CN115422151A

CN115422151A - Data life cycle management method and device, computer equipment and storage medium

Info

Publication number: CN115422151A
Application number: CN202210984401.XA
Authority: CN
Inventors: 张瑞祥; 谢云龙; 顾锋
Original assignee: Weizheng Technology Service Co ltd
Current assignee: Weizheng Technology Service Co ltd
Priority date: 2022-08-17
Filing date: 2022-08-17
Publication date: 2022-12-02

Abstract

The application discloses a management method and a device of a data life cycle, computer equipment and a storage medium, wherein the management method of the data life cycle is realized by applying a primary state machine, and the primary state machine comprises at least two primary life nodes in the life cycle of the data life cycle; the data management method comprises the following steps: acquiring at least two logic period management lines, wherein each logic period management line comprises at least two event state nodes and a primary trigger event; acquiring a secondary state machine and a secondary trigger event; and if the secondary life node corresponding to any event state node triggers the corresponding primary trigger event and/or secondary trigger event as a target trigger event, performing associated data management on node data on all target state nodes. The method can efficiently realize data updating of each scene, effectively improve the efficiency of big data management, and realize high management predictability of event state nodes.

Description

Data life cycle management method and device, computer equipment and storage medium

Technical Field

The invention relates to the technical field of big data application, in particular to a method and a device for managing a data life cycle, computer equipment and a storage medium.

Background

Data Life Cycle Management (DLM), a policy-based method for managing the flow of Data of an information system throughout its Life Cycle, is: from creation and initial storage, to its obsolescence is deleted. The maturity level requirements of data acquisition safety, data transmission safety, data storage safety, data processing safety, data exchange safety, data destruction safety and general safety are also stipulated in an information security technology-data security capability maturity model (GB/T37988-2019) as a published and implemented national standard.

If all data owned by an enterprise are compared to one iceberg, the enterprise is really put into use, and the data volume for realizing value mining is only one corner of the iceberg. The existing enterprises have 73% of data which are hardly utilized. Data scientists and authoritative experts, vkkor meier schenberg, indicated in their big data age that although big data has not yet been listed in the corporate balance sheet, this is only a time issue. As data grows explosively, more and more businesses recognize the importance of data as data assets. Data is not equal to data assets, however, and must be organized in a reasonable, easy-to-use, secure, and easy-to-understand manner to inject significant value as data assets for a business. How to efficiently coil the value of mass data and realize the flow of data assets becomes a problem to be solved urgently.

Disclosure of Invention

The embodiment of the invention provides a method and a device for managing a data life cycle, computer equipment and a storage medium, which are used for solving the problems of efficiently recording the value of mass data and realizing the data capitalization and flowing.

A management method of a data life cycle is realized by applying a primary state machine, wherein the primary state machine comprises at least two primary life nodes which are sequenced in sequence according to the life cycle of the data life cycle; the management method of the data life cycle comprises the following steps:

acquiring at least two logic period management lines, wherein each logic period management line comprises at least two event state nodes positioned at different first-level life nodes and a first-level trigger event between every two event state nodes;

acquiring a corresponding secondary state machine in each primary life node based on all event state nodes and primary trigger events, wherein the secondary state machine comprises at least two secondary life nodes and a secondary trigger event between every two secondary life nodes;

and if the secondary life node corresponding to any event state node is used as an initial node to trigger the corresponding primary trigger event and/or the secondary trigger event is used as a target trigger event, performing data management on node data on all target state nodes related to the initial node and the target trigger event.

Further, based on all event state nodes and primary trigger events, acquiring a corresponding secondary state machine in each primary life node, including:

merging the same first-stage trigger events, and merging event state nodes in each first-stage life node according to the reverse order with the same number of metadata to form a second-stage life node;

and performing logic analysis on all secondary life nodes in each primary life node to obtain a secondary trigger event between every two secondary life nodes, and forming a secondary state machine corresponding to each primary life node.

Further, merging event state nodes in each primary life node in a reverse order of the number of the primary life nodes with the same metadata to form a secondary life node, comprising:

acquiring each event state node included in the first-level life node as all metadata included in the node to be merged;

at least two nodes to be merged with the same amount of metadata are merged in a reverse order to form a merged life node;

all the same metadata are used as shared management data of the merged life node, and the metadata which is individually held by each node to be merged is used as specific management data corresponding to a certain logic period management line.

Further, the secondary life node comprises shared management data and specific management data; after obtaining the corresponding secondary state machine in each primary life node, the method further comprises:

acquiring a logic management line adding request, wherein the logic management line adding request comprises at least two newly added state nodes of different first-stage life nodes and a first-stage newly added trigger event between every two newly added state nodes;

determining whether a primary newly-added trigger event exists based on the primary trigger event;

if a first-stage newly-added trigger event exists, acquiring two second-stage life nodes corresponding to the first-stage newly-added trigger event, and continuously determining shared management data and specific management data in nodes in a newly-added state;

and if the first-stage newly-added trigger event does not exist, newly adding the first-stage newly-added trigger event to the first-stage state machine as the first-stage trigger event, and continuously determining the shared management data and the specific management data in the newly-added state nodes.

Further, the logical cycle management line includes a cycle management line ID; the secondary life nodes comprise shared management data and specific management data;

after obtaining the corresponding secondary state machine in each primary life node, the method further comprises the following steps:

acquiring a logic management line deleting request carrying a periodic management line ID;

acquiring all related event state nodes as to-be-processed state nodes based on the periodic management line ID;

if the node of the state to be processed is a leaf node and only one primary trigger event corresponding to the periodic management line ID exists in the node of the state to be processed as a target deletion event, directly deleting the node of the state to be processed and the target deletion event;

if the node in the state to be processed is a second-level life node and the number of application logic management lines of the second-level life node is more than 2, deleting specific management data of the period management line ID on the node in the state to be processed;

and if the node in the state to be processed is a second-stage life node and the number of the application logic management lines of the second-stage life node is equal to 2, deleting the specific management data corresponding to the periodic management line ID on the node in the state to be processed, combining the shared management data and the rest of the specific management data of the second-stage life node into node data corresponding to the second-stage life node, and unbinding the node in the state to be processed into an intermediate node or a leaf node.

Further, if any event state node is used as an initial node to trigger a primary trigger event and/or a secondary trigger event corresponding to the initial node as a target trigger event, performing data management on node data on all event state nodes related to the initial node and the target trigger event, including:

if any event state node is used as an initial node to trigger a corresponding primary trigger event and/or a corresponding secondary trigger event as a target trigger event, acquiring an event state node pointed by the target trigger event as a target node, synchronizing node data corresponding to the initial node and the target node according to a time sequence of a secondary state machine and/or a primary state machine, and acquiring a synchronization result;

if any synchronization result causes any primary trigger event and/or secondary trigger event, the step of triggering the corresponding primary trigger event and/or secondary trigger event as the target trigger event by using any event state node as the starting node is repeatedly executed until the final synchronization result does not cause any primary trigger event and/or secondary trigger event any more.

Further, after performing data management on node data on all target state nodes related to the starting node and the target trigger event, the method further comprises the following steps:

acquiring a timing task comprising an activation task time;

when the current time of the system meets the time of activating the task, respectively drawing a primary logic thermodynamic diagram and a secondary logic thermodynamic diagram based on the triggering times of a primary triggering event and a secondary triggering event which are respectively triggered on each logic period management line, and analyzing the activity degrees of all event state nodes.

An apparatus for managing a data lifecycle, comprising:

the system comprises an acquisition cycle management line module, a storage module and a processing module, wherein the acquisition cycle management line module is used for acquiring at least two logic cycle management lines, and each logic cycle management line comprises at least two event state nodes positioned at different first-stage life nodes and a first-stage trigger event between every two event state nodes;

the acquisition secondary state machine module is used for acquiring a corresponding secondary state machine in each primary life node based on all event state nodes and primary trigger events, and the secondary state machine comprises at least two secondary life nodes and a secondary trigger event between every two secondary life nodes;

and the management associated data module is used for carrying out data management on node data on all target state nodes related to the starting node and the target trigger event if a secondary life node corresponding to any event state node is used as the starting node to trigger a corresponding primary trigger event and/or a secondary trigger event as the target trigger event.

A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the method for data lifecycle management when executing the computer program.

A computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, implements the above-described method of data lifecycle management.

According to the management method and device of the data life cycle, the computer equipment and the storage medium, the data in the data life cycle is subjected to flow type synchronous management in a finite state machine form, so that the data can be subjected to a primary trigger event and/or a secondary trigger event in the data life cycle, the data update of each scene can be efficiently realized, the efficiency of the management of the large data life cycle is effectively improved, pain points of data redundancy which are difficult to synchronize are reduced, and the management high predictability of event state nodes is realized; the method is convenient for realizing data unit test, has good expansibility and is convenient for realizing combination and relation separation of logic period management lines; the storage structure is optimized, the online data scale is effectively controlled, the production data access efficiency is improved, the system resource utilization efficiency is improved, and the safe, stable and efficient operation of the system is ensured; the method is beneficial to management of the life cycle of historical data, provides data support for customer service and operation analysis of users, and is beneficial to mining more effective data values from the data.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.

FIG. 1 is a schematic diagram illustrating an application environment of a method for managing a data lifecycle according to an embodiment of the invention;

FIG. 2 is a first flowchart illustrating a method for managing a data lifecycle according to a first embodiment of the present invention;

FIG. 3 is a second flowchart of a method for managing a data lifecycle according to a second embodiment of the present invention;

FIG. 4 is a schematic illustration showing an FSM mechanism employed in the method for managing a data lifecycle according to the first embodiment of the present invention;

FIG. 5 is a schematic diagram illustrating an HFSM mechanism used in a method for managing a data lifecycle of a data according to a second embodiment of the invention;

FIG. 6 is a third flowchart of a method for managing a data life cycle according to a third embodiment of the present invention;

FIG. 7 is a fourth flowchart illustrating a method for managing a data lifecycle according to a fourth embodiment of the present invention;

FIG. 8 is a fifth flowchart illustrating a method for managing a data lifecycle according to a fifth embodiment of the present invention;

FIG. 9 is a sixth flowchart illustrating a method for managing a data lifecycle according to a sixth embodiment of the present invention;

FIG. 10 is a seventh flowchart illustrating a method for managing a data lifecycle according to a seventh embodiment of the invention;

FIG. 11 is a schematic diagram of a data lifecycle management apparatus according to an embodiment of the invention;

FIG. 12 is a diagram illustrating a computer device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

The method for managing the data lifecycle provided by the embodiment of the present invention can be applied to an application environment as shown in fig. 1, and the method for managing the data lifecycle is applied to a system for managing the data lifecycle, where the system for managing the data lifecycle includes a client and a server, and the client communicates with the server through a network. The client is also called a client, and refers to a program corresponding to the server and providing local services for the client. Further, the client is a computer program, an APP program of the intelligent device or a third-party applet embedded with other APPs. The client can be installed on computer equipment such as but not limited to various personal computers, notebook computers, smart phones, tablet computers and portable wearable equipment. The server may be implemented as a stand-alone server or as a server cluster consisting of a plurality of servers.

The data lifecycle includes six phases:

1. data acquisition: organizing the newly generated data in the internal system and collecting the data from the external system; 2. data transmission: a phase of data transmission from one entity to another; 3. data storage: a stage of storing the data in any digital format; 4. data processing: organizing the internal phase of operations such as calculation, analysis, visualization and the like on data; 5. data exchange: the phase of data exchange between the organization and the organization or the individual; 6. data destruction: the data and the data storage media are completely deleted by corresponding operation means and cannot be restored by any means.

Data is an important resource nowadays, becomes a social production element, and is promoted to be as important as labor, land and capital, so that it is very necessary to establish a data asset life cycle management model, which can help enterprises to promote data production, use, governance, realize enterprise digital transformation and benefit maximization. First, the cost of the enterprise is reduced. The contradiction exists between the data cost and the efficiency, a plurality of companies can use space for time when making big data, and the computing efficiency is influenced finally along with the increase of the data, if the management and the storage are not carried out in time, the cost, namely the storage space, is increased continuously. Second, risk is circumvented. When the data is supervised and audited, related data can be reserved, when a client loses personal information, the whole-course tracing can be carried out, and risks can be avoided. Thirdly, the data quality is improved. One of the important goals of data lifecycle management is to improve the quality of data, and it is difficult to ensure the overall quality level of data without managing data through the full lifecycle, and it is necessary to specify perfect business rules and standards in the system early construction and development processes to ensure to obtain high-quality data. Fourth, value is maximized. The maximization of value and benefits cannot be looked at from the data without the full life cycle management, and the enterprise can see the cost and the expected benefits behind the product through the data at present in investment items, so that whether the investment is reasonable or not is judged. The processing history of the data assets is tracked, the whole process from generation to internal business integration, warehouse counting and application of the data assets is communicated, and a good foundation is established for data cost accounting, investment income collection and other information through refined management.

In an embodiment, as shown in fig. 2, a method for managing a data lifecycle is provided, which is described by taking an example that the method is implemented by a primary state machine in a server in fig. 1, where the primary state machine includes at least two primary lifecycle nodes that are ordered in sequence by lifecycle in the data lifecycle. The method specifically comprises the following steps:

s10, at least two logic period management lines are obtained, wherein each logic period management line comprises at least two event state nodes located at different first-level life nodes and a first-level trigger event between every two event state nodes.

The logic cycle management line is a life line which extends the business related to the client of the management system adopting the data life cycle in a plurality of life periods according to the data life cycle, and manages the business data by importing (data acquisition), storing, processing, deleting and the like of the business data. For example, business to an enterprise declaration project extends over multiple lifespans from a data lifecycle perspective, including: acquiring a policy item and enterprise information (importing and storing business data), matching the policy item and the enterprise information and acquiring a matching result (data processing), and determining whether to keep the policy item and/or the enterprise information (deleting data) according to the matching result. The event state node and the primary trigger event are described by this example, as shown in table one below:

watch 1

As can be seen from the above table, the first-level life node is a node corresponding to different periods in which the logic cycle management line is sequenced according to the life periods, the first-level trigger time is an event that activates an event state node corresponding to a previous one-level life node on the logic cycle management line as an event state node corresponding to a current one-level life node, and such activation mechanism is to use an FSM (finite state machine) mechanism to manage data of the data life cycle.

Specifically, the FSM is a mathematical model representing a finite number of states and behaviors such as transitions and actions between the states, and the FSM can decouple the multi-state of the model and the transition conditions between the multi-state. Maintenance can be facilitated. Understanding the finite state machine firstly needs to understand the whole FSM model, taking the switch of the lamp as an example, as shown in fig. 3, and extracting several key points by abstraction:

1. state (primary vital node); 2. an action; 3. state transitions (primary trigger events); 4, converting the event; FSM.

The switch of lamp divide into state and action at first, and general state all can correspond an action, puts state and action in the state, and then state transition and transition incident are put in the state transition, and the final drive is carried out by the state machine also FSM state machine model by the state machine, includes: states, state transitions, and state machines. The relationship between the three is: the states are managed and driven by a state machine, and then transitions between each state are determined by the states and state transitions within the states.

The state transition in the FSM state machine is a condition (primary trigger event) for mutual transition between each state, and the transition condition between each state can be decoupled, so that subsequent system maintenance is facilitated. The state machine can only be in one state at a time. It is not possible for the lamp to be on and off at the same time. In fact, preventing this is one of the reasons that the FSM mechanism is used by the present system to manage the data lifecycle.

S20, acquiring a corresponding secondary state machine in each primary life node based on all event state nodes and primary trigger events, wherein the secondary state machine comprises at least two secondary life nodes and secondary trigger events between every two secondary life nodes.

Wherein, the secondary state machine is a HFSM (hierarchical state machine) formed by nesting a FSM in each primary life node, as shown in FIG. 4. The HFSM is not convenient to maintain when the number of FSM states is too large, the first-stage state can be classified and extracted, and the states of the same type can be maintained as a state machine.

Taking a decision dog as an example for explanation: a number of activities are defined for puppies, such as running, eating, sleeping, barking, cozzing, or wagging. If each behavior is a state, using conventional state machines requires defining transitions between these states, such as in a "running" state, going to a "sleeping" state if tired, or going to a "barking" state if a threat is felt, etc. in a "cozy" state, the transition to a "barking" state is required. If a hierarchical state machine is adopted, the behaviors are classified, a plurality of small states are merged into one state, and then jump links of internal small states in a high-level state and the high-level state are defined.

In fact, the hierarchical state machine limits the jump of the state machine to a certain extent, and the state in the state does not need to care about the jump of the external state, so that the isolation among irrelevant states is realized. Continuing with the above example, the states of a puppy are defined as fatigue, happiness and anger, and then the states are defined again, for example, in the happy state, there are small states such as cozy and waggy tail, so that the outside only needs to care about the jumping of three states (fatigue, happiness and anger), and the inside of each state only needs to care about the jumping of its own small state. In addition, if the two-layer state machine adopted in the embodiment still has more states, more state hierarchies can be defined to reduce the number of jump links, which is not specifically limited herein.

In a typical HFSM system, the role of non-leaf behavior is to make decisions, and leaf behavior is to accomplish specific tasks. If the decision process occurs on the former, there are generally two ways: (a) Letting the parent act make a decision using a special secondary trigger event, or (b) letting the child act compete, letting the parent act decide the final trade-off based on the desirability and relevance of the child act.

And S30, if a secondary life node corresponding to any event state node serves as an initial node to trigger a primary trigger event corresponding to the initial life node and/or a secondary trigger event serves as a target trigger event, performing data management on node data on all target state nodes related to the initial life node and the target trigger event.

The target trigger event may exist in a one-to-many manner, that is, a starting node corresponds to a plurality of terminal nodes and serves as target state nodes, and node data on the target state nodes can be simultaneously stimulated through one-time target trigger time to manage corresponding data, so that the management efficiency of the data life cycle is effectively improved, and related data are quickly located.

According to the management method for the data life cycle, the data in the data life cycle is subjected to flow type synchronous management in a finite state machine mode, the data can be subjected to primary trigger events and/or secondary trigger events in the data life cycle, data updating of all scenes can be efficiently realized, the efficiency of management of the large data life cycle is effectively improved, pain points of data redundancy which are difficult to synchronize are reduced, and high predictability of management of event state nodes is realized. The method is convenient for realizing data unit test, has good expansibility and is convenient for realizing combination and relation separation of logic period management lines. The storage structure is optimized, the online data scale is effectively controlled, the production data access efficiency is improved, the system resource utilization efficiency is improved, and the safe, stable and efficient operation of the system is ensured. The method is beneficial to management of the life cycle of historical data, provides data support for customer service and operation analysis of users, and is beneficial to mining more effective data values from the data.

In a specific embodiment, as shown in fig. 5, in step S20, that is, based on all event state nodes and primary trigger events, acquiring a corresponding secondary state machine in each primary life node specifically includes the following steps:

and S21, merging the same primary trigger events, and merging event state nodes in each primary life node according to the reverse order with the same number of metadata to form a secondary life node.

S22, performing logic analysis on all secondary life nodes in each primary life node to obtain a secondary trigger event between every two secondary life nodes, and forming a secondary state machine corresponding to each primary life node.

In particular, to improve the efficiency and synchronicity of the management of the data lifecycle. The system provided by the embodiment can further analyze the logic relationship among all secondary life nodes in the same primary life node. For example, in a one-level life node, there are the following event state nodes: the patent is not applied for, and the project is not reported. For the items to be declared, the application of a patent is a precondition, that is, the items cannot be declared unless a patent is applied. Thereby establishing a secondary trigger event between patent non-application and project declaration: patent materials can be applied in preparation to form a secondary state machine corresponding to the primary life node.

In a specific embodiment, as shown in fig. 6, in step S21, that is, event state nodes are merged in reverse order of the number of the same metadata in each primary life node to form a secondary life node, the method specifically includes the following steps:

s211, acquiring each event state node included in the first-level life node as all metadata included in the node to be merged.

S212, at least two nodes to be merged with the same amount and size of the metadata are merged in a reverse order to form a merged life node.

S213, all the same metadata are used as shared management data of the merged life node, and the metadata individually held by each node to be merged is used as specific management data corresponding to a certain logic period management line.

Specifically, in order to improve the data reuse rate and reduce the data redundancy, event state nodes having a plurality of identical metadata may be merged into one, for example, the event state node 1 includes metadata: A. b, C, D and E, the event state node 2 includes metadata: A. b, C, D and F, at this time, the event state nodes 1 and 2 can be merged into a merged life node, the data a, B, C and D corresponding to the merged life node are used as the shared management data of the event state nodes 1 and 2, E is the specific management data of the event state node 1, and similarly, F is the specific management data of the event state node 2.

In a particular embodiment, the secondary life nodes include shared management data and specific management data. As shown in fig. 7, after step S20, that is, after acquiring the corresponding secondary state machine in each primary life node, the method further includes the following steps:

and S2011, a logic management line adding request is obtained, wherein the logic management line adding request comprises at least two newly added state nodes which are positioned at different first-stage life nodes and a first-stage newly added trigger event between every two newly added state nodes.

S2012, determining whether a primary new trigger event exists based on the primary trigger event.

S2013, if a primary newly-added trigger event exists, two secondary life nodes corresponding to the primary newly-added trigger event are obtained, and shared management data and specific management data in nodes in a newly-added state are continuously determined.

S2014, if the first-level newly-increased trigger event does not exist, the first-level newly-increased trigger event is newly added to the first-level state machine to serve as the first-level trigger event, and shared management data and specific management data in the newly-increased state nodes are continuously determined.

Specifically, in this embodiment, analysis of newly added state nodes is performed on event state nodes corresponding to two sides of the same newly added trigger event, and whether two sides have secondary life nodes is determined, and it can be understood that if two sides have secondary life nodes, the two sides are merged; if not, the node is newly added as a secondary life node.

In one embodiment, the logical cycle management line includes a cycle management line ID. The secondary life nodes include shared management data and specific management data. As shown in fig. 8, after step S20, that is, after acquiring the corresponding secondary state machine in each primary vital node, the method further includes the following steps:

s2021, acquiring a logic management line deleting request carrying the periodic management line ID.

The cycle management line ID is a unique identifier for distinguishing the logical cycle management line.

S2022, acquiring all relevant event state nodes as to-be-processed state nodes based on the periodic management line ID.

S2023, if the node of the state to be processed is a leaf node and only one primary trigger event corresponding to the periodic management line ID exists in the node of the state to be processed as a target deletion event, directly deleting the node of the state to be processed and the target deletion event.

The leaf node is a unilateral node, that is, the node is a termination state node, and the node does not involve any trigger time to cause the change of the state of other events.

And S2024, if the node in the state to be processed is the second-level life node and the number of the application logic management lines of the second-level life node is greater than 2, deleting the specific management data of the periodic management line ID on the node in the state to be processed.

Specifically, when the number of the application logic management lines of the secondary life nodes is greater than 2, it indicates that the secondary life nodes correspond to at least three event state nodes, and at this time, one event state node is deleted, and at least 2 event state nodes remain, and the state of the secondary life nodes is maintained.

And S2025, if the node in the state to be processed is a second-level life node and the number of the application logic management lines of the second-level life node is equal to 2, deleting the specific management data corresponding to the periodic management line ID on the node in the state to be processed, combining the shared management data of the second-level life node and the rest of the specific management data to form node data corresponding to the second-level life node, and unbinding the node in the state to be processed to form an intermediate node or a leaf node.

Specifically, when the number of the application logic management lines of the second-level life node is equal to 2, it indicates that the second-level life node corresponds to 2 event state nodes, and at this time, only 1 event state node is left (which does not form a necessary condition to become the second-level life node) after deleting one event state node, and at this time, the remaining event state nodes no longer have shared management data and specific management data, that is, the node data of the event state node itself is the node data corresponding to the node.

In a specific embodiment, as shown in fig. 9, in step S30, that is, if any event state node serves as an initial node to trigger a primary trigger event and/or a secondary trigger event corresponding to the initial node to serve as a target trigger event, data management is performed on node data on all event state nodes related to the initial node and the target trigger event, which specifically includes the following steps:

and S31, if any event state node serves as an initial node to trigger a corresponding primary trigger event and/or a secondary trigger event to serve as a target trigger event, acquiring an event state node pointed by the target trigger event as a target node, synchronizing node data corresponding to the initial node and the target node according to a time sequence of a secondary state machine and/or a primary state machine, and acquiring a synchronization result.

And S32, if any synchronization result causes any primary trigger event and/or secondary trigger event, repeatedly executing the step that any event state node serves as a starting node to trigger the corresponding primary trigger event and/or secondary trigger event as a target trigger event until the final synchronization result does not cause any primary trigger event and/or secondary trigger event any more.

It is understood that "moving the whole body while dragging", sometimes only one primary trigger event and/or secondary trigger event may cause a chain reaction in the system, and the embodiment may automatically process such a chain reaction by using HFSM, thereby improving the consistency and synchronization of the management of the data life cycle.

In a specific embodiment, as shown in fig. 10, after step S30, that is, after performing data management on node data on all target state nodes related to the start node and the target trigger event, the method further includes the following steps:

s301, acquiring a timing task comprising the activation task time.

S302, when the current time of the system meets the time of activating the task, respectively drawing a primary logic thermodynamic diagram and a secondary logic thermodynamic diagram based on the triggering times of a primary triggering event and a secondary triggering event which are respectively triggered on each logic period management line, and analyzing the activity degree of all event state nodes.

Specifically, the embodiment can provide the primary logic thermodynamic diagram and the secondary logic thermodynamic diagram, provide all-around service reference for a user, facilitate visual checking of the activity or the ice-cold degree of the service type, and take corresponding measures according to the activity or the ice-cold degree.

According to the management method of the data life cycle, the data in the data life cycle is subjected to flow type synchronous management in a finite state machine mode, the data can be subjected to primary trigger events and/or secondary trigger events in the data life cycle, the data update of each scene can be efficiently realized, the efficiency of the management of the big data life cycle is effectively improved, pain points of data redundancy which are difficult to synchronize are reduced, and the management high predictability of event state nodes is realized; the method is convenient for realizing data unit test, has good expansibility and is convenient for realizing combination and relation separation of logic period management lines; the storage structure is optimized, the online data scale is effectively controlled, the production data access efficiency is improved, the system resource utilization efficiency is improved, and the safe, stable and efficient operation of the system is ensured; the method is beneficial to management of the life cycle of historical data, provides data support for customer service and operation analysis of users, and is beneficial to mining more effective data values from the data.

Further, data full lifecycle management is also inseparable from enterprise data strategies. The data strategy determines the resource investment such as data acquisition strategy and range, storage and calculation resource investment, data integration capability, visualization program and analysis breadth and depth.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not limit the implementation process of the embodiments of the present invention in any way.

In an embodiment, a data lifecycle management apparatus is provided, where the data lifecycle management apparatus corresponds to the data lifecycle management method in the foregoing embodiments one to one. As shown in fig. 11, the data lifecycle management apparatus includes an acquisition cycle management line module 10, an acquisition secondary state machine module 20, and a management associated data module 30. The functional modules are explained in detail as follows:

an obtaining cycle management line module 10, configured to obtain at least two logic cycle management lines, where each logic cycle management line includes at least two event state nodes located at different first-level life nodes and a first-level trigger event between every two event state nodes;

an acquiring secondary state machine module 20, configured to acquire a corresponding secondary state machine in each primary life node based on all event state nodes and primary trigger events, where the secondary state machine includes at least two secondary life nodes and a secondary trigger event between every two secondary life nodes;

and the management associated data module 30 is configured to perform data management on node data on all target state nodes related to the start node and the target trigger event if a secondary life node corresponding to any event state node serves as the start node to trigger a corresponding primary trigger event and/or a corresponding secondary trigger event serving as the target trigger event.

For specific limitations of the management apparatus of the data lifecycle, reference may be made to the above limitations of the management method of the data lifecycle, which are not described herein again. The modules in the data lifecycle management apparatus can be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 12. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for data related to a management method of a data life cycle. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of data lifecycle management.

In an embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method for managing a data lifecycle of the foregoing embodiments is implemented, for example, in steps S10 to S30 shown in fig. 2. Alternatively, the processor, when executing the computer program, implements the functions of the modules/units of the management apparatus for data lifecycle in the above embodiments, for example, the functions of the modules 10 to 30 shown in fig. 11. To avoid repetition, the description is omitted here.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program is executed by a processor to implement the data lifecycle management methods of the foregoing embodiments, such as S10 to S30 shown in fig. 2. Alternatively, the computer program, when executed by the processor, implements the functions of each module/unit in the management apparatus for data lifecycle in the above-described apparatus embodiments, such as the functions of modules 10 to 30 shown in fig. 11. To avoid repetition, further description is omitted here.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other storage medium used in the embodiments of the present application may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims

1. The management method of the data life cycle is characterized in that the management method of the data life cycle is realized by applying a primary state machine, wherein the primary state machine comprises at least two primary life nodes which are sequenced in sequence according to the life cycle of the data life cycle; the management method of the data life cycle comprises the following steps:

acquiring at least two logic period management lines, wherein each logic period management line comprises at least two event state nodes of different first-stage life nodes and a first-stage trigger event between every two event state nodes;

acquiring a corresponding secondary state machine in each primary life node based on all the event state nodes and the primary trigger events, wherein the secondary state machine comprises at least two secondary life nodes and secondary trigger events between every two secondary life nodes;

and if a secondary life node corresponding to any event state node is used as an initial node to trigger the corresponding primary trigger event and/or secondary trigger event as a target trigger event, performing data management on node data on all target state nodes related to the initial node and the target trigger event.

2. The method according to claim 1, wherein the obtaining a corresponding secondary state machine in each of the primary lifecycle nodes based on all the event state nodes and the primary trigger event comprises:

merging the same first-stage trigger events, and merging event state nodes in each first-stage life node according to the reverse order of the number of the same metadata to form a second-stage life node;

and performing logic analysis on all secondary life nodes in each primary life node, acquiring a secondary trigger event between every two secondary life nodes, and forming a secondary state machine corresponding to each primary life node.

3. The method for managing the data lifecycle of claim 2, wherein the merging event state nodes in each primary lifecycle into secondary lifecycle nodes in a reverse order with the same number of metadata comprises:

acquiring all event state nodes included in the first-level life nodes as all metadata included in the nodes to be merged;

combining at least two nodes to be combined with the same amount of metadata into a combined life node in a reverse order;

and taking all the same metadata as shared management data of the merging life nodes, and taking the metadata independently held by each node to be merged as specific management data corresponding to a certain logic cycle management line.

4. The method for managing a data lifecycle of claim 1, wherein the secondary lifecycle nodes comprise shared management data and specific management data;

after the obtaining of the corresponding secondary state machine in each of the primary vital nodes, the method further includes:

determining whether the primary newly-added trigger event exists based on the primary trigger event;

if the primary newly-added trigger event exists, acquiring two secondary life nodes corresponding to the primary newly-added trigger event, and continuously determining the shared management data and the specific management data in the newly-added state nodes;

and if the primary newly-added trigger event does not exist, newly adding the primary newly-added trigger event to the primary state machine as a primary trigger event, and continuously determining the shared management data and the specific management data in the newly-added state node.

5. The method of managing a data lifecycle of claim 1, wherein the logical cycle management line comprises a cycle management line ID; the secondary vital nodes comprise shared management data and specific management data;

acquiring a logic management line deleting request carrying the periodic management line ID;

if the node in the state to be processed is a secondary life node and the number of application logic management lines of the secondary life node is greater than 2, deleting the specific management data of the periodic management line ID on the node in the state to be processed;

if the node in the state to be processed is a second-level life node and the number of application logic management lines of the second-level life node is equal to 2, deleting the specific management data corresponding to the periodic management line ID on the node in the state to be processed, combining the shared management data and the rest of the specific management data of the second-level life node into node data corresponding to the second-level life node, and unbinding the node in the state to be processed into an intermediate node or a leaf node.

6. The method according to claim 1, wherein if any event state node is used as an initial node to trigger the corresponding primary trigger event and/or secondary trigger event as a target trigger event, performing data management on node data on all event state nodes related to the initial node and the target trigger event, including:

if any event state node is used as an initial node to trigger the corresponding primary trigger event and/or secondary trigger event as a target trigger event, acquiring an event state node pointed by the target trigger event as a target node, synchronizing node data corresponding to the initial node and the target node according to the time sequence of a secondary state machine and/or a primary state machine, and acquiring a synchronization result;

if any one of the synchronization results causes any one of the primary trigger events and/or secondary trigger events, the step of triggering the corresponding primary trigger event and/or secondary trigger event as a target trigger event if any one of the event state nodes is used as a starting node is repeatedly executed until the final synchronization result does not cause any primary trigger event and/or secondary trigger event any more.

7. The method for managing data life cycle according to claim 1, further comprising, after the data managing node data on all target state nodes related to the starting node and the target trigger event, the steps of:

acquiring a timing task comprising an activation task time;

and when the current time of the system meets the activation task time, respectively drawing a primary logic thermodynamic diagram and a secondary logic thermodynamic diagram based on the triggering times of the primary triggering event and the secondary triggering event which are respectively triggered on each logic period management line, and analyzing the activity degrees of all event state nodes.

8. The management device of the data life cycle is characterized by comprising a primary state machine, wherein the primary state machine comprises at least two primary life nodes which are sequenced in sequence according to the life cycle in the data life cycle; the management device of the data life cycle comprises:

the system comprises an acquisition cycle management line module, a data processing module and a data processing module, wherein the acquisition cycle management line module is used for acquiring at least two logic cycle management lines, and each logic cycle management line comprises at least two event state nodes which are positioned at different first-stage life nodes and a first-stage trigger event between every two event state nodes;

the acquisition secondary state machine module is used for acquiring a corresponding secondary state machine in each primary life node based on all the event state nodes and the primary trigger events, and the secondary state machine comprises at least two secondary life nodes and secondary trigger events between every two secondary life nodes;

and the management associated data module is used for carrying out data management on node data on all target state nodes related to the starting node and the target trigger event if a secondary life node corresponding to any event state node is used as the starting node to trigger the corresponding primary trigger event and/or secondary trigger event as the target trigger event.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a method of managing a data lifecycle of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out a method for managing a data lifecycle of any one of claims 1 to 7.