Data processing method, apparatus, device, and medium

Abstract

The data processing method, device, equipment and medium provided by the embodiments of the present disclosure include: constructing a data processing flow according to the data types of data received by a data acquisition system, wherein the data processing flow includes a timing trigger task node, a data server node and a log printing node, the number of the data server node and the log printing node is the same as the number of the data types of data received by the data acquisition system; in response to receiving a timing trigger task node triggered by a target object, configuring a trigger time interval of the timing trigger task node; obtaining a device address, a device port and a data IP address corresponding to 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 point information added by a target object, obtaining target data according to the point information and the trigger time interval, and printing the target data to a console, thereby improving the processing efficiency of data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing and related technical fields, in particular, to a data processing method, device, equipment and medium. BACKGROUND

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

[0003] The existing sensors and devices in the industrial field usually generate high-frequency data streams, which have strong real-time requirements and contain a large amount of noise and outliers. The traditional batch processing and cleaning method cannot meet the real-time processing requirements of high-frequency data. Specifically, the existing high-frequency data collection and cleaning scheme mostly adopts a batch processing mode, which cleans and stores data after accumulation to a certain amount, which easily leads to insufficient real-time performance. At the same time, the existing cleaning rules are mostly fixed configurations, which are difficult to adapt to changes in different data sources and data characteristics, affecting the cleaning effect and accuracy.

[0004] In order to solve the problems of data loss, large delay and low cleaning efficiency in the prior art when processing data, there is an urgent need for a data processing method. SUMMARY

[0005] The embodiments described herein provide a data processing method, device, equipment 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, comprising:

[0007] According to the data type of the data received by the data collection system, a data processing flow is constructed, wherein the data processing flow comprises a timing 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 type received by the data collection system;

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

[0009] 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;

[0010] In response to receiving point information added by a target object, target data is obtained according to the point information and the trigger time interval, and the target data is printed to the console.

[0011] In some embodiments of the present disclosure, before the data processing flow is constructed according to the data types received by the data acquisition system, the method further comprises:

[0012] According to the frequency of the data corresponding to different data types received by the data acquisition system, attribute information of the data corresponding to different data types is determined.

[0013] The data processing flow is constructed according to the data types received by the data acquisition system, comprising:

[0014] 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, a data processing flow is constructed, wherein the data processing flow comprises a timing trigger task node, a data server node and a log printing node, the number of timing 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.

[0015] In some embodiments of the present disclosure, in response to receiving a target object triggered timing trigger task node, the trigger time interval of the timing trigger task node is configured, comprising:

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

[0017] In some embodiments of the present disclosure, 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, comprising:

[0018] According to the data type of the data received by the data acquisition system, a data server node is determined.

[0019] 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.

[0020] In some embodiments of the present disclosure, in response to receiving point information added by a target object, target data is obtained according to the point information and the trigger time interval, and the target data is printed to the console, comprising:

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

[0022] According to the data region, the start address and the data tag, obtain target data according to a trigger time interval;

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

[0024] In some embodiments of the present disclosure, before the target data is obtained according to the point information and the trigger time interval and printed to the console in response to receiving the point information added by the target object, the method further comprises:

[0025] Obtain a data region, a start address and a data tag selected by the target object;

[0026] According to the data region, the start address and the data tag selected by the target object, generate point information to a data point table.

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

[0028] According to the point information and the trigger time interval, obtain target data and print the target data to a console, comprising:

[0029] According to the point information and the trigger time interval, obtain initial data;

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

[0033] A data processing flow construction module is configured to construct a data processing flow according to a data type of data received by a data acquisition system, wherein the data processing flow comprises a timing 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 type of data received by the data acquisition system;

[0034] A trigger time interval configuration module is configured to configure a 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 is configured to acquire a device address, a device port and a data IP address corresponding to data received by the data server node, and configure connection of the data server node according to the device address, the device port and the data IP address.

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

[0037] In a third aspect, a computer device is provided according to the present disclosure, and includes:

[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, a computer readable storage medium is provided according to the present disclosure, and the computer readable storage medium stores a computer program, which, when executed by a processor, implements the method according to any one of the first aspect.

[0042] The data processing method, device and medium provided by the embodiments of the present disclosure first construct a data processing flow according to a data type of data received by a data acquisition system, wherein the data processing flow includes a timing 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 received by the data acquisition system; then, in response to receiving a timing trigger task node triggered by a target object, a trigger time interval of the timing trigger task node is configured; and a device address, a device port and a data IP address corresponding to data received by the data server node are acquired, and connection of the data server node is configured according to the device address, the device port and the data IP address; in response to receiving point information added by a target object, target data is acquired according to the point information and a trigger time interval, and the target data is printed to a console. Since the data processing flow includes data server nodes corresponding to different data types, concurrent acquisition of data of different data sources can be implemented, and the processing efficiency of data is improved; in addition, in the process of acquiring target data according to point information and a trigger time interval, a user can customize the point information to implement acquisition of different data, and by configuring the trigger time interval, the acquisition efficiency of data can be changed, which has a certain flexibility.

[0043] The above description is only a summary of the technical solutions of the embodiments of the present application. In order to more clearly understand the technical means of the embodiments of the present application, the embodiments of the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, characteristics and advantages of the embodiments of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF 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 noted that the drawings described below only relate to some embodiments of the present disclosure, not to the limitation of the present disclosure, wherein:

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

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

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

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

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

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

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

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

[0053] In the drawings, the marks 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

[0054] In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions of the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the protection scope 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 one of ordinary skill in the art to which this present subject matter belongs. It will be further 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 relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. As used herein, the statement that two or more parts are "connected" or "coupled" together refer to an indirect or direct connection or coupling.

[0056] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase "in an embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. A person of ordinary skill in the art will readily recognize from the disclosure herein, given the total volume of this application that one or more passages that are described as an embodiment is / are also an embodiment of another embodiment.

[0057] The term "and / or", merely used as a description of associated objects, means that there can be three kinds of relations, for example, A and / or B, which can represent: A exists, A and B exist, and B exists. In addition, the character " / " in this paper generally represents that the front and rear associated objects are a "or" relationship.

[0058] In addition, in all embodiments of the present disclosure, terms such as "first" and "second" are only used to distinguish one component (or 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 of" is two or more (including two), and similarly, "a plurality of groups" means two or more groups (including two groups).

[0060] In order to make the person skilled in the art better understand the scheme of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings.

[0061] Based on the problems existing in the prior art, the embodiments of the present disclosure provide a data processing method,Figure 1 is a flowchart of a data processing method provided by an embodiment of the present disclosure, as shown in Figure 1 The data processing method comprises the following steps.

[0062] S110, constructing a data processing flow according to the data types of the data received by the data acquisition system.

[0063] The data processing flow comprises a timing 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 of the data received by the data acquisition system.

[0064] In a specific embodiment, the data acquisition system receives data of multiple data types, for example, the data acquisition system acquires sensor data, PLC data, database data and API data, the data sources acquired by the data acquisition system are different, the data types are different, and by constructing the data processing flow, the number of the data server node and the log printing node is the same as the number of the data types of the data received by the data acquisition system, the simultaneous reception and processing of data of different data types is realized.

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

[0066] S120, in response to receiving the timing trigger task node triggered by the target object, configuring the trigger time interval of the timing trigger task node.

[0067] After the data processing flow is constructed, the target object triggers the timing trigger task node in the selected data processing flow, and configures the trigger time interval of the timing trigger task node. By configuring the trigger time interval of the timing trigger task node, the frequency of data acquisition by the data acquisition system can be changed. The shorter the trigger time interval of the configured timing trigger task node, the faster the frequency of data acquisition by the data acquisition system, and the acquisition of high-frequency data is realized.

[0068] As a specific embodiment, the trigger time interval of the timing trigger task node is the same as the efficiency of the time interval of the data processing expected by the target object.

[0069] S130, obtaining the device address, device port and data IP address corresponding to the data received by the data server node, and configuring the connection of the data server node according to the device address, device port and data IP address.

[0070] After the data processing flow is constructed and the trigger time interval of the timing trigger task node in the data processing flow is configured, the data server node needs to be connected and configured to obtain data from different data sources through the data server node.

[0071] As a specific implementation, the device address, device port and data IP address corresponding to the data received by the data server node are acquired, and the data server node is connected and configured 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; acquiring the device address, device port and data IP address corresponding to the data received by the data server node according to the tag identification of the data server node, and connecting and configuring the data server node according to the device address, device port and data IP address.

[0072] Specifically, first, the data server node is determined according to the data type of the data received by the data acquisition system and the number of different data types of the received data, and then the device address, device port and data IP address corresponding to the tag identification of the data server node are acquired, and the data server node is connected and configured through the device address, device port and data IP address, so that the data server node can obtain the data type of the data that the data server node can process from the IP address of the target device corresponding to the data server node. In the process of collecting the data type of the data that the data server node can process from the IP address of the target device, the time interval of collecting data is the same as the trigger time interval of the timing trigger task node.

[0073] A specific example is that if the data type of the data received by the data acquisition system includes PLC data and API data, then the data server corresponding to the PLC data and the data server corresponding to the API data are selected according to the data type of the data received by the data acquisition system.

[0074] S140, in response to receiving the point information added by the target object, acquiring target data according to the point information and the trigger time interval and printing the target data to the console.

[0075] In a specific implementation, after the data server node obtains data from the device, the obtained data is stored according to the point information, wherein the point information includes a data region, a starting address and a data tag. In an example, the data stored in the data server node is as follows: Figure 2BAs shown, the data stored in the point positions "4_0", "4_1", "4_2" are 100, 200, 300 respectively, wherein F03 represents a data area, "4_0", "4_1", "4_2" are data tags, 0 is the starting address of the point position "4_0", 1 is the starting address of the point position "4_1", and 2 is the starting address of the point position "4_2".

[0076] Specifically, when the target object triggers the add button at the data server node and generates point position information through adding data point positions, at this time, according to the point position information added by the target object and the trigger time interval, the data corresponding to the point position information is acquired according to the trigger time interval, and the data corresponding to the point position information acquired according to the trigger time interval is printed to the console, realizing the collection of data.

[0077] As a specific implementation, in response to receiving the point position information added by the target object, the target data is acquired according to the point position information and the trigger time interval, and the target data is printed to the console, including: in response to receiving the point position information added by the target object, acquiring the data area, the starting address and the data tag included in the point position 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.

[0078] Specifically, after the data server node is connected and configured according to the device address, the device port and the data IP address, the target object can trigger the add button, for example, Figure 2C As shown, a configuration box for adding data point positions is displayed, and the target object can select a data area, a starting address and a data tag in the configuration box for adding data point positions to generate point position information in the data point table, for example, Figure 2D As shown, at this time, the data server node acquires the target data from the corresponding position of the data server node according to the data area, the starting address and the data tag according to the point position information in the data point table according to the trigger time interval, and prints the acquired target data to the console according to the trigger time interval, realizing the collection and printing of data, for example, Figure 2D As shown.

[0079] The data processing method provided by the embodiment of the present disclosure first constructs a data processing flow according to the data types of the data received by the data acquisition system, wherein the data processing flow comprises a timing trigger task node, a data server node and a log printing node, the number of the data server nodes is the same as the number of the data types received by the data acquisition system; then, in response to receiving the timing trigger task node triggered by the target object, the trigger time interval of the timing trigger task node is configured; and the device address, the device port and the data IP address corresponding to the data received by the data server node are acquired, and the data server node is connected and configured 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. Since the data processing flow comprises the data server nodes corresponding to different data types, concurrent collection of data of different data sources can be realized, and the processing efficiency of the data is improved. In addition, in the process of collecting the 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 collection of different data, and by configuring the trigger time interval, the collection efficiency of the data can be changed, which has a certain flexibility.

[0080] On the basis of the above embodiment, Figure 3 is a flow diagram of another data processing method provided by the embodiment of the present disclosure, and the embodiment of the present disclosure is based on the above embodiment, as shown in Figure 3 Before step S110 is executed, it further comprises:

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

[0082] Specifically, the attribute information of the data comprises 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 important, and if the attribute information of the data is low-frequency data, it means that this type of data is non-important data.

[0083] The data acquisition system determines the attribute information of the data corresponding to different data types by analyzing the frequency of the data corresponding to different data types. In an exemplary manner, 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, and 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 mode of step S110 comprises:

[0085] S111, constructing a data processing flow according to the data type received by the data collection system and the attribute information of the data corresponding to different data types received by the data collection system.

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

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

[0088] In a specific example, when the data type of the data received by the data collection system includes four types, namely sensor data, PLC data, database data and API data, if the attribute information of the PLC data, the database data and the API data is low frequency data, and the attribute information of the sensor data is high frequency data, at this time, the number of data server nodes in the data flow constructed is four, and the number of timing trigger task nodes is two, as shown in Figure 3A The timing trigger task node 1 receives sensor data, and the timing trigger task node 2 receives PLC data, database data and API data. The trigger time interval corresponding to the timing trigger task node 1 and the trigger time interval corresponding to the timing trigger task node 2 are different, and the trigger time interval corresponding to the timing trigger task node 1 is smaller than the trigger time interval corresponding to the timing trigger task node 2.

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

[0090] S121, in response to receiving a target timing trigger task node triggered by a target object, configuring the trigger time interval of the timing trigger task node according to the attribute information of the data corresponding to the target data type received by the target timing trigger task node.

[0091] Specifically, in combination with Figure 3AWhen the number of the timing triggered task nodes is two in the constructed data processing flow, the timing triggered task node 1 receives sensor data, and the timing triggered task node 2 receives PLC data, database data and API data. At this time, the trigger time interval of the timing triggered task node 2 is configured according to the attribute information of the data corresponding to the target data type received by the timing triggered task node 1, and the trigger time interval of the timing triggered task node 2 is configured according to the attribute information of the data corresponding to the target data type received by the timing triggered task node 2. After the trigger time intervals of the timing triggered task node 1 and the timing triggered task node 2 are configured, the data server node 1 connected to the timing triggered task node 1 collects sensor data according to the trigger time interval of the timing triggered task node 1, the data server node 2 connected to the timing triggered task node 2 collects PLC data according to the trigger time interval of the timing triggered task node 2, the data server node 3 connected to the timing triggered task node 2 collects database data according to the trigger time interval of the timing triggered task node 2, and the data server node 4 connected to the timing triggered task node 2 collects API data according to the trigger time interval of the timing triggered task node 2, so as to realize 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, and the collection efficiency of high-frequency data is improved.

[0092] On the basis of the above embodiment, Figure 4 is a flow diagram of another data processing method provided by the embodiment of the present disclosure, Figure 4A is a structural diagram of another data processing flow provided by the embodiment of the present disclosure, in combination with Figure 4 and Figure 4A The specific implementation mode of step S140 includes:

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

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

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

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

[0097] A specific example is assumed that the value range of the read PLC data is from 100 to 400, and the read PLC data is mapped to a value range of 0 to 100 by selecting a processing function. 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, the collected initial data can be processed according to the target processing function.

[0100] S143, printing the target data to the console.

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

[0102] It should be noted that the processing function includes but is not limited to deduplication, format conversion, anomaly detection and elimination, and missing value filling, wherein the deduplication refers to deduplicating the specified field (such as the primary key, timestamp) when the data flows into the cleaning module, and eliminating duplicate records; the format conversion refers to converting the original data format (such as XML) to the target format (such as JSON) for unified storage and analysis; the anomaly detection and elimination refers to setting threshold rules (such as the temperature range is 10-100℃), and the data exceeding the range is marked or eliminated; the missing value filling refers to filling the missing field data, supporting zero padding, mean value filling, etc.

[0103] On the basis of the above embodiment, the embodiment of the present disclosure further provides a data processing device, Figure 5 is a structural schematic diagram of a data processing device provided by the embodiment of the present disclosure, as Figure 5 shown, the data processing device comprises:

[0104] The data processing flow construction module 501 is configured 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 comprises a timing 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 type of the data received by the data acquisition system.

[0105] The trigger time interval configuration module 502 is 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.

[0106] The connection configuration module 503 is configured to obtain the device address, device port and data IP address corresponding to the data received by the data server node, and to configure the connection of the data server node according to the device address, device port and data IP address.

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

[0108] The data processing apparatus 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, wherein the data processing flow comprises timing trigger task nodes, data server nodes and log printing nodes, and the number of the data server nodes is the same as the number of the data types received by the data acquisition system; then, in response to receiving the timing trigger task node triggered by the target object, the trigger time interval of the timing trigger task node is configured; and the device address, the device port and the data IP address corresponding to the data received by the data server node are acquired, and the data server node is connected and configured 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, target data is acquired according to the point information and the trigger time interval, and the target data is printed to a console. Since the data processing flow comprises the data server nodes corresponding to different data types, concurrent acquisition of data of different data sources can be realized, and the processing efficiency of the data is improved; in addition, in the process of acquiring the target data according to the point information and the trigger time interval, the user can customize the point information to realize acquisition of different data, and by configuring the trigger time interval, the acquisition efficiency of the data can be changed, and a certain flexibility is achieved.

[0109] In specific embodiments, before the data processing flow is constructed according to the data types received by the data acquisition system, the method further comprises:

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

[0111] The data processing flow is constructed 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, wherein the data processing flow comprises timing trigger task nodes, data server nodes and log printing nodes, the number of the timing 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 the data server nodes and the log printing nodes is the same as the number of the data types received by the data acquisition system.

[0112] The data processing flow is constructed 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, wherein the data processing flow comprises timing trigger task nodes, data server nodes and log printing nodes, the number of the timing 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 the data server nodes and the log printing nodes is the same as the number of the data types received by the data acquisition system.

[0113] In specific embodiments, the trigger time interval of the timing trigger task node is configured in response to receiving the timing trigger task node triggered by the target object, comprising:

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

[0115] In specific embodiments, the device address, device port, and data IP address corresponding to the data received by the data server node are acquired, and the data server node is configured for connection according to the device address, device port, and data IP address, including:

[0116] According to the data type of the data received by the data acquisition system, a data server node is determined.

[0117] According to the tag 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 acquired, and the data server node is configured for connection according to the device address, device port, and data IP address.

[0118] In specific embodiments, in response to receiving point information added by a target object, target data is acquired and printed to a console according to the point information and a trigger time interval, including:

[0119] In response to receiving point information added by a target object, the data region, starting address, and data tag included in the point information are acquired.

[0120] According to the data region, starting address, and data tag, target data is acquired according to a trigger time interval.

[0121] According to the trigger time interval, the target data is printed to a console.

[0122] In specific embodiments, before the target data is acquired and printed to a console according to the point information and a trigger time interval in response to receiving point information added by a target object, the method further includes:

[0123] The data region, starting address, and data tag selected by the target object are acquired.

[0124] According to the data region, starting address, and data tag selected by the target object, point information is generated to a data point table.

[0125] In specific embodiments, the data processing flow further includes a data cleaning node.

[0126] The target data is acquired and printed to a console according to the point information and a trigger time interval, including:

[0127] According to the point information and the trigger time interval, initial data is acquired;

[0128] In response to receiving a target object selected target processing function, the initial data is processed to obtain target data;

[0129] The target data is printed to the console.

[0130] The embodiments of the present application also provide a computer device, please refer to Figure 6 , Figure 6 The basic structure block diagram of the computer device of the present embodiment.

[0131] The computer device includes a memory 510 and a processor 520 which are communicatively connected through a system bus. It should be noted that only the computer device with components 510-520 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or less components can be alternatively implemented. Among them, the computer device herein is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions, which hardware includes but is not limited to microprocessor, application specific integrated circuit (ASIC), field-programmable gate array (FPGA), digital signal processor (DSP), embedded device, etc.

[0132] The computer device can be a desktop computer, a notebook, a palm computer, and a cloud server, etc. The computer device can interact with the user through a keyboard, a mouse, a remote controller, a touchpad, a voice control device, etc.

[0133] The memory 510 includes at least one type of readable storage medium, including non-volatile memory or volatile memory, for example, flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an 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), a magnetic memory, a magnetic disk, an optical disk, etc. The RAM can include static RAM or dynamic RAM. In some embodiments, the memory 510 can be an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. In other embodiments, the memory 510 can also be an external storage device of the computer device, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, or a flash card, etc. equipped on the computer device. Of course, the memory 510 can include both an internal storage unit and an external storage device of the computer device. In this embodiment, the memory 510 is generally used to store an operating system and various application software installed on the computer device, for example, program codes of the above-described method, etc. In addition, the memory 510 can also be used to temporarily store various data that has been output or will be output.

[0134] The processor 520 is generally used to perform the overall operation of the computer device. In this embodiment, the memory 510 is used to store program codes or instructions, which include computer operation instructions, and the processor 520 is used to execute the program codes or instructions stored in the memory 510 or process data, for example, run the program codes of the above-described method.

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

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

[0137] The computer readable medium includes but is not limited to electronic, magnetic, optical, electromagnetic, infrared, semiconductor system, device or apparatus, or any appropriate combination of the foregoing, for storing program code or instructions, which include computer operation instructions, and processor for executing the program code or instructions of the above method stored in the memory.

[0138] The definition of the memory and the processor can refer to the description of the foregoing computer device embodiment, which will not be repeated here.

[0139] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiment described above is only schematic, for example, the division of modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between the devices or units, which can be electrical, mechanical or other forms.

[0140] The function units or modules in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software function unit.

[0141] If the integrated unit is implemented in the form of a software function 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 solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the embodiments of the method of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0142] Unless the context clearly indicates otherwise, as used herein and in the appended claims, the singular form "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Accordingly, the use of "a" or "an" herein and in the following claims is intended to be interpreted to include the plural, unless the context clearly indicates otherwise. Similarly, the words "comprise," "comprises," and "comprising" are to be interpreted inclusively rather than exclusively. Likewise, the terms "include," "including," and "includes" should be construed to be inclusive, unless otherwise indicated herein. Where the term "example" is used occurring in this document, particularly with respect to a term or phrase, the "example" is merely an example and is not to be construed as preferred or advantageous over other examples.

[0143] Further aspects and scope of adaptation become apparent from the description provided herein. It should be appreciated that individual aspects of the present application can be implemented alone or in combination with one or more other aspects. It should also be appreciated that the description and specific examples herein are intended to be for illustrative purposes only and are not intended to limit the scope of the present application.

[0144] The above detailed description of several embodiments of the present disclosure has been described, but it is obvious that 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: Based on the data type 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 data types received by the data acquisition system; In response to receiving a timed trigger task node triggered by the target object, configure the trigger time interval of the timed trigger task node; 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; In response to receiving the location information added by the target object, the target data is obtained based on the location information and the trigger time interval, and the target data is printed to the console; The response to receiving the location information added by the target object, based on the location information and the trigger time interval, to obtain target data and print the target data to the console includes: In response to receiving location information added by the target object, the location information includes the data area, starting address, and data tag. Based on the data region, starting address, and data tag, the target data is acquired according to the trigger time interval. The target data is printed to the console according to the trigger time interval.

2. The method according to claim 1, characterized in that, Before constructing the data processing stream based on the data type received by the data acquisition system, the process also includes: Based on the frequency of data corresponding to different data types received by the data acquisition system, the attribute information of the data corresponding to different data types is determined; The step of constructing a data processing stream based on the data type received by the data acquisition system includes: 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. The data processing flow includes timed trigger task nodes, data server nodes, and log printing nodes. The number of 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. 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.

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

4. The method according to claim 1, characterized in that, The step of obtaining the device address, device port, and data IP address corresponding to the data received by the data server node, and configuring the connection of the data server node according to the device address, device port, and data IP address, includes: Determine the data server node based on the type of data received by the data acquisition system; Based on the tag 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 configure the connection of the data server node according to the device address, device port, and data IP address.

5. The method according to claim 1, characterized in that, Before responding to receiving the point information added by the target object, acquiring the target data based on the point information and the trigger time interval, and printing the target data to the console, the method further includes: Obtain the selected data region, starting address, and data label of the target object; Based on the selected data area, starting address, and data label of the target object, point information is generated into the data point table.

6. The method according to claim 1, characterized in that, The data processing stream also includes a data cleaning node; The step of acquiring target data based on the location information and trigger time interval and printing the target data to the console includes: Based on the location information and the trigger time interval, initial data is obtained; In response to receiving the target processing function selected by the target object, the initial data is processed to obtain the target data; Print the target data to the console.

7. A data processing apparatus, characterized in that, include: A data processing flow construction module is used to construct a data processing flow based on the data type 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 data server nodes and log printing nodes is the same as the number of data types received by the data acquisition system. The trigger interval configuration module is used to configure the trigger interval of the timed trigger task node in response to receiving a timed trigger task node triggered by the target object. The connection configuration module is used to obtain the device address, device port, and data IP address corresponding to the data received by the data server node, and to configure the connection of the data server node according to the device address, device port, and data IP address. The printing module is used to respond to the received 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; The response to receiving the location information added by the target object, based on the location information and the trigger time interval, to obtain target data and print the target data to the console includes: In response to receiving location information added by the target object, the location information includes the data area, starting address, and data tag. Based on the data region, starting address, and data tag, the target data is acquired according to the trigger time interval. The target data is printed to the console according to the trigger time interval.

8. A computer device, characterized in that, include: One or more processors; 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 as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

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