CN110399359B

CN110399359B - Data backtracking method, device and equipment

Info

Publication number: CN110399359B
Application number: CN201910670974.3A
Authority: CN
Inventors: 梁婷
Original assignee: Advanced New Technologies Co Ltd
Current assignee: Advanced New Technologies Co Ltd; Advantageous New Technologies Co Ltd
Priority date: 2019-07-24
Filing date: 2019-07-24
Publication date: 2023-09-01
Anticipated expiration: 2039-07-24
Also published as: CN110399359A

Abstract

The embodiment of the specification discloses a data backtracking method, a device and equipment. The scheme comprises the following steps: determining an original trace-back path corresponding to the data to be traced, wherein the initial position of the original trace-back path is a field corresponding to the data to be traced, and screening the original trace-back path according to the direction from the initial position to the end position of the original trace-back path; and when the effective backtracking path is searched, generating data to be backtracked according to the first effective backtracking path.

Description

Data backtracking method, device and equipment

The present application relates to the field of computer data processing technologies, and in particular, to a data backtracking method, apparatus, and device.

Background

With the rapid growth of Data volumes generated during modern enterprise development, data Warehouse (Data Warehouse) technology is also becoming increasingly popular. The data warehouse acquires data from each data source, converts the acquired data in the data warehouse, and generates various types of data such as detail data, aggregate data, multidimensional analysis data and the like, thereby providing data support for decision making of enterprises. Because data generated by a data warehouse during operation generally has a certain life cycle, the data warehouse will clean up data exceeding the survival time indicated by the life cycle, so when data analysis is required to be performed by using the cleaned-up data subsequently, data backtracking is required to be performed on the required cleaned-up data so as to restore the required data at the historical time points.

Currently, when data backtracking is performed on data to be backtracked in a field to be backtracked, an original backtracking path of the field to be backtracked is determined based on metadata of the field to be backtracked in a data warehouse, the starting position of the original backtracking path is the data source, and the ending position is the field to be backtracked. And carrying out data backtracking on the fields corresponding to each node in the original backtracking path one by one according to the direction from the data source to the fields to be backtracked in the original backtracking path so as to obtain the required data to be backtracked. The data backtracking method is large in calculated amount and affects the data backtracking efficiency.

Based on this, it is necessary to provide a data backtracking method with higher operation efficiency.

Disclosure of Invention

In view of this, the embodiment of the application provides a data backtracking method, a device and equipment, which are used for solving the problem that a data backtracking method with higher operation efficiency needs to be provided.

In order to solve the above technical problems, the embodiments of the present specification are implemented as follows:

the data backtracking method provided by the embodiment of the specification comprises the following steps:

acquiring a data backtracking request, wherein the data backtracking request is used for requesting to generate data to be backtracked, and the data to be backtracked is data in a specified time period in a field to be backtracked;

Determining an original backtracking path of the field to be backtracked;

screening the original backtracking path according to the direction from the starting position to the ending position of the original backtracking path, and searching for an effective backtracking path, wherein the starting position is the field to be backtracked;

and when the effective backtracking path is found, processing the data backtracking request according to the first found effective backtracking path to obtain the data to be backtracked.

The embodiment of the present disclosure provides a data backtracking device, including:

the data backtracking request acquisition module is used for acquiring a data backtracking request, wherein the data backtracking request is used for requesting to generate data to be backtracked, and the data to be backtracked is data in a specified time period in a field to be backtracked;

the original backtracking path determining module is used for determining an original backtracking path of the field to be backtracked;

the effective backtracking path searching module is used for screening the original backtracking path according to the direction from the starting position to the ending position of the original backtracking path, and searching the effective backtracking path, wherein the starting position is the field to be backtracked;

and the data backtracking generation module is used for processing the data backtracking request according to the first effective backtracking path when the effective backtracking path is searched, so as to obtain the data backtracking.

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to:

determining an original backtracking path of the field to be backtracked;

The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect:

the method comprises the steps of determining an original trace path corresponding to data to be traced, wherein the initial position of the original trace path is a field corresponding to the data to be traced, screening the original trace path according to the direction from the initial position to the end position of the original trace path, and generating the data to be traced according to the first effective trace path which is searched under the condition that the data to be traced can be generated according to the intermediate node of the original trace path, so that the number of nodes needing data tracing can be reduced, the data calculation amount is reduced, and the operation efficiency of the data tracing method is improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

fig. 1 is a schematic diagram of an original trace-back path for data to be traced in a field to be traced;

fig. 2 is a schematic flow chart of a data backtracking method according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of an original trace-back path according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a data backtracking device corresponding to the method in fig. 2 according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a data backtracking device according to an embodiment of the present disclosure.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

As described in the background section, currently, when data backtracking is performed on data to be backtracked in a field to be backtracked, according to a direction from a data source to the field to be backtracked in an original backtracking path, data backtracking is performed on fields corresponding to each node in the original backtracking path one by one, so as to obtain required data to be backtracked. Fig. 1 is a schematic diagram of an original trace back path for a field to be traced back, as shown in fig. 1, when tracing back data in the field to be traced back, the data source 1 (i.e. node 101) and the data source 2 (i.e. node 102) are required to be used as starting positions, the field to be traced back (i.e. node 104) is used as an ending position, and each node in the original trace back path is screened and traced back one by one according to an arrow direction in fig. 1, so as to generate the data to be traced back in the field to be traced back.

In practical applications, there are cases where the data required for generating the data to be traced is not included in the node 101 or the node 102, but the data required for generating the data to be traced is included in the node 103, and at this time, the data to be traced can be generated based on the data in the node 103. However, in the data backtracking method in the prior art, it is determined that the data to be backtracked cannot be generated because the data required in the node 103 cannot be generated according to the nodes 101 and 102. Therefore, the existing data backtracking method has low backtracking success rate. In the case that the node 101, the node 102 and the node 103 all include the data required for generating the data to be traced, the data in the node 103 can be directly used to generate the data to be traced, but the data tracing method in the prior art still needs to trace the data of the node 103 based on the node 101 and the node 102, and then generates the data to be traced based on the data in the node 103 obtained by tracing.

In view of this, the embodiments of the present disclosure provide a data backtracking method with higher operation efficiency and higher success rate. Fig. 2 is a schematic diagram of a data backtracking method according to an embodiment of the present disclosure. From a program perspective, the execution subject of the flow may be a program carried on a server, which may be used to implement the data warehouse function. As shown in fig. 2, the process may include the steps of:

step 201: and acquiring a data backtracking request, wherein the data backtracking request is used for requesting to generate data to be backtracked, and the data to be backtracked is the data in a specified time period in a field to be backtracked.

In the embodiment of the present specification, the data backtracking request is generated based on information to be backtracked that is input in the server by the user. The information to be backtraced input by the user specifically may include: the identification of the data table to which the data to be traced belongs, the identification of the field to which the data to be traced belongs, and the start time and the end time corresponding to the data to be traced. In practical application, a time period formed by the start time and the end time in the information to be traced input by the user can be used as a designated time period to which the data in the field to be traced corresponding to the data to be traced belongs. For example, the information to be backtraced input by the user may be: table 1, field a, 1 st 2019, 1 st 10 th, means that data backtracking is requested for data in field a in table 1 from 1 st 2019 to 10 st 2019.

Step 202: and determining an original backtracking path of the field to be backtracked.

In this embodiment of the present disclosure, since the data corresponding to the field to be traced is the data in the data warehouse, the original trace path of the field to be traced may be determined based on the metadata corresponding to the field to be traced in the data warehouse, where the original trace path includes all the fields related to the generation of the field to be traced, and each field included in the original trace path is connected according to the blood-edge relationship between the fields; the initial position of the original backtracking path is a field to be backtracked; the end position of the original backtracking path is the data source, namely, the data acquired from each data source by the original data layer (Operational Data Store, ODS layer) of the data warehouse. The data in the fields to be traced are all based on the data generation in each field in the original trace-back path.

Wherein the Metadata (Metadata) is data (data about data) that can be used to describe the structure and method of creation of data within a data warehouse. The metadata includes a blood-edge relationship between fields, where the blood-edge relationship refers to an association relationship between a first field and a second field when data in the first field is directly used to generate data in the second field, and may be expressed as: the second field-the first field has a blood relationship, and the first field and the second field are different fields.

For ease of understanding, an implementation of determining an original backtracking path of a field to be backtracked based on metadata is illustrated in the present embodiments. It is assumed that metadata of the field to be traced includes: the data source comprises a field A, a field B, a data source and other information. The original trace-back path is determined based on the metadata of the field to be traced, as shown in fig. 3, and the original trace-back path of the field to be traced is sequentially, from the start position to the end position, a field to be traced 301-a field 302-a field B303-a first data source 305, and a field to be traced 301-a second data source 305.

Step 203: and screening the original backtracking path according to the direction from the starting position to the ending position of the original backtracking path, searching for an effective backtracking path, wherein the starting position is the field to be backtracked.

In this embodiment of the present disclosure, screening the original trace-back path according to a direction from a start position to an end position of the original trace-back path, and searching for an effective trace-back path may specifically include: screening the nodes in the original trace-back path according to the order of the nodes in the original trace-back path from high to low, and searching for an effective trace-back path; one node in the original traceback path corresponds to a field, and the level of a neighboring node in the original traceback path used for directly generating a non-termination node is lower than the level of the non-termination node.

In practical applications, the original trace-back path may include three types of nodes, including a start node, an intermediate node, and a termination node, where the start node and the intermediate node belong to non-termination nodes. The starting node in the original trace-back path may be a field to be traced, and the ending node in the original trace-back path may be a data source. In the original backtracking path, the level of the adjacent node used for directly generating the non-termination node is lower than that of the non-termination node, namely, for the second field and the first field with blood-edge relation, the level of the first field is lower than that of the second field because the data in the first field is required to be directly used for generating the data in the second field.

Specifically, in the original trace-back path, the hierarchy of the start node is highest, and the hierarchy of each node involved in the direction from the start node to the end node is sequentially lowered. For ease of understanding, the original trace-back path shown in fig. 3 is still used for explanation, and it is assumed that the level of the field 301 to be traced back is one level, and the larger the field level value is, the lower the level corresponding to the field is; the level of field a302 is two, the level of field B303 is three, the level of the first data source 305 is four, and the level of the second data source 305 is two in fig. 3.

In practical application, in step 201, the information to be traced input by the user may further include a tracing level value, where the tracing level value is used to indicate that when the original tracing path is screened, the screening is stopped when the node of the level corresponding to the tracing level value is screened. The description will be given here with reference to the original trace-back path shown in fig. 3, for example, when the trace-back level value is 2, in the case of screening the nodes in fig. 3, only the nodes with the level value less than or equal to 2 from the level value of the starting node need to be screened, that is, only the field a302 (second level), the field B303 (third level) and the second data source 305 (second level) need to be screened.

Step 204: and when the effective backtracking path is found, processing the data backtracking request according to the first found effective backtracking path to obtain the data to be backtracked.

In the embodiment of the present specification, the effective trace-back path means a path capable of generating required data to be traced back according to each node included in the path. In practical applications, the original trace-back path determined in step 202 may have an effective trace-back path, and may not have an effective trace-back path. When a plurality of effective traceback paths exist in the original traceback path determined in step 202, the first found effective traceback path can be considered to contain the least number of nodes compared with other effective traceback paths obtained by continuing to screen, so that the calculated amount is the least and the efficiency is the highest when the data to be traceback is generated.

In the embodiment of the present disclosure, an original trace path of a field to which data to be traced belongs is first determined, and the initial position of the original trace path is the field to which the data to be traced belongs, and the original trace path is screened according to a direction from the initial position to the end position of the original trace path, so that under the condition that the data to be traced can be generated according to an intermediate node of the original trace path, the data to be traced is generated according to the first valid trace path searched, and the number of nodes to be traced can be reduced, thereby reducing the data calculation amount and improving the operation efficiency of the data trace method. And the field corresponding to the termination position of the original trace-back path does not contain data required for generating the data to be traced, but under the condition that the field at the middle position of the original trace-back path contains the data required for generating the data to be traced, the effective trace-back path can be searched, the data to be traced is generated, and the data trace-back success rate is improved.

Based on the method in fig. 2, the present description example also provides some specific implementations of the method, which are described below.

In the embodiment of the present specification, an implementation of finding a valid backtracking path in step 203 is presented. In this implementation manner, the screening the nodes in the original traceback path according to the order of the nodes in the original traceback path from high to low, and searching the effective traceback path may specifically include:

And taking the field to be backtraced as a current node, and determining a next-stage node, wherein the next-stage node is used for directly generating the current node.

And judging whether the next-stage node meets the backtracking condition or not, and obtaining a judging result.

And when the judging result shows that the next-stage node accords with the backtracking condition, generating an effective backtracking path according to the next-stage node.

And when the judging result shows that the next-stage node does not meet the backtracking condition, taking the next-stage node as the updated current node, returning to the step of determining the next-stage node until the next-stage node meeting the backtracking condition is determined, and generating an effective backtracking path according to each determined next-stage node.

When the judging result indicates that the next-stage node does not meet the backtracking condition, taking the next-stage node as an updated current node, returning to the step of determining the next-stage node until the updated current node does not have the next-stage node, and generating search failure information according to each determined next-stage node, where the search failure information is used to indicate that an effective backtracking path cannot be found, and the search failure information specifically may include: and backtracking the failure path and the related information of the nodes which do not accord with the backtracking condition in the backtracking failure path.

For ease of understanding, the present implementation will be described herein with reference to the original trace-back path in fig. 3. Specifically, when screening the original trace-back path in fig. 3, first, the field to be traced back is taken as the current node, and two fields, namely the field a302 and the second data source 305, are determined for the next level node.

It is determined whether field a302 and second data source 305 meet the backtracking condition.

When the field a302 and the second data source 305 both meet the backtracking condition, the data to be backtracked can be directly generated according to the field a302 and the second data source 305. At this time, the effective trace-back path obtained by arranging from low to high according to the node level is as follows: field a 302-second data source 305-to-backtrack field 301. In practical application, the searched effective trace-back path can be displayed for the user, and specifically, fields corresponding to all nodes in the effective trace-back path and blood relationship among the fields corresponding to all nodes in the effective trace-back path can be displayed for the user; the data table to which the fields corresponding to the nodes in the effective trace-back path belong and the association relationship between the data tables to which the fields corresponding to the nodes in the effective trace-back path belong can also be displayed to the user. Thus, the effective backtracking paths with two granularities, namely a field level and a data table level, are shown to the user.

If the second data source 305 does not meet the valid backtracking condition, the step of determining the next level node is returned by taking the second data source 305 as the updated current node. Since the second data source 305 does not have a next node and does not meet the valid backtracking condition, even if the field a302 meets the valid backtracking condition, the data of the field to be backtracked cannot be generated due to the lack of a portion directly used for generating the data of the field to be backtracked, and at this time, the search failure information can be directly generated without continuing to screen the field B and the first data source 304. The searching failure information can comprise a backtracking failure path, and the backtracking failure path comprises each node which is screened. The search failure information may further include: the reason why the blood relationship among all nodes in the backtracking failure path does not accord with the backtracking condition is that all nodes are in line with the backtracking condition. For example, assuming that the second data source 305 does not meet the valid trace-back condition because it does not include the numerical data required to generate the data to be traced, the trace-back failure path generated at this time may be expressed as: a second data source 305-to-backtrack field 301; the search failure information may include: the field 301 to be traced-the second data source 305 has a blood relationship, and the second data source 305 lacks information such as numerical data required for generating the data to be traced.

Similarly, if the second data source 305 meets the valid backtracking condition, but the field a does not meet the valid backtracking condition, the step of determining the next level node is returned by taking the field a302 as the updated current node, and the corresponding next level node determined for the second time is the field B303, so as to determine whether the field B303 meets the backtracking condition.

If the field B303 meets the backtracking condition, the effective backtracking path obtained by the arrangement from low to high according to the node level is: field B303-field a 302-field to be backtraced 301, and a second data source 305-field to be backtraced 301.

If the field B303 does not meet the backtracking condition, it is determined and judged whether the next node (i.e., the second data source 304) of the field B303 meets the backtracking condition, and if so, a valid backtracking path, i.e., the second data source 304-field B303-field a 302-field to be backtracked 301, and the second data source 305-field to be backtracked 301, can be obtained. If the second data source 304 does not meet the backtracking condition, the second data source 304 does not have a next node and does not meet the backtracking condition, so as to generate the search failure information. At this time, the corresponding backtracking failure path may be expressed as: the second data source 304-field B303-field a 302-field to be backtraced 301.

In this implementation manner, by screening the nodes in the original trace-back path according to the order of the nodes in the original trace-back path from high to low, under the condition that the data to be traced can be generated according to the intermediate nodes of the original trace-back path, the effective trace-back path with the minimum number of nodes can be screened out, and compared with the existing method that the data trace-back processing is required to be performed on each node in the original trace-back path to generate the data to be traced, the calculation amount is less when the data to be traced is generated based on the effective trace-back path screened by the implementation manner, so that the efficiency of data trace-back can be improved.

In the implementation mode, when the termination node does not meet the backtracking condition, but an intermediate node meeting the backtracking condition exists on a data link between the termination node and the starting node, an effective backtracking path can be found, the problem that the existing data backtracking method cannot backtrack data under the condition is solved, the data backtracking success rate is improved, and therefore the operation stability and the effectiveness of the data backtracking method are improved.

Meanwhile, in the implementation mode, when an effective backtracking path is not found, search failure information is generated, the search failure information comprises the backtracking failure path and reason information that each node in the backtracking failure path does not accord with backtracking conditions, the intuitiveness is good, a user can conveniently know the problems existing in the data backtracking process, and the user can conveniently solve the problem that the data backtracking cannot be performed.

In the embodiment of the present disclosure, whether the next node meets the backtracking condition is determined, so as to obtain a determination result, which may have multiple implementation manners. The first implementation way is: judging whether a field corresponding to the next-stage node belongs to a preset field. The second implementation mode is as follows: and judging whether the field corresponding to the next node contains data required for generating the field to be traced.

In the first implementation manner of determining whether the next-stage node meets the backtracking condition, the determining whether the next-stage node meets the backtracking condition to obtain the determination result may specifically include:

judging whether the field corresponding to the next-stage node belongs to a preset field or not, and obtaining a first judging result.

When the first judgment result indicates that the field corresponding to the next-stage node belongs to the preset field, the judgment result indicates that the next-stage node accords with a backtracking condition.

In this implementation manner, the preset field refers to a field including data in any time period used for generating the field to be traced. The preset field can be a manually specified field or a field screened by a server based on a certain rule. When the field corresponding to the next node is a preset field, the field corresponding to the next node can be considered to contain data required for generating the data to be traced back, and at this time, the first judgment result can indicate that the next field accords with a tracing back condition.

The determining whether the field corresponding to the next level node belongs to the preset field may specifically include:

sending a query request to a knowledge base, wherein the query request is used for requesting whether information matched with a field corresponding to the next-level node is stored or not, and the information matched with the field corresponding to the next-level node comprises: the information identical to the field attribute information of the field corresponding to the next-level node or the information identical to the table attribute information of the data table to which the field corresponding to the next-level node belongs.

And acquiring a query result fed back by the knowledge base in response to the query request.

And judging whether the field corresponding to the next-stage node belongs to a preset field or not according to the query result.

In the embodiment of the present specification, information of each preset field is stored in the knowledge base. Specifically, the information of the stored preset field in the knowledge base may have multiple expression modes, where one expression mode is: field level information, another is data table level information.

One piece of field level information may include: the identification of the data table to which the preset field belongs, the identification of the preset field, the time period information corresponding to all the valid data in the preset field, etc., for example, for one piece of information expressed as: the field level information of table 1, field a, and 2017, 1/7/1 means that all data of field a generated from 2017, 1/1 to 2019, 7/1 are included in field a in table 1.

One piece of data table level information may include: the identification of the preset data table and the time period information corresponding to all the valid data in the preset data table, for example, for one piece of information expressed as: data table level information of 1 st 2017 st 1 st to 7 st 2019 st means that all data of each field in table 1 generated from 1 st 2017 st 1 st to 7 st 2019 st 1 are included in table 1. At this time, all the fields in the preset data table may be considered as preset fields.

In the embodiment of the present disclosure, the query request sent to the knowledge base carries information of a field corresponding to the next level node to be determined. For example, assuming that the field corresponding to the next node to be determined is the field a in table 1, the query request carries information such as "table 1" and "field a". The knowledge base can inquire whether the data table level information of the preset data table, which is identified as 'table 1', is stored, if the data table level information is inquired, the field corresponding to the next-stage node belongs to the preset field based on the inquiry result fed back by the knowledge base, and the next-stage node accords with the backtracking condition. Or, the knowledge base may query whether the knowledge base itself stores the field level information of the data table to which the preset field belongs, where the identifier is "table 1" and the identifier of the preset field is "field a", and if the knowledge base queries that the field level information is stored, it may determine, based on the query result fed back by the knowledge base, that the field corresponding to the next node belongs to the preset field, and the symbol backtracking condition of the next node.

In this implementation, the data table level information stored in the knowledge base may be input into the knowledge base in advance based on human experience. Specifically, the staff can input the table information of the full table of each service information in the data warehouse as the information of the preset data table into the knowledge base based on personal experience, so as to generate the data table level information. The full-volume table refers to a data table containing all data generated by a certain business every day from the time of online. For example, a piece of data table level information may be generated based on a transaction information full table that contains all transaction information generated since a certain business was online. Alternatively, the staff may input table information of a data table, which may be stored unchanged, as information of a preset data table into the knowledge base based on personal experience, thereby generating data table level information. For example, a piece of data table level information may be generated based on the country province-city-county name data table. Of course, the data sheet level information may also be generated based on a country-by-country zip code data sheet, a member information data sheet, or the like.

The field level information stored in the knowledge base may be information of fields screened by the server based on a certain rule. Specifically, after the server generates the data to be traced by adopting the method in fig. 2, the field information of the field corresponding to the data to be traced, which accords with the screening condition, can be stored into the knowledge base based on the preset screening policy, so as to generate field level information, and update the knowledge base is completed. In practical applications, the knowledge base may be updated periodically according to the requirements, for example, once a month or a quarter.

In practical applications, there may be a case where part of the information in the knowledge base fails, that is, there is a case where part of the data in the fields corresponding to the field level information in the knowledge base is lost or part of the data in the data table corresponding to the data table level information is lost. Therefore, when the knowledge base is periodically updated, besides the field level information in the knowledge base is increased, the information stored in the knowledge base can be screened, and the screened invalid information is cleared, so that the accuracy and the effectiveness of the knowledge base are improved.

In the implementation mode, based on the information stored in the knowledge base, whether the next-stage node accords with the backtracking condition can be judged, the data in the field corresponding to the next-stage node does not need to be screened one by one, and the efficiency is high.

In the second implementation manner of determining whether the next-stage node meets the backtracking condition, the determining whether the next-stage node meets the backtracking condition to obtain the determination result may specifically include:

and judging whether the field corresponding to the next-stage node contains effective data for generating the data to be backtraced or not, and obtaining a second judging result.

When the second judgment result indicates that the field corresponding to the next-stage node contains effective data for generating the data to be traced back, the second judgment result indicates that the next-stage node accords with a tracing condition.

The determining whether the field corresponding to the next level node includes valid data for generating the data to be backtraced may specifically include:

and determining a target time period corresponding to data for generating the data to be traced in a field corresponding to the next-stage node according to a field to be traced generation rule.

And sending a query request to a database, wherein the query request is used for requesting whether at least one character type data which is not null or at least one numerical value data which is not zero exists in the target time period in the field corresponding to the next node.

And acquiring a query result fed back by the database in response to the query request.

And judging whether the field corresponding to the next node contains effective data for generating the data to be traced or not according to the query result.

In this implementation manner, according to the field to be traced generation rule, the determined target time period corresponding to each next-stage node may be the same or different from the specified time period corresponding to the data to be traced. For example, it is assumed that the data to be traced is data in a total number of daily user transactions field generated between 1 month and 10 days of 19 years and 1 month and 15 days of 19 years (i.e., specified time period), and a next-stage field of the field to which the data to be traced belongs is a field in a user transaction full scale, and at this time, a target time period corresponding to the data for generating the data to be traced in the next-stage field is also 19 years 1 month 1 day to 19 years 1 month 5 days. If the data to be traced is data in the field of the total number of user transactions of the last week generated between 1 month and 10 days of 19 years and 1 month and 15 days of 19 years (namely, the designated time period), and the next-stage field of the field to which the data to be traced belongs is a field in the user transaction total scale, at this time, the target time period corresponding to the data for generating the data to be traced in the next-stage field is 19 years, 1 month, 3 days and 19 years, 1 month and 14 days.

In this implementation manner, the database stores data in each field to be traced and the determined field corresponding to each next-level node. The query request sent to the database may carry the identifier of the field corresponding to the next level node to be determined, the identifier of the data table to which the field corresponding to the next level node to be determined belongs, and the target time period of the field corresponding to the next level node to be determined. For example, when the query request sent to the database carries information such as table 1, field a, and 19 years 1, month 3, and 19 years 1, month 14, it means that the data generated in field a in table 1 between 19 years 1, month 3, and 19 years 1, month 14 is requested to query the database whether the data contains at least one character type data that is not null or at least one numerical data that is not zero and not null; if yes, judging that the field corresponding to the next-stage node contains effective data for generating the data to be traced back, wherein the next-stage node accords with a tracing condition; if not, the field corresponding to the next-stage node does not contain effective data for generating the data to be traced back, and the next-stage node does not accord with the tracing back condition. In practical applications, the data in the string type field or the data in the datetime type field may be character type data. The data in the big type field or the data in the double type field may be numerical data.

In the implementation manner, a specific implementation manner for judging whether the field corresponding to the next-stage node contains the effective data for generating the data to be traced is provided, and the accuracy of the obtained judgment result is higher when judging whether the next-stage field accords with the tracing condition based on the implementation manner.

In practical application, the two implementation modes for judging whether the next-stage node accords with the backtracking condition can be combined at the same time to generate a corresponding judgment result. For example, the first implementation mode is used to determine whether the next-stage node meets the backtracking condition, if not, the second implementation mode is used to determine whether the next-stage node meets the backtracking condition, so as to obtain a final determination result. The specific step of generating the judgment result by combining the two implementation modes for judging whether the next node meets the backtracking condition is not repeated here.

Based on the same thought, the embodiment of the present disclosure also provides an apparatus corresponding to the method in fig. 2. Fig. 4 is a schematic structural diagram of a data trace-back device corresponding to the method in fig. 2 according to an embodiment of the present disclosure. As shown in fig. 4, the apparatus may include:

the data backtracking request obtaining module 401 is configured to obtain a data backtracking request, where the data backtracking request is used for requesting to generate data to be backtracked, and the data to be backtracked is data in a specified time period in a field to be backtracked.

An original traceback path determining module 402, configured to determine an original traceback path of the field to be traceback.

And an effective trace-back path searching module 403, configured to screen the original trace-back path according to a direction from a start position to an end position of the original trace-back path, and search for an effective trace-back path, where the start position is the field to be traced back.

And the to-be-traced data generating module 404 is configured to process the data tracing request according to the first valid tracing path to obtain the to-be-traced data when the valid tracing path is found.

The effective traceback path searching module 403 may specifically be configured to:

screening the nodes in the original trace-back path according to the order of the nodes in the original trace-back path from high to low, and searching for an effective trace-back path; one node in the original traceback path corresponds to a field, and the level of a neighboring node in the original traceback path used for directly generating a non-termination node is lower than the level of the non-termination node.

The effective traceback path searching module 403 may specifically include:

the next-stage node determining unit is used for determining a next-stage node by taking the field to be traced as a current node, and the next-stage node is used for directly generating the current node.

And the judging unit is used for judging whether the next-stage node accords with the backtracking condition or not to obtain a judging result.

An effective backtracking path generating unit, configured to generate an effective backtracking path according to the next node when the determination result indicates that the next node meets the backtracking condition; or when the judging result indicates that the next-stage node does not meet the backtracking condition, taking the next-stage node as the updated current node, returning to the step of determining the next-stage node until the next-stage node meeting the backtracking condition is determined, and generating an effective backtracking path according to each determined next-stage node.

The judging unit may specifically be configured to:

judging whether the field corresponding to the next-stage node belongs to a preset field or not, and obtaining a first judging result. Specifically, a query request may be sent to a knowledge base, where the query request is used to request whether information matched with a field corresponding to the next node is stored in the query request; the information matched with the field corresponding to the next-level node comprises: the information identical to the field attribute information of the field corresponding to the next-level node or the information identical to the table attribute information of the data table to which the field corresponding to the next-level node belongs. Acquiring a query result fed back by the knowledge base in response to the query request; and judging whether the field corresponding to the next-stage node belongs to a preset field or not according to the query result.

The judging unit may be further configured to:

and judging whether the field corresponding to the next-stage node contains effective data for generating the data to be backtraced or not, and obtaining a second judging result. Specifically, according to a field to be traced generating rule, a target time period corresponding to data for generating the data to be traced in a field corresponding to the next level node is determined; sending a query request to a database, wherein the query request is used for requesting whether at least one character type data which is not null or at least one numerical value data which is not zero exists in the character type data in the target time period in a field corresponding to the next node; acquiring a query result fed back by the database in response to the query request; and judging whether the field corresponding to the next node contains effective data for generating the data to be traced or not according to the query result.

The data backtracking apparatus in fig. 4 may further include:

and the searching failure information generating module is used for taking the next-stage node as an updated current node when the judging result shows that the next-stage node does not meet the backtracking condition, returning to the step of determining the next-stage node until the updated current node does not have the next-stage node, and generating searching failure information, wherein the searching failure information is used for showing that an effective backtracking path cannot be searched.

The search failure information generation module may be specifically configured to:

generating search failure information according to each determined next-level node, wherein the search failure information comprises: and backtracking the failure path and the related information of the nodes which do not accord with the backtracking condition in the backtracking failure path.

Based on the same thought, the embodiment of the present disclosure further provides an apparatus corresponding to the method in fig. 2. Fig. 5 is a schematic structural diagram of a data backtracking device according to an embodiment of the present disclosure. As shown in fig. 5, the apparatus 500 may include:

at least one processor 510; the method comprises the steps of,

a memory 530 communicatively coupled to the at least one processor; wherein,,

the memory stores instructions 520 executable by the at least one processor 510, the instructions being executable by the at least one processor 510 to enable the at least one processor 510 to:

determining an original backtracking path of the field to be backtracked;

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose logic function is determined by the user programming the device. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in the same piece or pieces of software and/or hardware when implementing the present application.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may 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 instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may 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 which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

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

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer 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 Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," 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 may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims

1. A data backtracking method, comprising:

determining an original backtracking path of the field to be backtracked; the original backtracking path comprises fields related to the generation of the fields to be backtracked;

screening the original backtracking path according to the direction from the starting position to the ending position of the original backtracking path, and searching for an effective backtracking path, wherein the starting position is the field to be backtracked; the effective backtracking path is a path capable of generating the data to be backtracked according to each field corresponding to each node included in the path;

2. The method of claim 1, wherein the screening the original trace-back path according to the direction from the start position to the end position of the original trace-back path, and searching for an effective trace-back path specifically comprises:

3. The method of claim 2, wherein the screening the nodes in the original trace-back path according to the order of the level of the nodes in the original trace-back path from high to low, and searching for the effective trace-back path specifically comprises:

taking the field to be backtraced as a current node, determining a next-stage node, wherein the next-stage node is used for directly generating the current node;

Judging whether the next-stage node accords with a backtracking condition or not to obtain a judging result;

when the judging result shows that the next-stage node accords with the backtracking condition, generating an effective backtracking path according to the next-stage node;

4. The method of claim 3, wherein the determining whether the next level node meets the backtracking condition, to obtain the determination result, specifically includes:

judging whether a field corresponding to the next-stage node belongs to a preset field or not, and obtaining a first judging result;

5. The method of claim 4, wherein the determining whether the field corresponding to the next level node belongs to a preset field specifically includes:

Sending a query request to a knowledge base, wherein the query request is used for requesting whether information matched with a field corresponding to the next-level node is stored or not;

acquiring a query result fed back by the knowledge base in response to the query request;

6. The method of claim 5, wherein the information matching the field corresponding to the next level node comprises: the information identical to the field attribute information of the field corresponding to the next-level node or the information identical to the table attribute information of the data table to which the field corresponding to the next-level node belongs.

7. The method of claim 3, wherein the determining whether the next level node meets a backtracking condition specifically includes:

judging whether a field corresponding to the next-stage node contains effective data for generating the data to be traced or not, and obtaining a second judging result;

8. The method of claim 7, wherein the determining whether the field corresponding to the next level node includes valid data for generating the data to be backtraced specifically includes:

determining a target time period corresponding to data for generating the data to be traced in a field corresponding to the next-stage node according to a field to be traced generation rule;

sending a query request to a database, wherein the query request is used for requesting whether at least one character type data which is not null or at least one numerical value data which is not zero exists in the character type data in the target time period in a field corresponding to the next node;

acquiring a query result fed back by the database in response to the query request;

9. The method of claim 3, wherein after the determining whether the next level node meets the backtracking condition, further comprising:

and when the judging result shows that the next-stage node does not meet the backtracking condition, taking the next-stage node as an updated current node, returning to the step of determining the next-stage node until the updated current node does not have the next-stage node, and generating search failure information, wherein the search failure information is used for indicating that an effective backtracking path cannot be searched.

10. The method of claim 9, wherein the generating the lookup failure information specifically comprises:

11. A data backtracking apparatus, comprising:

the original backtracking path determining module is used for determining an original backtracking path of the field to be backtracked; the original backtracking path comprises fields related to the generation of the fields to be backtracked;

the effective backtracking path searching module is used for screening the original backtracking path according to the direction from the starting position to the ending position of the original backtracking path, and searching the effective backtracking path, wherein the starting position is the field to be backtracked; the effective backtracking path is a path capable of generating the data to be backtracked according to each field corresponding to each node included in the path;

12. The apparatus of claim 11, wherein the effective backtracking path lookup module is specifically configured to:

13. The apparatus of claim 12, wherein the effective backtracking path lookup module specifically comprises:

the next-stage node determining unit is used for determining a next-stage node by taking the field to be traced as a current node, and the next-stage node is used for directly generating the current node;

the judging unit is used for judging whether the next-stage node accords with the backtracking condition or not to obtain a judging result;

14. The apparatus of claim 13, the judging unit is specifically configured to:

15. The apparatus of claim 13, the judging unit is specifically configured to:

16. The apparatus of claim 13, further comprising:

17. The apparatus of claim 16, wherein the search failure information generation module is specifically configured to:

18. A data backtracking apparatus, comprising:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,