JPH06324930A - Data processor and data processing method - Google Patents

Abstract

PURPOSE:To provide a data processor capable of simultaneously updating the data related to main data while keeping the consistency of data in updating the main data. CONSTITUTION:A processing method storage device 2 stores a check rule for defining limit conditions for the contents of the main data, a local rule for defining a method to update the contents of the main data themselves by using the contents of the main data, a fetch rule for defining a method to update the contents of the main data by using the contents of the data related to the main data, and a derivation rule for updating the contents of the data related to the main data by using the contents of the main data. A data update processor 3 extracts any relevant rule from the processing method storage device 2, executes the update processing of the main data and the update processing of the related data according to that rule and further executes the update processing of further related data derived from the update of the related data.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a data processing device and a data processing method, and more particularly to a data processing device and a data processing method for updating related data related to the data when updating the data.

[0002]

2. Description of the Related Art Conventionally, in a data processing device using a computer, the data updating process has been defined by a system developer and given on a program. Therefore, the system developer has studied the update processing method of a certain data and the related data related to the data in all cases, coded and tested the update processing method in all cases, and described it in the program. Therefore, the developed program was very complicated.

[0003]

As described above, since the program becomes very complicated, it takes a long time to develop and test the program and the development cost is high. Moreover, the reliability of the update process was low, and it was very difficult to maintain data consistency. Moreover, there is a problem that the logic cannot be easily changed because the program is very complicated.

An object of the present invention is to provide a data processing device and a data processing method capable of updating related data that are complicatedly related by defining a relationship between some data while maintaining its consistency. That is.

[0005]

[Means for Solving the Problems]

(1) First Invention A data processing apparatus according to the first invention comprises a processing method storage means and a processing means.

[0006] The processing method storage means, for each type of data, constraint conditions regarding the content of the data, a first processing method for processing the content of the data using the content of the data, and related data related to the data. A second processing method for processing the content of the data using the content of the above, and a third processing method for processing the content of the related data related to the data using the content of the data are stored.

At the time of updating the main data, which is the center of the data updating process, the processing means stores a constraint condition, a first processing method, a second processing method and When the applicable constraint condition or the applicable process method among the third process methods is read, data processing is performed according to the read constraint condition or the process method, and the related data related to the main data is updated by the data process. And a constraint condition, a first processing method, a second processing method, and a third processing method from the processing method storage unit based on the type of updated related data and the updating method.
The applicable processing condition or applicable processing method is read out, and data processing is performed according to the read constraint condition or processing method.

(2) Second Invention A data processing method according to the second invention includes the following steps. For each type of data, the constraint condition regarding the content of the data, the first processing method for processing the content of the data using the content of the data, the content of the data using the content of the related data related to the data And a third processing method for processing the content of the related data related to the data by using the content of the data.

At the time of updating main data, which is the center of data updating, stored constraint conditions, first processing method, second processing method, and third processing method are stored based on the type and updating method of the main data. When the applicable constraint condition or processing method is read, data processing is performed according to the read constraint condition or processing method, and the related data related to the main data is updated by the data processing,
Based on the updated related data type and update method, the applicable constraint condition or applicable processing method among the stored constraint conditions, the first processing method, the second processing method, and the third processing method is read. , Data processing is performed according to the read constraint condition or processing method.

[0010]

In the data processing apparatus according to the first aspect of the invention and the data processing method according to the second aspect of the invention, when the main data is updated, based on the type and update method of the main data,
A corresponding constraint condition or a corresponding processing method is read, and data processing is performed according to the read constraint condition or processing method. When the related data is updated by the data processing, the applicable constraint condition or the applicable processing method is read based on the type and update method of the related data, and the data is read according to the read constraint condition or processing method. Processing is performed.

When the constraint is read, only the data satisfying the constraint is processed. When the first processing method is read, the content of the data itself is updated using the content of the data. When the second processing method is read, the content of the relevant data is updated using the content of the related data. When the third processing method is read, the content of the relevant data is updated using the content of the relevant data.

As described above, by only storing the constraint condition, the first processing method, the second processing method, and the third processing method for each data type, the main data is updated when the main data is updated. The related data derived from can be processed at the same time. Therefore, even if a plurality of data have a complicated relationship, it is possible to update the related data at the same time while maintaining the consistency of the data.

[0013]

1 is a block diagram showing the overall construction of a data processing apparatus according to an embodiment of the present invention. 1 includes a data storage file 1, a processing method storage device 2, a data update processing device 3, and a data input device 4.
including.

The data storage file 1 stores the data input and processed by the data processing apparatus for each data type. Therefore, the structure of the record in the data storage file 1 is the same as the structure of the stored data. In this embodiment, the data storage file 1 includes an order file 11 that stores order data, an inventory file 12 that stores inventory data, and a manufacturing order file 13 that stores manufacturing order data.

The processing method storage device 2 includes a check rule storage unit 21 for storing check rules, a local rule storage unit 22 for storing local rules, a fetch rule storage unit 23 for storing fetch rules, and a derivation rule for storing derivation rules. The bastion rule storage unit 24. These rules are stored in the respective corresponding storage units prior to the execution of data processing, together with the application timing at which they are applied. Hereinafter, the contents stored in the processing method storage device 2 will be referred to as an associated definition file.

Here, the application timing indicates which update method the rule is applied to, and whether the rule is added to data, changed, or deleted. Indicates when it applies.

The check rule defines a constraint condition for the content of the data. Only data satisfying this check rule is stored in the data storage file 1.

The local rule defines a method of updating the content of the data itself using the content of the data.
The fetch rule defines a method of updating the content of the data using the content of the related data related to the data. The data is stored in the data storage file 1 after being updated by the local rule or the fetch rule.

The derivation rule defines a method of updating the content of related data related to the data using the content of the data. Related data is updated by this derivation rule.

When the data input device 4 inputs data, the data update processing device 3 determines the type of the data and the update method, and based on these, the rule to be applied is stored in the processing method storage device. Extract from 2.
Then, the data update process is executed according to the extracted rule. When the related data is updated by the update processing, the data update processing device 3 extracts the rule to be applied from the processing method storage device 2 based on the type of the related data and the update method, and the extracted rule is extracted. Update data according to the rules.

FIG. 2 shows an example of the association definition file stored in the processing method storage device 2. This related definition file includes a rule type field 21, a main data name field 22, a related data field 23, an application timing field 24 and a processing content field 25 for each rule. The related data field 23 includes a data name field 23a and a key field 23b.

The rule type field 21 stores the type of rule to be applied. The main data name field 22 stores the type of main data to which the rule is applied, and the related data field 23 stores the related data type and key item name updated in association with the main data. It In the application timing field 24, “◯” is used to specify which update method of the data addition process, the data change process, and the data deletion process should be applied. The processing content field 25 stores the processing method in the rule.

The check rule C is stored in the first line of the related definition file. This check rule C is “inventory quantity” ≧ 0 when inventory data is added or changed.
Indicates that it is necessary to satisfy Only inventory data satisfying this condition is stored in the inventory file 12.

The derivation rule D1 is stored in the second line. In this derivation rule D1, when the stock data is changed and the "stock quantity" of the stock data is 0, the production order data having the same "product code" as the stock data is changed to the "production order quantity". "= 50
And "delivery date" = current day + 5 days are set, and the production instruction data is stored in the production instruction file 13. The derivation rule D2 is shown in the third line. In this derivation rule D2, when order data is added, changed, or deleted, the "order quantity" in the order data is changed from the "stock quantity" in the stock data having the same "product code" as the order data. Then, a new “stock quantity” is set in the stock data, and the stock data is stored in the stock file 12.

The fetch rule F is stored in the fourth row. In this fetch rule F, when the order data is added or changed, the "unit price" is taken out from the inventory data having the same "product code" as the order data and set as the "unit price" in the order data. The order data is stored in the order file 11. The local rule L is stored in the fifth line. In this local rule L, when the order data is added or changed, the "unit price" and the "order quantity" in the order data are multiplied, and the result is set to the "total amount" in the order data. .

The processing content field 25 of the derivation rule D2 shows the update processing method when data is added (positive case) and the update processing method when data is changed or deleted (negative case). Not not. When the order data is changed, the difference between the new “order quantity” and the old “order quantity” of the order data is subtracted from the “stock quantity” in the corresponding inventory data, and the result is set in the stock data. Further, when deleting data, the "order quantity" in the order data is added to the "stock quantity" in the corresponding stock data, and the result is set as the new "stock quantity" in the stock data.

As described above, in the derivation rule, only the processing content in the positive case is defined in the processing content field 25. When updating the negative case, the data update processing device 3 converts the update processing method in the positive case into the update processing method in the negative case.

Next, the operation of the data processing apparatus shown in FIG. 1 will be described with reference to the flow charts shown in FIGS.

When data is input from the data input device 4 (step S1), the data update processing device 3 first
The type of data and the updating method are determined, and the related definition file in the processing method storage device 2 is searched based on them (step S2). If there is a rule applied in that condition in the related definition file, that rule is read (step S3), and it is determined whether the rule is a derivation rule and the input data update method is a negative case. It is determined (step S4).

When the read rule is the derivation rule and the input data update method is the negative case, the data update processing device 3 changes the related data update processing method in the positive case to the negative case. The relevant data is converted into the update processing method (step S5), and the update processing is executed according to the converted rule (step S6). When the input data update method is the positive case or when the read rule is not the derivation rule, the data update processing device 3 executes the update processing according to the read rule (step S7).

When the applied rule is the check rule, the data update processing device 3 determines whether or not the input data satisfies the constraint condition (step S).
8). If the input data does not satisfy the constraint condition, an error message is output (step S1).
7).

When the related data is not updated by the applied rule, that is, when the applied rule is not the derivation rule (step S9), the process returns to step S2. When the applied rule is the derivation rule (step S9), the data update processing device 3
Determines the type of updated related data and its updating method, and searches the related definition file in the processing method storage device 2 based on them (step S10). If there is no rule applied in that condition in the related definition file (step S11), the process returns to step S2.

If the related definition file has a rule applied under the condition, the data update processing device 3 reads the rule (step S11), and the rule is the derivation rule and the updated related data. It is determined whether or not the updating method of is a negative case (step S12).

When the read rule is the derivation rule and the updated related data update method is a negative case, the data update processing device 3 determines the related data update processing method in the positive case to be a negative case. It is converted to the related data update processing method in step S13, and the update processing is executed according to the converted rule (step S14). When the update method of the updated related data is a positive case or when the read rule is not the derivation rule, the data update processing device 3 executes the update processing according to the read rule (step S1).
5).

When the applied rule is the check rule, the data update processing device 3 determines whether or not the updated related data satisfies the constraint condition (step S16). If the updated related data does not satisfy the constraint condition, an error message is output (step S17). If the related data satisfies the check rule (step S16), the process returns to step S10.

In this way, step S1 is performed for the related data that is directly derived from the input data and updated.
The processing from 0 to step S16 is executed, and further,
The processes from step S10 to step S16 are executed for all the further related data that is derived and updated by updating the related data.

After the processes of steps S2 to S16 are executed for all the rules to be applied to the input data, the updated data and the related data updated as a result thereof are stored in the data storage file 1, respectively. It is stored (step S18).

The operation of the data processing apparatus shown in FIG. 1 will be described below in more detail with reference to the example shown in FIG. FIG. 5 shows an example of inventory data stored in the inventory file 12. In this example, the unit price of the product with the product code AAAAA is 1000 yen and the stock quantity is 20 pieces. The unit price of the product with the product code BBBBB is 3000 yen, and the stock quantity is 5.

Here, the product code BBB from the customer xxx
It is assumed that 10 BB products have been ordered. in this case,
The order data is input to the data update processing device 3 by the data input device 4 (step S1).

The data update processing device 3 determines that the input data is the order data and the update method is the addition process (positive case) of the order data, and in the relation definition file in the processing method storage device 2. The main data name is order data, and a rule applied when data is added is searched (step S2). In the association definition file of FIG. 2, the derivation rule D2, the fetch rule F, and the local rule L from the third line to the fifth line are extracted (step S3).

The data update processing device 3 sequentially executes update processing according to the extracted rule. First, an update process for order data is executed according to the derivation rule D2 in the third line (steps S4 to S).
6). That is, the stock data of the product code = BBBBB is read from the stock file 12, the stock quantity = 5 pieces in the stock data is subtracted from the order quantity = 10 pieces in the order data, and the new stock quantity is -5 pieces. It is calculated.

In this case, since the inventory data is changed in relation to the input order data (step S9), the data update processing device 3 sets the main data in the associated definition file in the processing method storage device 2 as inventory data. Search for rules that are data and that are applied at the time of modification (step S1)
0). In the relation definition file of FIG. 2, the check rule C and the derivation rule D1 on the first and second lines are extracted (step S11).

The data update processing device 3 sequentially executes update processing according to the extracted rules. First, the check rule C on the first line is applied. In this case, the new inventory quantity = -5 does not satisfy the constraint condition that the inventory quantity = 0, so an error message is output (step S16,
In S17), the input order data is discarded.

Next, the product code BBBB from the customer yyy
It is assumed that 5 items of B are ordered. The order data is input from the data input device 4 to the data update processing device 3 (step S1).

Also in this case, as in the above example, first,
Derivation rules D2, fetch rules F, and local rules L from the third line to the fifth line in the relation definition file of FIG. 2 are extracted (steps S2, S).
3) The rules are applied in order.

First, an update process for order data is executed according to the derivation rule D2 (steps S4 to S6). Therefore, product code = BBBBB
The stock quantity becomes 0 in the stock data.

Also in this case, as in the above example, since the inventory data is changed in relation to the input order data (step S9), the main data name is the inventory data and is applied at the time of the change. Rules are searched (step S
10). Also in this case, the check rules C and the derivation rules D1 on the first and second lines in the relation definition file of FIG. 2 are extracted (step S11),
An update process related to inventory data is executed according to those rules.

First, in the check rule C on the first line, the new inventory quantity = 0 satisfies the constraint condition that the inventory quantity ≧ 0 (step S16), and then the derivation rule on the second row. D1 applies.

According to the derivation rule D1 on the second line, new production instruction data is added to the production instruction file 13 when the stock quantity is zero. Here, since the new stock quantity = 0 satisfies the condition of the derivation rule D1, the product code = BBBBBB, the production order quantity = 5.
New production order data of 0 pieces, delivery date = current day + 5 days is prepared (steps S12 and S15).

In this way, the check rule C and the derivation rule D1 regarding the inventory data are applied in relation to the derivation rule D2 regarding the order data.

After that, the fetch rule F regarding the order data is applied (steps S2 to S7). As a result, the unit price from the stock data of product code = BBBBB = 300
Zero yen is read and set in the order data. further,
The local rule L regarding the order data is applied (step S2 to step S7). As a result, the unit price in the order data = 3000 yen is multiplied by the order quantity = 5 in the order data, and the total amount = 15,000 yen is set in the order data.

In this way, when all the rules related to the input data among the rules stored in the processing method storage device 2 are applied, the updated data, the updated related data, and the updated related data are applied. Further related data that is derived from and updated is stored in the data storage file 1 (step S18).

In the above example, the inputted and updated order data is stored in the order file 11, the manufacturing order data is additionally stored in the manufacturing order file 13, and the inventory data is changed and stored in the inventory file 12.

In the above embodiment, regarding the derivation rule, only the processing content in the positive case is defined in the related definition file, and the processing content in the negative case is inferred from the processing content in the positive case by the data update processing device 3. However, a rule is defined for each application timing, and the data update processing device 3
However, the processing content in the defined rule may be executed as it is.

[0055]

As described above, according to the first and second aspects of the present invention, the constraint condition and the first to third processing methods are stored for each data type, so that the main data is updated when the main data is updated. The processing of all relevant data that results from updating the data can be performed simultaneously.

Therefore, even if a plurality of data have complicated relationships, related data can be updated at the same time while maintaining the consistency of the data. In addition, the reliability of the update process is improved and the logic can be easily changed. Further, the time for developing and testing the program is shortened, and the development cost is reduced. .

[Brief description of drawings]

FIG. 1 is a block diagram showing an overall configuration of a data processing device according to an embodiment of the present invention.

FIG. 2 is a diagram showing an example of a related definition file stored in a processing method storage device shown in FIG.

FIG. 3 is a flowchart for explaining the operation of the data processing device of FIG.

FIG. 4 is a flowchart for explaining the operation of the data processing device of FIG.

5 is a diagram showing an example of inventory data stored in the data storage file shown in FIG. 1. FIG.

[Explanation of symbols]

 1 data storage file 2 processing method storage device 3 data update processing device 4 data input device 11 order file 12 inventory file 13 manufacturing instruction file 21 check rule storage unit 22 local rule storage unit 23 fetch rule storage unit 24 derivation rule storage unit In the drawings, the same reference numerals indicate the same or corresponding parts.

Claims (2)

[Claims] 1. A constraint condition regarding the content of the data, a first processing method for processing the content of the data using the content of the data, and a content of related data related to the data are used for each type of data. And a third processing method for processing the content of related data related to the data by using the content of the data.
Processing method storing means for storing the processing method of, and at the time of updating the main data which is the center of the data updating processing, the constraint condition, the first processing from the processing method storing means based on the type of the main data and the updating method. A corresponding restriction condition or a corresponding processing method among the method, the second processing method, and the third processing method is read, and data processing is performed according to the read restriction condition or processing method.
When the related data related to the main data is updated by the data processing, the applicable constraint condition or the applicable processing method is read from the processing method storage means based on the type and update method of the updated related data. ,
A data processing device, comprising: a processing unit that performs data processing according to the read constraint condition or processing method. 2. A constraint condition relating to the content of the data, a first processing method of processing the content of the data using the content of the data, and a content of related data related to the data are used for each type of data. And a third processing method for processing the content of related data related to the data by using the content of the data.
The processing method is stored, and the stored constraint condition, the first processing method, and the second processing method are stored based on the type of the main data and the update method at the time of updating the main data, which is the center of the data update processing. And reading the applicable constraint condition or the applicable processing method from the third processing method, performing data processing according to the read constraint condition or processing method, and updating the related data related to the main data by the data processing. And the stored constraint condition, the first
Processing method, the second processing method, and the third processing method, the corresponding constraint condition or the corresponding processing method is read, and data processing is performed according to the read constraint condition or processing method. .