Large object processing system and large object processing method

Abstract

The invention provides a large object processing system and a large object processing method. The large object processing system comprises a storage device and a processor. The storage device is used for storing a plurality of large object variable tables, a process variable processing module and a large object processing module. The process variable processing module receives a processing request and queries the storage device according to the processing request to obtain a process variable table and a plurality of object values in the process variable table. The large object processing module determines whether the plurality of object values include an object reference string. And when the plurality of object values comprise the object reference character string, the large object processing module obtains corresponding large object data according to the object reference character string. The process variable processing module replaces the object reference character string in the process variable table with large object data, and assembles the process variable table.

Description

Technical Field

[0001] The present invention relates to a data processing technology, in particular to a large object processing system and a large object processing method. Background Art

[0002] Generally speaking, in the process of executing task data, multiple processes need to be executed one by one, and each process consists of multiple activities. However, the current activity will use the process variables generated in the previous activity. Similarly, the current activity will also generate new process variables for subsequent activities to use. In order to isolate the process variables between activities, each activity will store the current activity variables (i.e., context process variables). However, storing the process variables of each activity separately takes up a lot of storage space. In addition, when the current activity needs to use a value (data) in the process variable table, all the contents in the process variable need to be loaded into the computer device, resulting in a lot of runtime memory being occupied, and even causing insufficient memory to restart the computer. Summary of the invention

[0003] The present invention is directed to a large object processing system and a large object processing method, which can effectively improve the storage process and the reading process of large object data in active data.

[0004] According to an embodiment of the present invention, the large object processing system of the present invention includes a storage device and a processor. The storage device is used to store multiple large object variable tables, a process variable processing module and a large object processing module. The processor is coupled to the storage device and is used to execute the process variable processing module and the large object processing module. The process variable processing module receives a processing request, and the process variable processing module queries the storage device according to the processing request to obtain a process variable table and multiple object values ​​in the process variable table. The large object processing module determines whether the multiple object values ​​include an object reference string. In response to the multiple object values ​​including the object reference string, the large object processing module obtains the corresponding large object data according to the object reference string. The process variable processing module replaces the object reference string in the process variable table with the large object data, and assembles the process variable table.

[0005] According to an embodiment of the present invention, the large object processing method of the present invention includes the following steps: receiving a processing request through a process variable processing module, and the process variable processing module queries a storage device according to the processing request to obtain a process variable table and multiple object values ​​in the process variable table; judging through the large object processing module whether the multiple object values ​​include an object reference string; in response to the multiple object values ​​including the object reference string, obtaining corresponding large object data according to the object reference string through the large object processing module; replacing the object reference string in the process variable table with the large object data through the process variable processing module, and assembling the process variable table.

[0006] Based on the above, the large object processing system and large object processing method of the present invention can efficiently store large objects in the active variable table and replace them with reference strings, thereby improving the usage of storage space and memory.

[0007] In order to make the above features and advantages of the present invention more clearly understood, embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic diagram of a large object processing system according to an embodiment of the present invention;

[0009] Figure 2 is a flow chart of a large object processing method according to an embodiment of the present invention;

[0010] Figure 3 is a schematic diagram of the execution of tasks and activities of an embodiment of the present invention;

[0011] Figure 4 is a schematic diagram of a process variable processing module and a database according to an embodiment of the present invention;

[0012] Figure 5 is a relationship diagram between a process variable table and a large object variable table according to an embodiment of the present invention;

[0013] Figure 6 is a schematic diagram of a large object processing system, a computer device and a server according to an embodiment of the present invention;

[0014] Figure 7 is a schematic diagram of an execution server, a storage server, and a large object processing system according to an embodiment of the present invention;

[0015] Figure 8 is a storage flow chart of a large object processing method according to an embodiment of the present invention;

[0016] Fig. 9It is a schematic diagram of a large object threshold comparison table according to an embodiment of the present invention.

[0017] Description of Reference Numerals

[0018] 100: Large object processing system;

[0019] 110: processor;

[0020] 120: storage device;

[0021] 121: process variable processing module;

[0022] 122: Large object processing module;

[0023] 310: Task A;

[0024] 311: Activity A;

[0025] 312: Activity B;

[0026] 320: Task B;

[0027] 321: Activity C;

[0028] 322: Activity D;

[0029] 330: Task C;

[0030] 331: Activity E;

[0031] 332: Activity F;

[0032] 400: Database;

[0033] 410: process variable table;

[0034] 420: Large object variable table;

[0035] 411: Active process variable table;

[0036] 411A: Process variable table of activity A;

[0037] 4111: variable name k1;

[0038] 4112: variable name k2;

[0039] 4113: Object 1 references string;

[0040] 4114: Object 2 references string;

[0041] 411B: process variable table of activity B;

[0042] 411C: process variable table of activity C;

[0043] 420: Large object variable table;

[0044] 421: Large object data;

[0045] 610: Computer device;

[0046] 611: Request;

[0047] 630: Large object processing system;

[0048] 631: Processor;

[0049] 632: Memory;

[0050] 6321: process variable processing module;

[0051] 6322: Large object processing module;

[0052] 640: server;

[0053] 641: disk;

[0054] 642: processor;

[0055] 700: Large object processing system;

[0056] 701: data;

[0057] 702: data;

[0058] 710: Process variable processing module

[0059] 711: process variable reading unit;

[0060] 712: Process variable assembly unit;

[0061] 713: Data Analysis Unit;

[0062] 714: process variable storage unit;

[0063] 720: large object processing module;

[0064] 721: Object reference analysis unit;

[0065] 722: object reading unit;

[0066] 723: data router;

[0067] 724: Object Storage Calculator;

[0068] 725: object storage;

[0069] 730: Configurator;

[0070] 731: threshold configurator;

[0071] 732: Large Object Threshold Reader;

[0072] 740: Statistical unit;

[0073] 750: Execution server;

[0074] 760: storage server;

[0075] S210-S270, S801-S811: steps;

[0076] 910: Large object threshold comparison table. DETAILED DESCRIPTION

[0077] Reference will now be made in detail to exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and the description to refer to the same or like parts.

[0078] Figure 1 FIG. 1 is a schematic diagram of a large object processing system according to an embodiment of the present invention. Figure 1 , the large object processing system 100 includes a processor 110 and a storage device 120. The processor 110 is coupled to the storage device 120. The large object processing system 100 may also include a communication interface or a data transmission interface with actual circuit elements, so that the processor 110 can communicate or transmit data with an external business process system, a task execution system, a database or a server. In this embodiment, the large object processing system 100 and the database can be implemented in a cloud server or a private server within the enterprise, for example. The database can also be integrated into an enterprise resource planning (Enterprise Resource Planning, ERP) system, and multiple application programming interfaces (Application Programming Interface, API) can be executed to call the process variable processing module 121 and the large object processing module 122. In one embodiment, the external business process system refers to a system for executing data such as processes, tasks and activities, such as a program for executing a function of generating a purchase order based on activity data (such as executing procurement operation data), or a program for executing a function of generating a purchase order based on operation purchase request data (i.e., purchase request task data), and the present invention is not limited thereto.

[0079] In this embodiment, the processor 110 of the large object processing system 100 may include, for example, a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessors, digital signal processors (DSP), application specific integrated circuits (ASIC), programmable logic devices (PLD), other similar processing circuits, or a combination of these devices.

[0080] The storage device 120 may also implement a remote cloud storage service or a local data storage service. The storage device 120 may include a memory and / or a database, wherein the memory may be, for example, a non-volatile memory (NVM). The storage device 120 may store the relevant programs, modules, systems or algorithms for implementing the various embodiments of the present invention, so that the processor 110 can access and execute to implement the relevant functions and operations described in the various embodiments of the present invention. The storage device 120 may cache the process variable table, variable data, large object threshold, large object threshold comparison table and running time of the tasks and activities described in the various embodiments of the present invention. In addition, the process variable table described in the various embodiments of the present invention refers to the variable data generated by the previous and next (context) processes, and the variable data in the process variable table corresponding to each activity is the context (i.e., the previous and next processes) process variables are captured when the current activity is executed, so it is not affected by the subsequent process execution, thereby achieving absolute isolation.

[0081] Figure 2 The flowchart of a large object processing method according to an embodiment of the present invention. Figure 3 FIG. 1 is a schematic diagram of the execution of tasks and activities of an embodiment of the present invention. Figure 1 as well as Figure 2 The storage device 120 can store a process variable processing module 121 and a large object processing module 122. The process variable processing module 121 and the large object processing module 122 can be implemented in a programming language such as JSON (JavaScript Object Notation), Extensible Markup Language (XML) or YAML, but the present invention is not limited thereto.

[0082] Specifically, the process variable processing module 121 can be used to receive one of a processing request and a storage request from an external process execution system. In addition, the process variable processing module 121 can obtain the corresponding process variable table according to the request, and read the variable value or object value in the process variable table at the same time. The large object processing module 122 can be used to determine whether the object value in the process variable table includes an object reference string, and obtain the corresponding storage block according to the object reference string. The storage block can be set in the storage device 120 of the large object processing system 100, or it can be set in an external database.

[0083] Figure 3 FIG. 1 is a schematic diagram of the execution of tasks and activities of an embodiment of the present invention. Figure 3 As shown, when executing a process or executing a task process, task A310, task B320 and task C330 can be executed in sequence, and task A310 includes activity A311 and activity B312. Task B320 includes activity C321 and activity D322, and task C330 includes activity E331 and activity F332. Tasks can be, for example, distribution tasks, script tasks, data integration tasks, data quality inspection tasks, or data acquisition tasks. Activities refer to the detailed operations of executing tasks, and activities can be, for example, data management activities, data acquisition activities, data matching activities and other operational logic. It should be noted that when executing the current activity, the process variables of the upper and lower processes will be used, and new process variables will also be generated for use by subsequent activities. Therefore, it is necessary to record the process variables generated by the upper and lower activities of each activity, and then generate an independent process variable table to achieve absolute isolation. In other words, when executing each process and each activity, the process processing system or the external process execution device will issue a processing request to the large object processing system 100, thereby obtaining the process variable table of the current activity, and confirming whether the process variable table of the current process includes a large object and loading the required large object.

[0084] Please refer to Figures 1 to 3, the large object processing system 100 executes the following steps S210 to S270. In step S210, the process variable processing module 121 receives a processing request. Specifically, when the processor or the external process execution server executes any activity, in order to obtain the process variable table and variable value (i.e., process variable (variable)) of the current activity, a processing request is issued to the process variable processing module 121. In step S220, the process variable processing module 121 queries the storage device 120 or an external database according to the processing request, and then obtains the process variable table corresponding to the processing request and multiple object values ​​in the process variable table. Specifically, the process variable processing module 121 is based on the activity information in the processing request (for example, activity B312), and searches for the process variable table corresponding to activity B312 from the storage device 120 or the external database according to the activity information. The process variable table includes multiple object values ​​(Value).

[0085] In step S230, the large object processing module 122 determines whether the multiple object values ​​include an object reference string. In this embodiment, the object value can be a variable value (Value) or an object reference string. For example, the variable value can be variable data such as "Object 1", "Object 2". The object reference string can be marked with words such as "ref-Object 1" or "ref-Object 2".

[0086] In step S240, the large object processing module 122 obtains the corresponding large object data from the storage device 120 or the external database according to the object reference string. Specifically, the storage device 120 or the database stores a plurality of large object data (i.e., data whose required storage space is greater than a threshold), and the object reference string is used as a unique identifier for searching for the corresponding large object data. In this way, the large object processing module 122 can obtain the large object data corresponding to the object reference string from the storage device 120 or the database.

[0087] In step S250, the process variable processing module replaces the object reference string in the process variable table with the large object data, and assembles the process variable table. Specifically, the process variable assembly unit of the process variable processing module 121 replaces the object reference string in the process variable table with the large object data, and assembles the process variable table. Assembling the process variable table means correspondingly loading and restoring the object data or large object data to be used by the current activity in accordance with the data required by the activity.

[0088] In step S270, in response to the fact that the plurality of object values ​​do not include the object reference string, the large object processing module 122 ends the process. For example, when the large object processing module 122 determines that the process variable table does not include the object reference string, the process ends. In another embodiment, when each object reference string in the process variable table has been restored to the corresponding large object data, the process variable processing module 121 outputs the assembled process variables to the terminal device (such as an electronic device) corresponding to the processing request, and ends the process. Therefore, the large object processing system 100 of this embodiment can significantly reduce the required storage space of the process variable table by designing that the process variable table includes the object reference string. In addition, according to the setting of the large object threshold, additional storage for large object data can be achieved, thereby improving the utilization rate of storage space.

[0089] Figure 4 It is a schematic diagram of a process variable processing module and a database according to an embodiment of the present invention. Figure 5 It is a relationship diagram between the process variable table and the large object variable table of an embodiment of the present invention. After the process variable processing module 121 assembles the process variable table 410, it obtains the corresponding data group (i.e., the restored / loaded data) in the process variable table 410, and then the process variable processing module 121 outputs the data group required for the current activity.

[0090] Please refer to Figure 4 as well as Figure 5 , the database 400 stores a plurality of process variable tables 410 and a plurality of large object variable tables 420. Each activity corresponds to a process variable table (411A, 411B, 411C) of a specific activity. The process variable tables (411A, 411B, 411C) include a plurality of variable values ​​and a plurality of said variable names. Moreover, each variable name corresponds to one of a plurality of variable values, and each of a plurality of object values ​​is a variable value or an object reference string. Specifically, each process variable table (411A, 411B, 411C) includes a plurality of pairs of variable names and variable values. For example, the process variable table 411A of activity A includes a variable name k1 4111 and a variable name k2 4112. Moreover, the variable name k1 4111 corresponds to the object 1 reference string 4113, and the variable name k2 4112 corresponds to the object 2 reference string 4114. As Figure 5 As shown, the large object processing module 122 finds the corresponding large object variable table 420 from the plurality of large object variable tables 420 according to the object reference string, and further searches for the corresponding large object data 421. It is worth noting that the large object processing module 122 includes a data router, and the data router establishes a plurality of large object variable tables 420 according to the processing time or the number value. In one embodiment, the data router is used to search for the corresponding large object data 421 according to the object reference string.

[0091] Figure 6 It is a schematic diagram of a large object processing system, a computer device, and a server according to an embodiment of the present invention. Figure 7 FIG. 1 is a schematic diagram of an execution server, a storage server, and a large object processing system according to an embodiment of the present invention. Figure 6 As shown, the large object processing system 630 is communicatively connected to the computer device 610 and the server 640. The large object processing system 630 includes a processor 631 and a memory 632. The server 640 includes a disk 641 and a processor 642. When the computer device 610 performs any activity, it sends a processing request 611 to the large object processing system 630. In this way, the processor 631 of the large object processing system 630 executes the process variable processing module 6321 and the large object processing module 6322, and then obtains the corresponding large object data from the external server 640 according to the processing request 611. Then, the large object processing system 630 returns the required data corresponding to the processing request 611 to the computer device 610.

[0092] like Figure 7 As shown, the large object processing system 700 also includes a configurator 730 and a statistics unit 740. The process variable processing module 710 includes a process variable reading unit 711, a process variable assembly unit 712, a data analysis unit 713 and a process variable storage unit 714. The configurator 730 includes a threshold configurator 731 and a large object threshold reader 732. The large object processing module 720 includes an object reference analysis unit 721, an object reading unit 722, a data router 723, an object storage calculator 724 and an object storage 725. In this embodiment, the large object processing system 700 is communicatively connected to the execution server 750 and the storage server 760, and then receives data 701 (e.g., processing request) and data 702 (e.g., storage request) respectively.

[0093] Figure 8 It is a storage flow chart of a large object processing method according to an embodiment of the present invention. Fig. 9Schematic diagram of a large object threshold comparison table of an embodiment of the present invention. The storage process refers to storing the large object data in the original process variable table into a storage device or a database, and replacing the stored large object data with an object reference string, thereby greatly reducing the storage space required for the process variable table. In other words, the large object processing system 700 greatly improves the utilization rate of the storage space by storing large object data separately and establishing multiple large object variable tables. The large object processing system 700 performs the following steps S801 to S811. In step S801, the process variable processing module 710 receives a storage request (such as data 702) through the data analysis unit 713. And the storage request corresponds to the process variable table. Specifically, the storage request can be any active storage request and includes an active process variable table. In step S802, the large object threshold 732 of the configurator 730 reads the large object threshold comparison table 910 corresponding to the storage request from the storage device 120 or the database according to the storage request. Specifically, the large object threshold comparison table 910 is a comparison table including a plurality of pre-set size thresholds, each size threshold corresponding to a user number and an activity number. Thus, the large object threshold device 732 obtains the large object threshold comparison table 910 corresponding to the storage request according to the user number and the execution activity corresponding to the storage request.

[0094] In step S803, the data analysis unit 713 obtains multiple variable values ​​in the process variable table corresponding to the storage request one by one. In step S804, the object storage calculator 724 calculates the required storage space for the variable value. In step S805, the data analysis unit 713 determines whether the required storage space belongs to large object data according to the large object threshold comparison table 910. For example, the size threshold corresponding to the current activity in the large object threshold comparison table 910 is 1024. When the size of one of the required storage spaces in the current activity is 512, the data analysis unit 713 determines that the required storage space does not belong to large object data. When the size of one of the required storage spaces in the current activity is 2048, the data analysis unit 713 determines that the required storage space belongs to large object data.

[0095] In step S806, in response to the required storage space belonging to the large object data, the data router 723 matches the variable name corresponding to the variable value to one of the plurality of large object variable tables. In other words, the data router 723 finds the corresponding large object variable table according to the variable name. In step S807, the object storage 725 stores the variable value and outputs the corresponding object reference string to the process variable storage unit 714.

[0096] In step S808, the process variable storage unit 714 replaces the corresponding variable value in the process variable table with the object reference string. In step S809, the data analysis unit 713 determines whether each variable value in the process variable table has been judged, that is, whether the loop of the variable values ​​is finished one by one. In step S810, after the data analysis unit 713 has judged each variable value in the process variable table, the process variable storage unit 714 stores the process variable table.

[0097] In one embodiment, each processing request corresponds to an executed activity and a required data list. The required data list refers to the variable values ​​required to execute the current activity. The large object processing module 720 is further used to determine whether multiple object values ​​include an object reference string, and at the same time determine whether the object reference string complies with the required data list. In other words, when the object reference string does not comply with the required data list, the large object processing module 720 does not restore the corresponding large object data to reduce the required storage space of the restored data group. Then, in response to multiple object values ​​including an object reference string and complying with the required data list, the process variable processing module 710 replaces the object reference string that complies with the required data list with the large object data.

[0098] In one embodiment, the statistical unit 740 records the median of historical running time, and the median of historical running time may be, for example, the median of the activity running time of the previous working day or any day. In addition, the statistical unit 740 outputs the median of historical running time to the threshold configurator 731. The threshold configurator 731 matches the median of historical running time to one of a plurality of large object thresholds according to the time length, and the threshold configurator 731 adds a plurality of running time lengths and large object thresholds in the large object threshold comparison table according to the median of historical running time to adjust the large object threshold comparison table 910. In one embodiment, the plurality of large object thresholds in the large object threshold comparison table may be pre-set, for example, different size thresholds are pre-set, namely: 512KB, 1024KB, and 2048KB, etc. For example, when the corresponding user number 1 (such as Fig. 9 "tenant_1") and activity number a (such as Fig. 9 If the median activity running time of the previous working day of "template_a") is 50 seconds, the threshold configurator 731 adds the time threshold 50 and the size threshold 512 to the large object threshold comparison table 910, and then adjusts the large object threshold comparison table 910.

[0099] In this way, the data analysis unit 713 can obtain the corresponding threshold value from the large object threshold comparison table according to the running time of the process variable. Specifically, the threshold configurator 731 matches the multiple running time lengths and the multiple large object thresholds in the large object threshold comparison table 910 according to the size, and the multiple running times and the multiple large object thresholds are arranged and matched in the large object threshold comparison table in a negative correlation. For example, in the large object threshold comparison table 910, the size threshold 1024 corresponds to the sample length threshold 30, and the size threshold 2048 corresponds to the length threshold 5. Specifically, since the activities with short running time have a short running time, the time they occupy the memory space is also short, so a larger large object threshold can be allowed, thereby reducing the repeated storage and restoration. However, the activities with long running time occupy a long time of memory space during execution, so it is designed to be a lower large object threshold and only restore the variable values ​​(such as data) used by the current activity, thereby achieving the effect of saving storage space.

[0100] In summary, the large object processing system and large object processing method of the present invention can significantly reduce the storage space required for the process variable table by designing that the process variable table includes an object reference string. In addition, according to the setting of the large object threshold, additional storage is performed for large object data, thereby avoiding duplication of multiple large object data in different process variable tables. In this way, the large object processing system and large object processing method further improve the utilization rate of storage space. In addition, the large object processing system only restores the data needed for the current activity, thereby reducing the use of memory space and improving processing efficiency.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A large object processing system, characterized in that: include: A storage device for storing a plurality of large object variable tables, process variable processing modules and large object processing modules; as well as a processor, coupled to the storage device and used to execute the process variable processing module and the large object processing module, The process variable processing module receives a processing request, and obtains a process variable table and a plurality of object values ​​in the process variable table according to the processing request. The large object processing module determines whether the plurality of object values ​​include an object reference string. In response to the plurality of object values ​​including the object reference string, the large object processing module obtains corresponding large object data according to the object reference string, The process variable processing module replaces the object reference string in the process variable table with the large object data, and assembles the process variable table.

2. The large object processing system according to claim 1, characterized in that: After the process variable processing module assembles the process variable table, the corresponding data group in the process variable table is obtained. And the process variable processing module outputs the data group.

3. The large object processing system according to claim 1, characterized in that: It also includes: a configurator, wherein the process variable processing module includes a data analysis unit and a process variable storage unit, wherein the large object processing module includes a data router, an object storage calculator and an object storage, wherein the data analysis unit receives a storage request, wherein the storage request corresponds to the process variable table, The large object threshold device of the configurator reads a corresponding large object threshold comparison table from the storage device according to the storage request. The data analysis unit obtains variable values ​​of the process variable table corresponding to the storage request one by one, The object storage calculator calculates the required storage space for the variable value. The data analysis unit determines whether the required storage space belongs to large object data according to the large object threshold comparison table. In response to the required storage space belonging to the large object data, the data router matches the variable value to one of the plurality of large object variable tables according to the variable name corresponding to the variable value, The object memory stores the variable value and outputs the corresponding object reference string to the process variable storage unit. The process variable storage unit replaces the corresponding variable value in the process variable table with the object reference string.

4. The large object processing system according to claim 3, characterized in that: After the data analysis unit determines each variable value in the process variable table, the process variable storage unit stores the process variable table.

5. The large object processing system according to claim 3, characterized in that: The process variable table includes the plurality of variable values ​​and the plurality of variable names, wherein each of the variable names corresponds to one of the plurality of variable values, and each of the plurality of object values ​​is one of the variable value and the object reference string.

6. The large object processing system according to claim 3, characterized in that: The data router establishes the plurality of large object variable tables according to one of the processing time and the number value, Each of the variable names is matched to one of the plurality of large object variable tables through a hash value calculation and one of an index value.

7. The large object processing system according to claim 3, characterized in that: The threshold configurator matches a plurality of run time lengths and a plurality of large object thresholds in the large object threshold comparison table with each other according to size, and the plurality of run times and the plurality of large object thresholds are arranged and matched in the large object threshold comparison table in a negative correlation, The large object threshold value device obtains the large object threshold value comparison table corresponding to the storage request according to the user number and the execution activity corresponding to the storage request.

8. The large object processing system according to claim 3, characterized in that: The processing request corresponds to an execution activity and a list of required data, The large object processing module determines whether the plurality of object values ​​include an object reference string and whether the object reference string conforms to the required data list. In response to the multiple object values ​​including the object reference string and the list of data that meets the requirement, the process variable processing module replaces the object reference string that meets the list of data that meets the requirement with the large object data.

9. The large object processing system according to claim 8, characterized in that: The configurator further includes a threshold configurator, wherein the threshold configurator matches the median of the historical running time to one of the plurality of large object thresholds according to the time length, and the threshold configurator adds the plurality of running time lengths and the large object thresholds in the large object threshold comparison table according to the median of the historical running time to adjust the large object threshold comparison table. The data analysis unit obtains the corresponding threshold value from the large object threshold comparison table according to the running time of the process variable.

10. The large object processing system according to claim 9, characterized in that: The system further includes a statistical unit, wherein the statistical unit records the median of the historical running time and outputs the median of the historical running time to the threshold configurator.

11. A large object processing method, characterized in that: include: Receiving a processing request through a process variable processing module, and the process variable processing module queries a storage device according to the processing request to obtain a process variable table and a plurality of object values ​​in the process variable table; Determining, by a large object processing module, whether the plurality of object values ​​include an object reference string; In response to the plurality of object values ​​including the object reference string, obtaining corresponding large object data according to the object reference string by the large object processing module; and The object reference string in the process variable table is replaced with the large object data by the process variable processing module, and the process variable table is assembled.

12. The large object processing method according to claim 11, characterized in that: Also includes: After the process variable processing module has assembled the process variable table, the corresponding data group in the process variable table is obtained through the process variable processing module; as well as The data set is outputted by the process variable processing module.

13. The large object processing method according to claim 11, characterized in that: Also includes: receiving a storage request by a data analysis unit, wherein the storage request corresponds to the process variable table; Reading a corresponding large object threshold comparison table from the storage device according to the storage request by a large object threshold device of the configurator; Acquiring variable values ​​of the process variable table corresponding to the storage request one by one through the data analysis unit; Calculate the required storage space of the variable value by an object storage calculator; Determining, by the data analysis unit according to the large object threshold comparison table, whether the required storage space belongs to large object data; In response to the required storage space belonging to the large object data, matching the variable value to one of the plurality of large object variable tables according to the variable name corresponding to the variable value through a data router; Storing the variable value through the object memory, and outputting the corresponding object reference string to the process variable storage unit; as well as The corresponding variable value in the process variable table is replaced with the object reference string through the process variable storage unit.

14. The large object processing method according to claim 13, characterized in that: Also includes: After the data analysis unit determines each variable value in the process variable table, the process variable storage unit stores the process variable table.

15. The large object processing method according to claim 13, characterized in that: The process variable table includes the plurality of variable values ​​and the plurality of variable names, wherein each of the variable names corresponds to one of the plurality of variable values, and each of the plurality of object values ​​is one of the variable value and the object reference string.

16. The large object processing method according to claim 13, characterized in that: Also includes: The data router establishes the plurality of large object variable tables according to one of the processing time and the number value, Each of the variable names is matched to one of the plurality of large object variable tables through a hash value calculation and one of an index value.

17. The large object processing method according to claim 13, characterized in that: Also includes: The threshold configurator matches a plurality of running time lengths and a plurality of large object thresholds in the large object threshold comparison table with each other according to their sizes, and the plurality of running times and the plurality of large object thresholds are arranged and matched in the large object threshold comparison table in a negative correlation; as well as The large object threshold comparison table corresponding to the storage request is obtained by the large object threshold device according to the user number and the execution activity corresponding to the storage request.

18. The large object processing method according to claim 13, characterized in that: The detection data is changing business data. The processing request corresponds to an execution activity and a list of required data, The step of the large object processing module determining whether the plurality of object values ​​include the object reference string comprises: Determine, by the large object processing module, whether the plurality of object values ​​include an object reference string and whether the object reference string conforms to the required data list; The step in which the process variable processing module replaces the object reference string in the process variable table with the large object data includes: In response to the plurality of object values ​​including the object reference string and the list of data that meets the requirement, the object reference string that meets the list of data that meets the requirement is replaced with the large object data by the process variable processing module.

19. The large object processing method according to claim 18, characterized in that: Also includes: Matching the median of the historical running time to one of the plurality of large object thresholds according to the time length by a threshold configurator; as well as The threshold configurator adds the multiple running time lengths and the large object threshold in the large object threshold comparison table according to the median of the historical running time to adjust the large object threshold comparison table, The step of the data analysis unit determining whether the required storage space belongs to the large object data according to the large object threshold comparison table further includes: The data analysis unit obtains a corresponding threshold value from the large object threshold comparison table according to the running time of the process variable.

20. The large object processing method according to claim 19, characterized in that: Also includes: The historical running time median is recorded by a statistical unit, and the historical running time median is output to the threshold configurator.

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