Workflow data processing method and device, storage medium and program product

Abstract

The embodiment of the invention provides a workflow data processing method and device, a storage medium and a program product, and the workflow data processing method comprises the steps: collecting and storing workflow data in a database at a preset collection frequency, the workflow data comprising multiple pieces of business process information corresponding to multiple process instances; after the workflow data are preprocessed, the workflow data conforming to the field logic relation are obtained, and flow index data of each time period of the workflow data are calculated at a preset calculation frequency; and comparing the process index data with an index threshold value, and generating an early warning result of the workflow data based on a size relationship between the process index data and the index threshold value. According to the workflow data processing method provided by the embodiment of the invention, accurate analysis and early warning of each service can be realized, so that the situation of service delay is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a workflow data processing method and device, a storage medium and a program product. BACKGROUND

[0002] In the process of enterprise operation, the business process is usually more and more complex, therefore, the enterprise usually uses a workflow management system to manage and monitor the business process. Flowable as a popular workflow engine provides certain management functions, but lacks monitoring functions for specific businesses. For example, the Flowable workflow system can only display and monitor the current process state and process instance of the business, and cannot realize deep analysis and early warning of business indicators of a certain type of business, which is easy to cause delay of part of the business and cause loss. SUMMARY

[0003] The embodiments of the present application aim to provide a workflow data processing method, device, storage medium and program product to solve the above problems.

[0004] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a workflow data processing method, comprising: collecting and storing workflow data in a database at a preset collection frequency, the workflow data comprising a plurality of pieces of business process information corresponding to a plurality of process instances; after preprocessing the workflow data, obtaining the workflow data conforming to the field logical relationship, calculating the process indicator data of each time period of the workflow data at a preset calculation frequency; comparing the process indicator data with the indicator threshold value, and generating an early warning result of the workflow data based on the size relationship between the process indicator data and the indicator threshold value.

[0005] In the embodiments of the present application, the step of preprocessing the workflow data comprises: detecting and eliminating duplicate data in the workflow data; traversing the workflow data after eliminating the duplicate data, filling the missing fields in the workflow data; after filling the missing fields, checking the field logical relationship in each piece of business process information in the workflow data, and adjusting the abnormal fields to obtain the preprocessed workflow data.

[0006] In the embodiments of the present application, the field logical relationship includes time sequence logic, state conversion logic, data correlation logic, and business rule logic, and the step of checking the field logical relationship in each piece of business process information in the workflow data and adjusting the field with a checking exception comprises: checking the time sequence logic and / or the state conversion logic and / or the data correlation logic and / or the business rule logic of the field in each piece of business process information in the workflow data, and when the field in the business process information does not satisfy any one of the logical relationships, adjusting the field with an exception to a state conforming to the corresponding logical relationship based on the logical relationship corresponding to the field with an exception.

[0007] In the embodiments of the present application, the step of preprocessing the workflow data further comprises: after removing the duplicate data, formatting the workflow data.

[0008] In the embodiments of the present application, the step of filling the missing field in the workflow data comprises: traversing each piece of business process information in the workflow data, marking the missing field in the business process information and generating missing information; and in response to the instruction of filling the missing field, filling the missing field in each piece of business process information based on the missing information.

[0009] In the embodiments of the present application, the process indicator data is the average processing time of the completed process instances, the task timeout rate, and the link transfer rate, and the step of calculating the process indicator data of each time period of the workflow data at a preset calculation frequency comprises: screening the business process information corresponding to the process instances in the completed state from the preprocessed workflow data; calculating the average processing time of all the completed process instances; traversing all the tasks in each piece of business process information to calculate the processing time of each task; judging whether the processing time of each task exceeds the task time threshold value, and calculating the task timeout rate based on the number of tasks exceeding the timeout and the total number of tasks; and based on each piece of business process information, detecting the process link state in each process instance; based on the process link state of each process instance and the number of process instances, calculating the link transfer rate of each process link.

[0010] In the embodiments of the present application, after obtaining the process indicator data, the workflow data processing method further comprises: comparing the process indicator data with a preset process indicator threshold value, generating early warning information of the process instance when the process indicator data corresponding to any process instance is less than the process indicator threshold value; and in response to the early warning information, associating the process indicator data of the corresponding process instance with the early warning information.

[0011] In the embodiments of the present application, the preset collection frequency is obtained based on the following steps: obtaining historical data of each piece of business process information in the workflow data; determining a historical update frequency of each piece of business process information based on the historical data; determining a preset collection frequency of each piece of business process information based on the historical update frequency, and collecting the corresponding business process information in the workflow data at the preset collection frequency.

[0012] In the embodiments of the present application, the step of collecting and storing the workflow data in the database at the preset collection frequency comprises: collecting and storing the workflow data in the database at the preset collection frequency when no new workflow data is detected to be received in the database; and after the last workflow data collection is completed, detecting that at least one piece of new workflow data is received in the database, and generating a collection instruction; in response to the collection instruction, collecting the newly added workflow data.

[0013] In the embodiments of the present application, after the warning result of the workflow data is generated, the workflow data processing method further comprises: generating process state information of each corresponding process instance based on the warning result and the business process information, the process state information comprising a completion state of the corresponding process instance and a current process link; and generating a query interface of each process instance based on the warning result, the business process information and the process state information.

[0014] In the embodiments of the present application, each piece of business process information comprises a process field, a task field and a user field, the process field comprising a process ID, a process name, a process start time, a process end time and a process state, the task field comprising a task ID, a task name, a task start time, a task end time, a task handler and a task state, and the user field comprising user identity information.

[0015] The second aspect of the present application provides an electronic device, comprising a processor and a memory, the memory storing instructions; the processor invokes the instructions in the memory to enable the electronic device to implement the workflow data processing method of any of the above-mentioned embodiments of the first aspect of the present application.

[0016] The third aspect of the present application provides a machine-readable storage medium, the machine-readable storage medium storing instructions, the instructions being executed by a processor to configure the processor to perform the workflow data processing method of any of the above-mentioned embodiments of the first aspect of the present application.

[0017] The fourth aspect of the present application provides a computer program product, comprising a computer program, the computer program being executed by a processor to implement the workflow data processing method of any of the above-mentioned embodiments of the first aspect of the present application.

[0018] Through the technical solution, the process instances of different services can be monitored and analyzed in real time, accurate analysis and early warning of each service are realized, and service delay is avoided.

[0019] Other features and advantages of the embodiments of the present application will be described in detail in the following specific implementation part. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings are included to provide a further understanding of the embodiments of the present application, and constitute a part of the specification, and are used to explain the embodiments of the present application together with the following specific implementation, but do not constitute the limitation to the embodiments of the present application. In the drawings: Figure 1 The application environment schematic diagram of the workflow data processing method according to the first embodiment of the present application is schematically shown; Figure 2 The flow schematic diagram of the workflow data processing method according to the first embodiment of the present application is schematically shown; Figure 3 The flow schematic diagram of the step of acquiring the preset acquisition frequency in step S110 in the workflow data processing method according to the first embodiment of the present application is schematically shown; Figure 4 The flow schematic diagram of the step of acquiring the workflow data in step S110 in the workflow data processing method according to the first embodiment of the present application is schematically shown; Figure 5 The flow schematic diagram of step S120 in the workflow data processing method according to the first embodiment of the present application is schematically shown; Figure 6 The flow schematic diagram of step S122 in the workflow data processing method according to the first embodiment of the present application is schematically shown; Figure 7 The flow schematic diagram of the workflow data processing method according to the second embodiment of the present application is schematically shown; Figure 8 The internal structure diagram of the computer device according to the embodiments of the present application is schematically shown. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiments of the present application, and is not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0022] It should be noted that if the application embodiments involve directionality indication (such as up, down, left, right, front, back, etc.), the directionality indication is only used to explain the relative position relationship, motion condition, etc. between components in a certain posture (as shown in the drawings), and if the certain posture changes, the directionality indication also changes accordingly.

[0023] In addition, if the application embodiments involve descriptions such as "first", "second", etc., the descriptions of "first", "second", etc. are only for description purposes and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include at least one of the features. In addition, the technical solutions of various embodiments can be combined with each other, but must be based on the realization of ordinary skilled persons in the art, and when the combination of technical solutions contradicts each other or cannot be realized, it should be considered that the combination of technical solutions does not exist and is not within the protection scope required by the application.

[0024] The acquisition, transmission, storage, use, processing, etc. of data in the technical solutions of the application comply with the relevant provisions of laws and regulations. In addition, it should be noted that in the embodiments of the application, some industry existing solutions, components, models, etc. may be mentioned, which should be considered as exemplary, and the purpose is only to illustrate the feasibility of the implementation of the technical solutions of the application, but it does not mean that the applicant has or will necessarily use the solution.

[0025] The workflow data processing method provided by the application can be applied to an application environment as shown in Figure 1 . Among them, the terminal 110 communicates with the server 120 through the network to realize the workflow data processing method of the application embodiment. Among them, the terminal 110 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices, and the server 120 can be realized by an independent server or a server cluster composed of multiple servers.

[0026] As shown in Figure 2 , in the embodiments of the application, a workflow data processing method is provided, and the embodiments mainly take the method applied to the server 120 in the above Figure 1 or as an example to illustrate the workflow data processing method, which includes steps S110 to S130.

[0027] In step S110, the workflow data in the database is collected and stored at a preset collection frequency. Among them, the workflow data includes a plurality of pieces of business process information corresponding to a plurality of process instances.

[0028] As shown in Figure 3As shown, in this embodiment, step S110 includes steps S111 to S113.

[0029] In step S111, historical data of each business process information in the workflow data is obtained.

[0030] In step S112, the historical update frequency of each business process information is determined based on historical data.

[0031] In step S113, based on the historical update frequency, a preset collection frequency for each business process information is determined, and the corresponding business process information in the workflow data is collected at the preset collection frequency.

[0032] In this embodiment, when the real-time traffic of business process information of workflow data is not confirmed, a preset collection frequency is obtained by confirming its historical update frequency to ensure the real-time nature of the business process information when collecting it.

[0033] like Figure 4 As shown, step S110 further includes steps S114 to S116.

[0034] In step S114, when no new workflow data is detected in the database, workflow data in the database is collected and stored at a preset collection frequency.

[0035] In step S115, when at least one new workflow data entry is detected in the database after the previous workflow data acquisition is completed, an acquisition command is generated.

[0036] In step S116, in response to the acquisition command, newly added workflow data is acquired.

[0037] In this embodiment, taking the workflow engine of the Flowable database as an example, workflow data is extracted from the Flowable database at predetermined time intervals (e.g., every 5 minutes) and stored in a local cache database or data warehouse.

[0038] The workflow data processing method in this application combines incremental query and timed query to collect workflow data. Incremental query refers to collecting only the data updated since the last collection, so as to reduce the repeated data transmission and processing, reduce redundant data, and speed up data processing.

[0039] For example, when data in a Flowable workflow is updated, the Flowable workflow engine's message queue generates update information. When the update information detects that new workflow data has been updated in the database, the updated workflow data is collected.

[0040] Specifically, each piece of business process information of the embodiment of the present application comprises a process field, a task field and a user field, the process field comprises a process ID, a process name, a process start time, a process end time and a process state, the task field comprises a task ID, a task name, a task start time, a task end time, a task handler and a task state, and the user field comprises user identity information.

[0041] By means of the historical data and real-time flow of the workflow data, the frequency and range of data collection are adjusted, for example, for a key process node with high-frequency update, the collection frequency is increased to ensure the real-time nature of the data; and for a node with low-frequency update, the collection frequency is reduced to optimize the resource utilization.

[0042] In step S120, after the workflow data is preprocessed, the workflow data conforming to the field logical relationship is acquired, and the process indicator data of each time period of the workflow data is calculated at a preset calculation frequency.

[0043] In the embodiment, after the workflow data is collected, the workflow data is cleaned and preprocessed to remove invalid data and repeated data therein, so as to ensure the accuracy and integrity of the data, and the specific steps of cleaning and preprocessing the workflow data are described as follows.

[0044] As shown in FIG. 1, Figure 5 In some optional embodiments, step S120 comprises steps S121 to S123.

[0045] In step S121, the repeated data in the workflow data is detected and removed.

[0046] Further, after the repeated data is removed, the workflow data is formatted.

[0047] Specifically, when the data is collected, firstly, the primary keys or identifiers (such as process instance IDs, task IDs, etc.) corresponding to the process field, the task field and the user field in the data table of the workflow data are checked, and then the workflow data is de-duplicated by means of a SQL query statement or a data processing tool (such as Apache Spark).

[0048] For example, for the workflow data, the following SQL query statement can be used for de-duplication: SELECT DISTINCT process_instance_id, process_instance_name, start_time, end_time; FROM process_instances; After the workflow data is de-duplicated, the missing fields therein need to be filled, and the steps are as follows.

[0049] In step S122, the repeated data removed workflow data is traversed to fill the missing fields in the workflow data.

[0050] As shown in Figure 6 Further, step S122 includes steps S1221 to S1222.

[0051] In step S1221, each piece of business process information in the workflow data is traversed to mark the missing fields in the business process information and generate missing information.

[0052] In step S1222, in response to the instruction to fill the missing fields, the missing fields in each piece of business process information are filled based on the missing information.

[0053] In this embodiment, when filling the missing fields in the workflow data, first check whether the field formats in the workflow data are consistent, such as the date and time format of the date field, the numerical value format of the numerical value field, etc. Take the date field as an example, for the inconsistent date field, the format of all date fields can be adjusted to the following format: YYYY-MM-DD HH:MM:SS; or the corresponding field can be formatted, the field is converted to ensure the consistency of the field format.

[0054] After adjusting the formats of all fields to be consistent, each piece of business process information in the data table of the workflow data is traversed to check whether there are missing fields (such as process start time, process end time, user identity information, etc.) in the fields of each corresponding piece of business process information: process field, task field and user field. When a missing field is found, the missing field in the business process information is marked and missing information is generated. The missing information is used to record the missing field marked and sent to the user for processing.

[0055] When receiving the instruction of the user to fill the missing fields, the missing fields in each piece of business process information are filled based on the missing information.

[0056] In step S123, after filling the missing fields, the logical relationship of the fields in each piece of business process information in the workflow data is verified, and the fields with verification exceptions are adjusted to obtain preprocessed workflow data.

[0057] In this embodiment, the logical relationship of the fields includes time sequence logic, state conversion logic, data correlation logic, and business rule logic.

[0058] The step of verifying the logical relationship of the fields in each piece of business process information in the workflow data and adjusting the fields with verification exceptions includes: The time sequence logic and / or state transition logic and / or data association logic and / or business rule logic in each piece of business process information in the verification workflow data is checked, and when the fields in the business process information do not satisfy any logical relationship, the abnormal field is adjusted to a state that meets the corresponding logical relationship based on the logical relationship corresponding to the abnormal field.

[0059] Specifically, after filling in the missing fields, the logical relationship of the filled fields may be incorrect, and the abnormal field is adjusted by checking the logical relationship between the fields to ensure the normality of the workflow data.

[0060] For example, for time sequence logic, the start time of the process should not be later than the end time; the completion time of the task should not be earlier than the start time of the task, and for a task chain with a clear time sequence, task B cannot be started until task A is completed.

[0061] For state transition logic, it is unreasonable for a process instance to jump directly from the "not started" state to the "completed" state, and it must go through the "in progress" state. For a process instance, check whether its state changes in the logical order of "start → execute → complete" or "start → execute → terminate", and for fields that do not meet the logic, confirm them as abnormal fields.

[0062] For data association logic, the association between different data tables needs to be checked for reasonableness, for example, the user ID assigned to a task must exist in the user table, and the creator of a process instance must be a registered user in the system. For business processes involving multiple entities, such as procurement processes involving suppliers, purchase orders, and approvers, verify whether the association between these entities meets the business rules, and for fields that do not meet the logic, confirm them as abnormal fields.

[0063] For business rule logic, the data is verified according to the business rules of each process instance. For example, in the business process of a process instance, the approval amount of a business must be within the specified approval authority range, and the priority of a task needs to be determined according to the task type and urgency. For fields that do not meet the logic of approval amount and priority, confirm them as abnormal fields.

[0064] By checking whether each field is abnormal, marking the fields with abnormal checking results in time, automatically adjusting the fields or notifying the maintenance personnel to adjust the fields, so that the adjusted fields meet the state of the time sequence logic, state transition logic, data correlation logic and business rule logic, and sending the processed workflow data to a relational database (such as MySQL) or a database (such as Hadoop HDFS, Apache Cassandra) for subsequent calling index.

[0065] Further, the flow indicator data of the embodiment is the average processing time of the completed process instances, the task timeout rate and the link transfer rate. After step S123, step S120 further includes the following steps: filtering the business process information corresponding to the process instances in the completed state from the preprocessed workflow data, and calculating the average processing time of all completed process instances; and traversing all tasks in each piece of business process information, calculating the processing time of each task, and then judging whether the processing time of each task exceeds the task time threshold, and calculating the task timeout rate based on the number of timeout tasks and the total number of tasks; and based on each piece of business process information, detecting the process link state in each process instance, and based on the process link state of each process instance and the number of process instances, calculating the link transfer rate of each process link.

[0066] Specifically, the average processing time is calculated by the following steps: filtering the business process information corresponding to the process instances in the completed state from the preprocessed workflow data, According to the business process information of the filtered process instances, the processing time of each process instance is calculated according to the process start time and the process end time of each process instance, and then the average processing time of all process instances is calculated.

[0067] The task timeout rate is calculated by the following steps: Each process instance may include one, two or more tasks. By traversing all tasks in each piece of business process information, the processing time of each task is calculated according to the task end time and the task start time, and the processing time of each task is compared with the task time threshold. When the processing time of the task is less than or equal to the task time threshold, it is judged that the task is not timeout, otherwise the task is timeout The task time threshold can be 24 hours, 48 hours, etc., which is not limited by the present application.

[0068] Then, the task timeout rate of the process instance is calculated according to the total number of tasks and the number of timeout tasks of each process instance.

[0069] The turnover rate of the loop is calculated by the following steps: The turnover path of the process instance is determined, for example, the turnover path of a process instance is: Process A→Process B→Process C. When a process instance successfully turns over from the current loop to the next loop, for example, from Process A to Process B, one turnover occurs.

[0070] The conversion rate of each loop is calculated by counting the number of times that flow into the loop and the number of times that flow out of the loop.

[0071] For example, in a process instance, 100 tasks flow into the loop of Process A, of which 80 tasks successfully turn over to the loop of Process B, so the turnover rate of the loop of Process A is 80%.

[0072] By accurately calculating the above-mentioned key business indicators of workflow data, users can intuitively confirm the running efficiency and abnormal situation of the workflow.

[0073] Further, after obtaining the process indicator data, the workflow data processing method further includes steps S124 and S125.

[0074] In step S124, the process indicator data is compared with the preset process indicator threshold value, and when the process indicator data corresponding to any process instance is less than the process indicator threshold value, an early warning information of the process instance is generated.

[0075] In step S125, in response to the early warning information, the process indicator data of the corresponding process instance is associated with the early warning information.

[0076] In this embodiment, the process indicator data is the threshold value of the corresponding average processing time, task timeout rate, and loop turnover rate, for example, the average processing time threshold of the process instance is: 30 hours; the task timeout rate threshold is: 10%; and the loop conversion rate threshold is: 80%.

[0077] By comparing the process indicator data with the preset process indicator threshold value, when the corresponding process indicator data is found to be abnormal, for example, the average processing time of a process instance suddenly increases significantly to exceed the process indicator threshold value, or the number of task timeouts increases to exceed the process indicator threshold value, an early warning information is generated and sent to the user, so as to timely remind the user to handle the abnormality and avoid greater losses due to business delay.

[0078] In step S130, the process indicator data is compared with the indicator threshold value, and based on the size relationship between the process indicator data and the indicator threshold value, an early warning result of the workflow data is generated.

[0079] In the embodiment, the early warning result includes the corresponding abnormal field of the abnormal process instance, the corresponding abnormal index data (for example, the average processing time, the task timeout rate, and the link transfer rate), and the time of triggering the abnormality.

[0080] The user can confirm the abnormality of the abnormal process instance in time through the early warning result, and locate the abnormal position of the process instance in time according to the early warning result, so as to quickly handle the abnormality.

[0081] The working flow data processing method provided in the embodiment includes: collecting and storing working flow data in a database at a preset collection frequency, the working flow data including a plurality of pieces of business process information corresponding to a plurality of process instances; pre-processing the working flow data, and calculating process index data of each time period of the working flow data at a preset calculation frequency; comparing the process index data with an index threshold value, and generating an early warning result of the working flow data based on a size relationship between the process index data and the index threshold value.

[0082] The working flow data processing method provided in the embodiment can monitor and analyze and calculate the process instances of different businesses in real time, accurately analyze and early warn each business, and avoid business delay.

[0083] Figure 7 A flowchart of a working flow data processing method according to the second embodiment of the application is schematically shown. The second embodiment has some structures same as the first embodiment, and the differences between the two embodiments will be described below, and the same parts will not be described in detail.

[0084] As shown in the figure, Figure 7 In the second embodiment of the application, the working flow data processing method includes steps S210 to S250. Steps S210 to S230 are same as steps S110 to S130 in the first embodiment of the application, and will not be repeated here.

[0085] In step S210, working flow data in a database is collected and stored at a preset collection frequency. The working flow data includes a plurality of pieces of business process information corresponding to a plurality of process instances.

[0086] In step S220, the working flow data is pre-processed, and process index data of each time period of the working flow data is calculated at a preset calculation frequency.

[0087] In step S230, the process index data is compared with an index threshold value, and an early warning result of the working flow data is generated based on a size relationship between the process index data and the index threshold value.

[0088] In step S240, based on the early warning result and the business process information, process state information corresponding to each process instance is generated, and the process state information includes a completion state of the corresponding process instance and a process link currently located.

[0089] In step S250, based on the early warning result, the business process information and the process state information, a query interface of each process instance is generated.

[0090] In the embodiment, the corresponding business process information is obtained from the database, and a visual query interface is generated, so that the user can interact through the query interface, such as selecting a specific process, a time period, viewing task information and process links of the corresponding process instance, etc., to realize query monitoring of the Flowable workflow and help the user quickly understand and obtain the running state of the workflow.

[0091] It should be understood that, although Figure 2 the steps in the flowchart are displayed in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 2 at least part of the steps in the flowchart can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be alternately executed with other steps or at least part of the sub-steps or stages of other steps.

[0092] For the above method embodiment, the embodiment of the application further provides an electronic device, which includes a processor and a memory, and the memory stores instructions; the processor calls the instructions in the memory to enable the electronic device to implement the workflow data processing method of any embodiment of the application.

[0093] The electronic device provided by the embodiment of the application can realize real-time monitoring and analysis calculation of process instances of different businesses by implementing the above method, realize accurate analysis and early warning of each business, and avoid business delay.

[0094] The processor of the electronic device contains a kernel, and the kernel retrieves corresponding program units from the memory. The kernel can be set to one or more, and the kernel parameters are adjusted to implement the workflow data processing method of the above embodiments of the application.

[0095] The memory can include non-persistent memory in a computer readable medium, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory, and the memory includes at least one memory chip.

[0096] The embodiment of the present application also provides a machine readable storage medium, which stores a program, and the program is executed by a processor to implement the workflow data processing method of the above embodiment.

[0097] Specifically, the electronic device of the embodiment of the present application can be a computer device, which can be a server, and the internal structure diagram thereof can be as shown in the figure. Figure 8 When the computer device is deployed, first, parameter configuration is performed, including relevant information of connecting the Flowable workflow database, such as database address, username, password, user permission, etc., so that the workflow data processing system is deployed in the computer device and is initialized. When a user logs in the workflow data processing system, first, the identity of the user is verified, and then according to the user identity and the permission, the corresponding user interface and operation menu are dynamically generated.

[0098] The computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected through a system bus. The processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operating system B01 and the computer program B02 in the non-volatile storage medium A04 to run. The database of the computer device is used to store a program capable of executing the workflow data processing method of the embodiment of the present application. The network interface A02 of the computer device is used to communicate with the external terminal through network connection. The computer program B02 is executed by the processor A01 to implement a workflow data processing method of the above embodiment.

[0099] Those skilled in the art can understand that, Figure 8 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0100] In one embodiment, the workflow data processing method of the embodiment of the present application can also be implemented in the form of a computer program, which can be executed in a computer device such as Figure 7The computer program product is run on the computer device shown. The memory of the computer device can store various program modules for implementing the workflow data processing method of the embodiments of the present application, and the computer program composed of the various program modules can enable the processor to execute the steps in the workflow data processing method of the various embodiments of the present application described in the specification.

[0101] The present application also provides a computer program product adapted to execute the program of the following method steps when executed on a data processing device: In step S110, the workflow data in the database is collected and stored at a preset collection frequency. The workflow data includes a plurality of pieces of business process information corresponding to a plurality of process instances.

[0102] In step S120, after preprocessing the workflow data, the process indicator data of each time period of the workflow data is calculated at a preset calculation frequency.

[0103] In step S130, the process indicator data is compared with the indicator threshold value, and based on the size relationship between the process indicator data and the indicator threshold value, an early warning result of the workflow data is generated.

[0104] The computer program product provided by the embodiments of the present application can realize real-time monitoring and analysis calculation on the process instances of different businesses by implementing the above method, and realizes accurate analysis and early warning on each business to avoid business delay.

[0105] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0106] The present application is described with reference to the flowcharts and / or block diagrams according to the method, device (system), and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The device for implementing the functions specified in one flow or multiple flows and / or blocks. Figure 1 The device for implementing the functions specified in one flow or multiple flows and / or blocks.

[0107] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that are executed on the computer or other programmable apparatus provide steps for implementing the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0109] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0110] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) about which the computer stores information such as computer program instructions. Memory is an example of computer readable media. A computer can further include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory, or non-volatile random access memory (NVRAM) about which the computer stores information, such as computer program instructions. Thus, computer readable media

[0111] Computer readable media includes permanent and non-permanent, moveable and non- moveable media that can be implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that is accessible to a computing device. According to the definition provided herein, computer readable media excludes transitory media, such as modulated data signals and carrier waves.

[0112] It should also be noted that the terms "comprising", "comprises", "including", "includes" or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0113] The above embodiments of the present application are only used to illustrate the technical solutions of the present application, and not intended to limit the present application. Although the present application has been described in detail, it should be understood that those skilled in the art can make various modifications and changes without departing from the spirit and scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

Claims

1. A workflow data processing method, characterized by, Comprise: Collect and store workflow data in the database at a preset collection frequency, the workflow data comprising a plurality of pieces of business process information corresponding to a plurality of process instances; After preprocessing the workflow data, obtain the workflow data that meets the field logical relationship, and calculate the process indicator data of each time period of the workflow data at a preset calculation frequency; Compare the process indicator data with the indicator threshold value, and generate an early warning result of the workflow data based on the size relationship between the process indicator data and the indicator threshold value.

2. The workflow data processing method of claim 1, wherein, The preprocessing step of the workflow data comprises: Detect and remove duplicate data in the workflow data; Iterate through the workflow data after removing duplicate data, and fill in missing fields in the workflow data; After filling in the missing fields, check the field logical relationship in each piece of business process information in the workflow data, and adjust the abnormal fields to obtain the preprocessed workflow data.

3. The workflow data processing method of claim 2, wherein, The field logical relationship includes time sequence logic, state transition logic, data correlation logic, and business rule logic, and the step of checking the field logical relationship in each piece of business process information in the workflow data and adjusting the abnormal fields comprises: Check the time sequence logic and / or the state transition logic and / or the data correlation logic and / or the business rule logic of the fields in each piece of business process information in the workflow data, and when the fields in the business process information do not meet any one of the logical relationships, adjust the abnormal fields to meet the corresponding logical relationship based on the logical relationship corresponding to the abnormal field.

4. The workflow data processing method of claim 2, wherein, The preprocessing step of the workflow data further comprises: After removing duplicate data, format the workflow data.

5. The workflow data processing method of claim 2, wherein, The step of filling in the missing fields in the workflow data comprises: Iterate through each piece of business process information in the workflow data, mark the missing fields in the business process information, and generate missing information; In response to the instruction to fill in the missing fields, fill in the missing fields in each piece of business process information based on the missing information.

6. The workflow data processing method of claim 1, wherein, The process indicator data is the average processing time of completed process instances, the task timeout rate, and the link flow rate, and the step of calculating the process indicator data of each time period of the workflow data at a preset calculation frequency comprises: Filter the business process information corresponding to the process instances in the completed state from the preprocessed workflow data; Calculate the average processing time of all completed process instances; and Iterate through all tasks in each piece of business process information to calculate the processing time of each task; Determine whether the processing time of each task exceeds the task time threshold value, and calculate the task timeout rate based on the number of overdue tasks and the total number of tasks; and Detect the process link state in each process instance based on each piece of business process information; Calculate the link flow rate of each process link based on the process link state of each process instance and the number of process instances.

7. The workflow data processing method of claim 1, wherein, After obtaining the process indicator data, the workflow data processing method further comprises: The process indicator data is compared with a preset process indicator threshold value, and when the process indicator data corresponding to any process instance is less than the process indicator threshold value, early warning information of the process instance is generated; In response to the early warning information, the process indicator data of the corresponding process instance is associated with the early warning information.

8. The workflow data processing method of claim 1, wherein, The preset collection frequency is obtained based on the following steps: Obtain historical data of each piece of business process information in the workflow data; Based on the historical data, determine the historical update frequency of each piece of business process information; Based on the historical update frequency, determine the preset collection frequency of each piece of business process information, and collect the corresponding business process information in the workflow data at the preset collection frequency.

9. The workflow data processing method of claim 1, wherein, The step of collecting and storing the workflow data in the database at the preset collection frequency includes: When no new workflow data is detected in the database, collect and store the workflow data in the database at the preset collection frequency; and After the last workflow data collection is completed, when at least one new piece of workflow data is detected in the database, a collection instruction is generated; In response to the collection instruction, the newly added workflow data is collected.

10. The workflow data processing method of claim 1, wherein, After the early warning result of the workflow data is generated, the workflow data processing method further includes: Based on the early warning result and the business process information, generate process state information of each corresponding process instance, the process state information including the completion state of the corresponding process instance and the current process link; and Based on the early warning result, the business process information and the process state information, generate a query interface of each process instance.

11. The workflow data processing method of claim 1, wherein, Each piece of business process information includes a process field, a task field and a user field, The process field includes process ID, process name, process start time, process end time, and process state, The task field includes task ID, task name, task start time, task end time, task handler, and task state, The user field includes user identity information.

12. An electronic device, comprising: The electronic device includes a processor and a memory, and the memory stores instructions; The processor invokes the instructions in the memory to enable the electronic device to implement the workflow data processing method according to any one of claims 1 to 11.

13. A machine-readable storage medium having stored thereon instructions, the instructions being executable by a machine to cause the machine to: The instructions, when executed by the processor, cause the processor to be configured to perform the workflow data processing method according to any one of claims 1 to 11.

14. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the workflow data processing method according to any one of claims 1 to 11.

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