WO2016127585A1 - 关键数据处理方法和装置、关键数据显示方法和系统 - Google Patents

关键数据处理方法和装置、关键数据显示方法和系统 Download PDF

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WO2016127585A1
WO2016127585A1 PCT/CN2015/084840 CN2015084840W WO2016127585A1 WO 2016127585 A1 WO2016127585 A1 WO 2016127585A1 CN 2015084840 W CN2015084840 W CN 2015084840W WO 2016127585 A1 WO2016127585 A1 WO 2016127585A1
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key data
data
frequency
priority
weight
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PCT/CN2015/084840
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English (en)
French (fr)
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彭建华
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中兴通讯股份有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor

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  • This paper relates to the field of computer technology, and in particular, to a key data processing method and apparatus, and a key data display method and system.
  • An event is a very broad concept, and usually means something that is worth noting.
  • an event can trigger the execution of an activity, which can occur in a given state, can occur during the execution of an activity, or can be generated when certain conditions are met.
  • Complex event processing technology uses pattern comparison, event correlation, and event aggregation. It finds meaningful events from the event cloud and triggers business activities through this meaningful event. The complete complex event processing flow is shown in Figure 1. Shown.
  • real-time data visualization is one of the important components and key links.
  • the configurable key data visualization of complex events it can provide flexibility and adaptability to the data display of complex event processing of data streams.
  • the related art does not realize the visualization of key data in complex event processing; therefore, the technical problem of how to realize the visualization of key data in complex event processing is urgently needed to be solved.
  • Embodiments of the present invention provide a key data processing method and apparatus, and a key data display method and system, which can solve the technical problem of how to realize visualization of key data in complex event processing.
  • An embodiment of the present invention provides a key data processing method, including the following steps:
  • Key data identification for data in complex event processing including: raw data and/or complex event processed data;
  • the key data is sent to the client according to the priority of the key data for the client to display the key data.
  • the step of performing key data identification on the data includes:
  • Key data is identified based on key data model flags and key data weight markers.
  • the method before the performing critical data identification on the data in the process of processing the complex event, the method further includes:
  • the steps of obtaining the key data model flag and the key data weight flag include:
  • the key data model configuration file is parsed to obtain a key data model identifier, and the key data weight file is parsed to obtain a key data weight indicator.
  • the step of setting a priority of the key data includes:
  • Determining the type of the key data obtaining a frequency of occurrence of the determined type of key data, the frequency including: a current frequency and a historical frequency;
  • the priority of the key data is set according to the frequency.
  • the step of obtaining the frequency of occurrence of the determined type of key data includes:
  • the current frequency at which the critical data of the determined type occurs is calculated based on the key data model flag and the historical frequency.
  • the step of setting a priority of the critical data according to the frequency includes:
  • the priority of the key data is set according to the frequency and the key data weight corresponding to the determined type of key data.
  • the method further includes: calculating key data corresponding to each type of key data. Weights.
  • the step of calculating key data weights corresponding to each type of key data includes:
  • the ratio of the initial key data weights corresponding to the total weights of each type of key data is respectively taken as the key data weight corresponding to each type of key data, and the total weight is the key of all types.
  • the sum of the initial key data weights corresponding to the data is the sum of the initial key data weights corresponding to the data.
  • the step of setting a priority of the key data according to the frequency and the key data weight corresponding to the determined type of key data includes:
  • the priority of the key data is set according to the average value.
  • the embodiment of the invention further provides a key data display method, comprising the following steps:
  • the key data is visually displayed based on the determined key data levels.
  • the embodiment of the invention further provides another key data processing device, comprising: an identification module, a setting module and a sending module, wherein:
  • the identification module is configured to perform key data identification on data in a complex event processing process, where the data includes: original data and/or data processed by complex events;
  • the setting module is configured to set a priority of the key data when the identification module identifies key data
  • the sending module is configured to send the key data to the client according to the priority of the key data, so that the client displays the key data.
  • the device further includes: a loading module, the identification module includes: a parsing module and a key data identifying module, wherein:
  • the loading module is configured to load a key data model configuration file and a key data weight configuration file during an initialization phase of complex event processing
  • the parsing module is configured to parse the key data model configuration file to obtain a key data model identifier, and parse the key data weight file to obtain a key data weight indicator;
  • the key data identification module is configured to perform key data identification on the data according to the key data model flag and the key data weight indicator.
  • the setting module includes: a frequency acquiring module and a priority setting module, where:
  • the frequency acquisition module is configured to determine a type of the key data, and obtain a frequency of occurrence of a key data of a determined type, where the frequency includes: a current frequency and a historical frequency;
  • the priority setting module is configured to set a priority of the key data according to the frequency and a key data weight corresponding to the determined type of key data.
  • the priority setting module is set to:
  • the priority of the key data is set according to the average value.
  • the embodiment of the invention further provides a key data display system, comprising: a client and a key data processing device according to any of the above;
  • the client is set to:
  • Determining a key data level corresponding to the key data Determining a key data level corresponding to the key data, and visualizing the key data according to the determined key data level.
  • the embodiment of the invention further provides a computer readable storage medium storing program instructions, which can be implemented when the program instructions are executed.
  • the embodiment of the present invention provides a key data processing method and apparatus, and a key data display method and system.
  • the key data processing method includes the following steps: performing key data identification on data in a complex event processing process, where the data includes: Raw data and/or complex event processed data; setting priority of the key data when identifying key data; sending the key data to the client according to the priority of the key data for the The client displays the key data; the foregoing processing method can identify the key data in the process of the complex event processing, and send the key data to the client display according to the priority of the set key data; it can be seen that the embodiment of the present invention is applied.
  • Key data processing methods can visualize key data in complex event processing and pass The key data priority setting sends important key data to the client for display in advance.
  • Figure 1 is a schematic flow chart of complex event processing
  • FIG. 2 is a schematic flowchart of a key data processing method according to Embodiment 1 of the present invention.
  • FIG. 3 is a schematic flowchart of another key data processing method according to Embodiment 1 of the present invention.
  • FIG. 5 is a schematic structural diagram of a key data display method according to Embodiment 2 of the present invention.
  • FIG. 6 is a schematic structural diagram of a first key data processing apparatus according to Embodiment 3 of the present invention.
  • FIG. 7 is a schematic structural diagram of a second key data processing apparatus according to Embodiment 3 of the present invention.
  • FIG. 8 is a schematic structural diagram of a third key data processing apparatus according to Embodiment 3 of the present invention.
  • FIG. 9 is a schematic structural diagram of a key data display system according to Embodiment 3 of the present invention.
  • Embodiment 1 is a diagrammatic representation of Embodiment 1:
  • the present embodiment provides a key data processing method, as shown in FIG. 2, which includes the following steps, in view of the fact that there is currently no solution for realizing the visualization of key data in complex event processing.
  • Step 201 Perform key data identification on data in the process of complex event processing, where the data includes: raw data and/or data processed by complex events.
  • the key data processing method of this embodiment can be applied to the 10 position as shown in FIG. 1.
  • the 10 position of FIG. 1 is a merge calculation function in the system, and the part receives the data of the complex event processing system, and the data includes: original data. And/or result data after complex event processing.
  • the method for identifying the key data of the data may be identified by using the key data model identifier and the key data weight indicator. Therefore, the process of identifying the key data in the data in this step may include:
  • Key data is identified based on key data model flags and key data weight markers.
  • the process of obtaining the key data model identifier and the key data weight indicator in the embodiment may include: parsing the key data model configuration file to obtain the key data model identifier, parsing the key data weight file to obtain the key data weight flag; and the key data model Profiles and weight files can be loaded during the initialization phase of complex event processing.
  • the key data model configuration file and the key data weight file are loaded, and then the key data model configuration file and the key data weight file are respectively parsed to obtain the key data model flag and the key data weight flag, and then The acquisition flag information is placed in the memory for subsequent identification of the data.
  • the process of parsing the file in this embodiment may be performed in the initialization phase, or may be performed when critical data identification is required, and the timing of the parsing process is not limited.
  • the key data model flag can be parsed by the algorithm formula (1) after loading the key data model configuration file
  • the key data weight flag can be parsed by the algorithm formula (2) after loading the key data weight file:
  • MS is the model flag
  • PMs is the key data model configuration file. This function parses the key data configuration file, the process is:
  • the key of the map is the model flag
  • the value is the instance of the attribute object of the corresponding model in the model configuration file.
  • WS is a weight indicator
  • PWs is a key data weight configuration file. This function parses the key data weight configuration file, the process is:
  • the key of the map is the weight flag
  • the value is the attribute object instance of the corresponding weight in the weight configuration file.
  • key data can be identified by using MS and WS.
  • key data can be identified by algorithm formula (3):
  • DATA is the identified data (which can be raw data or complex event processed data)
  • MS is the key data model flag
  • WS is the key data weight indicator. This function identifies key data for the data. The process is:
  • the intercepted flag is: determine the segmentation flag of the data stream, intercept according to the segmentation flag, each segment has a data type record value, indicating what type of data the segment data belongs to, according to the data The type record value, instantiate each piece of data into the corresponding data type object, and the key data instantiation object contains the key data reference count attribute;
  • Step 202 Set priority of the key data when identifying key data.
  • the method of this embodiment also needs to set the priority of key data, so that the priority can be high when sending.
  • the key data (that is, high importance) is sent to the client for display, and priority data with high priority is displayed first.
  • the embodiment may set the priority based on the key data type and the frequency of occurrence of the key data. Therefore, the process of setting the priority of the key data in this step may include:
  • Determining the type of the key data obtaining a frequency of occurrence of the determined type of key data, the frequency including: a current frequency and a historical frequency;
  • the priority of the key data is set according to the frequency.
  • the current frequency at which the critical data of the determined type occurs is calculated based on the key data model flag and the historical frequency.
  • the historical frequency is the frequency calculated or acquired before the current time.
  • the frequency of occurrence of the identified key data of the type is increased by one, that is, based on the historical frequency of the key data of the type. 1. If the current data in the data stream is not critical data, or the key data source is not in the memory, the frequency of the key data of the type does not change. In this embodiment, the frequency of the key data can be calculated by the frequency formula (4). :
  • DATA is the identified data
  • KS is the key data
  • MS is the key data model flag. This function performs frequency calculation on the data, and the process is:
  • the intercepted flag is: determine the segmentation flag of the data stream, intercept according to the segmentation flag, each segment has a data type record value, indicating what type of data the segment data belongs to, according to the data Type record value, instantiate each piece of data into the corresponding data type object, and the key data instantiated object contains key data frequency attributes;
  • the method of the embodiment may set the priority of the key data based on the frequency, and optionally, according to the frequency and the key data corresponding to the determined type of key data.
  • the weight sets the priority of the key data.
  • the key data of the visual display is prioritized, and the data with high priority is displayed in real time.
  • the embodiment can average the product of the frequency and the weight of the key data, and then set according to the average value. Priority, the average value is large and the priority is high.
  • the average value can be calculated by formula (5):
  • Pre a is the key data frequency of the type a
  • Pre a1 is the initial frequency value of the key data of the a type
  • PSa is the weight value corresponding to the key data of the type a.
  • the method of the embodiment may further calculate a key data weight corresponding to each type of key data before setting the priority, so as to perform frequency calculation in the setting priority phase; loading the key data model configuration file and the key After the data weight profile is configured, before the priority of the key data is set according to the frequency, the method in this embodiment further includes: calculating a key data weight corresponding to each type of key data.
  • the key data weights corresponding to each type of key data can be calculated and then stored (for example, stored in memory).
  • the key data weights are calculated as the ratio of the initial key data weights corresponding to the total weights of each type of key data to the key data weights of each type of key data, and the total weights are all types of key data.
  • PS a is the weight value of the key data of type a
  • IPr a is the initial weight value of the key data of type a
  • IPr i is the weight value of each type of key data.
  • Step 203 Send the key data to the client according to the priority of the key data, so that the client displays the key data.
  • key data can be sent periodically, and when the transmission time point arrives, If critical data exists, key data is sent to the client for display based on the priority of the key data.
  • the processing method of the embodiment can identify the key data in the process of the complex event processing, and send the key data to the client according to the priority of the set key data. It can be seen that the key data processing method of the embodiment can be implemented. Visualize key data in complex event processing, effectively and timely identify and visualize key data, and send important key data to the client for display in advance through key data priority settings.
  • the key data processing method in this embodiment may be:
  • Step 301 Loading a key data model configuration file when the complex event processing system is initialized
  • Step 302 Determine whether the loading is successful, if yes, proceed to step 303, and if not, proceed to step 311;
  • Step 303 load the key data weight file, and determine whether the loading is successful, and if so, proceed to step 304, and if not, proceed to step 311;
  • the system starts. After the power is turned on, it enters the system initialization state, and loads various resources in the initialization state, including: key data model configuration files and weight files.
  • the key data model configuration file and the weight file may be associated with the weight file through the complex event ID, that is, the data to be identified (for example, the original data or the complex event processed data) and the weight configuration file are passed through the complex event.
  • the ID corresponds.
  • Step 304 Store the key data model configuration file and the weight file, respectively parse the key data model configuration file and the weight file to obtain the key data model flag and the weight flag, and store the flag information, and calculate the key data corresponding to each type of key data. Weight, and store the calculated key data weights, then the system enters the working state;
  • the model configuration file and the weight file are stored in the memory, and after the parsing is completed, the identification information is stored in the memory; in the case of using the complex event ID association, the association relationship needs to be stored, optionally
  • the key data model configuration file and the weight file are placed in the memory in the form of a list, the complex event ID and the weight configuration are put into the variable of the MAP type, and the association relationship is stored in the memory.
  • the key data model and the weight flag can be parsed by the formula (1) (2), and the key data weight corresponding to each type of key data is calculated by the formula (6).
  • Step 305 After the visual event planning, perform key data identification on the data in the complex event processing process according to the key data model flag and the key data weight flag;
  • the identification process can refer to the above description, such as using equation (3) for identification.
  • Step 306 If key data is identified, storing the key data, and calculating a frequency of occurrence of the key data;
  • key data is placed in the redis database and flagged.
  • Step 307 Determine a type of the key data, and set a priority of the key data according to a frequency of occurrence of the key data of the determined type and a key data weight corresponding to the key data of the determined type;
  • the frequency includes a current frequency and a historical frequency, wherein the current frequency is calculated by referring to formula (4); and then obtaining the product of the frequency and the key data weight
  • the average value is calculated by referring to formula (5); finally, the priority of the key data is set according to the average value.
  • the frequency (current frequency and historical frequency) of the key data of type a is obtained, and the weight corresponding to the key data of type a; then the average of the product of the frequency and the weight is taken, and finally The priority of this critical data is set based on the average. The higher the average value, the higher the priority.
  • Step 308 Determine whether the time point of data transmission is reached, and if so, proceed to step 309, and if not, return to step 305;
  • key data is sent periodically, and when the transmission time point is not reached, the data is continuously identified and the priority is set. When the transmission time point arrives, the key data is transmitted.
  • Step 309 polling to check whether key data is stored, if yes, executing step 310, and if not, continuing to check;
  • Step 310 Send key data to the client for display according to the priority of the stored key data
  • Step 311 Write a log.
  • the key data model configuration files and weight files need to be loaded, and then the key data model configuration files and weight files are respectively parsed to obtain key data model flags and weight flags, and stored in the memory to prepare for data identification;
  • the above formula (1) (2) it is also necessary to calculate the weight corresponding to each type of key data.
  • the calculation process can refer to the above formula (6), that is, by summing all types of weights and then taking the reciprocal, and then accumulating the weights of each type of key data. Calculate the weight value corresponding to each type of key data, and store the weight value of each type of key data in the memory to prepare for the priority setting.
  • the 1-6 and 8-9 links in Figure 1 belong to the data and event processing process of the complex event working state.
  • the data is processed through the 1-6 and 8-9 links in Figure 1, entering the 7 and 10 links, and the data ( Including raw data and/or data processed by complex events) combined with key model flags and weight markers in memory for key data identification.
  • the identification method can be matched by data and weight flag and model flag. If the match is successful, then The data indicating that the matching is the key data, the matching key data is put into the redis database and marked, and the identification algorithm is shown in formula (3).
  • the data is processed through the steps 1-6 and 8-9 in Figure 1, and enters the 7 and 10 links.
  • Key data frequency calculation and identification the identification method can be matched with key data and model flags. If the matching is successful, the key data of this type grows by 1, and the frequency data is put into the redis database and marked, in the frequency calculation process. In the case, the key data of the same type is locked, and the synchronous and asynchronous operation control is performed.
  • the calculation algorithm is shown in formula (4).
  • the system After the priority of the key data is calculated, the system periodically pushes the data to the client according to the key data priority, and displays the visual data. By clicking the alarm point, the alarm information traceback interface is popped up. The data of the alarm information is restored and displayed.
  • the key data push process includes the following steps:
  • Step 401 When the system starts, start a key data push thread
  • Step 402 Thread timing polling detects whether there is key data in the storage area (for example, the key data memory area and the redis database), and if yes, executing step 403, and if not, continuing to detect;
  • key data for example, the key data memory area and the redis database
  • Step 403 Sort the priority of the key data installation, and simultaneously push the key data to the client according to the priority from high to low;
  • Step 404 Set the priority of the key data after the push.
  • Embodiment 2 is a diagrammatic representation of Embodiment 1:
  • this embodiment provides a key data display method, including the following steps:
  • Step 501 Send key data to the client by using the key data processing method described in Embodiment 1.
  • Step 502 The client determines a key data level corresponding to the key data.
  • the level corresponding to the key data value may be determined according to the key data value. For example, if the key data priority is set according to the average value, the average value corresponding to the key data (such as Pra of the embodiment) may be determined to determine The corresponding level.
  • Step 503 Perform visual data display on the key data according to the determined key data level.
  • different display modes can be used to display key data according to different levels, for example, different levels correspond to different display colors, or corresponding display window shapes.
  • the method in this embodiment can also backtrack key data, track the formation process of key data, and display it in a graphical manner.
  • the display manner of the embodiment may be: the time is the X axis, the Pra is the Y axis, and the complete process of the Pra calculation is displayed by the line graph manner, that is, Graphically show the formation process of Pra.
  • Embodiment 3 is a diagrammatic representation of Embodiment 3
  • the embodiment provides a key data processing apparatus, including: an identification module, a setting module, and a sending module;
  • the identification module is configured to perform key data identification on data in a complex event processing process, where the data includes: original data and/or data processed by complex events;
  • the setting module is configured to set a priority of the key data when the identification module identifies key data
  • the sending module is configured to send the key data to the client according to the priority of the key data, so that the client displays the key data.
  • the apparatus of this embodiment further includes: a loading module, where the identifying module includes: a parsing module and a key data identifying module, where:
  • the loading module is configured to load a key data model configuration file and a key data weight configuration file during an initialization phase of complex event processing
  • the parsing module is configured to parse the key data model configuration file to obtain a key data model identifier, and parse the key data weight file to obtain a key data weight indicator;
  • the key data identification module is configured to perform key data identification on the data according to the key data model flag and the key data weight indicator.
  • the setting module in the apparatus of this embodiment includes: a frequency acquiring module and a priority setting module, where:
  • the frequency acquisition module is configured to determine a type of the key data, and obtain a frequency of occurrence of a key data of a determined type, where the frequency includes: a current frequency and a historical frequency;
  • the priority setting module is configured to set a priority of the key data according to the frequency and a key data weight corresponding to the determined type of key data.
  • the priority setting module is set to:
  • the priority of the key data is set according to the average value.
  • the key data processing apparatus provided in this embodiment can realize visual display of data for complex event processing.
  • the embodiment further provides a key data display system, including a client and a key data processing device as described in any of FIGS. 6-8;
  • the client is set to:
  • Determining a key data level corresponding to the key data Determining a key data level corresponding to the key data, and visualizing the key data according to the determined key data level.
  • the solution of the key data in the complex event processing can be realized by applying the solution of the embodiment of the present invention, and the important key data can be sent to the client for display in advance through the setting of the key data priority.

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Abstract

提供一种关键数据处理方法和装置、关键数据显示方法和系统。所述关键数据处理方法包括：对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据（201）；当识别有关键数据时，设置所述关键数据的优先级（202）；根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据（203）。

Description

关键数据处理方法和装置、关键数据显示方法和系统 技术领域
本文涉及计算机技术领域，尤其涉及一种关键数据处理方法和装置、关键数据显示方法和系统。
背景技术
事件是一个很广泛的概念，通常意义上指有值得注意的事发生。在编程逻辑关系中，事件可以触发活动的执行，它可以在某个既定状态下发生，可以在活动执行过程中产生，也可以是因为某些条件被满足时产生。复杂事件处理技术是使用模式比对、事件的相互关系、事件间的聚合关系，从事件云中找出有意义的事件，通过这个有意义的事件触发业务活动；完整复杂事件处理流程如图1所示。
基于数据流的复杂事件处理，实时数据可视化是其中一个重要组成部分与关键环节，基于可配置的复杂事件关键数据可视化，能够对数据流的复杂事件处理的数据展示提供灵活性与适应性。然而，相关技术中并没有实现复杂事件处理中关键数据的可视化的方式；因此，如何实现复杂事件处理中关键数据的可视化的技术问题急需解决。
发明内容
本发明实施例提供一种关键数据处理方法和装置、关键数据显示方法和系统，能够解决如何实现复杂事件处理中关键数据的可视化的技术问题。
本发明实施例提供一种关键数据处理方法，包括如下步骤:
对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据；
当识别有关键数据时，设置所述关键数据的优先级；
根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据。
可选地，所述对数据进行关键数据识别的步骤包括：
获取关键数据模型标志和关键数据权重标志；
根据关键数据模型标志和关键数据权重标志对数据进行关键数据识别。
可选地，在所述对复杂事件处理过程中的数据进行关键数据识别之前，所述方法还包括：
在复杂事件处理的初始化阶段，加载关键数据模型配置文件和关键数据权重配置文件；
所述获取关键数据模型标志和关键数据权重标志的步骤包括：
对所述关键数据模型配置文件进行解析获取关键数据模型标志，对所述关键数据权重文件进行解析获取关键数据权重标志。
可选地，所述设置所述关键数据的优先级的步骤包括：
确定所述关键数据的类型，获取确定类型的关键数据出现的频率，所述频率包括：当前频率和历史频率；
根据所述频率设置所述关键数据的优先级。
可选地，所述获取确定类型的关键数据出现的频率的步骤包括：
获取确定类型的关键数据出现的历史频率；
根据关键数据模型标志和所述历史频率计算出确定类型的关键数据出现的当前频率。
可选地，所述根据所述频率设置所述关键数据的优先级的步骤包括：
根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级。
可选地，在加载关键数据模型配置文件和关键数据权重配置文件之后，根据所述频率设置所述关键数据的优先级之前，所述方法还包括：计算每个类型的关键数据对应的关键数据权重。
可选地，所述计算每个类型的关键数据对应的关键数据权重的步骤包括:
分别将每个类型的关键数据对应的初始关键数据权重占总权重的比例作为每个类型的关键数据对应的关键数据权重，所述总权重为所有类型的关键 数据对应的初始关键数据权重之和。
可选地，所述根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级的步骤包括：
获取所述频率与所述关键数据权重乘积的平均值；
根据所述平均值设置所述关键数据的优先级。
本发明实施例还提供了一种关键数据显示方法，包括如下步骤：
利用上任一项所述的关键数据处理方法发送关键数据至客户端；
所述客户端确定所述关键数据对应的关键数据级别；
根据确定的关键数据级别对所述关键数据进行可视化数据显示。
本发明实施例还提供另一种关键数据处理装置，包括：识别模块、设置模块和发送模块，其中：
所述识别模块，设置为对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据；
所述设置模块，设置为当所述识别模块识别有关键数据时，设置所述关键数据的优先级；
所述发送模块，设置为根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据。
可选地，所述装置还包括：加载模块，所述识别模块包括：解析模块和关键数据识别模块，其中：
所述加载模块，设置为在复杂事件处理的初始化阶段，加载关键数据模型配置文件和关键数据权重配置文件；
所述解析模块，设置为对所述关键数据模型配置文件进行解析获取关键数据模型标志，对所述关键数据权重文件进行解析获取关键数据权重标志；
所述关键数据识别模块，设置为根据关键数据模型标志和关键数据权重标志对数据进行关键数据识别。
可选地，所述设置模块包括：频率获取模块和优先级设置模块，其中：
所述频率获取模块，设置为确定所述关键数据的类型，获取确定类型的关键数据出现的频率，所述频率包括：当前频率和历史频率；
所述优先级设置模块，设置为根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级。
可选地，所述优先级设置模块是设置为：
获取所述频率与所述关键数据权重乘积的平均值；
根据所述平均值设置所述关键数据的优先级。
本发明实施例还提供了一种关键数据显示系统，包括：客户端和如上任一项所述的关键数据处理装置；
所述客户端，设置为：
接收所述关键数据显示装置发送的关键数据；
确定所述关键数据对应的关键数据级别，根据确定的关键数据级别对所述关键数据进行可视化数据显示。
本发明实施例还提供一种计算机可读存储介质，存储有程序指令，当该程序指令被执行时可实现上述方法。
本发明实施例提供了一种关键数据处理方法和装置、关键数据显示方法和系统，其中，关键数据处理方法包括如下步骤：对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据；当识别有关键数据时，设置所述关键数据的优先级；根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据；上述处理方法可以识别出复杂事件处理过程中的关键数据，且按照设置的关键数据的优先级来将关键数据发送给客户端显示；可见，应用本发明实施例的关键数据处理方法可以实现复杂事件处理中关键数据的可视化，且可通过 关键数据优先级的设置将重要的关键数据提前发送给客户端显示。
附图概述
图1为复杂事件处理的流程示意图；
图2为本发明实施例一提供的一种关键数据处理方法的流程示意图；
图3为本发明实施例一提供的另一种关键数据处理方法的流程示意图；
图4为本发明实施例一提供的一种数据推送的流程示意图；
图5为本发明实施例二提供的一种关键数据显示方法的结构示意图；
图6为本发明实施例三提供的第一种关键数据处理装置的结构示意图；
图7为本发明实施例三提供的第二种关键数据处理装置的结构示意图；
图8为本发明实施例三提供的第三种关键数据处理装置的结构示意图；
图9为本发明实施例三提供的一种关键数据显示系统的结构示意图。
本发明的实施方式
下面结合附图对本发明实施例作详细说明。
实施例一：
考虑到目前没有实现复杂事件处理中关键数据的可视化的方案，本实施例提供了一种关键数据处理方法，如图2所示，包括如下步骤：
步骤201：对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据。
本实施例的关键数据处理方法可以应用在如图1所示的10位置，图1的10位置在系统中是一个归并计算功能，该部分接收到复杂事件处理系统的数据，数据包含：原始数据和/或复杂事件处理后的结果数据。
本实施例对数据进行关键数据识别的方式可以为利用关键数据模型标志和关键数据权重标志进行识别，因此，本步骤中对数据进行关键数据识别的过程可以包括：
获取关键数据模型标志和关键数据权重标志；
根据关键数据模型标志和关键数据权重标志对数据进行关键数据识别。
本实施例中获取关键数据模型标志和关键数据权重标志的过程可以包括：对关键数据模型配置文件进行解析获取关键数据模型标志，对关键数据权重文件进行解析获取关键数据权重标志；而关键数据模型配置文件和权重文件可以在复杂事件处理的初始化阶段加载。
例如在复杂事件处理系统初始化时，对关键数据模型配置文件、关键数据权重文件进行加载，然后对关键数据模型配置文件和关键数据权重文件分别进行解析获取关键数据模型标志和关键数据权重标志，然后将获取标志信息放入内存中，以供后续对数据进行识别。本实施例中对文件解析的过程可以在初始化阶段进行，也可以在需要进行关键数据识别时进行，解析过程的时序不受限制。
本实施例可以在加载关键数据模型配置文件之后可通过算法公式(1)解析出关键数据模型标志，在加载关键数据权重文件之后可通过算法公式(2)解析出关键数据权重标志：
MS＝LOADM(PMs)  (1)
其中，MS是模型标志，PMs是关键数据模型配置文件。该函数解析关键数据配置文件，过程为：
●把关系数据模型配置文件加载到内存；
●解析关键数据模型配置文件，获取配置文件中的模型标志；
●解析关键数据模型配置文件，获取配置文件中的模型标志对应模型的属性实例；
●把模型标志放入map中，map的key为模型标志，value为模型配置文件中对应模型的属性对象实例。
WS＝LOADP(PWs)  (2)
其中，WS是权重标志，PWs是关键数据权重配置文件。该函数解析关键数据权重配置文件，过程为：
●把关键数据权重配置文件加载到内存；
●解析关键数据权重配置文件，获取配置文件中的权重标志；
●解析关键数据权重配置文件，获取配置文件中的权重标志对应权重的属性实例；
●把权重标志放入map中，map的key为权重标志，value为权重配置文件中对应权重的属性对象实例。
本实施例可通过MS和WS对数据进行关键数据识别，可选地，可通过算法公式(3)进行关键数据识别：
Figure PCTCN2015084840-appb-000001
其中，DATA是被识别的数据(可以为原始数据或者复杂事件处理后的数据)，MS是关键数据模型标志，WS是关键数据权重标志。该函数对数据进行关键数据识别，过程为：
●接收需要被识别的数据流DATA；
●对数据流进行分段截取，截取的标志是：判断数据流的分段标志，按照分段标志进行截取，每段有一个数据类型记录值，标示该段数据属于什么类型的数据，根据数据类型记录值，把每段数据实例化到对应的数据类型对象中，关键数据实例化对象包含关键数据引用计数属性；
●通过数据类型记录值，结合关键数据模型标志，如果在map中能够找到关键数据属性，则更新对应关键数据属性中的关键数据引用计数值，也就是对应关键数据属性的引用计数加1。
步骤202：当识别有关键数据时，设置所述关键数据的优先级。
在被识别的数据为关键数据时，考虑到不同关键数据的重要性或者属性或者用户需求等不相同，因此，本实施例方法还需要设置关键数据的优先级，这样可以在发送时优先级高(即重要性高)的关键数据先发送给客户端显示，优先显示优先级高的关键数据。
可选地，本实施例可以基于关键数据类型和关键数据出现的频率来设置优先级，所以，本步骤中设置所述关键数据的优先级的过程可以包括：
确定所述关键数据的类型，获取确定类型的关键数据出现的频率，所述频率包括：当前频率和历史频率；
根据所述频率设置所述关键数据的优先级。
本实施例中获取确定类型的关键数据出现的频率的过程可以包括：
获取确定类型的关键数据出现的历史频率；
根据关键数据模型标志和所述历史频率计算出确定类型的关键数据出现的当前频率。
本实施例中历史频率为在当前时刻之前计算或者获取过的频率。
例如，如果数据流中的当前数据是关键数据，且关键数据源在内存中，则识别出的该类型的关键数据出现的频率加1，即在该类型的关键数据的历史频率的基础上加1，如果数据流中的当前数据不是关键数据，或者关键数据源不在内存中，则该类型的关键数据出现的频率不变，本实施例可以通过频率公式(4)来计算关键数据出现的频率：
Figure PCTCN2015084840-appb-000002
其中，DATA是被识别的数据，KS是关键数据，MS是关键数据模型标志。该函数对数据进行频率计算，过程为：
●接收需要被识别的数据流DATA；
●对数据流进行分段截取，截取的标志是：判断数据流的分段标志，按照分段标志进行截取，每段有一个数据类型记录值，标示该段数据属于什么类型的数据，根据数据类型记录值，把每段数据实例化到对应的数据类型对象中，关键数据实例化对象包含关键数据频率属性；
●通过数据类型记录值，结合关键数据模型标志，如果在map中能够找到关键数据属性，则更新对应关键数据属性中的关键数据频率值，也就是对应关键数据属性的频率加1。
在获取识别出的关键数据出现的频率之后，本实施例方法可以基于该频率来设置该关键数据的优先级，可选地，可以根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级。
在本实施例中对可视化显示的关键数据进行优先级设置，实时、优先显示优先级高的数据，本实施例可以通过对关键数据出现的频率与权重的乘积取平均，然后根据平均值来设置优先级，平均值大则优先级高，本实施例可通过公式(5)计算平均值：
Figure PCTCN2015084840-appb-000003
其中，Prea是第a类型的关键数据频率，Prea1是第a类型的关键数据出现的频率初始值，PSa是第a类型的关键数据对应的权重值。
Pra值大的，则关键数据优先级越高，数据越关键，需要优先推送与显示。
可选地，本实施例方法在设置优先级之前还可以事先计算出每个类型的关键数据对应的关键数据权重，以供在设置优先级阶段进行频率计算；在加载关键数据模型配置文件和关键数据权重配置文件之后，根据所述频率设置所述关键数据的优先级之前，本实施例方法还包括：计算每个类型的关键数据对应的关键数据权重。
例如，在复杂事件处理的初始化阶段，加载关键数据模型配置文件和关键数据权重配置文件之后，可以计算每个类型的关键数据对应的关键数据权重，然后进行存储(比如存放在内存中)。
计算关键数据权重的方式为：分别将每个类型的关键数据对应的初始关键数据权重占总权重的比例作为每个类型的关键数据对应的关键数据权重，所述总权重为所有类型的关键数据对应的初始关键数据权重之和。以a类型的关键数据为例，可以通过公式(6)来计算a类型的关键数据的权重:
Figure PCTCN2015084840-appb-000004
其中：PSa是第a类型的关键数据的权重值，IPra是第a类型关键数据的初始权重值，IPri是每类关键数据的权重值。
步骤203：根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据。
在数据发送阶段，可以采用定时发送关键数据，到发送时间点到达时， 若有关键数据存在，则根据关键数据的优先级来发送关键数据至客户端进行显示。
本实施例的处理方法可以识别出复杂事件处理过程中的关键数据，且按照设置的关键数据的优先级来将关键数据发送给客户端显示；可见，应用本实施例的关键数据处理方法可以实现复杂事件处理中关键数据的可视化，有效、及时对关键数据进行识别与可视化展示，且可通过关键数据优先级的设置将重要的关键数据提前发送给客户端显示。
根据上述对关键数据处理方法的描述，如图3所示，本实施例的关键数据处理方法可以为：
步骤301：在复杂事件处理系统初始化时加载关键数据模型配置文件；
步骤302：判断是否加载成功，若是，则执行步骤303，若否，则执行步骤311；
步骤303：加载关键数据权重文件，并判断是否加载成功，若是，则执行步骤304，若否，则执行步骤311；
系统开始，上电完成后，进入系统初始化状态，在初始化状态对多种资源进行加载，其中包括：关键数据模型配置文件和权重文件。本实施例还可以将关键数据模型配置文件与权重文件通过复杂事件ID与权重文件进行关联，也就是将待识别的数据(例如原始数据或者复杂事件处理后的数据)与权重配置文件通过复杂事件ID进行对应。
步骤304：存储关键数据模型配置文件和权重文件，分别对关键数据模型配置文件和权重文件进行解析获取关键数据模型标志和权重标志，并存储标志信息，计算每个类型的关键数据对应的关键数据权重，并存储计算的关键数据权重，然后系统进入工作状态；
在加载完成后，将模型配置文件和权重文件存放在内存中，在解析完成后，将标识信息存放在内存中；在利用复杂事件ID关联的情况下，还需要将关联关系存储，可选地，将关键数据模型配置文件与权重文件以列表形式放于内存，复杂事件ID、权重配置放入MAP类型的变量中，关联关系存入内存。
本实施例方法可以通过公式(1)(2)解析出关键数据模型和权重标志，通过公式(6)计算每个类型的关键数据对应的关键数据权重。
步骤305：在可视化事件规划之后，根据关键数据模型标志和关键数据权重标志对复杂事件处理过程中数据进行关键数据识别；
识别过程可以参考上述描述，比如采用公式(3)进行识别。
步骤306：若识别有关键数据，则存储所述关键数据，并计算该关键数据出现的频率；
可选地，将关键数据放入redis数据库并进行标志。
步骤307：确定所述关键数据的类型，根据确定类型的关键数据出现的频率和确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级；
可选地，先获取确定类型的关键数据出现的频率，该频率包括当前频率和历史频率，其中当前频率的计算方式可参考公式(4)；然后获取所述频率与所述关键数据权重乘积的平均值，计算方式参考公式(5)；最后，根据所述平均值设置所述关键数据的优先级。
例如在识别的关键数据为a类型后，获取a类型的关键数据出现的频率(当前频率和历史频率)和a类型的关键数据对应的权重；然后将取频率与权重的乘积的平均值，最后根据平均值设置该关键数据的优先级。平均值越大优先级越高。
步骤308：判断数据发送的时间点是否达到，若是，则执行步骤309，若否，则返回步骤305；
本实施例采用定时发送关键数据，在发送时间点未到时，继续识别数据和设置优先级，在发送时间点到达时，则进行关键数据的发送。
步骤309：轮询检查是否存储有关键数据，若有，执行步骤310，若否，继续检查；
步骤310：根据存储的关键数据的优先级发送关键数据给客户端进行显示；
步骤311：写日志。
下面结合图1所示的复杂事件处理流程来介绍本实施例的处理方法：
在系统初始化时，需要加载关键数据模型配置文件和权重文件，然后分别解析关键数据模型配置文件和权重文件获取关键数据模型标志和权重标志，并存入内存中为数据识别做准备；解析过程参考上述公式(1)(2)。另外，还需要计算出每个类型的关键数据对应的权重，计算过程可以参考上述公式(6)，即通过对所有类型的权重求和后取倒数，然后对每类关键数据的权重求积，计算出每类关键数据对应的权重值，将每个类型的关键数据的权重值存入内存中，为优先级设置做准备。
图1中的1-6与8-9环节，属于复杂事件工作状态的数据、事件处理过程，数据通过图1中的1-6与8-9环节的处理，进入7与10环节，数据(包括原始数据和/或复杂事件处理后的数据)与内存中的关键模型标志以及权重标志进行结合，进行关键数据识别，识别方式可以通过数据与权重标志、模型标志进行匹配，如果匹配成功，则标示被匹配的数据是关键数据，把匹配的关键数据放入redis数据库并进行标志，识别算法见公式(3).
数据出现的频率越高，同时是关键数据的话，一般情况下这个数据具有相对较高的紧急性，数据通过图1中的1-6与8-9环节的处理，进入7与10环节，进行关键数据频率计算与识别，识别方式可以通过数据与关键数据、模型标志进行匹配，如果匹配成功，则该类型的关键数据自增长1，把频率数据放入redis数据库并进行标志，在频率计算过程中，对同种类型的关键数据进行加锁，进行同步与异步操作控制，计算算法见公式(4)。
关键数据中，紧急数据需要优先显示，由于数据复杂事件中的数据是持续的数据流，通过系统处理后的数据也在不断变动，数据紧急性也在不断改变，因此需要对不断变化的紧急数据的优先级进行判断，通过公式(4)，已经在持续计算关键数据的频率，并把计算结果Pre放入redis数据库中，同时，在系统初始化时，通过公式(2)，得到了权重标志WS并放WS在内存中，通过不断对每类关键数据的频率与权重的乘积取平均，得到关键数据不断变化的优先级。
关键数据的优先级计算出来后，系统根据关键数据优先级定时推送数据到客户端，进行可视化数据显示，通过点击告警点，弹出告警信息追溯界面， 对该告警信息的数据进行还原显示。
关键数据推送过程，如图4所示，包括如下步骤：
步骤401：系统启动时，开启一个关键数据推送线程；
步骤402：线程定时轮询检测存储区(例如关键数据内存区与redis数据库)是否存在关键数据，若是则执行步骤403，若否，继续检测；
步骤403：对关键数据安装优先级进行排序，同时定时对关键数据按照优先级由高到低向客户端进行推送；
步骤404：对推送后的关键数据的优先级进行置位。
实施例二：
如图5所示，本实施例提供了一种关键数据显示方法，包括如下步骤：
步骤501：利用实施例一所述的关键数据处理方法发送关键数据至客户端。
步骤502：所述客户端确定所述关键数据对应的关键数据级别。
可选地，可以根据关键数据值来确定与之对应的级别，例如在根据平均值设置关键数据优先级的情况下，可以关键数据对应的平均值(比如实施例一种的Pra)来确定与之对应的级别。
步骤503：根据确定的关键数据级别对所述关键数据进行可视化数据显示。
在确定关键数据的级别之后，可以根据不同的级别采用不同的显示方式来显示关键数据，例如不同级别对应不同显示颜色，或者对应显示窗口形状等。
可选地，本实施例方法还可以对关键数据进行回溯，追踪关键数据的形成过程并以图形化方式进行展示。
例如在处理端根据平均值(Pra)设置优先级的情况下，本实施例的展示方式可以为：以时间为X轴，Pra为Y轴，通过线图方式展示Pra计算的完整过程，也就是图形化展示Pra的形成过程。
实施例三：
如图6所示，本实施例提供了一种关键数据处理装置，包括：识别模块、设置模块和发送模块；
所述识别模块，设置为对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据；
所述设置模块，设置为当所述识别模块识别有关键数据时，设置所述关键数据的优先级；
所述发送模块，设置为根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据。
可选地，如图7所示，本实施例装置还包括：加载模块，其中所述识别模块包括：解析模块和关键数据识别模块，其中：
所述加载模块，设置为在复杂事件处理的初始化阶段，加载关键数据模型配置文件和关键数据权重配置文件；
所述解析模块，设置为对所述关键数据模型配置文件进行解析获取关键数据模型标志，对所述关键数据权重文件进行解析获取关键数据权重标志；
所述关键数据识别模块，设置为根据关键数据模型标志和关键数据权重标志对数据进行关键数据识别。
可选地，如图8所示，本实施例装置中所述设置模块包括：频率获取模块和优先级设置模块，其中：
所述频率获取模块，设置为确定所述关键数据的类型，获取确定类型的关键数据出现的频率，所述频率包括：当前频率和历史频率；
所述优先级设置模块，设置为根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级。
可选地，所述优先级设置模块是设置为：
获取所述频率与所述关键数据权重乘积的平均值；
根据所述平均值设置所述关键数据的优先级。
本实施例提供的关键数据处理装置可以实现对复杂事件处理的数据可视化显示。
如图9所示，本实施例还提供了一种关键数据显示系统，包括客户端和如图6-8任一所述的关键数据处理装置；
所述客户端，设置为：
接收所述关键数据显示装置发送的关键数据；
确定所述关键数据对应的关键数据级别，根据确定的关键数据级别对所述关键数据进行可视化数据显示。
本领域普通技术人员可以理解上述方法中的全部或部分步骤可通过程序来指令相关硬件完成，上述程序可以存储于计算机可读存储介质中，如只读存储器、磁盘或光盘等。可选地，上述实施例的全部或部分步骤也可以使用一个或多个集成电路来实现。相应地，上述实施例中的各模块/单元可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。本发明不限制于任何特定形式的硬件和软件的结合。
工业实用性
应用本发明实施例方案可以实现复杂事件处理中关键数据的可视化，且可通过关键数据优先级的设置将重要的关键数据提前发送给客户端显示。

Claims (16)

  1. 一种关键数据处理方法，包括如下步骤：
    对复杂事件处理过程中的数据进行关键数据识别，所述数据包括：原始数据和/或复杂事件处理后的数据；
    当识别有关键数据时，设置所述关键数据的优先级；
    根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据。
  2. 如权利要求1所述的方法，其中，所述对数据进行关键数据识别的步骤包括：
    获取关键数据模型标志和关键数据权重标志；
    根据关键数据模型标志和关键数据权重标志对数据进行关键数据识别。
  3. 如权利要求2所述的方法，在所述对复杂事件处理过程中的数据进行关键数据识别之前，所述方法还包括：
    在复杂事件处理的初始化阶段，加载关键数据模型配置文件和关键数据权重配置文件；
    所述获取关键数据模型标志和关键数据权重标志的步骤包括：
    对所述关键数据模型配置文件进行解析获取关键数据模型标志，对所述关键数据权重文件进行解析获取关键数据权重标志。
  4. 如权利要求3所述的方法，其中，所述设置所述关键数据的优先级的步骤包括：
    确定所述关键数据的类型，获取确定类型的关键数据出现的频率，所述频率包括：当前频率和历史频率；
    根据所述频率设置所述关键数据的优先级。
  5. 如权利要求4所述的方法，其中，所述获取确定类型的关键数据出现的频率的步骤包括：
    获取确定类型的关键数据出现的历史频率；
    根据关键数据模型标志和所述历史频率计算出确定类型的关键数据出现的当前频率。
  6. 如权利要求4所述的方法，其中，所述根据所述频率设置所述关键数据的优先级的步骤包括：
    根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级。
  7. 如权利要求6所述的方法，在加载关键数据模型配置文件和关键数据权重配置文件之后，根据所述频率设置所述关键数据的优先级之前，所述方法还包括：计算每个类型的关键数据对应的关键数据权重。
  8. 如权利要求7所述的方法，其中，所述计算每个类型的关键数据对应的关键数据权重的步骤包括：
    分别将每个类型的关键数据对应的初始关键数据权重占总权重的比例作为每个类型的关键数据对应的关键数据权重，所述总权重为所有类型的关键数据对应的初始关键数据权重之和。
  9. 如权利要求6-8任一项所述的方法，其中，所述根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级的步骤包括：
    获取所述频率与所述关键数据权重乘积的平均值；
    根据所述平均值设置所述关键数据的优先级。
  10. 一种关键数据显示方法，包括如下步骤：
    利用如权利要求1-9任一项所述的关键数据处理方法发送关键数据至客户端；
    所述客户端确定所述关键数据对应的关键数据级别；
    根据确定的关键数据级别对所述关键数据进行可视化数据显示。
  11. 一种关键数据处理装置，包括：识别模块、设置模块和发送模块，其中：
    所述识别模块，设置为对复杂事件处理过程中的数据进行关键数据识别， 所述数据包括：原始数据和/或复杂事件处理后的数据；
    所述设置模块，设置为当所述识别模块识别有关键数据时，设置所述关键数据的优先级；
    所述发送模块，设置为根据所述关键数据的优先级将所述关键数据发送至客户端，以供所述客户端显示所述关键数据。
  12. 如权利要求11所述的装置，所述装置还包括：加载模块，所述识别模块包括：解析模块和关键数据识别模块，其中：
    所述加载模块，设置为在复杂事件处理的初始化阶段，加载关键数据模型配置文件和关键数据权重配置文件；
    所述解析模块，设置为对所述关键数据模型配置文件进行解析获取关键数据模型标志，对所述关键数据权重文件进行解析获取关键数据权重标志；
    所述关键数据识别模块，设置为根据关键数据模型标志和关键数据权重标志对数据进行关键数据识别。
  13. 如权利要求10所述的装置，所述设置模块包括：频率获取模块和优先级设置模块，其中：
    所述频率获取模块，设置为确定所述关键数据的类型，获取确定类型的关键数据出现的频率，所述频率包括：当前频率和历史频率；
    所述优先级设置模块，设置为根据所述频率和所述确定类型的关键数据对应的关键数据权重设置所述关键数据的优先级。
  14. 如权利要求11所述的装置，所述优先级设置模块是设置为：
    获取所述频率与所述关键数据权重乘积的平均值；
    根据所述平均值设置所述关键数据的优先级。
  15. 一种关键数据显示系统，包括：客户端和如权利要求11-14任一项所述的关键数据显示装置；
    所述客户端，设置为：
    接收所述关键数据显示装置发送的关键数据；
    确定所述关键数据对应的关键数据级别，根据确定的关键数据级别对所 述关键数据进行可视化数据显示。
  16. 一种计算机可读存储介质，存储有程序指令，当该程序指令被执行时可实现权利要求1-9任一项所述的方法。
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