A method, device, terminal and medium for data aggregation

Abstract

The present invention discloses a method, device, terminal and medium for data aggregation, the method comprising: receiving an aggregation rule, determining the aggregation time and aggregation attribute of target aggregated data; reading initial reported data, and determining the reporting scenario of the initial reported data based on the aggregation time, the reporting scenario including a first reporting scenario and a second reporting scenario; performing single attribute identification on the initial reported data of the first reporting scenario, determining the first target reported data, the first target reported data being the reported data of the non-aggregated attribute; performing single attribute identification on the initial reported data of the second reporting scenario, determining the second target reported data, the second target reported data being the reported data of the aggregated attribute; obtaining the target aggregated data based on the first target reported data and the first target reported data. The present invention can perform data aggregation accurately to the attribute, thereby improving the integrity and accuracy of the reported data.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, terminal and medium for data aggregation. Background Art

[0002] With the development of the Internet of Things, people have higher and higher requirements for the quality of data reported by devices. In the reporting scenario of numerical changes, the data continues to grow. Using data aggregation to report data can reduce the bandwidth cost during data transmission, reduce data storage costs, and improve data analysis efficiency.

[0003] However, in existing value change reporting scenarios, all messages within the device time period are often aggregated and reported, or only data with aggregated fields within the device time period are aggregated and reported, resulting in the loss of data of non-aggregated fields within the device time period. It can be seen that in existing value change reporting scenarios, when devices report data, it is still impossible to accurately aggregate data by attribute.

[0004] Therefore, the prior art still needs to be improved and enhanced. Summary of the invention

[0005] The technical problem to be solved by the present invention is that, in view of the above-mentioned defects of the prior art, a method, device, terminal and medium for data aggregation are provided, aiming to solve the problem that the reporting scenario of numerical change in the prior art often aggregates and reports all messages within the device time period, or only the data carrying the aggregation field within the device time period can be aggregated and reported, resulting in the loss of data of the non-aggregate field within the device time period.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0007] In a first aspect, the present invention provides a method for data aggregation, wherein the method comprises:

[0008] Receive aggregation rules and determine the aggregation time and aggregation attributes of target aggregation data;

[0009] Reading initial reporting data, and determining a reporting scenario of the initial reporting data based on the aggregation time, where the reporting scenario includes a first reporting scenario and a second reporting scenario;

[0010] Performing single attribute identification on the initial reporting data of the first reporting scenario to determine first target reporting data, where the first target reporting data is reporting data of non-aggregated attributes;

[0011] Performing single attribute identification on the initial reporting data of the second reporting scenario to determine second target reporting data, where the second target reporting data is the reporting data of the aggregated attribute;

[0012] The target aggregated data is obtained based on the first target reported data and the first target reported data.

[0013] In one implementation, the reading of the initial reporting data and determining, based on the aggregation time, a reporting scenario of the initial reporting data, wherein the reporting scenario includes a first reporting scenario and a second reporting scenario, include:

[0014] Obtaining initial reporting data and the aggregation time;

[0015] When the reporting time of the initial reported data does not reach the aggregation time, determining that the reporting scenario of the initial reported data is the first reporting scenario;

[0016] When the reporting time of the initially reported data reaches the aggregation time, it is determined that the reporting scenario of the initially reported data is the second reporting scenario.

[0017] In one implementation, the performing single attribute identification on the initial reporting data of the first reporting scenario to determine the first target reporting data, where the first target reporting data is reporting data of a non-aggregated attribute, includes:

[0018] Performing attribute separation on the initial reporting data of the first reporting scenario to obtain first single-attribute data;

[0019] Compare the first single attribute data with the aggregate attribute to obtain a comparison result;

[0020] The first target reporting data is determined according to the comparison result, where the first target reporting data is reporting data of a non-aggregated attribute.

[0021] In one implementation, the performing attribute separation on the initial reporting data of the first reporting scenario to obtain first single-attribute data includes:

[0022] Determining an attribute type of initial reporting data of the first reporting scenario, the attribute type including single-attribute data and multi-attribute data;

[0023] Attribute separation is performed on the multi-attribute data to obtain the first single-attribute data.

[0024] In an implementation manner, determining the first target reporting data according to the comparison result, where the first target reporting data is reporting data of a non-aggregate attribute, includes:

[0025] When the comparison result is that the first single attribute data does not belong to the aggregate attribute, it is determined that the first single attribute data is the first target reported data.

[0026] In one implementation, the performing single attribute identification on the initial reporting data of the second reporting scenario to determine the second target reporting data, where the second target reporting data is the reporting data of the aggregated attribute, includes:

[0027] Performing attribute separation on the initial reporting data of the second reporting scenario to obtain second single-attribute data;

[0028] Compare the second single attribute data with the aggregate attribute to obtain a comparison result;

[0029] According to the comparison result, the second target reporting data is determined, where the second target reporting data is reporting data of the aggregated attribute.

[0030] In an implementation manner, determining the second target reporting data according to the comparison result, where the second target reporting data is reporting data of an aggregated attribute, includes:

[0031] When the comparison result is that the second single attribute data belongs to the aggregate attribute, it is determined that the second single attribute data is the second target reported data.

[0032] In a second aspect, an embodiment of the present invention further provides a data aggregation device, wherein the device includes:

[0033] An aggregation rule determination module, used to receive the aggregation rule and determine the aggregation time and aggregation attributes of the target aggregation data;

[0034] A reporting scenario determination module, used to read the initial reporting data, and determine the reporting scenario of the initial reporting data based on the aggregation time, wherein the reporting scenario includes a first reporting scenario and a second reporting scenario;

[0035] a non-aggregate attribute data determination module, configured to perform single attribute recognition on the initial reporting data of the first reporting scenario to determine first target reporting data, where the first target reporting data is reporting data of non-aggregate attributes;

[0036] An aggregated attribute data determination module, configured to perform single attribute recognition on the initial reported data of the second reporting scenario to determine second target reported data, where the second target reported data is the reported data of the aggregated attribute;

[0037] The target aggregate data determination module is used to obtain the target aggregate data based on the first target reported data and the first target reported data.

[0038] In a third aspect, an embodiment of the present invention further provides a terminal, wherein the terminal includes a memory, a processor, and a data aggregation program stored in the memory and executable on the processor, and when the processor executes the data aggregation program, the steps of the data aggregation method of any one of the above-mentioned schemes are implemented.

[0039] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein a data aggregation program is stored on the computer-readable storage medium, and when the data aggregation program is executed by a processor, the steps of the data aggregation method described in any one of the above schemes are implemented.

[0040] Beneficial effects: Compared with the prior art, the present invention discloses a method, device, terminal and medium for data aggregation, the method comprising: receiving aggregation rules, determining the aggregation time and aggregation attributes of target aggregated data; reading initial reported data, and determining the reporting scenario of the initial reported data based on the aggregation time, the reporting scenario including a first reporting scenario and a second reporting scenario; performing single attribute identification on the initial reported data of the first reporting scenario, determining the first target reported data, the first target reported data is the reporting data of the non-aggregated attribute; performing single attribute identification on the initial reported data of the second reporting scenario, determining the second target reported data, the second target reported data is the reporting data of the aggregated attribute; obtaining the target aggregated data based on the first target reported data and the first target reported data. Therefore, the present invention can accurately aggregate data according to attributes, which not only improves the accuracy of the device reported data, but also ensures the integrity of the target reported data. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention provides a flowchart of a specific implementation of the method for data aggregation provided by the embodiment of the present invention.

[0042] Figure 2 Schematic diagram of the implementation steps of existing data aggregation methods.

[0043] Figure 3 A schematic diagram of specific implementation steps of the data aggregation method provided in an embodiment of the present invention.

[0044] Figure 4 A functional schematic diagram of a data aggregation device provided in an embodiment of the present invention.

[0045] Figure 5 A functional block diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples.

[0047] Those skilled in the art will appreciate that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Unless specifically stated, the singular forms "one", "said", and "the" used herein may also include plural forms, and the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or their groups. It should be understood that when an element is "connected" or "coupled" to another element, it may be directly connected or coupled to other elements, or there may also be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0048] The present embodiment provides a method, device, terminal and medium for data aggregation. In specific implementation, the present embodiment first receives the aggregation rules, determines the aggregation time and aggregation attributes of the target aggregated data, and then reads the initial reported data. Based on the aggregation time, the reporting scenario of the initial reported data is determined, and the reporting scenario includes a first reporting scenario and a second reporting scenario. Next, the initial reported data of the first reporting scenario is subjected to single attribute identification to determine the first target reported data, and the first target reported data is the reported data of the non-aggregated attribute; the initial reported data of the second reporting scenario is subjected to single attribute identification to determine the second target reported data, and the second target reported data is the reported data of the aggregated attribute. Finally, the target aggregated data is obtained based on the first target reported data and the first target reported data. Therefore, the present embodiment can perform data aggregation accurately to the attribute, which not only improves the accuracy of the device reported data, but also ensures the integrity of the target reported data.

[0049] The data aggregation method of this embodiment can be applied to a terminal, which can be a preset mobile terminal such as a mobile phone, a tablet, a computer, or an intelligent device such as a smart TV. In this embodiment, the terminal can be an external device connected to the data aggregation device, or a device built into the data aggregation device. Figure 1 As shown in , the data aggregation method of this embodiment includes the following steps:

[0050] Step S100: Receive aggregation rules and determine the aggregation time and aggregation attributes of target aggregation data.

[0051] Due to the existing reporting scenarios of value changes, all messages in the device time period are often aggregated and reported, or only the data carrying the aggregated field in the device time period can be aggregated and reported, resulting in the loss of data of non-aggregated fields in the device time period. In order to solve this technical problem, this embodiment first needs to receive the aggregation rules of the data receiving platform (i.e. Figure 2 and Figure 3 The aggregation time and aggregation attributes of the target aggregated data are determined according to the delivery rules in the aggregation rule, which reflects the target demand data of the platform. Then, the aggregation attributes and non-aggregation attributes in the initial reported data are distinguished based on this aggregation attribute. Next, before the aggregation time arrives, the data carrying non-aggregation fields in the device time period are aggregated and reported. When this aggregation time arrives, the data carrying aggregation fields in the device time period are aggregated and reported.

[0052] like Figure 3 As shown, the devices in this embodiment store various data to be reported. When these devices are connected to the controller (i.e. Figure 2 and Figure 3 When L2 in the example is reached, all the data to be reported can be cleaned in the controller, and then the cleaned data can be reported to the corresponding data receiving platform, which can effectively reduce the bandwidth cost during data transmission, reduce the data storage cost of the platform, and improve the data analysis efficiency of the platform. The controller in this embodiment takes the Shenzhen Kaihong Super Device Controller based on the KaiHongOS system as an example.

[0053] Common data cleaning techniques usually include: data filtering, data deduplication and data aggregation. Specifically, the data cleaning technology used in this implementation is data aggregation. By aggregating the reported data received by the controller before reporting, the data storage cost of the platform is effectively reduced and the data analysis efficiency of the platform is improved. Generally speaking, different data cleaning techniques correspond to different types of data to be reported. Common data types to be reported include: numerical fluctuation data, that is, filtering invalid or slightly changed data points according to the set threshold; numerical change data / continuous growth data, that is, only retaining the cumulative value of the last state; data duplication data, that is, removing duplicate records through a deduplication algorithm; character state change data / state change data, that is, merging continuous repeated states or only recording key state change events. Specifically, the data cleaning method of data aggregation used in this embodiment is precisely aimed at solving the reporting scenario of numerical change data.

[0054] Step S200: read the initial reporting data, and determine the reporting scenario of the initial reporting data based on the aggregation time, where the reporting scenario includes a first reporting scenario and a second reporting scenario.

[0055] Specifically, after the Shenzhen Kaihong super device controller based on the KaiHongOS system in this embodiment receives the aggregation rule and determines the aggregation time and aggregation attributes of the target aggregation data, the Shenzhen Kaihong super device controller based on the KaiHongOS system in this embodiment will further read the connected device, determine the initial reporting data stored in the device, and determine the reporting scenario of the initial reporting data based on the aggregation time of the target aggregation data received in the aggregation rule, wherein the reporting scenario includes a first reporting scenario and a second reporting scenario.

[0056] In one implementation, step S200 of this embodiment specifically includes the following steps:

[0057] Step S201, obtaining initial reporting data and the aggregation time;

[0058] Step S202: When the reporting time of the initial reported data does not reach the aggregation time, determining that the reporting scenario of the initial reported data is the first reporting scenario;

[0059] Step S203: When the reporting time of the initially reported data reaches the aggregation time, determine that the reporting scenario of the initially reported data is the second reporting scenario.

[0060] Due to the existing reporting scenarios of value changes, the data carrying the aggregated field in the device time period can only be aggregated and reported when the aggregation time arrives, resulting in the loss of the data of the non-aggregated field in the device time period. Therefore, in this embodiment, the reporting scenarios of the initial reporting data are divided by the aggregation time of the target aggregated data, and the reporting scenarios are divided into the first reporting scenario and the second reporting scenario, in order to facilitate the implementation of: before the aggregation time arrives, the technical means of aggregating and reporting the data carrying the non-aggregated field in the device time period.

[0061] Specifically, the first reporting scenario in this embodiment is a reporting scenario of the initial reporting data determined when the reporting time of the initial reporting data has not reached the aggregation time. The second reporting scenario is a reporting scenario of the initial reporting data determined when the reporting time of the initial reporting data has reached the aggregation time. Further, this embodiment will consider how to aggregate and report the data carrying non-aggregate fields in the first reporting scenario, and how to aggregate and report the data carrying aggregate fields in the second reporting scenario.

[0062] Step S300: Perform single attribute identification on the initial reporting data of the first reporting scenario to determine first target reporting data, where the first target reporting data is reporting data of non-aggregated attributes.

[0063] During specific implementation, this embodiment first considers how to aggregate and report the data carrying non-aggregate fields in the first reporting scenario.

[0064] In one implementation, step S300 of this embodiment specifically includes the following steps:

[0065] Step S301: performing attribute separation on the initial reporting data of the first reporting scenario to obtain first single attribute data;

[0066] Step S302: Compare the first single attribute data with the aggregate attribute to obtain a comparison result;

[0067] Step S303: Determine the first target reported data according to the comparison result, where the first target reported data is reported data of a non-aggregated attribute.

[0068] like Figure 3 As shown, the initial reporting data of the first reporting scenario in this embodiment includes reporting messages {a=20}, {a=30, b=10}, {b=5} and {a=50, b=15} in sequence. Further, this embodiment will perform attribute separation on the initial reporting data of these first reporting scenarios to obtain target reporting data of a single attribute. Therefore, by setting the attribute separation step, this embodiment can accurately aggregate data to the attribute, thereby improving the integrity and accuracy of the reported data.

[0069] On the other hand Figure 2 The implementation steps of the existing data aggregation method cannot accurately aggregate data on a single attribute, so when the aggregation time arrives, the reported data containing the aggregated attribute can only be read as the target reported data, resulting in the loss of data of non-aggregated fields within the device time period.

[0070] In one implementation, this embodiment performs attribute separation on the initial reporting data of the first reporting scenario to obtain first single attribute data, specifically including the following steps:

[0071] Step S3011: Determine the attribute type of the initial reporting data of the first reporting scenario, where the attribute type includes single-attribute data and multi-attribute data;

[0072] Step S3012: perform attribute separation on the multi-attribute data to obtain the first single-attribute data.

[0073] That is to say, before performing attribute separation on the initial reporting data of the first reporting scenario, this embodiment will first determine the attribute type of the initial reporting data of the first reporting scenario. When the attribute type is single-attribute data, the single-attribute data itself is the first single-attribute data, so there is no need to further perform attribute separation, such as: the reporting message of the first reporting scenario {a=20} and {b=5}. When the attribute type is multi-attribute data, the multi-attribute data will be attribute separated to obtain the first single-attribute data, such as: the reporting message of the first reporting scenario {a=30, b=10} will be attribute separated to become {a=30} and {b=10}, and { =50, b=15} will be attribute separated to become {a=50} and {b=15}.

[0074] Next, this embodiment compares the target reporting data of the single attribute obtained after attribute separation with the aggregated attribute to obtain a comparison result, and then determines the first target reporting data according to the comparison result, wherein the first target reporting data is the reporting data of the non-aggregated attribute.

[0075] In an implementation manner, this embodiment, when determining the first target reported data according to the comparison result, and the first target reported data is reported data of a non-aggregate attribute, specifically includes the following steps:

[0076] Step S3031: When the comparison result is that the first single attribute data does not belong to the aggregate attribute, determine that the first single attribute data is the first target reported data.

[0077] like Figure 3 As shown, the aggregation rule in this embodiment is "aggregate 30 minutes of attribute a", so the aggregation time in this embodiment is 30 minutes, and the aggregation attribute is attribute a. That is to say, when the comparison result of this embodiment is that the first single attribute data does not belong to the aggregation attribute, the first single attribute data is determined to be the first target reporting data, for example, the single attribute b {b=10} and {b=15} after attribute separation are determined to be the first target reporting data.

[0078] Step S400: Perform single attribute identification on the initial reporting data of the second reporting scenario to determine second target reporting data, where the second target reporting data is the reporting data of the aggregated attribute.

[0079] During specific implementation, this embodiment will also consider how to aggregate and report the data carrying the aggregation field in the second reporting scenario.

[0080] In one implementation, step S400 of this embodiment specifically includes the following steps:

[0081] Step S401: performing attribute separation on the initial reporting data of the second reporting scenario to obtain second single attribute data;

[0082] Step S402: Compare the second single attribute data with the aggregate attribute to obtain a comparison result;

[0083] Step S403: Determine the second target reporting data according to the comparison result, where the second target reporting data is reporting data of an aggregated attribute.

[0084] like Figure 3 As shown, the initial reporting data of this embodiment in the second reporting scenario (i.e., when the reporting time reaches the aggregation time) is {a=50, b=15}. This embodiment first determines the attribute type of the initial reporting data of the second reporting scenario. When the attribute type is multi-attribute data, it separates the attributes to obtain the second single attribute data of a single attribute, such as: {a=50} and {b=15}. Then, the second single attribute data is compared with the aggregated attribute to obtain the comparison result. Finally, the second target reporting data is determined based on the comparison result, wherein the second target reporting data is the reporting data of the aggregated attribute.

[0085] In an implementation manner, this embodiment determines the second target reported data according to the comparison result, and when the second target reported data is reported data of an aggregated attribute, specifically includes the following steps:

[0086] Step S4031: When the comparison result is that the second single attribute data belongs to the aggregate attribute, determine that the second single attribute data is the second target reported data.

[0087] Since the aggregate attribute in this embodiment is attribute a, when the comparison result of this embodiment is that the second single attribute data belongs to the aggregate attribute, the target reporting data of the single data is determined to be the first target reporting data, for example, the single attribute a {a=50} after attribute separation is determined to be the second target reporting data.

[0088] Step S500: Obtain the target aggregated data based on the first target reported data and the second target reported data.

[0089] Specifically, the first target reported data is data carrying non-aggregate fields within the device time period before the aggregation time arrives, and the second target reported data is data carrying aggregate fields within the device time period when the aggregation time arrives. Therefore, this embodiment uses the first target reported data and the second target reported data to accurately aggregate data to a single attribute. Not only can the data carrying aggregate fields within the device time period be aggregated and reported, but also the data of non-aggregate fields within the device time period can be aggregated and reported, ensuring that the target aggregation data reported by the device is complete.

[0090] In summary, this embodiment provides a method for data aggregation. When it is specifically implemented, this embodiment first receives the aggregation rules, determines the aggregation time and aggregation attributes of the target aggregated data, and then reads the initial reported data. Based on the aggregation time, the reporting scenario of the initial reported data is determined, and the reporting scenario includes a first reporting scenario and a second reporting scenario. Next, the initial reported data of the first reporting scenario is subjected to single attribute identification to determine the first target reported data, and the first target reported data is the reported data of the non-aggregated attribute; the initial reported data of the second reporting scenario is subjected to single attribute identification to determine the second target reported data, and the second target reported data is the reported data of the aggregated attribute. Finally, the target aggregated data is obtained based on the first target reported data and the first target reported data. Therefore, this embodiment can perform data aggregation accurately to the attribute, which not only improves the accuracy of the device reported data, but also ensures the integrity of the target reported data.

[0091] Based on the above embodiments, the present invention also provides a data aggregation device, such as Figure 4 As shown in , the data aggregation device includes: an aggregation rule determination module 10, a reporting scenario determination module 20, a non-aggregation attribute data determination module 30, an aggregation attribute data determination module 40 and a target aggregation data determination module 50. Specifically, the aggregation rule determination module 10 is used to receive the aggregation rule, determine the aggregation time and aggregation attribute of the target aggregation data. The reporting scenario determination module 20 is used to read the initial reporting data, and determine the reporting scenario of the initial reporting data based on the aggregation time, and the reporting scenario includes a first reporting scenario and a second reporting scenario. The non-aggregation attribute data determination module 30 is used to perform single attribute recognition on the initial reporting data of the first reporting scenario, and determine the first target reporting data, and the first target reporting data is the reporting data of the non-aggregation attribute. The aggregation attribute data determination module 40 is used to perform single attribute recognition on the initial reporting data of the second reporting scenario, and determine the second target reporting data, and the second target reporting data is the reporting data of the aggregation attribute. The target aggregation data determination module 50 is used to obtain the target aggregation data based on the first target reporting data and the first target reporting data.

[0092] In one implementation, the reporting scenario determination module 20 includes:

[0093] An initial reporting data and aggregation time acquisition unit, used to acquire initial reporting data and the aggregation time;

[0094] a first reporting scenario determining unit, configured to determine, when the reporting time of the initial reporting data does not reach the aggregation time, that the reporting scenario of the initial reporting data is the first reporting scenario;

[0095] The second reporting scenario determining unit is configured to determine that the reporting scenario of the initial reporting data is the second reporting scenario when the reporting time of the initial reporting data reaches the aggregation time.

[0096] In one implementation, the non-aggregate attribute data determination module 30 includes:

[0097] a first single attribute data determining unit, configured to perform attribute separation on the initial reporting data of the first reporting scenario to obtain first single attribute data;

[0098] A first attribute comparison unit, used to compare the first single attribute data with the aggregate attribute to obtain a comparison result;

[0099] The first target reporting data determining unit is configured to determine the first target reporting data according to the comparison result, where the first target reporting data is reporting data of a non-aggregate attribute.

[0100] In one implementation, the first attribute separation unit includes:

[0101] An attribute type determination subunit, used to determine the attribute type of the initial reporting data of the first reporting scenario, wherein the attribute type includes single-attribute data and multi-attribute data;

[0102] The first attribute separation subunit is used to perform attribute separation on the multi-attribute data to obtain the first single-attribute data.

[0103] In one implementation, the first target reporting data determining unit includes:

[0104] The first target reported data determining subunit is configured to determine that the first single attribute data is the first target reported data when the comparison result is that the first single attribute data does not belong to the aggregate attribute.

[0105] In one implementation, the aggregated attribute data determination module 40 includes:

[0106] a second single attribute data determining unit, configured to perform attribute separation on the initial reporting data of the second reporting scenario to obtain second single attribute data;

[0107] A second attribute comparison unit, used to compare the second single attribute data with the aggregate attribute to obtain a comparison result;

[0108] The second target reporting data determining unit is used to determine the second target reporting data according to the comparison result, where the second target reporting data is reporting data of an aggregated attribute.

[0109] In one implementation, the second target reporting data determining unit includes:

[0110] The second target reported data determining subunit is configured to determine that the second single attribute data is the second target reported data when the comparison result is that the second single attribute data belongs to the aggregate attribute.

[0111] The working principles of each module in the data aggregation device of this embodiment are the same as the principles of each step in the above method embodiment, and will not be repeated here.

[0112] Based on the above embodiment, the present invention further provides a terminal, the principle block diagram of the terminal can be as follows: Figure 5 The terminal may include one or more processors 100 ( Figure 5 Only one is shown in the figure), a memory 101 and a computer program 102 stored in the memory 101 and executable on one or more processors 100, for example, a data aggregation program. When one or more processors 100 execute the computer program 102, the various steps in the method embodiment of data aggregation can be implemented. Alternatively, when one or more processors 100 execute the computer program 102, the functions of the various modules / units in the device embodiment of data aggregation can be implemented, which is not limited here.

[0113] In one embodiment, the processor 100 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0114] In one embodiment, the memory 101 may be an internal storage unit of an electronic device, such as a hard disk or memory of the electronic device. The memory 101 may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Further, the memory 101 may also include both an internal storage unit of the electronic device and an external storage device. The memory 101 is used to store computer programs and other programs and data required by the terminal. The memory 101 may also be used to temporarily store data that has been output or is to be output.

[0115] Those skilled in the art will understand that Figure 5 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the terminal to which the scheme of the present invention is applied. The specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0116] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, operating database or other media used in the embodiments provided by the present invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double operational data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0117] In summary, the present invention discloses a method, device, terminal and medium for data aggregation, the method comprising: receiving aggregation rules, determining the aggregation time and aggregation attributes of target aggregated data; reading initial reported data, and determining the reporting scenario of the initial reported data based on the aggregation time, the reporting scenario including a first reporting scenario and a second reporting scenario; performing single attribute identification on the initial reported data of the first reporting scenario, determining the first target reported data, the first target reported data being the reported data of the non-aggregated attribute; performing single attribute identification on the initial reported data of the second reporting scenario, determining the second target reported data, the second target reported data being the reported data of the aggregated attribute; obtaining the target aggregated data based on the first target reported data and the first target reported data. The present invention can perform data aggregation accurately to the attribute, thereby improving the integrity and accuracy of the reported data.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for data aggregation, characterized in that: The method comprises: Receive aggregation rules and determine the aggregation time and aggregation attributes of target aggregation data; Reading initial reporting data, and determining a reporting scenario of the initial reporting data based on the aggregation time, where the reporting scenario includes a first reporting scenario and a second reporting scenario; Performing single attribute identification on the initial reporting data of the first reporting scenario to determine first target reporting data, where the first target reporting data is reporting data of non-aggregated attributes; Performing single attribute identification on the initial reporting data of the second reporting scenario to determine second target reporting data, where the second target reporting data is the reporting data of the aggregated attribute; Obtaining the target aggregated data based on the first target reported data and the first target reported data; The reading of the initial reporting data and determining, based on the aggregation time, a reporting scenario of the initial reporting data, wherein the reporting scenario includes a first reporting scenario and a second reporting scenario, include: Acquire initial reporting data and the aggregation time; when the reporting time of the initial reporting data does not reach the aggregation time, determine that the reporting scenario of the initial reporting data is the first reporting scenario; when the reporting time of the initial reporting data reaches the aggregation time, determine that the reporting scenario of the initial reporting data is the second reporting scenario; The performing single attribute identification on the initial reporting data of the first reporting scenario to determine the first target reporting data, where the first target reporting data is reporting data of a non-aggregated attribute, includes: Performing attribute separation on the initial reporting data of the first reporting scenario to obtain first single attribute data of a single attribute; comparing the first single attribute data with the aggregated attribute to obtain a comparison result; determining the first target reporting data according to the comparison result, the first target reporting data being reporting data of a non-aggregated attribute; The performing single attribute identification on the initial reporting data of the second reporting scenario to determine the second target reporting data, where the second target reporting data is the reporting data of the aggregated attribute, includes: Perform attribute separation on the initial reporting data of the second reporting scenario to obtain second single attribute data of a single attribute; compare the second single attribute data with the aggregate attribute to obtain a comparison result; determine the second target reporting data based on the comparison result, and the second target reporting data is the reporting data of the aggregate attribute.

2. The data aggregation method according to claim 1, characterized in that: The performing attribute separation on the initial reporting data of the first reporting scenario to obtain first single attribute data includes: Determining attribute types of initial reporting data of the first reporting scenario, the attribute types including single-attribute data and multi-attribute data; Attribute separation is performed on the multi-attribute data to obtain the first single-attribute data.

3. The data aggregation method according to claim 2, characterized in that: The determining, according to the comparison result, the first target reporting data, where the first target reporting data is reporting data of a non-aggregate attribute, includes: When the comparison result is that the first single attribute data does not belong to the aggregate attribute, it is determined that the first single attribute data is the first target reported data.

4. The method for data aggregation according to claim 1, characterized in that: The determining, according to the comparison result, the second target reporting data, where the second target reporting data is reporting data of an aggregated attribute, includes: When the comparison result is that the second single attribute data belongs to the aggregate attribute, it is determined that the second single attribute data is the second target reported data.

5. A data aggregation device, characterized in that: The method for implementing the data aggregation method according to any one of claims 1 to 4 comprises: An aggregation rule determination module, used to receive the aggregation rule and determine the aggregation time and aggregation attributes of the target aggregation data; A reporting scenario determination module, used to read the initial reporting data, and determine the reporting scenario of the initial reporting data based on the aggregation time, wherein the reporting scenario includes a first reporting scenario and a second reporting scenario; a non-aggregate attribute data determination module, configured to perform single attribute recognition on the initial reporting data of the first reporting scenario to determine first target reporting data, where the first target reporting data is reporting data of non-aggregate attributes; An aggregated attribute data determination module, configured to perform single attribute recognition on the initial reported data of the second reporting scenario to determine second target reported data, where the second target reported data is the reported data of the aggregated attribute; The target aggregate data determination module is used to obtain the target aggregate data based on the first target reported data and the first target reported data.

6. A terminal, characterized in that: The terminal includes a memory, a processor, and a data aggregation program stored in the memory and executable on the processor. When the processor executes the data aggregation program, the steps of the data aggregation method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data aggregation program, and when the data aggregation program is executed by a processor, the steps of the data aggregation method according to any one of claims 1 to 4 are implemented.

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