodes is the same as the number of data types of the data received by the data acquisition system. Then, in response to receiving a timed trigger task node triggered by a target object, configure the trigger time interval of the timed trigger task node; and obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address; in response to receiving the point information added by the target object, obtain the target data according to the point information and the trigger time interval, and print the target data to the console. Since the data processing flow includes data server nodes corresponding to different data types, concurrent acquisition of data from different data sources can be achieved, improving the data processing efficiency. In addition, during the process of acquiring target data according to the point information and the trigger time interval, the user can customize the configuration of the point information to achieve the acquisition of different data, and by configuring the trigger time interval, the data acquisition efficiency can be changed, which has a certain degree of flexibility.

[0080] Based on the above embodiment, Figure 3 is a flowchart of another data processing method provided by the embodiments of the present disclosure. The embodiments of the present disclosure are based on the above embodiment, as Figure 3 shown, before executing step S110, it further includes:

[0081] S101. Determine the attribute information of the data corresponding to different data types according to the frequency of the data corresponding to different data types received by the data acquisition system.

[0082] Specifically, the attribute information of the data includes high-frequency data and low-frequency data. If the attribute information of the data is high-frequency data, it means that this type of data is relatively important. If the attribute information of the data is low-frequency data, it means that this type of data is unimportant data.

[0083] The data acquisition system determines the attribute information of the data corresponding to this data type by analyzing the frequency of the data corresponding to different data types received. Exemplarily, if the frequency of the data of the data type sent by the sensor is greater than the preset frequency, the attribute information of the data sent by the sensor is high-frequency data. If the frequency of the data of the data type sent by the PLC is less than the preset frequency, the attribute information of the data sent by the PLC is low-frequency data.

[0084] At this time, the specific implementation manner of step S110 includes:

[0085] S111. Construct a data processing flow according to the data types received by the data acquisition system and the attribute information of the data corresponding to different data types received by the data acquisition system.

[0086] Among them, the data processing flow includes a timed trigger task node, a data server node, and a log printing node. The number of timed trigger task nodes is related to the attribute information of the data corresponding to different data types received by the data acquisition system, and the number of data server nodes and log printing nodes is the same as the number of data types received by the data acquisition system.

[0087] When the attribute information of the data corresponding to different data types is different, the trigger time intervals of the timed trigger task nodes in the data processing flow are different. At this time, the constructed data processing flow needs to include multiple timed trigger task nodes.

[0088] Taking a specific example, when the data types of the data received by the data acquisition system include four types, namely sensor data, PLC data, database data, and API data. If the attribute information corresponding to PLC data, database data, and API data is low-frequency data, and the attribute information corresponding to sensor data is high-frequency data. At this time, the number of data server nodes in the constructed data flow is 4, and the number of timed trigger task nodes is 2. As Figure 3A shown, the timed trigger task node 1 receives sensor data, and the timed trigger task node 2 receives PLC data, database data, and API data. The trigger time interval corresponding to the timed trigger task node 1 and the trigger time interval corresponding to the timed trigger task node 2 are different, and the trigger time interval corresponding to the timed trigger task node 1 is less than the trigger time interval corresponding to the timed trigger task node 2.

[0089] At this time, the specific implementation method of step S120 includes:

[0090] S121. In response to receiving the target timed trigger task node triggered by the target object, configure the trigger time interval of the timed trigger task node according to the attribute information of the data corresponding to the target data type received by the target timed trigger task node.

[0091] Specifically, in combination with Figure 3A, when the number of task nodes triggered at regular intervals in the constructed data processing flow is two, the task node triggered at regular intervals 1 receives sensor data, and the task node triggered at regular intervals 2 receives PLC data, database data, and API data. At this time, according to the attribute information of the data corresponding to the target data type received by the task node triggered at regular intervals 1, the trigger time interval of the task node triggered at regular intervals 2 is configured. According to the attribute information of the data corresponding to the target data type received by the task node triggered at regular intervals 2, the trigger time interval of the task node triggered at regular intervals 2 is configured. After configuring the trigger time intervals of the task node triggered at regular intervals 1 and the task node triggered at regular intervals 2, the data server node 1 connected to the task node triggered at regular intervals 1 collects sensor data according to the trigger time interval of the task node triggered at regular intervals 1, the data server node 2 connected to the task node triggered at regular intervals 2 collects PLC data according to the trigger time interval of the task node triggered at regular intervals 2, the data server node 3 connected to the task node triggered at regular intervals 2 collects database data according to the trigger time interval of the task node triggered at regular intervals 2, and the data server node 4 connected to the task node triggered at regular intervals 2 collects API data according to the trigger time interval of the task node triggered at regular intervals 2, realizing parallel collection according to data sources, and the time intervals of parallel collection of different data sources are related to the attribute information of the data sources, improving the collection efficiency of high-frequency data.

[0092] Based on the above embodiments, Figure 4 is a schematic flowchart of another data processing method provided by an embodiment of the present disclosure, Figure 4A is a schematic structural diagram of another data processing flow provided by an embodiment of the present disclosure. Combining Figure 4 and Figure 4A , the specific implementation manner of step S140 includes:

[0093] S141. Obtain initial data according to the point position information and the trigger time interval.

[0094] S142. In response to receiving the target processing function selected by the target object, process the initial data to obtain target data.

[0095] As Figure 4A shown, the data processing flow further includes a data cleaning node.

[0096] By adding a data cleaning node to the data processing flow, the target object can trigger the data cleaning node, select the target processing function or edit the target processing function, and can realize processing the collected initial data according to the target processing function.

[0097] A specific example is that, assuming that the numerical range of the PLC data read is from 100 to 400, by selecting the processing function, the read PLC data is mapped to the numerical range of 0 to 100. At this time, the linear mapping formula is as follows:

[0098]

[0099] By adding a data cleaning node between the data server node and the log printing node and configuring the data processing function of the data cleaning node, it is possible to process the collected initial data according to the target processing function.

[0100] S143. Print the target data to the console.

[0101] After the target processing function processes the collected initial data, the obtained target data is printed to the console to achieve data unification.

[0102] It should be noted that the processing functions include but are not limited to deduplication, format conversion, anomaly detection and elimination, and missing value filling, etc. Among them, deduplication means that when the data flows into the cleaning module, deduplication is performed on the specified fields (such as primary key, timestamp) to eliminate duplicate records; format conversion means converting the original data format (such as XML) into the target format (such as JSON) for unified storage and analysis; anomaly detection and elimination means setting threshold rules (such as the temperature range is 10 - 100 °C), and the data outside the range is marked or eliminated; missing value filling means filling the data of the missing fields, supporting zero filling, mean filling, etc.

[0103] Based on the above embodiments, the embodiments of the present disclosure further provide a data processing device. Figure 5 It is a schematic structural diagram of a data processing device provided by the embodiments of the present disclosure. As Figure 5 shown, the data processing device includes:

[0104] A data processing flow construction module 501, configured to construct a data processing flow according to the data type of the data received by the data acquisition system. Among them, the data processing flow includes a timed trigger task node, a data server node, and a log printing node, and the number of data server nodes and log printing nodes is the same as the number of data types of the data received by the data acquisition system;

[0105] A trigger time interval configuration module 502, configured to configure the trigger time interval of the timed trigger task node in response to receiving the timed trigger task node triggered by the target object;

[0106] A connection configuration module 503, configured to obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address;

[0107] A printing module 504, configured to obtain target data according to the point information and the trigger time interval in response to receiving the point information added by the target object, and print the target data to the console.

[0108] The data processing device provided by the embodiments of the present disclosure first constructs a data processing flow according to the data types of the data received by the data acquisition system. The data processing flow includes a timed trigger task node, a data server node, and a log printing node, and the number of data server nodes is the same as the number of data types of the data received by the data acquisition system. Then, in response to receiving the timed trigger task node triggered by the target object, configure the trigger time interval of the timed trigger task node; and obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address. In response to receiving the point information added by the target object, obtain target data according to the point information and the trigger time interval, and print the target data to the console. Since the data processing flow includes data server nodes corresponding to different data types, concurrent acquisition of data from different data sources can be achieved, improving the data processing efficiency. In addition, during the process of acquiring target data according to the point information and the trigger time interval, the user can customize the configuration of the point information to achieve the acquisition of different data, and by configuring the trigger time interval, the data acquisition efficiency can be changed, which has a certain degree of flexibility.

[0109] In a specific embodiment, before constructing the data processing flow according to the data types of the data received by the data acquisition system, it further includes:

[0110] Determine the attribute information of the data corresponding to different data types according to the frequencies of the data corresponding to different data types received by the data acquisition system;

[0111] The constructing the data processing flow according to the data types of the data received by the data acquisition system includes:

[0112] Construct a data processing flow according to the data types of the data received by the data acquisition system and the attribute information of the data corresponding to different data types received by the data acquisition system. The data processing flow includes a timed trigger task node, a data server node, and a log printing node. The number of timed trigger task nodes is related to the attribute information of the data corresponding to different data types received by the data acquisition system, and the number of data server nodes and log printing nodes is the same as the number of data types of the data received by the data acquisition system.

[0113] In a specific embodiment, the configuring the trigger time interval of the timed trigger task node in response to receiving the timed trigger task node triggered by the target object includes:

[0114] In response to receiving a target timed trigger task node triggered by a target object, configure the trigger time interval of the timed trigger task node according to the attribute information of the data corresponding to the target data type received by the target timed trigger task node.

[0115] In a specific implementation manner, the obtaining the device address, device port, and data IP address corresponding to the data received by the data server node, and performing connection configuration on the data server node according to the device address, device port, and data IP address includes:

[0116] Determine the data server node according to the data type of the data received by the data acquisition system;

[0117] According to the label identifier of the data server node, obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port, and data IP address.

[0118] In a specific implementation manner, the responding to receiving the point information added by the target object, and obtaining the target data and printing the target data to the console according to the point information and the trigger time interval includes:

[0119] In response to receiving the point information added by the target object, obtain the data area, start address, and data label included in the point information;

[0120] According to the data area, start address, and data label, obtain the target data according to the trigger time interval;

[0121] Print the target data to the console according to the trigger time interval.

[0122] In a specific implementation manner, before the responding to receiving the point information added by the target object, and obtaining the target data and printing the target data to the console according to the point information and the trigger time interval, it further includes:

[0123] Obtain the data area, start address, and data label selected by the target object;

[0124] Generate point information to the data point table according to the data area, start address, and data label selected by the target object.

[0125] In a specific implementation manner, the data processing flow further includes a data cleaning node;

[0126] The obtaining the target data and printing the target data to the console according to the point information and the trigger time interval includes:

[0127] Obtain initial data according to the position information and trigger time interval;

[0128] In response to receiving the target processing function selected by the target object, process the initial data to obtain target data;

[0129] Print the target data to the console.

[0130] The embodiment of the present application also provides a computer device. For details, please refer to Figure 6 , Figure 6 , which is the basic structural block diagram of the computer device in this embodiment.

[0131] The computer device includes a memory 510 and a processor 520 that are communicatively connected to each other through a system bus. It should be noted that only the computer device with components 510-520 is shown in the figure. However, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Among them, those skilled in the art of the present technology can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0132] The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer device can perform human-computer interaction with the user through a keyboard, a mouse, a remote control, a touchpad or a voice control device, etc.

[0133] The memory 510 includes at least one type of readable storage medium, which includes non-volatile memory or volatile memory, such as flash memory, hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disc, etc. RAM can include static RAM or dynamic RAM. In some embodiments, the memory 510 can be an internal storage unit of the computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory 510 can also be an external storage device of the computer device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device. Of course, the memory 510 can also include both the internal storage unit and the external storage device of the computer device. In this embodiment, the memory 510 is generally used to store the operating system and various application software installed on the computer device, such as the program code of the above method. In addition, the memory 510 can also be used to temporarily store various types of data that have been output or will be output.

[0134] The processor 520 is generally used to execute the overall operations of the computer device. In this embodiment, the memory 510 is used to store program code or instructions, and the program code includes computer operation instructions. The processor 520 is used to execute the program code or instructions stored in the memory 510 or process data, such as running the program code of the above method.

[0135] In this text, the bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. This bus system can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, only a thick line is used in the figure to represent it, but it does not mean that there is only one bus or one type of bus.

[0136] Another embodiment of the present application further provides a computer-readable medium, which can be a computer-readable signal medium or a computer-readable medium. A processor in the computer reads the computer-readable program code stored in the computer-readable medium, so that the processor can execute the functional actions specified in each step or the combination of steps in the above method; and generate a device for implementing the functional actions specified in each block or the combination of blocks in the block diagram.

[0137] The computer-readable medium includes but is not limited to electronic, magnetic, optical, electromagnetic, infrared memories or semiconductor systems, devices or apparatuses, or any suitable combination of the foregoing. The memory is used to store program codes or instructions, and the program codes include computer operation instructions. The processor is used to execute the program codes or instructions of the above method stored in the memory.

[0138] For the definitions of the memory and the processor, reference can be made to the description of the foregoing computer device embodiments, and details are not described herein again.

[0139] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in an electrical, mechanical or other form.

[0140] In each embodiment of the present application, each functional unit or module can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0141] When an integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0142] Unless the context clearly indicates otherwise, the singular forms of the words used in this specification and the appended claims include the plural, and vice versa. Thus, when referring to the singular, the corresponding plural of the term is usually included. Similarly, the terms "comprising" and "including" will be interpreted as inclusive rather than exclusive. Likewise, the term "including" and "or" should be interpreted as inclusive, unless such an interpretation is explicitly prohibited in this specification. Where the term "example" is used in this specification, especially when it is located after a group of terms, the "example" is merely exemplary and illustrative and should not be considered exclusive or extensive.

[0143] Further aspects and scopes of adaptability become apparent from the description provided herein. It should be understood that the various aspects of this application can be implemented alone or in combination with one or more other aspects. It should also be understood that the description herein and the specific embodiments are for illustrative purposes only and are not intended to limit the scope of this application.

[0144] The above has described several embodiments of the present disclosure in detail. However, obviously, those skilled in the art can make various modifications and variations to the embodiments of the present disclosure without departing from the spirit and scope of the present disclosure. The protection scope of the present disclosure is defined by the appended claims.

Claims

1. A data processing method, characterized in that: include: According to the data type of the data received by the data acquisition system, a data processing flow is constructed, wherein the data processing flow includes a timed trigger task node, a data server node and a log printing node, and the number of the data server node and the log printing node is the same as the number of the data types received by the data acquisition system; In response to receiving a timed trigger task node triggered by a target object, configuring a triggering time interval of the timed trigger task node; Obtaining a device address, a device port, and a data IP address corresponding to the data received by the data server node, and performing connection configuration on the data server node according to the device address, the device port, and the data IP address; In response to receiving the point information added by the target object, the target data is acquired according to the point information and the trigger time interval and the target data is printed to the console.

2. The method according to claim 1, characterized in that Before constructing the data processing flow according to the data type received by the data acquisition system, the method further includes: Determining attribute information of data corresponding to different data types according to the frequency of data corresponding to different data types received by the data acquisition system; The data processing flow is constructed according to the data type received by the data acquisition system, including: A data processing flow is constructed based on the data types received by the data acquisition system and the attribute information of the data corresponding to the different data types received by the data acquisition system, wherein the data processing flow includes a timed trigger task node, a data server node and a log printing node, the number of the timed trigger task nodes is related to the attribute information of the data corresponding to the different data types received by the data acquisition system, and the number of the data server nodes and the log printing nodes is the same as the number of data types received by the data acquisition system.

3. The method according to claim 2, characterized in that The step of configuring a triggering time interval of the timer triggering task node in response to receiving the timer triggering task node triggered by the target object includes: In response to receiving a target timed trigger task node triggered by a target object, a trigger time interval of the timed trigger task node is configured according to attribute information of data corresponding to a target data type received by the target timed trigger task node.

4. The method according to claim 1, characterized in that: The obtaining of the device address, device port and data IP address corresponding to the data received by the data server node, and connection configuration of the data server node according to the device address, device port and data IP address, includes: Determine the data server node according to the data type of the data received by the data acquisition system; According to the label identification of the data server node, the device address, device port and data IP address corresponding to the data received by the data server node are obtained, and the data server node is connected and configured according to the device address, device port and data IP address.

5. The method according to claim 1, characterized in that In response to receiving the point information added by the target object, acquiring the target data according to the point information and the trigger time interval and printing the target data to the console, including: In response to receiving the point information added by the target object, acquiring the data area, the starting address and the data tag included in the point information; According to the data area, the starting address and the data tag, the target data is acquired according to the trigger time interval; According to the trigger time interval, the target data is printed to the console.

6. The method according to claim 1 or 5, characterized in that: In response to receiving the point information added by the target object, before acquiring the target data according to the point information and the trigger time interval and printing the target data to the console, the method further includes: Get the data area, starting address and data label selected by the target object; Generate point information to a data point table based on the data area, starting address and data label selected by the target object.

7. The method according to claim 1, characterized in that The data processing flow also includes a data cleaning node; The step of acquiring target data according to the point information and the trigger time interval and printing the target data to the console includes: Acquire initial data according to the point information and the trigger time interval; In response to receiving the target processing function selected by the target object, processing the initial data to obtain target data; Print the target data to the console.

8. A data processing device, characterized in that: include: A data processing flow construction module is used to construct a data processing flow according to the data type of the data received by the data acquisition system, wherein the data processing flow includes a timed trigger task node, a data server node and a log printing node, and the number of the data server node and the log printing node is the same as the number of the data types received by the data acquisition system; A trigger time interval configuration module, configured to configure a trigger time interval of a timer trigger task node in response to receiving a timer trigger task node triggered by a target object; A connection configuration module, used to obtain the device address, device port and data IP address corresponding to the data received by the data server node, and perform connection configuration on the data server node according to the device address, device port and data IP address; The printing module is used for, in response to receiving the point information added by the target object, acquiring the target data according to the point information and the trigger time interval and printing the target data to the console.

9. A computer device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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