CN110471902B - Metadata model based data processing method and device for bidding - Google Patents
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Abstract
The application discloses a data processing method and a device for bidding based on a metadata model, wherein the method comprises the following steps: acquiring new metadata; determining a new metadata model corresponding to the new metadata; combining the new metadata model with the existing metadata models in the metadata model library to obtain a combined result; and processing the new metadata according to the bidding result. The purpose of automatic bidding can be achieved, repeated and heavy work can be completed instead of manual work, metadata model analysis can be performed more efficiently and accurately, and then the technical effect of corresponding processing can be achieved according to the bidding result by the metadata model management system adopting the scheme of the application.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a metadata model based bidding data processing method and apparatus.
Background
Metadata is the underlying data that defines various attributes of format, type and length, scope, etc. of the real data. A series of specific data, conforming to the metadata definition, can be read, processed and stored by terminals conforming to the same metadata definition. The metadata is reusable. The metadata model that has been analyzed by the real data format may be saved to a metadata storage system. When a new metadata model needs to be analyzed, the new model can be compared with the existing model from the storage system, and subsequent operations can be performed according to the comparison result.
When storing and operating a large number of metadata models, a metadata management system is required. The metadata management system has the ability to extract metadata from a variety of sources. The various metadata sources are scanned and the metadata repository is updated periodically as necessary. According to the characteristics of the metadata model, similarity and equality check can be automatically carried out in the process of updating the metadata repository, and whether the metadata model meets specific standards or not is judged.
The effect of the bidding analysis on the database tables is evident: data that conforms to the structure of a data table, where the definition of the table is a type of metadata, can only be stored. In addition, the content of the bidding work is also included in analyzing whether a series of existing data tables meet the current standard of a certain version. In the past, this operation was performed manually. When the number of tables is large, the task takes a long time. And manual alignment may be subject to omission or other errors.
Aiming at various technical problems in the related art, no effective solution is provided at present.
Disclosure of Invention
The present application mainly aims to provide a method and an apparatus for processing data that performs bidding based on a metadata model, so as to solve at least one technical problem in the related art.
In order to achieve the above object, according to an aspect of the present application, there is provided a data processing method for bidding based on a metadata model.
The data processing method for performing bidding based on the metadata model comprises the following steps:
acquiring new metadata;
determining a new metadata model corresponding to the new metadata;
combining the new metadata model with the existing metadata models in the metadata model library to obtain a combined result;
and processing the new metadata according to the bidding result.
Further, as the aforementioned data processing method for performing bidding based on a metadata model, bidding the new metadata model with an existing metadata model in a metadata model library includes:
determining a bidding mode between the new metadata model and the existing metadata model;
and combining the new metadata model with the existing metadata model according to the combining standard mode.
Further, as in the foregoing data processing method for performing bidding based on a metadata model, the determining a bidding manner between the new metadata model and an existing metadata model, and performing bidding on the new metadata model and the existing metadata model according to the bidding manner includes:
combining the new metadata model with any existing metadata model in the metadata model library; for determining whether there is an existing metadata model consistent with the new metadata model;
merging one of said new metadata models with a plurality of said existing metadata models; for determining whether there are a plurality of existing metadata models that can compose the new metadata model;
combining a plurality of the new metadata models with any one of the existing metadata models; for determining whether there is an existing metadata model comprising an assembly of a plurality of said new metadata models;
combining the plurality of new metadata models with the plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose a composite of a plurality of said new metadata models.
Further, as the aforementioned data processing method for performing bidding based on a metadata model, the bidding of a plurality of new metadata models and a plurality of existing metadata models includes:
combining a plurality of the new metadata models to form a first new metadata model group;
combining the first new metadata model set with the existing metadata models; and
determining repeated items of a plurality of new metadata models, and forming a second new metadata model group after the repeated items are subjected to de-duplication;
and combining the second new metadata model group with a plurality of the existing metadata models.
Further, as the foregoing data processing method for performing bidding based on a metadata model, the processing the new metadata according to the bidding result includes:
when the bidding result is completely accorded, storing new metadata through the existing metadata model;
when the bidding result is partial coincidence, the coincidence part in the existing metadata model is reused, the non-coincidence part is newly built, a first metadata model is generated according to the coincidence part and the non-coincidence part, and the first metadata model is stored in the metadata model base;
when the bidding result is completely inconsistent, the new metadata model is saved in the metadata model library; and
and giving up the result of the standard combination and performing comparison again.
In order to achieve the above object, according to another aspect of the present application, there is provided a data processing apparatus for performing bidding based on a metadata model.
The metadata model-based bidding data processing device according to the application comprises: an acquisition unit configured to acquire new metadata;
the model determining unit is used for determining a new metadata model corresponding to the new metadata;
the bidding unit is used for bidding the new metadata model and the existing metadata model in the metadata model library to obtain a bidding result;
and the processing unit is used for processing the new metadata according to the bidding result.
Further, as for the foregoing data processing apparatus for performing bidding based on a metadata model, the bidding unit is specifically configured to:
determining a bidding mode between the new metadata model and the existing metadata model;
and combining the new metadata model with the existing metadata model according to the combining standard mode.
Further, a data processing apparatus for performing bidding based on a metadata model as described above, the bidding unit includes:
the first bidding module is used for bidding one new metadata model and any existing metadata model in the metadata model library; for determining whether there is an existing metadata model consistent with the new metadata model;
the second bidding module is used for bidding one new metadata model and a plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose the new metadata model;
the third bidding module is used for bidding the plurality of new metadata models and any existing metadata model; for determining whether there is an existing metadata model comprising an assembly of a plurality of said new metadata models;
a many-to-many bidding subunit, configured to bid the plurality of new metadata models and the plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose a composite of a plurality of said new metadata models.
Further, as the foregoing data processing apparatus for performing bidding based on a metadata model, the many-to-many bidding subunit includes: the fourth bidding combination module and the fifth bidding combination module;
the fourth marking module is used for
Combining a plurality of the new metadata models to form a first new metadata model group;
combining the first new metadata model set with the existing metadata models;
the fifth marking module is used for
Determining repeated items of a plurality of new metadata models, and forming a second new metadata model group after the repeated items are subjected to de-duplication;
and combining the second new metadata model group with a plurality of the existing metadata models.
Further, the data processing apparatus for performing bidding based on the metadata model as described above, the processing unit includes:
the first processing module is used for storing new metadata through the existing metadata model when the bidding result is completely met;
a second processing module, configured to, when the bidding result is a partial agreement, reuse the agreement portion in the existing metadata model, create a new non-agreement portion, generate a first metadata model according to the agreement portion and the non-agreement portion, and store the first metadata model in the metadata model library;
the third processing module is used for storing the new metadata model into the metadata model library when the bidding result is completely inconsistent; and
and the re-bidding module is used for giving up the bidding result and re-bidding.
In the embodiment of the application, a method and a device for processing data based on metadata model are adopted, wherein the method comprises the following steps: acquiring new metadata; determining a new metadata model corresponding to the new metadata; combining the new metadata model with the existing metadata models in the metadata model library to obtain a combined result; and processing the new metadata according to the bidding result. The purpose of automatic bidding can be achieved, repeated and heavy work can be completed instead of manual work, metadata model analysis can be performed more efficiently and accurately, and then the technical effect of corresponding processing can be achieved according to the bidding result by the metadata model management system adopting the scheme of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, are included to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
FIG. 1 is a schematic flow diagram of a data processing method for bidding based on a metadata model according to an embodiment of the present application;
FIG. 2 is a block diagram of functional modules of a data processing apparatus for performing bidding based on a metadata model according to an embodiment of the present application; and
FIG. 3 is a schematic diagram of a bidding process according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the accompanying drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances in order to facilitate the description of the embodiments of the application herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used in other meanings besides orientation or positional relationship, for example, the term "upper" may also be used in some cases to indicate a certain attaching or connecting relationship. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
Furthermore, the terms "mounted," "disposed," "provided," "connected," and "sleeved" are to be construed broadly. For example, it may be a fixed connection, a removable connection, or a unitary construction; can be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements or components. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as the case may be.
It should be noted that, in the present application, the embodiments and features of the embodiments may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to achieve the above object, according to an aspect of the present application, there is provided a data processing method for bidding based on a metadata model. As shown in fig. 1, the method includes steps S1 to S4 as follows:
s1, acquiring new metadata; specifically, the new metadata may be one or more; and the new metadata may be data including a data table form;
s2, determining a new metadata model corresponding to the new metadata; that is, each of the new metadata has its corresponding new metadata model;
s3, combining the new metadata model with the existing metadata model in the metadata model library to obtain a combined result;
specifically, when the new metadata is a data table, analyzing whether one or more obtained data tables meet the current standard of a certain version; if the data table does not meet the standard, a new standard data table is generated according to the acquired data table and used for storing the data in the acquired data table;
s4, processing the new metadata according to the bidding result;
that is, when there is an existing metadata model that is consistent with the metadata model of the new metadata, the existing metadata model may be directly stored, and when there is no existing metadata model, the model corresponding to the new metadata may be generated to store the new metadata.
In some embodiments, the aforementioned data processing method for performing bidding based on a metadata model, the bidding of the new metadata model with an existing metadata model in a metadata model library includes:
determining a bidding mode between the new metadata model and the existing metadata model;
that is, there are various bidding modes, and various information including information such as the number of new metadata and the number of existing metadata models used for bidding can be used as reference information for selecting the bidding modes;
and combining the new metadata model and the existing metadata model according to the combination standard mode.
As shown in fig. 3, in some embodiments, in the foregoing data processing method for performing bidding based on a metadata model, the determining a bidding manner between the new metadata model and an existing metadata model, and performing bidding on the new metadata model and the existing metadata model according to the bidding manner includes:
combining the new metadata model with any existing metadata model in the metadata model library; for determining whether there is an existing metadata model consistent with the new metadata model;
for example, a new metadata model qualifies an existing metadata model: and selecting a metadata model which is most likely to be matched with a new metadata in the existing system, and carrying out equivalence and similarity standard combination analysis. Or automatically comparing the new metadata model with the existing models of each system to obtain the existing models most possibly conforming to the new metadata model; generally, the equality and similarity may be judged by setting a specific rule or standard; the new metadata model and the existing metadata model can be judged to be equal or similar only by meeting the standard;
merging one of said new metadata models with a plurality of said existing metadata models; for determining whether there are a plurality of existing metadata models that can compose the new metadata model;
for example, a new metadata model qualifies multiple existing metadata models: and selecting a metadata model which is most likely to be matched with the new metadata in a plurality of existing systems, and performing equivalence and similarity standard combination analysis. The selected plurality of existing models combine to conform to the new metadata model. The process can realize automatic global matching under the condition that the user specifies the number n of the selected existing models. The more models are available, the larger the value of n, and the longer the run time will be.
Combining a plurality of the new metadata models with any one of the existing metadata models; for determining whether there is an existing metadata model comprising an assembly of a plurality of said new metadata models;
for example, multiple new metadata models bid on one existing metadata model: and selecting a metadata model which is most likely to be matched with a plurality of new metadata in the existing system, and carrying out equivalence and similarity standard combination analysis. The selected one of the existing models, possibly an assembly of a plurality of new metadata models, conforms to the new metadata model. This process may be automated for global matching. The more existing models are, the larger n value of the number of new metadata models is, and the longer the running time is.
Combining the plurality of new metadata models with the plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose a composite of a plurality of said new metadata models.
Specifically, when a plurality of new metadata models and a plurality of existing metadata models are combined, the new metadata models need to be combined, and preferably, in order to achieve the best matching effect in the matching process when combined, the new metadata models are combined into different orders according to the arrangement sequence of the different new metadata models, for example, when a new metadata model exists: A. b, C; six combinations of different orders of ABC, ACB, BAC, BCA, CAB, and CBA are obtained, and since the format in each new metadata model is different, the combinations obtained by combining different orders are different. Preferably, the ranking method of the output composition is selected as the ranking of the composition with the highest conformity of the bidding results.
As shown in fig. 3, in some embodiments, the aforementioned data processing method for performing bidding based on a metadata model performs bidding on a plurality of new metadata models and a plurality of existing metadata models, including:
combining a plurality of the new metadata models to form a first new metadata model group;
combining the first new metadata model group with a plurality of the existing metadata models;
specifically, when a plurality of new metadata models are sequentially merged to a plurality of existing metadata models: and selecting a metadata model which is most likely to be matched with the new metadata in a plurality of existing systems, and carrying out equivalence and similarity standard combination analysis. The selected combination of the plurality of existing models, possibly a combination of the plurality of new metadata models, conforms to the new metadata model. This process may be automated for global matching. The more existing models, the larger the number n of new metadata models, and the longer the runtime will be. This process takes into account the order in which the new/old metadata models appear.
Determining repeated items of a plurality of new metadata models, and forming a second new metadata model group after the repeated items are subjected to de-duplication;
and combining the second new metadata model group with a plurality of the existing metadata models.
Specifically, the plurality of new metadata models cross-bid the plurality of existing metadata models: and selecting a metadata model which is most likely to be matched with the new metadata in a plurality of existing systems, and carrying out equivalence and similarity standard combination analysis. The selected combination of the plurality of existing models, possibly a combination of the plurality of new metadata models, conforms to the new metadata model. This process may be automated for global matching. The more existing models are, the larger n value of the number of new metadata models is, and the longer the running time is. This process does not take into account the order in which the new/old metadata models appear. Repeated items in a plurality of new/old models can be removed in the combination process, and compared after being sorted according to a certain rule, so that the efficiency is improved.
The conforming definition: the coincidence may be equal or similar.
In some embodiments, the method for processing data based on metadata model bidding as described above, the processing the new metadata according to the bidding result includes:
when the bidding result is completely met, storing new metadata through the existing metadata model;
when the bidding result is partial coincidence, the coincidence part in the existing metadata model is reused, the non-coincidence part is newly built, a first metadata model is generated according to the coincidence part and the non-coincidence part, and the first metadata model is stored in the metadata model base;
when the bidding result is completely inconsistent, the new metadata model is saved in the metadata model library; and
and giving up the standard combination result, and carrying out comparison again.
Specifically, as shown in fig. 3:
when the agreement is complete: directly using the existing model to store the data corresponding to the new metadata model;
when the parts are coincident: reusing the conforming parts in the existing model, and creating the non-conforming parts to form a new existing metadata model and storing the new existing metadata model in a metadata model base;
when no agreement is made: the new metadata model can be directly stored in a metadata model base;
all three results can be abandoned by the user and compared again. Meanwhile, each comparison result can be forcibly modified by the user.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
According to an embodiment of the present invention, there is also provided a data processing apparatus for performing bidding based on a metadata model, the data processing apparatus being configured to implement the data processing method for performing bidding based on a metadata model, as shown in fig. 2, the apparatus includes: in order to achieve the above object, according to another aspect of the present application, there is provided a data processing apparatus for performing bidding based on a metadata model.
The metadata model-based bidding data processing device according to the application comprises:
an acquisition unit 1 for acquiring new metadata;
a model determining unit 2, configured to determine a new metadata model corresponding to the new metadata;
the bidding unit 3 is used for bidding the new metadata model and the existing metadata model in the metadata model library to obtain a bidding result;
and the processing unit 4 is used for processing the new metadata according to the bidding result.
Specifically, the specific process of implementing the functions of each module in the apparatus according to the embodiment of the present invention may refer to the related description in the method embodiment, and is not described herein again.
In some embodiments, the data processing apparatus for performing bidding based on a metadata model as described above, the bidding unit is specifically configured to:
determining a bidding mode between the new metadata model and the existing metadata model;
and combining the new metadata model with the existing metadata model according to the combining standard mode.
Specifically, the specific process of implementing the functions of each module in the apparatus according to the embodiment of the present invention may refer to the related description in the method embodiment, and is not described herein again.
In some embodiments, a data processing apparatus for performing bidding based on a metadata model as described above, the bidding unit includes:
the first bidding module is used for bidding the new metadata model and any existing metadata model in the metadata model library; for determining whether there is an existing metadata model consistent with the new metadata model;
the second bidding module is used for bidding one new metadata model and a plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose the new metadata model;
the third bidding module is used for bidding the plurality of new metadata models and any existing metadata model; for determining whether there is an existing metadata model comprising an assembly of a plurality of said new metadata models;
a many-to-many bidding subunit, configured to bid the plurality of new metadata models and the plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose a composite of a plurality of said new metadata models.
Specifically, the specific process of implementing the functions of each module in the apparatus according to the embodiment of the present invention may refer to the related description in the method embodiment, and is not described herein again.
In some embodiments, a data processing apparatus for bidding based on a metadata model as described above, the many-to-many bidding subunit includes: the fourth bidding module and the fifth bidding module;
the fourth marking module is used for
Combining a plurality of the new metadata models to form a first new metadata model group;
combining the first new metadata model set with the existing metadata models;
the fifth marking module is used for
Determining repeated items of a plurality of new metadata models, and forming a second new metadata model group after the repeated items are subjected to de-duplication;
and combining the second new metadata model group with a plurality of the existing metadata models.
Specifically, the specific process of implementing the functions of each module in the apparatus according to the embodiment of the present invention may refer to the related description in the method embodiment, and details are not described herein again.
In some embodiments, a data processing apparatus for performing bidding based on a metadata model as described above, the processing unit includes:
the first processing module is used for storing new metadata through the existing metadata model when the bidding result is completely met;
a second processing module, configured to, when the bidding result is a partial agreement, reuse the agreement portion in the existing metadata model, create a new non-agreement portion, generate a first metadata model according to the agreement portion and the non-agreement portion, and store the first metadata model in the metadata model library;
the third processing module is used for storing the new metadata model into the metadata model library when the bidding result is completely inconsistent; and
and the re-bidding module is used for giving up the bidding result and re-bidding.
Specifically, the specific process of implementing the functions of each module in the apparatus according to the embodiment of the present invention may refer to the related description in the method embodiment, and is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (4)
1. A data processing method for performing bidding based on a metadata model is characterized by comprising the following steps:
acquiring new metadata;
determining a new metadata model corresponding to the new metadata;
combining the new metadata model with the existing metadata model in the metadata model library to obtain a combined result, comprising: determining a bidding mode between the new metadata model and the existing metadata model;
combining the new metadata model with the existing metadata model according to the combining standard mode; wherein, the determining a bidding mode between the new metadata model and the existing metadata model, and bidding the new metadata model and the existing metadata model according to the bidding mode includes: combining the new metadata model with any existing metadata model in the metadata model library; for determining whether there is an existing metadata model consistent with the new metadata model; combining one of said new metadata models with a plurality of said existing metadata models; for determining whether there are a plurality of existing metadata models that can compose the new metadata model; combining a plurality of the new metadata models with any one of the existing metadata models; for determining whether there is an existing metadata model comprising an assembly of a plurality of said new metadata models; combining the plurality of new metadata models with the plurality of existing metadata models; a step for judging whether or not there are a plurality of existing metadata models that can compose a composite of the plurality of new metadata models;
processing the new metadata according to the bidding result; and processing the new metadata according to the bidding result, wherein the processing comprises the following steps: when the bidding result is completely accorded, storing new metadata through the existing metadata model; when the bidding result is partial coincidence, multiplexing the coincidence part in the existing metadata model, creating a non-coincidence part, generating a first metadata model according to the coincidence part and the non-coincidence part, and storing the first metadata model in the metadata model library; when the bidding result is completely inconsistent, the new metadata model is saved in the metadata model library; and giving up the result of the standard combination and comparing again.
2. The metadata model-based data processing method of claim 1, wherein the bidding the plurality of new metadata models with the plurality of existing metadata models comprises:
combining a plurality of the new metadata models to form a first new metadata model group;
combining the first new metadata model group with a plurality of the existing metadata models; and
determining repeated items of a plurality of new metadata models, and forming a second new metadata model group after the repeated items are subjected to de-duplication;
and combining the second new metadata model group with a plurality of the existing metadata models.
3. A data processing apparatus for bidding based on a metadata model, comprising:
an acquisition unit configured to acquire new metadata;
the model determining unit is used for determining a new metadata model corresponding to the new metadata;
the bidding unit is used for bidding the new metadata model and the existing metadata model in the metadata model library to obtain a bidding result; the marking unit is specifically configured to: determining a bidding mode between the new metadata model and the existing metadata model; combining the new metadata model with the existing metadata model according to the combining standard mode; wherein, the mark combining unit includes: the first bidding module is used for bidding the new metadata model and any existing metadata model in the metadata model library; for determining whether there is an existing metadata model consistent with the new metadata model; the second bidding module is used for bidding one new metadata model and a plurality of existing metadata models; for determining whether there are a plurality of existing metadata models that can compose the new metadata model; the third bidding module is used for bidding the plurality of new metadata models and any existing metadata model; for determining whether there is an existing metadata model comprising an assembly of a plurality of said new metadata models; a many-to-many bidding subunit, configured to bid the plurality of new metadata models and the plurality of existing metadata models; a step for judging whether or not there are a plurality of existing metadata models that can constitute a composite of the plurality of new metadata models;
the processing unit is used for processing the new metadata according to the bidding result; wherein the processing unit comprises: the first processing module is used for storing new metadata through the existing metadata model when the bidding result is completely in accordance with the bidding result; a second processing module, configured to, when the bidding result is a partial agreement, reuse the agreement portion in the existing metadata model, create a new non-agreement portion, generate a first metadata model according to the agreement portion and the non-agreement portion, and store the first metadata model in the metadata model library; the third processing module is used for storing the new metadata model into the metadata model library when the bidding result is completely inconsistent; and the re-bidding module is used for giving up the bidding result and re-bidding.
4. The metadata model-based bidding data processing apparatus according to claim 3, wherein said many-to-many bidding subunit comprises: the fourth bidding module and the fifth bidding module;
the fourth standard combining module is used for
Combining a plurality of the new metadata models to form a first new metadata model group;
combining the first new metadata model group with a plurality of the existing metadata models;
the fifth marking module is used for
Determining repeated items of a plurality of new metadata models, and forming a second new metadata model group after the repeated items are subjected to de-duplication;
and combining the second new metadata model group with a plurality of the existing metadata models.
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