CN117971827A - Data table association method, device, electronic equipment and computer readable medium - Google Patents

Abstract

Embodiments of the present disclosure disclose a data table association method, apparatus, electronic device, and computer readable medium. One embodiment of the method comprises the following steps: determining data table operation information corresponding to each target data table in the target data table set in response to determining that the data table triggering the data table re-association condition exists in the target database; for a target data table, determining the target data table as a filtered data table in response to determining that a data table operation record with a preset operation type and an executed operation state exists in a data table operation record sequence corresponding to the target data table; determining data table description information corresponding to the filtered data table; determining a historical data table association graph for the filtered data table set; carrying out association diagram update on the history data table association diagram; and carrying out data table compression on the filtered data table corresponding to the updated data table association diagram. According to the embodiment, automatic data table association is realized, and the association efficiency of the data table is improved.

Description

Data table association method, device, electronic equipment and computer readable medium

Technical Field

Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a data table association method, apparatus, electronic device, and computer readable medium.

Background

The data table association refers to a technology for associating a plurality of data tables to improve data retrieval efficiency. Currently, in making a data table association, the following methods are generally adopted: the association relation between the data tables is preset in a manual mode, so that the purpose of data table association is achieved.

However, when the above manner is adopted, there are often the following technical problems:

because the association relationship between the data tables often needs to be reset manually when the data tables are changed, when the changed data tables are more, the association efficiency of the data tables is poorer.

The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.

Disclosure of Invention

The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose data table association methods, apparatus, electronic devices, and computer-readable media to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a data table association method, the method comprising: in response to determining that a data table triggering a data table re-association condition exists in a target database, determining data table operation information corresponding to each target data table in a target data table set, wherein the target data table set is each data table stored in the target database, the data table operation information represents a data table operation record aiming at the corresponding target data table in a preset time period, the preset time period represents a time interval when the data table re-association condition is triggered twice consecutively, and the data table operation information comprises: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status; for each target data table in the target data table set, determining the target data table as a filtered data table in response to determining that a data table operation record with a preset operation type and an executed operation state exists in a data table operation record sequence corresponding to the target data table; determining data table description information corresponding to each filtered data table in the obtained filtered data table set, wherein the data table description information comprises: historical data table description information and real-time data table description information; determining a history data table association diagram aiming at the filtered data table set according to history data table description information included in the data table description information; and updating the association diagram of the historical data table association diagram according to the real-time data table description information included in the data table description information to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: the association graph node sets have corresponding relations with the compressed data table; and carrying out data table compression on the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information.

In a second aspect, some embodiments of the present disclosure provide a data table associating apparatus, the apparatus comprising: a first determining unit configured to determine, in response to determining that a data table triggering a data table re-association condition exists in a target database, data table operation information corresponding to each target data table in a target data table set, where the target data table set is each data table stored in the target database, the data table operation information represents a data table operation record for the corresponding target data table within a preset period of time, the preset period of time represents a time interval at which the data table re-association condition is triggered twice consecutively, the data table operation information including: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status; a second determining unit configured to determine, for each target data table in the target data table set, the target data table as a filtered data table in response to determining that a data table operation record whose operation type is a preset operation type and whose operation state is an executed state exists in a data table operation record sequence corresponding to the target data table; a third determining unit configured to determine data table description information corresponding to each filtered data table in the obtained filtered data table set, where the data table description information includes: historical data table description information and real-time data table description information; a fourth determining unit configured to determine a history data table association map for the filtered data table set based on history data table description information included in the data table description information; the association diagram updating unit is configured to update the association diagram of the historical data table association diagram according to the real-time data table description information included in the data table description information to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: the association graph node sets have corresponding relations with the compressed data table; and the data table compression unit is configured to perform data table compression on the filtered data table corresponding to the association diagram node in the updated data table association diagram according to the real-time data table description information included in the data table description information.

In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors causes the one or more processors to implement the method described in any of the implementations of the first aspect above.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

The above embodiments of the present disclosure have the following advantageous effects: by the data table association method of some embodiments of the present disclosure, automatic data table association is realized, association efficiency of data tables is improved, and specifically, the reason for causing low data table association efficiency is that: because the association relationship between the data tables often needs to be reset manually when the data tables are changed, when the changed data tables are more, the association efficiency of the data tables is poorer. Based on this, the data table association method of some embodiments of the present disclosure, first, in response to determining that there is a data table triggering a data table re-association condition in a target database, determining data table operation information corresponding to each target data table in a target data table set, where the target data table set is each data table stored in the target database, the data table operation information characterizes a data table operation record for the corresponding target data table in a preset time period, where the preset time period characterizes a time interval during which the data table re-association condition is triggered twice consecutively, the data table operation information includes: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status. And automatically detecting whether a data table needing to be associated with the data table exists in the target database according to the data table re-association condition. And secondly, for each target data table in the target data table set, determining the target data table as a filtered data table in response to determining that a data table operation record with the operation type being a preset operation type and the operation state being an executed state exists in a data table operation record sequence corresponding to the target data table. The filtering of the data table is realized by combining the operation record of the data table, so that the occupation of cache resources caused by the pre-caching of the data table is avoided. Next, determining data table description information corresponding to each filtered data table in the obtained filtered data table set, wherein the data table description information comprises: historical data table description information and real-time data table description information. And determining the description information of the data table before and after the execution of the trigger data table re-association condition. Further, according to the history data table description information included in the data table description information, a history data table association diagram for the filtered data table set is determined. And determining the association relation of the filtered data tables in the filtered data table set before triggering the data table re-association condition. In addition, according to real-time data table description information included in the data table description information, carrying out association diagram update on the history data table association diagram to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: and the association graph nodes have corresponding relations with the compressed data table. And determining the association relation of the filtered data tables in the filtered data table set after triggering the data table re-association condition. And finally, carrying out data table compression on the filtered data table corresponding to the association diagram node in the updated data table association diagram according to the real-time data table description information included in the data table description information. And data table compression is carried out on the basis of data table association, so that unnecessary occupation of storage resources is reduced. By the method, automatic data table association is realized, and the association efficiency of the data table is improved.

Drawings

The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.

FIG. 1 is a flow chart of some embodiments of a data table association method according to the present disclosure;

FIG. 2 is a schematic diagram of the structure of some embodiments of a data table associating device according to the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

With continued reference to fig. 1, a flow 100 of some embodiments of a data table association method according to the present disclosure is shown. The data table association method comprises the following steps:

step 101, in response to determining that the data table triggering the data table re-association condition exists in the target database, determining data table operation information corresponding to each target data table in the target data table set.

In some embodiments, in response to determining that a data table exists in the target database that triggers a data table re-association condition, an executing body (e.g., computing device) of the data table association method may determine data table operation information corresponding to each target data table in the set of target data tables. Wherein the target data table set is each data table stored in the target database. The target database may be a database to be automatically detected for table associations. The data table operation information characterizes data table operation records for the corresponding target data table within a preset time period. The preset time period represents a time interval during which the data table re-association condition is triggered twice consecutively. The data table operation information includes: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status. Wherein the operation type characterizes the operation type for the data table. For example, the operation type may include at least one of: the method comprises the following steps of data table insertion operation type, data table update operation type, data table creation operation type, data table deletion operation type, data table association relation modification operation and data table structure modification operation. The operation state represents whether the data table operation corresponding to the data table operation record is successfully executed. For example, the operational state may include at least one of: operation success and operation failure. The data table reassociation condition may be detection of a table modification operation for the target data table. The table modification operation may include at least one of: data table association relation modifying operation and data table structure modifying operation. In practice, the execution subject may execute the data table reassociation condition by creating a trigger.

The computing device may be hardware or software. When the computing device is hardware, the computing device may be implemented as a distributed cluster formed by a plurality of servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices listed above. It may be implemented as a plurality of software or software modules, for example, for providing distributed services, or as a single software or software module. The present invention is not particularly limited herein. It should be appreciated that the number of computing devices may have any number of computing devices, as desired for implementation.

In some optional implementations of some embodiments, the determining, by the executing body, data table operation information corresponding to each target data table in the target data table set may include the following steps:

Step one, acquiring a data table operation log sequence corresponding to the target data table in the preset time period.

Wherein the data table operation log is a log file for recording data table operation records for the target data table. In practice, first, the execution body may obtain the log position of the data table operation log through the show command. And then, reading the data table operation log stored in the log position to obtain a data table operation log sequence corresponding to the target data table.

And secondly, carrying out log analysis on the data table operation logs for each data table operation log in the data table operation log sequence to generate candidate data table operation records, and obtaining a candidate data table operation record group.

In practice, the execution body may scan the log content of the data table operation log record to obtain a candidate data table operation record group. For example, the execution body may scan a data table oplog record by: SELECT FROM data table operation log record.

And thirdly, performing operation record filtering on the obtained candidate data table operation record group set according to the operation type and the operation state to obtain a data table operation record sequence included in the data table operation information corresponding to the target data table.

In practice, the executing body may filter, from the candidate data table operation record set, a candidate data table operation record whose operation type is a data table insertion operation type, a data table update operation type, a data table creation operation type, a data table deletion operation type, a data table association relationship modification operation, and a data table structure modification operation, where an operation state is a candidate data table operation record whose operation is successful, as a data table operation record, to obtain the data table operation record sequence.

Step 102, for each target data table in the target data table set, in response to determining that a data table operation record with an operation type being a preset operation type and an operation state being an executed state exists in the data table operation record sequence corresponding to the target data table, determining the target data table as a filtered data table.

In some embodiments, for each target data table in the target data table set, in response to determining that there is a data table operation record in the data table operation record sequence corresponding to the target data table, where the operation type is a preset operation type and the operation state is an executed state, the execution body may determine the target data table as a filtered data table. The preset operation type may include at least one of the following: data table association relation modifying operation and data table structure modifying operation. The operation state represents that the data table operation corresponding to the data table operation record is successful and the execution is successful. In practice, in order to avoid data table damage caused by data table misoperation, the execution of the data table operation may be delayed, that is, the data table operation is not immediately executed, so that the operation state that the operation is successful may be characterized by allowing the data table operation to be executed. The operation state characterizes the successful execution of the data sheet operation for the successful execution.

Step 103, determining data table description information corresponding to each filtered data table in the obtained filtered data table set.

In some embodiments, the executing entity may determine data table description information corresponding to each filtered data table in the obtained filtered data table set. Wherein the data table description information includes: historical data table description information and real-time data table description information. The historical data table description information is data table description information aiming at the filtered data table before triggering the data table re-association condition is not triggered. The real-time data table description information is the data table description information of the filtered data table after triggering the data table re-association condition. The data table description information may be Meta (metadata) information for the filtered data table. In practice, the filtered data table is a target data table of the data table operation record with the operation type being the preset operation type and the operation state being the executed state in the corresponding data table operation record sequence, so that after the triggering of the data table re-association condition, the description information of the data table is changed, and therefore, the filtered data table corresponds to the history data table description information and the real-time data table description information.

In some optional implementations of some embodiments, the determining, by the executing body, data table description information corresponding to each filtered data table in the obtained filtered data table set may include the following steps:

and step one, determining real-time field description information corresponding to the filtered data table.

The real-time field description information characterizes the field description of the filtered data table after the data table re-association condition is triggered. In practice, the real-time field description information may be database fields and database field types included in the filtered data table. Specifically, the execution body may read metadata information after the data table re-association condition is triggered, to obtain real-time field description information.

And secondly, determining real-time table structure description information corresponding to the filtered data table.

In practice, the execution body may obtain the real-time table structure description information corresponding to the filtered data table by reading ResultSetMetaData.

And thirdly, determining the history table association relation description information and the real-time table association relation description information corresponding to the filtered data table.

The history table association relation description information characterizes association relation between the filtered data table and other data tables before the data table re-association condition is triggered. The real-time table association relation description information characterizes association relation between the filtered data table and other data tables after the data table re-association condition is triggered. In practice, the execution subject can determine the history table association relation description information and the real-time table association relation description information corresponding to the filtered data table through the external keys of the filtered data table before and after the data table re-association condition is triggered.

And step four, generating the history data table description information included in the data table description information corresponding to the filtered data table according to the history table association relation description information.

And fifthly, generating real-time data table description information included in the data table description information corresponding to the filtered data table according to the real-time field description information, the real-time table structure description information and the real-time table association relation description information.

And 104, determining a historical data table association diagram for the filtered data table set according to the historical data table description information included in the data table description information.

In some embodiments, the executing entity may determine the history data table association map for the filtered data table set according to history data table description information included in the data table description information. Wherein the history data table association table characterizes association relations of the filtered data tables in the filtered data table set before the data table re-association condition is triggered.

In some optional implementations of some embodiments, the executing body may determine, according to the history data table description information included in the data table description information, a history data table association diagram for the filtered data table set, and may include the following steps:

first, an initial adjacency matrix is generated.

Wherein the initial adjacent matrix is a square matrix. The matrix dimension of the initial adjacency matrix is determined by the number of filtered data tables in the set of filtered data tables. The value of the adjacent matrix in the initial adjacent matrix is 0. For example, the matrix dimension of the initial adjacency matrix is m×m. Wherein M is the number of filtered data tables in the filtered data table set.

A second step of executing the following first processing step, with respect to each of the adjacent matrix values in the initial adjacent matrix, using the adjacent matrix value as a first adjacent matrix value:

And a first sub-step of determining a filtered data table corresponding to the first adjacent matrix value in the filtered data table set according to the matrix value position group corresponding to the first adjacent matrix value, so as to obtain a first filtered data table group.

As an example, the filtered set of data tables may include: filtered data table a, filtered data table B, and filtered data table C. The matrix dimension of the initial adjacency matrix is 3 x 3. The first adjacency matrix value may be a matrix value of a first row and a second column in the initial adjacency matrix. The matrix value position group of the first adjacency matrix value may be [1,2]. The first filtered data table set corresponding to the first adjacency matrix may include: filtered data table a and filtered data table B. The first adjacency matrix value may be a matrix value of a third column of the first row in the initial adjacency matrix. The matrix value position group of the first adjacency matrix value may be [1,3]. The first filtered data table set corresponding to the first adjacency matrix may include: filtered data table a and filtered data table C. The first adjacency matrix value may be a matrix value of a second row and a third column in the initial adjacency matrix. The matrix value position group of the first adjacency matrix value may be [2,3]. The first filtered data table set corresponding to the first adjacency matrix may include: filtered data table B and filtered data table C.

And a second sub-step of determining whether each first filtered data table in the first filtered data table group has a table association relationship according to the history table association relationship description information included in the history data table description information corresponding to the first filtered data table in the first filtered data table group.

In practice, when the history table association relationship description information characterizes that the table association relationship constrained by the foreign key exists in the first filtered data table group, the table association relationship exists in each first filtered data table in the first filtered data table group. When the history table association relation description information characterizes that the table association relation constrained by the foreign key does not exist in the first filtered data tables in the first filtered data table group, the table association relation does not exist in each first filtered data table in the first filtered data table group.

And a third sub-step of updating the matrix value of the first adjacent matrix value in response to the existence.

In practice, the execution body may update the first adjacency matrix value to 1.

And thirdly, generating the historical data table association graph according to the initial adjacent matrix updated by the matrix value.

In practice, since the graph may be characterized by a form of an adjacency matrix, the execution entity may generate the history data table association graph according to the initial adjacency matrix updated by the matrix value.

And 105, updating the association diagram of the historical data table association diagram according to the real-time data table description information included in the data table description information, and obtaining the updated data table association diagram.

In some embodiments, the executing body may update the association map of the history data table according to the real-time data table description information included in the data table description information, to obtain an updated data table association map. In practice, the executing body may update the matrix value of the initial adjacent matrix after updating the matrix value corresponding to the history data table association diagram according to the new table association relationship represented by the real-time data table description information, so as to obtain the updated data table association diagram.

In some optional implementations of some embodiments, the executing body updates the association diagram of the history data table association diagram according to the real-time data table description information included in the data table description information to obtain an updated data table association diagram, and may include the following steps:

a first step of executing the following second processing step, with respect to each of the initial adjacent matrix values after the matrix value update, using the adjacent matrix value as a second adjacent matrix value:

And a first sub-step of determining a filtered data table corresponding to the second adjacent matrix value in the filtered data table set according to the matrix value position group corresponding to the second adjacent matrix value, so as to obtain a second filtered data table group.

The executing body may determine the second filtered data table set by referring to a generating manner of the first filtered data table set, which is not described herein.

And a second sub-step of determining whether each second filtered data table in the second filtered data table group has a table association relationship according to the real-time table association relationship description information included in the history data table description information corresponding to the second filtered data table in the second filtered data table group.

In practice, when the real-time table association relation description information characterizes that the table association relation constrained by the foreign key exists in the second filtered data tables in the second filtered data table group, the table association relation exists in each second filtered data table in the second filtered data table group. When the real-time table association relation description information characterizes that the table association relation constrained by the foreign key does not exist in the second filtered data tables in the second filtered data table group, the table association relation does not exist in each second filtered data table in the second filtered data table group.

And a third sub-step of initializing matrix values of the second adjacent matrix values in response to absence.

In practice, the execution body may initialize the second adjacency matrix value to 0.

And secondly, generating the updated data table association diagram according to the initial adjacent matrix after the initialization of the matrix value.

In practice, since the graph may be characterized by a form of an adjacency matrix, the execution body may generate the updated data table association graph according to the initial adjacency matrix after the matrix value is initialized.

And 106, carrying out data table compression on the filtered data table corresponding to the association diagram node in the updated data table association diagram according to the real-time data table description information included in the data table description information.

In some embodiments, the executing body may compress the data table of the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information. In practice, when the same database field exists between the filtered data tables corresponding to the association graph nodes in the updated data table association graph and the same database field is not an external key or a primary key, the association relationship between tables can be created, and meanwhile, only the same database field exists in one table to compress the data volume. For example, filtered data table a, filtered data table B, and filtered data table C each contain database field M. The execution body may only retain the database field M in the filtered data table a, delete the database fields and the corresponding data in the filtered data table B and the filtered data table C. And creates the filtered data table a and the filtered data table B, and the association relationship between the filtered data table a and the filtered data table B (e.g., create left connection, right connection, inner connection, all-outer connection, etc.). Thereby compressing the data amounts of the filtered data table B and the filtered data table C.

In some optional implementations of some embodiments, the executing body performs data table compression on the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information, and may include the following steps:

The first step of executing the following third processing step, with respect to each adjacent matrix value in the updated data table association diagram, using the adjacent matrix value as a third adjacent matrix value:

And a first sub-step of determining a filtered data table corresponding to the third adjacent matrix value in the filtered data table set according to the matrix value position group corresponding to the second adjacent matrix value, so as to obtain a third filtered data table group.

The generating manner of the third filtered data table set may refer to the generating manner of the second filtered data table set, which is not described herein.

And a second sub-step of determining semantic association fields in the second filtered data table group according to real-time field description information included in the history data table description information corresponding to the second filtered data table to obtain a semantic association field set.

In practice, the executing body may calculate the semantic similarity, and the semantic association field in the second filtered data table set. Specifically, the real-time field description information records the database field in the second filtered data table. Therefore, the executing body can screen the semantic association field set by calculating the semantic similarity of the database fields in the second filtered data table corresponding to the second filtered data table group.

And a third sub-step of performing data table compression on the second filtered data table in the second filtered data table group according to the semantic association field set.

Optionally, the compressing the data table according to the semantic association field set may include the following steps:

For each semantic association field in the set of semantic association fields described above, the following fourth processing step is performed:

step 1: and determining the field atomicity probability of the semantically-related field.

Wherein the field atomicity probability characterizes the probability that the semantically associated field is an atomic type field. The atom type field may be a database field that is not field-splittable. For example, the "gender" database field is an atom type field. The "user identity information" database field may be a non-atomic type field.

In practice, the execution body can generate the field atomicity probability of the semantically related field through a classification model. Specifically, the two classification models can be obtained by training samples in a supervised training mode. The training samples include: database fields and atom type field identification. The atom type field identifies whether the database field included in the characterization training sample is an atom type field.

Step 2: and determining the fields of the atomic types associated with the semantically-related fields in the second filtered data table group as candidate fields in response to the field atomicity probability representation of the semantically-related fields and the non-atomic type fields, and obtaining a candidate field set.

In practice, the executing body may determine, by using a semantic similarity manner, an atomic type field associated with the semantic association field in the second filtered data table set as a candidate field, to obtain a candidate field set. For example, the "user identity information" database field may be a non-atomic type field, and the corresponding set of candidate fields may include: a "name" database field, an "age" database field.

Step 3: and in response to the candidate field set and the semantic association field being located in the same second filtered data table, optimizing real-time table structure description information of the corresponding second filtered data table to realize data table compression of the corresponding second filtered data table.

In practice, when the candidate field set and the semantic association field are located in the same second filtered data table, the execution body may delete the semantic association field and the corresponding data from the second filtered data table. For example, the second filtered data table a may include: a "user identity information" database field, a "name" database field, and an "age" database field. Therefore, the executing body can delete the database field of the user identity information and the corresponding field value so as to achieve the purpose of compressing the data table of the second filtered data table A.

Step 4: and in response to the candidate field set and the semantic association fields being located in each second filtered data table in the second filtered data table group, creating a data table association for the second filtered data table group, and updating real-time table association relationship description information and corresponding real-time table structure description information corresponding to the second filtered data table group so as to realize data table compression of the corresponding second filtered data table.

For example, the second filtered data table a includes a "user identity information" database field. The second filtered data table B includes a "name" database field and an "age" database field. Therefore, the executing body may delete the second filtered data table a including the database field of "user identity information" and the corresponding field value, and associate the second filtered data table a with the second filtered data table B by adopting any one of the connection modes of left connection, right connection and all-external connection, so that when the user identity information is retrieved, the field values corresponding to the database field of "name" and the database field of "age" can be read by connecting the second filtered data table a with the second filtered data table B. Meanwhile, the execution main body can update and synchronize the real-time table association relation description information and the corresponding real-time table structure description information corresponding to the second filtered data table A and the second filtered data table B. So that the real-time table association relation description information can record the association relation between the latest data tables, and the real-time table structure description information can record the table structure of the latest data tables.

The above embodiments of the present disclosure have the following advantageous effects: by the data table association method of some embodiments of the present disclosure, automatic data table association is realized, association efficiency of data tables is improved, and specifically, the reason for causing low data table association efficiency is that: because the association relationship between the data tables often needs to be reset manually when the data tables are changed, when the changed data tables are more, the association efficiency of the data tables is poorer. Based on this, the data table association method of some embodiments of the present disclosure, first, in response to determining that there is a data table triggering a data table re-association condition in a target database, determining data table operation information corresponding to each target data table in a target data table set, where the target data table set is each data table stored in the target database, the data table operation information characterizes a data table operation record for the corresponding target data table in a preset time period, where the preset time period characterizes a time interval during which the data table re-association condition is triggered twice consecutively, the data table operation information includes: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status. And automatically detecting whether a data table needing to be associated with the data table exists in the target database according to the data table re-association condition. And secondly, for each target data table in the target data table set, determining the target data table as a filtered data table in response to determining that a data table operation record with the operation type being a preset operation type and the operation state being an executed state exists in a data table operation record sequence corresponding to the target data table. The filtering of the data table is realized by combining the operation record of the data table, so that the occupation of cache resources caused by the pre-caching of the data table is avoided. Next, determining data table description information corresponding to each filtered data table in the obtained filtered data table set, wherein the data table description information comprises: historical data table description information and real-time data table description information. And determining the description information of the data table before and after the execution of the trigger data table re-association condition. Further, according to the history data table description information included in the data table description information, a history data table association diagram for the filtered data table set is determined. And determining the association relation of the filtered data tables in the filtered data table set before triggering the data table re-association condition. In addition, according to real-time data table description information included in the data table description information, carrying out association diagram update on the history data table association diagram to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: and the association graph nodes have corresponding relations with the compressed data table. And determining the association relation of the filtered data tables in the filtered data table set after triggering the data table re-association condition. And finally, carrying out data table compression on the filtered data table corresponding to the association diagram node in the updated data table association diagram according to the real-time data table description information included in the data table description information. And data table compression is carried out on the basis of data table association, so that unnecessary occupation of storage resources is reduced. By the method, automatic data table association is realized, and the association efficiency of the data table is improved.

With further reference to fig. 2, as an implementation of the method shown in the above figures, the present disclosure provides some embodiments of a data table associating apparatus, which correspond to those method embodiments shown in fig. 1, and which are particularly applicable in various electronic devices.

As shown in fig. 2, the data table associating means 200 of some embodiments includes: the first determination unit 201, the second determination unit 202, the third determination unit 203, the fourth determination unit 204, the association map updating unit 205, and the data table compression unit 206. Wherein the first determining unit 201 is configured to determine, in response to determining that a data table triggering a data table re-association condition exists in a target database, data table operation information corresponding to each target data table in a target data table set, where the target data table set is each data table stored in the target database, the data table operation information characterizes a data table operation record for the corresponding target data table within a preset time period, the preset time period characterizes a time interval in which the data table re-association condition is triggered twice consecutively, and the data table operation information includes: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status; a second determining unit 202 configured to determine, for each target data table in the target data table set, the target data table as a filtered data table in response to determining that a data table operation record whose operation type is a preset operation type and whose operation state is an executed state exists in a data table operation record sequence corresponding to the target data table; a third determining unit 203, configured to determine data table description information corresponding to each filtered data table in the obtained filtered data table set, where the data table description information includes: historical data table description information and real-time data table description information; a fourth determining unit 204 configured to determine a history data table association map for the filtered data table set based on history data table description information included in the data table description information; the association diagram updating unit 205 is configured to update the association diagram of the history data table association diagram according to the real-time data table description information included in the data table description information, so as to obtain an updated data table association diagram, where the updated data table association diagram includes: the association graph node sets have corresponding relations with the compressed data table; and a data table compressing unit 206 configured to compress the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information.

It will be appreciated that the elements described in the data table association device 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above for the method are equally applicable to the data table associating device 200 and the units contained therein, and are not described herein.

Referring now to fig. 3, a schematic diagram of an electronic device (e.g., computing device) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with programs stored in a read-only memory 302 or programs loaded from a storage 308 into a random access memory 303. In the random access memory 303, various programs and data necessary for the operation of the electronic device 300 are also stored. The processing means 301, the read only memory 302 and the random access memory 303 are connected to each other by a bus 304. An input/output interface 305 is also connected to the bus 304.

In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from read only memory 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.

It should be noted that, the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (Hyper Text Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: in response to determining that a data table triggering a data table re-association condition exists in a target database, determining data table operation information corresponding to each target data table in a target data table set, wherein the target data table set is each data table stored in the target database, the data table operation information represents a data table operation record aiming at the corresponding target data table in a preset time period, the preset time period represents a time interval when the data table re-association condition is triggered twice consecutively, and the data table operation information comprises: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status; for each target data table in the target data table set, determining the target data table as a filtered data table in response to determining that a data table operation record with a preset operation type and an executed operation state exists in a data table operation record sequence corresponding to the target data table; determining data table description information corresponding to each filtered data table in the obtained filtered data table set, wherein the data table description information comprises: historical data table description information and real-time data table description information; determining a history data table association diagram aiming at the filtered data table set according to history data table description information included in the data table description information; and updating the association diagram of the historical data table association diagram according to the real-time data table description information included in the data table description information to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: the association graph node sets have corresponding relations with the compressed data table; and carrying out data table compression on the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes a first determination unit, a second determination unit, a third determination unit, a fourth determination unit, a correlation map updating unit, and a data table compression unit. The names of the units are not limited to the unit itself in some cases, for example, the second determining unit may be further described as "for each target data table in the target data table set, in response to determining that there is a data table operation record whose operation type is a preset operation type and whose operation state is an executed state in the data table operation record sequence corresponding to the target data table, determining the target data table as a unit of a filtered data table".

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims (10)

1. A data table association method, comprising:

In response to determining that a data table triggering a data table re-association condition exists in a target database, determining data table operation information corresponding to each target data table in a target data table set, wherein the target data table set is each data table stored in the target database, the data table operation information characterizes a data table operation record aiming at the corresponding target data table in a preset time period, the preset time period characterizes a time interval when the data table re-association condition is triggered twice consecutively, and the data table operation information comprises: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status;

For each target data table in the target data table set, determining the target data table as a filtered data table in response to determining that a data table operation record with a preset operation type and an executed operation state exists in a data table operation record sequence corresponding to the target data table;

determining data table description information corresponding to each filtered data table in the obtained filtered data table set, wherein the data table description information comprises: historical data table description information and real-time data table description information;

Determining a historical data table association diagram for the filtered data table set according to the historical data table description information included in the data table description information;

and updating the association diagram of the historical data table association diagram according to the real-time data table description information included in the data table description information to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: the association graph node sets have corresponding relations with the compressed data table;

and carrying out data table compression on the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information.

2. The method of claim 1, wherein the determining data table operation information corresponding to each target data table in the set of target data tables comprises:

acquiring a data table operation log sequence corresponding to the target data table in the preset time period;

For each data table operation log in the data table operation log sequence, carrying out log analysis on the data table operation log to generate candidate data table operation records, and obtaining a candidate data table operation record group;

and according to the operation type and the operation state, performing operation record filtering on the obtained candidate data table operation record group set to obtain a data table operation record sequence included in the data table operation information corresponding to the target data table.

3. The method of claim 2, wherein the determining the data table description information corresponding to each filtered data table in the resulting set of filtered data tables comprises:

Determining real-time field description information corresponding to the filtered data table, wherein the real-time field description information characterizes field description of the filtered data table after the data table re-association condition is triggered;

determining real-time table structure description information corresponding to the filtered data table;

Determining history table association relation description information and real-time table association relation description information corresponding to the filtered data table;

Generating historical data table description information included in the data table description information corresponding to the filtered data table according to the historical table association relation description information;

And generating real-time data table description information included in the data table description information corresponding to the filtered data table according to the real-time field description information, the real-time table structure description information and the real-time table association relation description information.

4. The method of claim 3, wherein the determining a historical data table association map for the filtered set of data tables from historical data table description information included in the data table description information comprises:

Generating an initial adjacency matrix, wherein the initial adjacency matrix is a square matrix, the matrix dimension of the initial adjacency matrix is determined by the number of filtered data tables in the filtered data table set, and the adjacency matrix value in the initial adjacency matrix is 0;

for each adjacency matrix value in the initial adjacency matrix, taking the adjacency matrix value as a first adjacency matrix value, performing the following first processing step:

Determining a filtered data table corresponding to the first adjacent matrix value in the filtered data table set according to the matrix value position group corresponding to the first adjacent matrix value, so as to obtain a first filtered data table group;

Determining whether a table association relationship exists in each first filtered data table in the first filtered data table group according to history table association relationship description information included in history data table description information corresponding to the first filtered data table in the first filtered data table group;

In response to the presence, matrix value updating the first adjacency matrix value;

and generating the historical data table association graph according to the initial adjacent matrix updated by the matrix value.

5. The method according to claim 4, wherein the updating the association map of the history data table according to the real-time data table description information included in the data table description information to obtain the updated data table association map includes:

for each adjacent matrix value in the initial adjacent matrix after the matrix value update, taking the adjacent matrix value as a second adjacent matrix value, executing the following second processing step:

determining a filtered data table corresponding to the second adjacent matrix value in the filtered data table set according to the matrix value position group corresponding to the second adjacent matrix value to obtain a second filtered data table group;

Determining whether a table association relationship exists in each second filtered data table in the second filtered data table group according to real-time table association relationship description information included in the history data table description information corresponding to the second filtered data table in the second filtered data table group;

In response to absence, initializing a matrix value for the second adjacency matrix value; and generating the updated data table association graph according to the initial adjacent matrix after the matrix value initialization.

6. The method of claim 5, wherein the performing data table compression on the filtered data table corresponding to the association graph node in the updated data table association graph according to the real-time data table description information included in the data table description information includes:

For each adjacency matrix value in the updated data table association graph, taking the adjacency matrix value as a third adjacency matrix value, executing the following third processing step:

determining a filtered data table corresponding to the third adjacent matrix value in the filtered data table set according to the matrix value position group corresponding to the second adjacent matrix value to obtain a third filtered data table group;

determining semantic association fields in the second filtered data table group according to real-time field description information included in the history data table description information corresponding to the second filtered data table to obtain a semantic association field set;

And carrying out data table compression on the second filtered data table in the second filtered data table group according to the semantic association field set.

7. The method of claim 6, wherein said performing data table compression on the second filtered data table of the second filtered data table set according to the set of semantic association fields comprises:

For each semantic association field in the set of semantic association fields, performing the fourth processing step of:

determining the field atomicity probability of the semantic association field, wherein the field atomicity probability characterizes the probability that the semantic association field is an atomic type field;

Responding to the field atomicity probability to represent the non-atomic type field of the semantic association field, determining the field of the atomic type associated with the semantic association field in the second filtered data table group as a candidate field, and obtaining a candidate field set;

Optimizing real-time table structure description information of the corresponding second filtered data table in response to the candidate field set and the semantic association field being located in the same second filtered data table, so as to realize data table compression of the corresponding second filtered data table;

And in response to the candidate field set and the semantic association field being located in each second filtered data table in the second filtered data table group, creating a data table association for the second filtered data table group, and updating real-time table association relation description information and corresponding real-time table structure description information corresponding to the second filtered data table group so as to realize data table compression of the corresponding second filtered data table.

8. A data table associating apparatus comprising:

A first determining unit configured to determine, in response to determining that a data table triggering a data table re-association condition exists in a target database, data table operation information corresponding to each target data table in a target data table set, wherein the target data table set is each data table stored in the target database, the data table operation information characterizes a data table operation record for the corresponding target data table within a preset time period, the preset time period characterizes a time interval at which the data table re-association condition is triggered twice consecutively, the data table operation information includes: a sequence of data table operation records, the data table operation records in the sequence of data table operation records comprising: operation type and operation status;

A second determining unit configured to determine, for each target data table in the target data table set, the target data table as a filtered data table in response to determining that a data table operation record whose operation type is a preset operation type and whose operation state is an executed state exists in a data table operation record sequence corresponding to the target data table;

A third determining unit configured to determine data table description information corresponding to each filtered data table in the obtained filtered data table set, where the data table description information includes: historical data table description information and real-time data table description information;

A fourth determining unit configured to determine a history data table association map for the filtered data table set based on history data table description information included in the data table description information;

the association diagram updating unit is configured to update the association diagram of the historical data table association diagram according to the real-time data table description information included in the data table description information to obtain an updated data table association diagram, wherein the updated data table association diagram comprises: the association graph node sets have corresponding relations with the compressed data table;

And the data table compression unit is configured to perform data table compression on the filtered data table corresponding to the association diagram node in the updated data table association diagram according to the real-time data table description information included in the data table description information.

9. An electronic device, comprising:

one or more processors;

A storage device having one or more programs stored thereon;

when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1 to 7.

10. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1 to 7.