JPH09179882A - Data base access system by cpu - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide the data base access system which enables the CPU to write and read a large amount of data in and out of a data base. SOLUTION: To access respective divisional data bases 1D-nD of matrix constitution of 1st-(n)th data in the format that time information is added to data by 1st-(m)th kinds, respective data storage destination definition tables 37, a table 44 wherein maximum data lengths of kind data are defined for the data numbers by the kinds of the respective data, a table 45 wherein column addresses are defined for the numbers are provided. Here, a 1st converting means 40 recognizes a received data storage destination from the respective data storage destination tables 37, a 3rd converting means 41 recognizes the (Tn)th row address corresponding to the difference time Tn between the head of recognition 1D-nD and reception time information, and a 2nd converting means 42 finds data correspondence numbers by reception kinds from the table 44, finds its number correspondence row address from the table 45, and stores received data in the storage address of the intersection of the column address and the recognition row address of the 3rd converting means 41.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a database access system using a CPU. In this database access method using a CPU, for example, a large amount of data transmitted from a plurality of branch offices is received by the central office, and the CPU of the central office
Under the control of (1), the received data is written and stored in a database having a vertical and horizontal table configuration (matrix configuration), and the stored data is read out and a predetermined arithmetic processing is performed.

In order to perform such processing, since the amount of received data is large, the operator grasps the number of received data in order to store it in a divided database, and calculates the required number of divided databases. Since such work is required, it takes time and labor, or the CPU needs to perform processing for recognizing where to store the received data and storing it in the database, and thus the processing takes time. Therefore, there is a demand for a method that saves the labor of the operator and shortens the access processing time.

[0003]

2. Description of the Related Art A conventional database access method using a CPU for processing a large amount of data will be described by taking a dam various quantity system as an example.

The dam quantity system is constructed such that the information collected in the station buildings provided for each dam existing in various places is further collected in one central station and the collected information is stored in the database.

FIG. 13 is a schematic block diagram of a dam quantity system in one station, and FIG. 14 is a flow chart for explaining a data receiving process by a CPU in the station.
FIG. 16 is a data table diagram for hourly information calculation, and FIG. 16 is a flow chart for explaining a data storage process in the data table for hourly information computation by the CPU in the station.

In FIG. 13, 1 is an input device and 2 is a CP
U, 3 is a memory of the CPU, 4 is a file, 5 is a console, 6 is a printer, 7 is a table such as a display, and 8 is a dumb gate.

First, rainfall, river water level, water storage level, opening,
Data related to dam amounts such as discharge amount are input to the input device 1 in units of seconds, and the CPU in the station is every 1 minute from the input device 1.
2 is sent.

Now, the process of receiving data relating to various dam quantities by the CPU 2 will be described with reference to the flow chart shown in FIG. As shown in step S1 of FIG.
U2 stores the data received every minute in the memory 3 as shown in FIG.
The data is stored in the hourly information calculation data table 10 shown in FIG.

In the hourly information calculation data table 10,
Water level (m) 11, water storage (m ³ ) 12, discharge (m ³ / sec) 13,
Inflow (m ³ / sec) 14, Gate opening (mm) 15, Adjusted flow rate (m
³ / sec) 16 or the like for each data type such as counter 17, integrated value 18, maximum value time 19, maximum value 20, minimum value time 21,
The area of the minimum value 22 and the average value 23 is secured.

When the CPU 2 receives and stores data every one minute, the CPU 2 performs the following processing for each type of all input data as shown in step S1 in the flowchart of FIG.

As shown in step S2, first, the counter 17 is incremented, and as shown in step S3,
The input data is added to the integrated value 18. Next, step S
As shown in FIG. 4, it is determined whether the input data added in step S3 is the first date information. If the determination result is NO (N), it is determined whether the input data is larger than the maximum value 20 as shown in step S5.

As a result of the judgment, if the input data is YES (Y) larger than the maximum value 20, the data input time is stored in the maximum value time 19 as shown in step S6, and the input data is stored as shown in step S7. Is stored in the maximum value 20.

Next, as shown in step S8, if the input data is YES, which is smaller than the minimum value 22, the data input time is stored in the minimum value time 21 as shown in step S9, and as shown in step S10. The input data is stored in the minimum value 22.

If YES in step S4, which is the first input data of the day information, in step S12.
The data input time is stored in the maximum value time 19 and the minimum value time 21 as shown in, and the input data is stored in the maximum value 20 and the minimum value 22 as shown in step S13.

When the storage process in step S1 of FIG. 14 is completed in this way, it is determined whether the present time is hour (00 minute every hour) as shown in step S2. If the result of this determination is NO, the entire processing ends (END), but if YES, as shown in step S3,
The hour information is calculated based on the data in the hour information calculation data table 10. That is, the CPU 2 calculates the hourly information at every hour based on the information received every minute and totaled for one hour.

The arithmetic processing of the hourly information will be described with reference to the flowchart shown in FIG. Step S of FIG.
As shown in FIG. 1, the following processing is performed for each type of all input data.

As shown in step S2, a value obtained by dividing the integrated value 18 by the counter value 17 is obtained as an average value 23 for each data type, and is stored in the hourly information calculation data table 10 as shown in step S3. To do.

Next, as shown in step S4, it is determined whether or not the input data of all types have been calculated. If the result of this determination is NO, the process returns to step S2 to perform the calculation processing again, and if YES. Ends the calculation.

When the calculation of all data types is completed in this way, the result (counter 17, integrated value 18, average value 23) is stored in the file 4 as shown in step S4 of FIG.
(See FIG. 13), the calculation result is transmitted to the central station as shown in step S5.

Next, as shown in step S6 of FIG. 14, it is determined whether the current time is 9:00 am. If the result of this determination is NO, the entire processing ends (END), but if YES, as shown in step S7,
The CPU 2 reads the hourly information for one day from the file 4, and calculates the day information as shown in step S8.

That is, the CPU 2 executes 1 at 9:00 am every day.
The hourly information for the day (only the counter value 17, the integrated value 18, and the average value 23) is read from the file 4 into the memory 3, and the day information is calculated based on this information.

The calculation processing of this day information will be described with reference to the flowchart shown in FIG. Step S1 of FIG.
As shown in, the following processing is performed for each type of all input data.

As shown in step S2, the counter values 17 of the hour information are summed to calculate the counter value of the day information,
Next, as shown in step S3, the integrated value 1 of the hour information is 1
8 is totaled and the integrated value of day information is calculated.

Next, as shown in step S4, a value obtained by dividing the integrated value of day information by the counter value of day information is obtained as an average value of day information, and as shown in step S5, hour information calculation is performed. The maximum value 20, the maximum value time 19, the minimum value 22, and the minimum value time 21 in the data table 10 are set as the maximum value, the maximum value time, the minimum value, and the minimum value time of the day information, and the respective values are not shown in the figure. Stored in the data table for information calculation.

Next, as shown in step S6, it is determined whether or not the input data of all types have been calculated. If the result of this determination is NO, the procedure returns to step S2 to perform the arithmetic processing again, and if YES. Ends the calculation.

When the calculation of all data types is completed in this way, the result is stored in the file 4 as shown in step S9 of FIG. 14 and the calculation result is transmitted to the central station as shown in step S10. To do.

Next, as shown in step S11, it is determined whether the present time is 9:00 am on a predetermined day within one month. If the result of this determination is NO, the entire processing ends (END), but if YES, step S12.
As shown in, the CPU 2 reads the hourly information for January from the file 4 and calculates the month information as shown in step S13.

That is, the CPU 2 reads the day information for January from the file 4 into the memory 3 at 9:00 am on the first day of every month, and calculates the month information based on this information. The calculation process of the month information will be described with reference to the flowchart shown in FIG.

As shown in step S1 of FIG. 19, the following processing is performed for each type of all input data. Step S
As shown in FIG. 2, the counter values of the day information are summed to calculate the counter value of the month information. Next, as shown in step S3, the integrated values of the day information are summed to calculate the integrated value of the month information. .

Next, as shown in step S4, the value obtained by dividing the integrated value of the month information by the counter value of the month information is obtained as the average value of the month information, and as shown in step S5, the maximum of the day information is obtained. The largest value among the values is searched for as the maximum value and the maximum value time of the month information, and the smallest value among the minimum values of the day information is searched as shown in step S6.
It is the minimum value and the minimum value time of the month information.

Next, as shown in step S7, it is judged whether or not the input data of all types have been calculated. If the result of this judgment is NO, the process returns to step S2 to perform the calculation process again, and if YES. Ends the calculation.

When the calculation of all data types is completed in this way, the result is stored in the file 4 as shown in step S14 of FIG. 14 and the calculation result is transmitted to the central station as shown in step S15. To do.

Next, as shown in step S16, it is determined whether or not the current time is January 1, 9:00 am. If the result of this determination is NO, the entire processing ends (END).
However, in the case of YES, the CPU 2 reads the hourly information for one year from the file 4 as shown in step S17, and calculates the year information as shown in step S18.

That is, the CPU 2 makes every January 1 at 9:00 am
Month information for one year is read from the file 4 into the memory 3 at 0 minutes, and year information is calculated based on the month information for one year. Since the calculation of this year information is the same as the calculation of the month information described with reference to FIG. 19, its description is omitted. However, FIG.
In, "day information" is "month information" and "month information" is "
Replaces "year information".

When the calculation of all data types of the year information is completed, the result is stored in the file 4 as shown in step S19 of FIG. 14 and the calculation result is transmitted to the central station as shown in step S20. To do. This completes the processing of the entire station building.

Since the memory capacity of the file 4 increases as the number of types of data to be stored increases, the normal storage period, for example, hour information is one month, day information is one year,
Month information is set to 2 years and year information is set to 10 years, and new data is overwritten after the storage period.

When data is stored in the file 4 by this method, the memory capacity in the file 4 almost reaches the limit.
Hourly information and daily information are used for daily reports, monthly information for monthly reports, and year information for annual reports.

Further, the operator operates the console 5 to print out the calculation result of the CPU 2 from the printer 6 and display it on the desk 7, and by referring to this, control of the dam equipment, for example, the gate 8 which is one of them. Is being controlled.

Next, FIG. 20 shows a schematic block configuration diagram of the dam various quantity system in the central office, and its explanation will be given.
In FIG. 20, reference numeral 25 is a CPU, 26 is a memory of the CPU, 27 is a file, 28 is a database, 29 is a console, 30 is a printer, 31 is a table such as a display.

To the CPU 25, various dam amount data are periodically transmitted from the above-mentioned stations existing in various places. The dam amount data is stored in the database 28. FIG. 21 shows the database 28 of the matrix structure.
An example of the configuration will be shown. However, it is assumed that the structure stores the hourly information of dam various data.

At the central station, the various data of dams which are periodically received from each station are stored in the database 28 as shown in FIG. 21 by hour information, day information, month information and year information.

As described above, the database 28 is considerably long in the lateral direction. In addition, as the number of stations that regularly transmit the dam volume data to the central station increases, the data types such as the water level and water storage of the dam volume data that each station station further transmits to the central station (hereinafter As the number of data names) increases, the database 28 becomes longer in the horizontal direction.

However, the number of data in the horizontal direction (data byte length) is limited in the normal database 28. If the number of pieces of dam quantity data is smaller than the number of laterally allowable data in the database 28, one of the functions of the CPU 25 shown in FIG.
The application program 33 (hereinafter referred to as an application), which is one of the two, can write data in the database 28 or read data in the database 28 without any particular problem.

However, when the number of dam quantity data is larger than the allowable number of data in the lateral direction of the database 28, the database 28 is divided in advance in the lateral direction as shown in FIG. Database is referred to as a table), and the application 33 has a database access interface 34,
Data will be written or data will be read from Table 1D to Table nD via the database access unit 35.

Now, the process of receiving the dam amount data from the station by the application 33 of the CPU 25 will be described with reference to FIG. When the system is started up, the operator of the central office operates the keyboard 36 shown in FIG. 22 to set the maximum allowable number of data in the horizontal direction of one table (hereinafter 8192).
Bytes) and the number of stations, and the required number of tables from the maximum value of the total number of data of various dam data received from one station at a time, etc., as well as the hourly information for each station, A table name definition table 37 in the application 33 as shown in FIG. 24 determines which table is to be stored for each file type (hereinafter referred to as a file No.) in which day information, month information, and year information are stored. Define.

After this, as shown in step S1 of FIG. 23, dam amount data is received from each station. Here, it is assumed that the data from the station building A is received. Next, step S
As shown in 2, the application 33 reads the data name such as the file number, the station name (for example, A), the date and time (hereinafter referred to as time information), the water level, and the stored water amount, and then proceeds to step S3. As shown in the table name definition table 37, the table name (hereinafter referred to as Table 1D) in which the information of the relevant file No. of the station A is stored is read, and the table is accessed through the database access interface 34 as shown in step S4. 1D is accessed, and the corresponding time information is searched in order from Table 1D.

Next, as shown in step S5, Table 1D
All the received data are stored in the corresponding time information area of 1. In this storage procedure, as shown in step S6, first, one data name is read, as shown in step S7, the area of the read data name is searched in order from the left, and as shown in step S8, the read data is read. The received data corresponding to the area corresponding to the first name is stored.

Then, as shown in step S9, it is determined whether or not the storage processing has been completed for all the data names. If the result of this determination is NO, step S6
To continue the processing, and if the answer is YES, the processing is terminated.

Since the vertical memory capacity of the database 28 increases as the number of types of data to be stored increases, the normal storage period, for example, hour information is 3 months, day information is 3 years, and month information is 20 years. The year information has been set to 100 years, and new data is overwritten when the storage period expires. Database 28
With the data stored therein, the memory capacity in the database 28 is almost reached. Hourly information and daily information are used for daily reports, monthly information for monthly reports, and year information for annual reports.

[0050]

By the way, the above-mentioned database access method by the CPU 25 in the central office has the following problems.

As described above, when the system is started up, the operator of the central station determines the maximum number of data and the number of stations that can be accepted in one table, and the total number of data of the dam amount data received from one station at a time. Calculate the required number of tables (divided databases) from maximum values, etc., and also for each station or file.
The table to be stored for each No is determined and defined in the table name definition table 37 in the application 33 as shown in FIG. 24. However, there is a problem that the work of the operator for making this definition is troublesome. Yes, and when the operator applies the app 33 to each dam quantity system,
It is necessary to rewrite the contents of the table name definition table 37 in this case, and in this case, the contents of the application 33 must be changed again, which causes a problem that the work is troublesome.

After reading the table name from the table name definition table 37, the application 33 performs a process of searching for the corresponding time information in order from the top of the table. However, as shown in FIG. There are a number of time information items, and particularly in the case of the lower time information item, there is a problem that the search takes time.

After searching the table for the relevant time information, the application 33 carries out a process for searching all the received data one by one from within the relevant time information area for the data name area. Especially, when there are many data names, it takes time to search the data name area from the time information area.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a database access system by the CPU, which enables the CPU to easily write / read a large amount of data to / from the database.

[0055]

FIG. 1 shows the principle of the present invention. In the database access method by the CPU shown in this figure, each receives the 1st to nth data in a format in which the time information is added to the continuous 1st to mth type data at fixed time intervals, and by the control of the CPU 25. The first to n-th divided databases 1D, 2D, ..., ND having a matrix configuration obtained by dividing the database 28 are accessed.

A feature of the present invention is that the CPU 25 is caused to store each of the first to nth data in the first to nth divided databases 1D to.
The first table 37 in which which of nD is to be stored is associated
And the first to mth data in the first to nth data
-The 2nd table 44 which matched the m-th classification data number and matched the maximum data length of the 1st-m-th classification data with the 1st-m-th classification data numbers, and the 1st-nth division databases 1D-nD. For each row of time information sequentially arranged in the column direction, the column address, which is the arrangement position of each of the first to mth type data sequentially arranged, is associated with the first to mth type data numbers. 3 table 45 and any one of the 1st to nth data is received, the first to nth division databases 1D to
first conversion means 40 for recognizing whether to store in nD;
Division databases 1D to nD recognized by the conversion means 40
It is recognized that the time information of the reception data is subtracted from the time information of the beginning of the to obtain the difference time Tn, and the reception data is stored in the row of the Tn-th row address of the divided databases 1D to nD corresponding to the difference time Tn. Second conversion means 41,
The first to mth type data numbers corresponding to the first to mth type data of the received data are obtained from the second table 44, and the column address corresponding to the obtained first to mth type data numbers is obtained in the third table. 45, the intersection of the matrix of the obtained column address and the row address recognized by the second conversion means 41 is used as a storage address, and the first to mth type data of the received data is stored at this storage address. The third conversion means 42 and the CPU 25 are included in the configuration.

According to this structure, the storage addresses of the received data can be easily retrieved even in the databases 1D to nD having a large-scale matrix structure. It is possible to solve the problem that it takes time by performing the search.

[0058]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. FIG. 2 is a CPU functional block configuration diagram of the central office in the dam various quantity system to which the database access method by the CPU of one embodiment of the present invention is applied. In FIG. 2, parts corresponding to the respective parts of the conventional example shown in FIG. 22 are designated by the same reference numerals, and description thereof will be omitted.

The embodiment shown in FIG. 2 is different from the conventional example shown in FIG. 22 in that the CPU 25 newly includes a first conversion means (table name conversion tool) 40 and a second conversion means (record No conversion tool). 41, a third conversion means (data name No conversion tool) 42, an input / output management program 43, a second table (data name No definition table) 44, and a third table (column name definition table) 45 are provided, and the conventional application 33 is provided. This is because the first table (table name definition table) 37 that was inside is provided outside the application 33.

The application of the embodiment shown in FIG. 2 is denoted by reference numeral 33 'to distinguish it from the application 33 of the conventional example. FIG.
A flow chart for explaining the processing operation performed by the input / output management program 43 at the time of starting the dam various quantity system is shown and explained.

As shown in step S1 of FIG. 3, when the system is started up, the operator of the central office can input the maximum number of data and the number of stations at one table (divided database) from the input means (keyboard) 36 at one time point. Input the maximum value of the total number of dam quantity data received from one station and all data names of dam quantity data that may be received, and the input / output management program 43 will receive it. To do.

As a result, as shown in step S2, the input / output management program 43 calculates the number of necessary tables in the database 28 from the input value of step S1, and also, as shown in step S3, for each station or file. Which table is stored for each No is determined and defined in the table name definition table 37 as shown in FIG.

Next, as shown in step S4, a data name No is determined for each data name from the information such as all data names of dam quantity data that may be received, and the maximum data length is shown in FIG. Data name No definition table 4 showing an example
4 is stored.

Next, as shown in step S5, for all the stations, for each station and for each file No., the example shown in FIGS. The column name definition table 45 shown is defined.

However, FIG. 5 shows an example of the column name definition table 45 when the file No. of the station A shown in FIG. 24 is hour information, and FIG. 6 shows the file No. of the station C shown in FIG. FIG. 24 shows an example of the column name definition table 45 for information.
It is an example figure of the column name definition table 45 when the file No. of the station building F shown in FIG.

As shown in step S6, the table names defined for each station and each file No. are read in order from the upper left from the table name definition table 37 shown in FIG. Next, as shown in step S7, the following steps S8 and S9 are applied to the station name and file No. read in step S6.
All data names in the column name definition table 45 by the procedure shown in
For No., define the column name in the corresponding table for each data No.

That is, as shown in step S8, the maximum data length of the last defined data No (read from the data name No definition table 44) is added to the last defined column name in the corresponding column name definition table 45. The column name in the corresponding table of the corresponding data name No is calculated and stored in the column name area of the corresponding data name No in the column name definition table 45. However, the column name in the case of the first definition is automatically set to "0".

For example, when the data name No. of the data name No. definition table 44 shown in FIG. 4 is "1", the "1" is used to first define the column name in the column name definition table 45 shown in FIG. Since the data name is No, the column name of the table 45 is "0".

Next, the column name defined in the data name No. "2" has the maximum data length "1" of the data name No. "1" in its "0".
It becomes "180" by adding 80 ". Next, for the column name defined in the data name No" 3 ", the maximum data length" 175 "of the data name No" 2 "is added to the" 180 ". "3
55 ". The column name is defined in the same way thereafter.

Next, as shown in step S9, it is determined whether or not the column name storage processing has been completed for all data name Nos. If the result of this determination is NO, the processing of step S8 is performed again. If YES, the process proceeds to step S10.

Then, as shown in step S10, it is determined whether or not the storage processing has been completed for all station buildings and all file Nos. If the result of this determination is NO, the procedure returns to step S6. If YES, the process ends.

According to the processing operation of the input / output management program 43 as described above, the maximum number of data and the number of stations that the operator of the central office can accept from the input means (keyboard) 36 in one table when the system is started up, 1 At this point, simply enter the maximum value of the total number of dam quantity data received from one station and all data names of dam quantity data that may be received. effective.

That is, as in the prior art, the maximum number of data and the number of stations allowed by the operator of the central station in one table at the time of system start-up, and the total data of various dam quantity data received from one station at a time It is not necessary to calculate the required number of tables from the maximum value of the number, etc., and which table to store for each station or file No. is decided, and the table name definition table in the application 33 as shown in FIG. There is no need to define it in 37.

Also, since the operator does not need to rewrite the contents of the table name definition table 37 in the app 33 when applying the app 33 to each dam quantity system, the contents of the app 33 are changed each time the rewriting is performed. There is no need to do this.

Next, after the system start-up described above is completed, the processing procedure performed by the application 33 'when the dam amount data is actually received from a certain station (hereinafter referred to as station A) will be described with reference to FIG. This will be described with reference to the flowchart shown in FIG.

First, as shown in step S1, the station A
It is assumed that the dam various data is received from. After this reception, the application 33 'reads the file number (hereinafter referred to as hourly information), station name (station A), time information, and data name from the received data, as shown in step S2.

Thereafter, as shown in step S3, the table name conversion tool 40 is used to store the table name (hereinafter referred to as "hour information") of the corresponding file No. of the station A from the table name definition table 37. Table 1D) is read.

Next, as shown in step S4, after accessing the table 1D via the database access interface 34, the table 1D is accessed using the record No conversion tool 41.
The address of the relevant time information is calculated from D.

For example, the station name of the received data is the station A, the file No is the hour information, and the station name is the file of the station A.
It is assumed that the time information of the received data stored at the top of the table corresponding to No. of hourly information is 10:00 on January 1st shown in FIG.

As shown in FIG. 21, since the hourly information data is received every hour thereafter, the time difference between the time information of the received data and the time information of the received data stored at the top of the table is used to calculate the time difference. It is possible to calculate which line of the line should be stored.

For example, when the time information data of 11:00 on February 1 is received, the time difference from the time information of the received data stored at the top of the table is 31 days and 1 hour, that is, 745 hours. It can be calculated that it should be stored in the 746th row of the table.

However, the data in the database 28 has a normal storage period. The newly received data has been overwritten in the database 28, but if the data stored at the beginning of the table is exactly before the retention period, it will be overwritten at the beginning of the table.

As a result, it is possible to solve the problem that it takes time to retrieve the corresponding time information from the top of the conventional table. Next, as shown in step S5, all the received data names are stored one by one using the data name No conversion tool 42 in the area of the address of the corresponding time information in the table 1D calculated in step S4. This storage procedure will be described in steps S6 to S10.

As shown in step S6, one received data name is read. After this, as shown in step S7, the data name No corresponding to the data name read using the data name No conversion tool 42 is set to the data name No definition table 4
Read from 4.

Next, as shown in step S8, it corresponds to the data name No read from the column name definition table 45 corresponding to the file No. (hour information) of the station A using the data name No conversion tool 42. The column name is read, and as shown in step S9, the received data is stored in the area corresponding to the read column name in the area of the address of the relevant time information in Table 1D.

For example, the station name of the received data is the station A and the file number is the hour information. The data name No. 1 corresponding to the data name read using the data name No conversion tool 42 is read one by one for the water level, stored water amount, discharge amount, inflow amount, gate opening, adjusted flow rate, etc. of the received data name.・ 2 ・ 3.4
・ 5, 6 ... Is the data name No definition table 44 shown in FIG.
Read more.

Further, using the data name number conversion tool 42, the file number of the station A corresponds to the hourly information. The column name corresponding to the data name number read from the column name definition table 45 shown in FIG.・ 355 ・ 525 ・ 695/865 ...
And stores the received data in the area (water level / reserved water amount ...) Of the column shown in FIG. 21 corresponding to the read column name. As a result, it is possible to solve the conventional problem that it takes time to search for a data name in the time information area.

Finally, as shown in step S10, it is determined whether or not the storage processing has been completed for all the data names. If the result of this determination is NO, then the procedure returns to step S6, and YES is reached. If so, the process ends.

According to the storage processing of the application 33 using the record No. conversion tool 41 and the data name No. conversion tool 42 as described above, in the conventional case, the application 33 has a table provided in itself as shown in FIG. After reading the table name from the name definition table 37, when searching for the relevant time information in order from the top of the table having a considerable number of time information shown in FIG. 21, especially in the case of the lower time information. It is possible to eliminate that it takes time to search.

Further, after the conventional application 33 searches the corresponding time information from the above table, the data name areas are sequentially searched from the left of the corresponding time information area for all the received data. In this case, it is possible to solve the problem that it takes time to search the data name area from the time information area, especially when there are many data names.

Next, a description will be given of a case where the memory amount of the CPU 25 is reduced by reducing the number of column name definition tables 45 to be defined. When the system is started up, as described in steps S5 to S10 of FIG. 8, the input / output management program 43 stores the column name definition table 45 in the memory of the CPU 25 for each station or each file No. for all stations. I have defined it, but as the number of stations increases here,
In addition, the amount of memory increases as the type of data name increases. But of course there is a limit to the amount of memory,
The memory capacity may be exceeded.

The column name definition table 45 of the file No of the hour information of the station A and the station C shown in FIG. 5 and FIG. 6 is different but the contents are exactly the same. Looking at the table name definition table 37 of FIG. 24, one table stores data of two stations having the same file number. Further, looking at the data name No definition table 44 of FIG. 4, since the maximum data length of the same data name is defined the same in all station data and all file No data, all column name definitions There are only two patterns in the table 45. That is, the column name definition table 45 shown in FIGS.
And the pattern of the column name definition table 45 shown in FIG. 7 exist.

Therefore, in the above case, when the system is started up, the input / output management program 43 causes the column name definition table 4
Only two types of 5 should be defined. Further, when actually storing the received data in the table, it is read from the station name after using the data name No conversion tool 42 after judging which pattern of the column name definition table 45 should be read. Read the column name corresponding to the data name No.

As a result, the number of column name definition tables 45 to be defined can be greatly reduced.
The memory amount of 5 can be reduced. Then the file
A description will be given of a case where the amount of memory in the database 28 is reduced by defining the data name No definition table 44 for each No type.

For example, in the case of the column name definition table shown in FIG. 7, when the received data of the same file No. in the same station is stored in the table in the database 28, the horizontal direction is 3200.
I understand that I need a part-time job.

Assuming that the maximum allowable number of data in the horizontal direction of one table is 8192 bytes, as shown in FIG. 24, only two types of received data of the same file number are stored in the same station in the horizontal direction. No, but as the number of stations increases and the types of data names increase, the database 28
The amount of memory inside will increase. However, as a matter of course, the memory capacity is limited, and the memory capacity may be exceeded.

In the data name No definition table 44 shown in FIG. 4, the maximum data length of the same data name is defined to be the same for all station data and all file No data.

This maximum data length is the maximum data length in the data of all stations and all file numbers for each data name. If the station name and file number are different, the maximum data length is different.

For example, considering the file No.,
Since the accumulated value and the counter value are accumulated, the maximum data length of the file number of the year information is the longest, and the maximum data length of the hour information is the shortest. In addition, considering the name of the station, the maximum data length differs because the water level, the amount of water stored, etc. naturally differ depending on the dam.

FIG. 9 shows another example of the data name No definition table,
FIG. 10 shows another example of the column name definition table 45 when the station A file No. shown in FIG. 24 is hourly information, and the column name when the station B file No. shown in FIG. 24 is hourly information FIG. 12 shows another example of the definition table 45, and FIG. 12 shows another example of the column name definition table 45 when the station C file No. shown in FIG. 24 is hour information.

In the data name No definition table 44 shown in FIG. 9, the maximum data length is changed depending on the file No. even with the same data name. As a result, for the file number of the hour information, it is possible to secure areas for three stations A, B, and C in the lateral direction of one table.
8 leads to a reduction in the amount of memory.

However, in the data name No definition table 44 shown in FIG. 9, the maximum data length of the same data name is defined to be the same in the data of all stations, but it can be changed depending on the station.

If such a process is used, it is necessary to increase the number of column name definition tables 45 to be reduced as described above in the memory of the CPU 25 when the system is started up. Next, a description will be given of the division processing of the database 28 when the allowable number of data in the horizontal direction of the database 28 is smaller than the number of received data of the same station and the same file No.

Up to now, when the allowable number of data in the horizontal direction of the database 28 is larger than the number of received data of the same station and the same file No., that is, in FIG. 5 to FIG. In FIGS. 10 to 12, the received data for three stations can be stored in the same row in the database 28.

However, when the number of received data of the same station and the same file No is extremely large, or when the allowable number of data in the horizontal direction of the database 28 is small, the same station,
It may happen that the received data with the same file number cannot be stored in the same row in the database 28.

In this case, when the system is started up, the input / output management program 43 causes the operator of the central office to input from the keyboard 36 the maximum number of data and stations allowable in one table, and one station at a time. Figure 3 shows the required number of tables from these input values after receiving the information such as the maximum value of the total number of dam quantity data to be received and all data names of dam quantity data that may be received. It is calculated as shown in step S2.

However, at this point, the input / output management program 43 determines that the received data of the same station and the same file No cannot be stored in the same line in the database 28, and thereafter, the data names of the same station and the same file are not stored. The table name definition table 37 is defined in which table to store in, and the table name definition table 37 in this case is different in configuration from FIG. Figure 24
The file No. and the data name are newly taken on the horizontal axis.

After that, as shown in step S6 of FIG. 3, the table name is read from the upper left of the table name definition table, but it is read for each station, each file number, and each data name.

As a result, the table can be divided and stored in the database 28 even when the allowable number of data in the horizontal direction of the database 28 is smaller than the number of received data of the same station and the same file No.

According to the database access method by the CPU of the above-described embodiment, the following effects can be obtained. The normal database 28 has a limit on the number of data in the horizontal direction (data byte length). Collected by each station,
The data such as dam quantities sent to the central station are sent to the central station's CP.
When U is stored in the database 28, the data of the same file No and the same station at the same time are normally stored in the same line in the database 28, but the maximum allowable data in the horizontal direction of the database 28. Even if the number is smaller than the number of data to be stored in the same row in the database 28,
Application 33 'is database access interface 3
It is possible to access the database 28 without paying particular attention to 4.

Further, when storing the received data in the database 28, the application 33 'can calculate its address without searching the time information, and can also calculate the column name without searching the data name. Can be read. This makes it possible to reduce the load on the CPU 25 and reduce the processing time.

[0112]

As described above, according to the present invention,
There is an effect that the CPU can easily write / read a large amount of data to / from the database.

[Brief description of the drawings]

FIG. 1 is a principle diagram of the present invention.

FIG. 2 is a CPU functional block configuration diagram of a central office in the dam various quantity system to which the database access method by the CPU of one embodiment of the present invention is applied.

FIG. 3 is a flowchart for explaining a processing operation performed by the input / output management program at system startup.

FIG. 4 is an example diagram of a data name No definition table.

5 is an example diagram of a column name definition table when the file No. of the station A shown in FIG. 24 is hourly information.

FIG. 6 is an example diagram of a column name definition table when the file number of the station C shown in FIG. 24 is hourly information.

7 is an example diagram of a column name definition table when the file number of the station F shown in FIG. 24 is hourly information.

FIG. 8 is a flowchart illustrating a processing operation performed by an application program of a CPU when receiving dam amount data from station A.

FIG. 9 is another example diagram of a data name No definition table.

FIG. 10 is another example diagram of the column name definition table when the file No. of the station A shown in FIG. 24 is hourly information.

FIG. 11 is an example diagram of a column name definition table when the file No. of the station B shown in FIG. 24 is hourly information.

12 is another example diagram of the column name definition table when the file No. of the station C shown in FIG. 24 is hour information.

FIG. 13 is a schematic block configuration diagram of a dam various quantity system in one station building.

FIG. 14 is a flowchart for explaining a data reception process by a CPU in a station building.

FIG. 15 is a data table diagram for hourly information calculation.

FIG. 16 is a flowchart for explaining a data storage process in the hourly information calculation data table by the CPU in the station building.

FIG. 17 is a flowchart for explaining hourly information calculation processing by a CPU in a station building.

FIG. 18 is a flowchart for explaining date and time information calculation processing by the CPU in the station building.

FIG. 19 is a flowchart for explaining a monthly information calculation process by the CPU in the station building.

FIG. 20 is a schematic block configuration diagram of a dam various quantity system in the central office.

FIG. 21 is a diagram showing an example of the configuration of a database of the CPU of the central office.

FIG. 22 is a CPU functional block configuration diagram of a conventional central office.

FIG. 23 is a flow chart for explaining a conventional receiving process of dam amount data by the CPU of the central office.

FIG. 24 is a table name definition table diagram.

[Explanation of symbols]

 25 CPU 28 database 36 input means (keyboard) 37 first table (table name definition table) 40 first conversion means (table name conversion tool) 41 second conversion means (record No conversion tool) 42 third conversion means (data name) No conversion tool) 43 input / output management means (input / output management program) 44 second table (data name No definition table) 45 third table (column name definition table) 1D to nD first to nth divided databases

Claims (6)

[Claims] 1. A matrix structure in which each receives first to nth data in a format in which time information is added to continuous first to mth type data at fixed time intervals, and a database is divided under the control of the CPU. In a database access method by a CPU for accessing the first to n-th divided databases, a first table in which each of the first to n-th data is stored in which of the first to n-th divided databases And the first to mth type data in the first to nth data are associated with the first to mth type data numbers, and the first to mth type data numbers are related to the first to mth type data. Of the first to m-th type data sequentially arranged for each row of the time information sequentially arranged in the column direction of the first to n-th divided databases. Each distribution Correspondence between the third table in which the column address that is the storage position is associated with the first to mth type data numbers, and the first table when any of the first to nth data is received. Which received data from which first
First conversion means for recognizing whether to store in the n-th divided database, and subtracting the time information of the received data from the time information at the head of the divided database recognized by the first conversion means to obtain a difference time Tn. Corresponding to second conversion means for recognizing and storing the received data in the row of the Tn-th row address of the divided database corresponding to the difference time Tn, and the first to m-th type data of the received data The first to mth type data numbers to be obtained from the second table,
The column address corresponding to the obtained first to mth type data numbers is obtained from the third table, and the intersection of the matrix of the obtained column address and the row address recognized by the second conversion means is determined. A database access method by a CPU, characterized in that the CPU is provided with a storage address, and third conversion means for storing the first to mth type data of the received data at the storage address. 2. The first to nth input from the input means
Input / output management means for performing first control in which the first table is stored in the first table according to the name and number of the data The database access method by the CPU according to claim 1, further comprising: 3. The input / output management means arranges the first to m-th type data inputted from the input means in the second table, and the arranged first to m-th type data are arranged in the arranged table. The first to mth type data numbers are associated with each other and the first
3. The database access method by the CPU according to claim 2, further comprising: performing a second control in which the maximum data length of the first to mth type data is associated with the mth type data number. 4. The input / output management means, after performing the second control, arranges the first to mth type data numbers in the third table and arranges the arranged first to mth type data. The first type data number at the beginning of the number is associated with "0" of the column address, and the second type data number is added with "0" and the maximum data length of the first type data of the second table. As the column address, and thereafter, the value of the column address associated with the type data number one smaller than the type data number with which the association is performed and the second
4. The database access method by the CPU according to claim 3, wherein control is performed such that a value added to the maximum data length of the type data having the next smaller number in the table is associated as the column address. 5. The first to nth data in the first
-When the maximum data lengths of the mth type data are equal, the input / output management means defines only one of the third tables related to the first to nth data having the same maximum data length, and the defined third 5. The CPU according to claim 4, wherein three tables are commonly used by the third conversion means.
Database access method by. 6. The first defined in the second table
The database access method by CPU according to any one of claims 1 to 5, wherein the maximum data length of the m-th type data is an actual data length.