Flow cutting method and device for batch data, equipment, medium and program product

Abstract

The invention provides a flow cutting method, device and equipment for batch data, a medium and a program product, and can be applied to the technical field of big data and the technical field of financial science and technology. The method comprises the following steps: adjusting a host time zone corresponding to host batch data from a host into a current system time zone of the distributed system to obtain system batch data corresponding to the host batch data; under the condition that a historical batch identifier matched with the batch identifier exists in the historical batch identifiers of at least one piece of historical system batch data, performing validity analysis on the system batch data according to the target historical system batch data and the expected effective time period; and under the condition that the validity analysis result represents that the system batch data is not matched with the target historical system batch data and the batch moment is in the expected effective time period, updating the target historical system batch data based on the batch data included in the system batch data so as to realize the stream cutting operation of the batch data.

Description

Technical Field

[0001] This application relates to the fields of big data technology and financial technology, specifically the field of data update technology, and more specifically to a method, apparatus, device, medium and program product for batch data switching. Background Technology

[0002] The host generates tasks. For a given task, the host will generate different batches of task data at different times. Since the host processes a large number of complex tasks, the job tasks need to be distributed to a distributed system.

[0003] In related technologies, if a distributed system executes a job task, the distributed system needs to integrate different batches of task data issued by a large number of hosts. In this process, the distributed system faces problems of low update efficiency and low update accuracy when updating different batches of task data. Summary of the Invention

[0004] In view of the above problems, embodiments of this application provide a method, apparatus, device, medium, and program product for batch data switching.

[0005] According to a first aspect of the embodiments of this application, a method for switching batch data is provided, comprising: adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system to obtain system batch data corresponding to the host batch data, wherein the system batch data includes batch data, batch identifier, and batch time, and the batch time is determined based on the generation time of the host batch data and the current system time zone; wherein, if a historical batch identifier matching the batch identifier exists in the historical batch identifiers of at least one historical system batch data, a validity analysis is performed on the system batch data based on the target historical system batch data and the expected effective period, wherein the target historical system batch data is the historical system batch data corresponding to the historical batch identifier matching the batch identifier; wherein, if the validity analysis result indicates that the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, the target historical system batch data is updated based on the batch data included in the system batch data to realize the batch data switching operation.

[0006] According to an embodiment of this application, a data validity analysis is performed on the system batch data based on the target historical system batch data and the expected effective period, including: obtaining a validity analysis result indicating whether the batch time is within the expected effective period based on the batch time and the expected effective period, wherein the expected effective period is determined based on the generation time of the target historical host batch corresponding to the target historical system batch data and the current system time zone, which serves as the time zone of the updated historical system; and obtaining a validity analysis result indicating whether the system batch data matches the target historical system batch data based on the similarity between the system batch data and the target historical system batch data.

[0007] According to an embodiment of this application, a validity analysis result characterizing whether the system batch data and the target historical system batch data match is obtained based on the similarity between the system batch data and the target historical system batch data. This includes: when the validity analysis result characterizes the batch time as being within the expected effective period, obtaining a validity analysis result characterizing whether the system batch data and the target historical system batch data match based on the similarity between the system batch data and the target historical system batch data.

[0008] According to an embodiment of this application, the above method further includes: obtaining an effectiveness analysis result characterizing the mismatch between the system batch data and the target historical system batch data when the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold.

[0009] According to an embodiment of this application, the above method further includes: obtaining the similarity between the system batch data and the target historical system batch data based on the respective summary data of the system batch data and the target historical system batch data.

[0010] According to embodiments of this application, the above method further includes: processing system time parameters associated with system batch data using a digest algorithm to obtain digest data of system batch data, wherein the system time parameters include at least one of the following: current batch time, batch time before adjustment, or time difference between the current batch time and a predetermined time, and the batch time before adjustment is the generation time of host batch data; processing historical system time parameters associated with target historical system batch data using a digest algorithm to obtain digest data of target historical system batch data, wherein the historical system time parameters include at least one of the following: historical batch time, historical batch time before adjustment, or time difference between the historical batch time and a predetermined time, and the historical batch time before adjustment is the generation time of historical host batch data corresponding to the target historical system batch data.

[0011] According to an embodiment of this application, the above method further includes: processing the batch data included in the system batch data using a digest algorithm to obtain digest data of the system batch data; and processing the target historical batch data included in the target historical system batch data using a digest algorithm to obtain digest data of the target historical system batch data.

[0012] According to an embodiment of this application, the above-mentioned method of obtaining the similarity between the system batch data and the target historical system batch data based on the respective summary data of the system batch data and the target historical system batch data includes: when the summary data of the system batch data and the summary data of the target historical system batch data are inconsistent, obtaining that the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold.

[0013] According to an embodiment of this application, the above method further includes: updating the target historical system batch data based on the batch data included in the system batch data when the validity analysis result indicates that the batch time is not in the expected effective period.

[0014] According to an embodiment of this application, when the system batch data includes multiple data sets, the method further includes: for any historical system batch data set in at least one historical system batch data set, if there is no batch identifier in the batch identifiers of the multiple system batch data sets that matches the historical batch identifier of the historical system batch data set, deleting the historical system batch data set.

[0015] According to an embodiment of this application, when there are multiple host batch data, the order in which update operations are performed based on the multiple host batch data is determined according to the region to which each of the multiple host batch data belongs.

[0016] According to an embodiment of this application, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the system to obtain system batch data corresponding to the host batch data includes: in response to the parameter indicated by the processing instruction being a predetermined update parameter, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the system to obtain system batch data corresponding to the host batch data.

[0017] According to an embodiment of this application, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system includes: using a data acquisition interface to adjust the host time zone corresponding to the host batch data from the host to the current system time zone of the system.

[0018] According to an embodiment of this application, the updated historical system time zone is obtained by updating the historical system time zone based on the current system time zone when the historical system time zone indicated by the historical interface parameters of the acquisition interface is inconsistent with the current system time zone indicated by the current interface parameters of the acquisition interface.

[0019] A second aspect of this application provides a batch data switching device, comprising: a first adjustment module, configured to adjust the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system, thereby obtaining system batch data corresponding to the host batch data, wherein the system batch data includes batch data, a batch identifier, and a batch time, the batch time being determined based on the generation time of the host batch data and the current system time zone; a first analysis module, configured to perform validity analysis on the system batch data based on the target historical system batch data and the expected effective period, wherein the target historical system batch data is the historical system batch data corresponding to the historical batch identifier that matches the batch identifier, when the validity analysis result indicates that the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, thereby realizing the batch data switching operation.

[0020] A third aspect of this application provides an electronic device, including: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0021] A fourth aspect of this application provides a computer-readable storage medium having a computer program or instructions stored thereon, wherein the computer program or instructions, when executed by a processor, implement the steps of the above-described method.

[0022] A fifth aspect of this application also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0023] According to the embodiments of this application, after obtaining the host batch data, the host time zone corresponding to the host batch data is adjusted to the current system time zone of the distributed system to obtain the system batch data corresponding to the host batch data. This solves the problem of update errors caused by time zone asynchrony during subsequent update operations. Furthermore, based on the target historical system batch data and the expected effective period, the system batch data is subjected to validity analysis to determine whether the batch time indicated by the system batch data is within the expected effective period to determine whether the system batch data is valid. This reduces the need to analyze unnecessary batch data, thereby improving the efficiency of validity analysis and thus improving the efficiency of update operations. Moreover, since it is determined whether the system batch data matches the target historical system batch data, the differences between the system batch data and the target historical system batch data can be accurately analyzed, thereby improving the reliability of update operations. Thus, the target historical system batch data can be updated based on the system batch data indicated by the validity analysis results, thereby improving both update efficiency and update accuracy. Attached Figure Description

[0024] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0025] Figure 1 The diagram illustrates application scenarios of batch data switching methods, apparatus, devices, media, and program products according to embodiments of this application.

[0026] Figure 2 A flowchart of a batch data switching method according to an embodiment of this application is shown;

[0027] Figure 3 A schematic diagram of execution scheduling according to an embodiment of this application is shown;

[0028] Figure 4 A schematic diagram illustrating the effectiveness analysis according to an embodiment of this application is shown;

[0029] Figure 5 A schematic diagram of a batch data switching method according to an embodiment of this application is shown;

[0030] Figure 6 A structural block diagram of a batch data switching device according to an embodiment of this application is shown; and

[0031] Figure 7 A block diagram of an electronic device suitable for implementing a batch data switching method according to an embodiment of this application is shown. Detailed Implementation

[0032] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0033] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0034] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0035] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0036] Figure 1 The diagram illustrates application scenarios for batch data switching methods, apparatus, devices, media, and program products according to embodiments of this application.

[0037] like Figure 1 As shown, the application scenario 100 according to this embodiment may include a host 101, a distributed system 102, and a network 103.

[0038] Network 103 is a medium used to provide a communication link between host 101 and distributed system 102. Network 103 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0039] The host 101 and the distributed system 102 interact, with the host 101 sending batch data to the distributed system 102.

[0040] After receiving batch data from the host, distributed system 102 performs a batch data switching operation based on the batch data.

[0041] It should be noted that the batch data switching method provided in this application embodiment can generally be executed by the distributed system 102. Accordingly, the batch data switching device provided in this application embodiment can generally be set in the distributed system 102.

[0042] It should be understood that Figure 1 The number of hosts, networks, and distributed systems in the system is only a few. Depending on implementation needs, there can be any number of hosts, networks, and distributed systems.

[0043] The following will be based on Figure 1 The described scene, through Figures 2-5 A method for switching batch data according to embodiments of this application will be described in detail.

[0044] Figure 2 A flowchart of a batch data switching method according to an embodiment of this application is shown.

[0045] like Figure 2 As shown, the batch data switching method in this embodiment includes operations S210 to S230.

[0046] In operation S210, the host time zone corresponding to the host batch data is adjusted to the current system time zone of the distributed system to obtain the system batch data corresponding to the host batch data.

[0047] In operation S220, if a historical batch identifier matching the batch identifier exists in the historical batch identifier of each of the historical system batch data, a validity analysis is performed on the system batch data based on the target historical system batch data and the expected effective period.

[0048] In operation S230, if the validity analysis results indicate that the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, the target historical system batch data is updated based on the batch data included in the system batch data to achieve the batch data switching operation.

[0049] The host can generate different tasks. These tasks can include job tasks for a specific business, which can be a financial business, such as loan or deposit business.

[0050] For any given task, the host generates different batches of task data at different times. For any batch of task data generated at any given time, the host packages the task's generation time, the batch identifier of the task batch indicator, and the task data into host batch data. The generation time in the host batch data is the time in the host's time zone.

[0051] A distributed system receives batch data from a host computer, updates the task status indicated by the batch data stored locally in the distributed system, and executes new tasks. Different distributed systems may support different task processing types, such as data processing, image processing, loan processing, or investment processing, etc.

[0052] Before distributing host batch data to multiple distributed systems, the host classifies the host batch data by task type, determines the task processing type of the host batch data, and adds a task processing type identifier corresponding to the task processing type to the host batch data.

[0053] The distributed system has a data acquisition interface, which collects batch data from the host based on the task processing type preset by the distributed system.

[0054] Because the host and the distributed system may be located in different regions, there will be a time zone difference between them. After receiving batch data from the host, it is necessary to adjust the host time zone indicated by the batch data (i.e., the time zone of the host's location) to the current system time zone (i.e., the time zone of the current distributed system's location).

[0055] After the distributed system synchronizes the timezone of the batch data received from the host, it obtains the system batch data. The system batch data includes batch data, a batch identifier, and a batch time. The batch time is determined based on the generation time of the host batch data and the current system timezone. The batch data can be the task data of the tasks generated by the host in the aforementioned host batch data, and the batch identifier can be used to specify task information to distinguish it from other tasks.

[0056] In some embodiments, after completing the above time zone synchronization operation, the distributed system will traverse the synchronized batch data of multiple systems (for example, store the batch data of multiple systems in a data table and traverse based on the data table) to determine whether the time zones of the batch data of multiple systems are consistent. If they are inconsistent, a synchronization failure alarm will be issued.

[0057] In the process of updating batch data, a distributed system needs to determine whether the batch identifier of the system batch data is consistent with the historical batch identifier of the historical system batch data. That is, to determine whether there is any batch data that has not been recorded by the system among the batch data received from multiple hosts.

[0058] If the target historical system batch data is the historical system batch data corresponding to the historical batch identifier that matches the batch identifier, that is, if the target historical system batch data and the system batch data both indicate the same task, then further analysis is needed to determine whether the target historical system batch data needs to be updated based on the system batch data.

[0059] After determining the target historical system batch data, a validity analysis is performed on the system batch data based on the target historical system batch data and the expected effective period. The expected effective period can be a time range determined based on multiple target historical system batch data sets, used to determine whether the batch time indicated by the system batch data has been recorded by the system.

[0060] Validity analysis can be used to analyze whether the batch data of the system matches the batch data of the target historical system and whether the batch time is within the expected effective period. Specifically, it can be used to analyze the differences between the batch data of the candidate system and the batch data of the historical system and whether the batch time indicated by the batch data of the system is recorded by the system, so as to analyze whether the batch data of the target historical system can be updated based on the batch data of the system.

[0061] If the validity analysis results indicate that the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, then it is confirmed that the target historical system batch data can be updated based on the system batch data. Updating the target historical system batch data can be done by deleting the target historical system batch data from the batch memory used to store the historical system batch data and inserting the system batch data corresponding to the target historical system batch data into the batch memory.

[0062] After the system updates the historical system batch data in the batch memory, it uses the system executor to execute the tasks indicated by the updated historical system batch data, based on the processing instructions issued by the system controller. Specifically, the system controller updates the task execution status based on the task indicated by the historical system batch data. This instruction can include starting task execution, pausing task execution, or resuming task execution, and may also include updating the executor load, issuing task execution messages, and refreshing execution parameters.

[0063] In some embodiments, if an exception occurs during task execution, a task execution exception alarm is issued.

[0064] According to the embodiments of this application, after obtaining the host batch data, the host time zone corresponding to the host batch data is adjusted to the current system time zone of the distributed system to obtain the system batch data corresponding to the host batch data. This solves the problem of update errors caused by time zone asynchrony during subsequent update operations. Furthermore, based on the target historical system batch data and the expected effective period, the system batch data is subjected to validity analysis to determine whether the batch time indicated by the system batch data is within the expected effective period to determine whether the system batch data is valid. This reduces the need to analyze unnecessary batch data, thereby improving the efficiency of validity analysis and thus improving the efficiency of update operations. Moreover, since it is determined whether the system batch data matches the target historical system batch data, the differences between the system batch data and the target historical system batch data can be accurately analyzed, thereby improving the reliability of update operations. Thus, the target historical system batch data can be updated based on the system batch data indicated by the validity analysis results, thereby improving both update efficiency and update accuracy.

[0065] According to an embodiment of this application, when there are multiple host batch data, the order in which update operations are performed based on the multiple host batch data is determined according to the region to which each of the multiple host batch data belongs.

[0066] After receiving batch data from multiple hosts, determine the region where each batch of data is located.

[0067] The distributed system prioritizes updates based on the regions where batch data from multiple hosts reside. This prioritization can be based on the quantity of batch data in each region, the task conflict status between tasks indicated by the batch data from different regions, or a pre-defined order.

[0068] Based on the order of the update priority instructions for different regions as determined above, the update operations indicated by operations S210 to S230 are performed on the host batch data of different regions. Specifically, after the update operations indicated by operations S210 to S230 are completed based on the host batch data of one region, the update operations indicated by operations S210 to S230 are performed on the host batch data of the next region according to the order of the update priority instructions.

[0069] According to the embodiments of this application, since the batch data of hosts in different regions is divided, the data load will not be too large during the process of the distributed system performing the update operations indicated by the above operations S210 to S230, so as to improve the update efficiency. In addition, if there is a conflict between the tasks indicated by the batch data of hosts in different regions, updating based on the update priority can reduce the occurrence of task processing anomalies.

[0070] According to an embodiment of this application, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the system to obtain system batch data corresponding to the host batch data includes: in response to the parameter indicated by the processing instruction being a predetermined update parameter, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the system to obtain system batch data corresponding to the host batch data.

[0071] The system controller issues processing instructions, which are used to instruct the system actuators on the processing actions.

[0072] If the processing instruction issued by the system controller includes a predetermined update parameter, such as "predetermined update parameter - refresh resources", then the system executor responds to the processing instruction by performing a time zone synchronization operation on the host batch data from the host to obtain system batch data corresponding to the host batch data, so as to continue to execute the update operation indicated by the above operations S220 to S230.

[0073] According to embodiments of this application, by issuing processing instructions to perform time zone synchronization operations based on processing instructions including predetermined update parameters, the processing actions of the system are reasonably scheduled, thereby ensuring the stability of the update operation.

[0074] Figure 3 A schematic diagram of execution scheduling according to an embodiment of this application is shown.

[0075] Before executing the update operations indicated in operations S210 to S230, a scheduling operation needs to be performed, such as... Figure 3As shown, in operation S310, it is determined whether the region to which the host batch data belongs is the specified region indicated by the update priority. If not, the scheduling operation ends. If the region to which the host batch data belongs is the specified region, operation S320 continues to be executed to determine whether the processing instructions issued by the system controller are related to the update operation. If not, the scheduling operation ends. If the processing instructions are related to the update operation, operation S330 continues to be executed to determine the scheduling status related to the update operation, such as whether the executor used to perform the update operation has been pre-started. In operation S340, processing instructions that have not yet been executed are identified. In operation S350, tasks are executed based on the identified processing instructions, such as executing the update operation indicated by operations S210 to S230, or executing the task indicated by the system batch data, etc.

[0076] According to an embodiment of this application, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone includes: using a data acquisition interface to adjust the host time zone corresponding to the host batch data from the host to the current system time zone.

[0077] The acquisition interface is used to collect batch data from the host and perform time zone synchronization on the batch data.

[0078] The current interface parameters of the acquisition interface indicate the current system time zone, so that the acquisition interface can perform time zone synchronization operations on batch data from the host.

[0079] After the acquisition interface receives the batch data from the host, if there is a time zone difference between the host and the system, time zone synchronization is required. This can be achieved by adjusting the generation time indicated by the host batch data to the time indicated by the current system time zone. For example, if the host's location is one hour ahead of the distributed system's location, and the task generation time indicated by the host batch data is 10:00, then the synchronized task generation time will be adjusted to 9:00.

[0080] In some embodiments, the current interface parameters of the acquisition interface can be corrected and updated based on a preset period to adjust the current system time zone indicated by the current interface parameters of the acquisition interface.

[0081] According to the embodiments of this application, since the acquisition interface is set with a current interface parameter to indicate the current system time zone, after acquiring the host batch data, a time zone synchronization operation can be performed on the host batch data based on the current system time zone indicated by the current interface parameter. This solves the problem of update anomalies caused by different time zones in subsequent update operations, thereby improving the accuracy of update operations.

[0082] According to an embodiment of this application, a data validity analysis is performed on the system batch data based on the target historical system batch data and the expected effective period, including: obtaining a validity analysis result indicating whether the batch time is within the expected effective period based on the batch time and the expected effective period, wherein the expected effective period is determined based on the generation time of the target historical host batch corresponding to the target historical system batch data and the current system time zone, which serves as the time zone of the updated historical system; and obtaining a validity analysis result indicating whether the system batch data matches the target historical system batch data based on the similarity between the system batch data and the target historical system batch data.

[0083] In analyzing the validity of batch data in the system, it is necessary to analyze whether the batch time of the batch data is valid, which can be to determine whether the batch time of the batch data is within the expected effective period.

[0084] The expected effective period can be determined based on the generation time of the target historical host batch corresponding to the target historical system batch data, and the current system time zone, which is the time zone of the updated historical system. Specifically, it can be determined that the generation times of multiple target historical host batches are indicated in the current system time zone, and after determining multiple times, the time range indicated by the multiple times is determined as the expected effective period.

[0085] For example, suppose there are target historical system batch data A, target historical system batch data B, and target historical system batch data C. The generation times of target historical system batch data A, target historical system batch data B, and target historical system batch data C in the current system time zone after the update are 10:00, 10:30, and 10:45, respectively. Then the expected effective period indicated by target historical system batch data A, target historical system batch data B, and target historical system batch data C can be 10:00 to 10:45. In addition, the time fluctuation range can be adjusted according to actual needs, such as 9:55 to 10:50 or 9:50 to 10:55, etc.

[0086] In some embodiments, a specified time range can be preset as the expected effective period according to actual needs.

[0087] If the timing indicated by the system batch data is determined to be within the expected time range, further validity analysis is performed to determine the similarity between the system batch data and the target historical system batch data, thereby determining whether there are differences between the system batch data and the target historical system batch data. Based on the differences between the system batch data and the target historical system batch data, it is determined whether the system batch data is valid, and then the system batch data that can be used to update the target historical system batch data can be identified, and validity analysis results are generated.

[0088] According to the embodiments of this application, since the batch time of the system batch data is analyzed based on the expected effective period, the system batch data that differs from the target historical system batch data can be quickly located based on the difference between the batch time and the expected effective period, thereby reducing the amount of data processing for subsequent validity analysis and improving the efficiency of validity analysis.

[0089] Figure 4 A schematic diagram illustrating the effectiveness analysis according to an embodiment of this application is shown.

[0090] like Figure 4 As shown, in operation S410, it is determined whether the system batch data and historical batch data have the same batch identifier, thereby determining the target historical batch data corresponding to the system batch data. If the system batch data and historical batch data do not have the same batch identifier, then operation S440 is executed to update the target historical system batch data based on the batch data included in the system batch data. If the system batch data and historical batch data have the same batch identifier, then operation S420 is executed. In operation S420, it is determined whether the system batch data is within the expected effective period. If it does not exist, then operation S440 is executed. If it exists, then operation S430 is executed to determine whether the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold. If it is greater than the predetermined threshold, then the validity analysis operation ends. If it is less than or equal to the predetermined threshold, then operation S440 is executed.

[0091] According to an embodiment of this application, the updated historical system time zone is obtained by updating the historical system time zone based on the current system time zone when the historical system time zone indicated by the historical interface parameters of the acquisition interface is inconsistent with the current system time zone indicated by the current interface parameters of the acquisition interface.

[0092] The historical interface parameters of the acquisition interface can be the parameters before the acquisition interface was corrected and updated. However, there may be differences between the historical interface parameters and the current interface parameters of the acquisition interface after correction and update.

[0093] In some embodiments, the data acquisition interface may be corrected and updated according to the time adjustment system indicated by Daylight Saving Time (DST).

[0094] If the historical system time zone indicated by the historical interface parameters of the acquisition interface is inconsistent with the current system time zone indicated by the current interface parameters of the acquisition interface, then before using the target historical system batch data to perform validity analysis on the system batch data, it is necessary to update the historical system time zone corresponding to the target historical system batch data to the current system time zone indicated by the current interface parameters of the acquisition interface.

[0095] The acquisition interface receives the historical target host batch data corresponding to the target historical system batch data, and adjusts the historical host time zone of the historical target host batch data to the historical system time zone indicated by the historical interface parameters of the acquisition interface.

[0096] According to an embodiment of this application, when the historical system time zone indicated by the historical interface parameters of the acquisition interface is inconsistent with the current system time zone indicated by the current interface parameters of the acquisition interface, the historical system time zone corresponding to the target historical system batch data is updated. This reduces the occurrence of update anomalies due to time zone inconsistencies when performing validity analysis on system batch data based on the target historical system batch data, thereby improving the accuracy of the analysis.

[0097] According to an embodiment of this application, a validity analysis result characterizing whether the system batch data and the target historical system batch data match is obtained based on the similarity between the system batch data and the target historical system batch data. This includes: when the validity analysis result characterizes the batch time as being within the expected effective period, obtaining a validity analysis result characterizing whether the system batch data and the target historical system batch data match based on the similarity between the system batch data and the target historical system batch data.

[0098] If the validity analysis results indicate that the batch time is within the expected effective period, the batch time of the system batch data is difficult to distinguish from the time within the time range indicated by the expected effective period. Further validity analysis is required. Specifically, it can be to calculate the similarity between the system batch data and the target historical system batch data.

[0099] The similarity between the system batch data and the target historical system batch data can be determined by comparing the consistency of the system batch data and the target historical system batch data. The higher the consistency between the system batch data and the target historical system batch data, the higher the similarity.

[0100] After determining the similarity between the system batch data and the target historical system batch data, the difference between the system batch data and the target historical system batch data can be used to determine whether the difference between the system batch data and the target historical system batch data can indicate whether the system batch data can be used to update the target historical system batch data, so as to obtain the validity analysis results characterizing whether the system batch data and the target historical system batch data match.

[0101] According to the embodiments of this application, by analyzing the similarity between the system batch data and the target historical system batch data when the validity analysis results characterize the batch time being within the expected effective period, it is possible to analyze the degree of difference between the system batch data and the target historical system batch data, solve the resource consumption caused by manually comparing the system batch data and the target historical system batch data one by one, improve the analysis efficiency, and thus improve the efficiency of the update operation.

[0102] According to an embodiment of this application, the above method further includes: updating the target historical system batch data based on the batch data included in the system batch data when the validity analysis result indicates that the batch time is not in the expected effective period.

[0103] If the validity analysis results indicate that the batch time is not within the expected effective period, the batch time of the system batch data is not recorded by the system, meaning there is a difference between the system batch data and the target historical system batch data.

[0104] If the validity analysis results indicate that the batch time is not within the expected effective period, the target historical system batch data is deleted from the batch memory, and the system batch data is inserted into the batch memory so that when the subsequent system executor executes the task indicated by the batch data included in the system batch data, the task is executed.

[0105] According to the embodiments of this application, since the batch time is not in the expected effective period, it can be directly confirmed that there is a difference between it and the target historical system batch data. Therefore, the target historical system batch data can be updated directly based on the batch data included in the system batch data without further validity analysis, reducing the amount of data to be processed in subsequent operations and improving the efficiency of validity analysis.

[0106] According to an embodiment of this application, the above method further includes: obtaining an effectiveness analysis result characterizing the mismatch between the system batch data and the target historical system batch data when the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold.

[0107] If the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold, it can be determined that the difference between the system batch data and the target historical system batch data indicates that the system batch data has changed compared to the target historical system batch data, and the target historical system batch data needs to be updated using the system batch data. In other words, the obtained validity analysis results indicate that the system batch data and the target historical system batch data do not match.

[0108] According to the embodiments of this application, since the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold, it can be determined that the difference between the system batch data and the target historical system batch data is large. This can accurately obtain the effectiveness analysis results characterizing the mismatch between the system batch data and the target historical system batch data, thereby reducing update errors and improving the stability of the update operation when performing subsequent update operations.

[0109] According to an embodiment of this application, the above method further includes: obtaining the similarity between the system batch data and the target historical system batch data based on the respective summary data of the system batch data and the target historical system batch data.

[0110] The summary data can be a set of fixed-length data. The summary data is unique. If there are differences between the system batch data and the target historical system batch data, then there will also be differences between the summary data of the system batch data and the target historical system batch data.

[0111] Summarize the system batch data and the target historical system batch data separately, and convert the system batch data and the target historical system batch data into a set of fixed-length data to obtain the summary data of the system batch data and the target historical system batch data respectively.

[0112] After obtaining the summary data of the system batch data and the target historical system batch data, the similarity between the system batch data and the target historical system batch data is determined based on the similarity between their respective summary data.

[0113] According to the embodiments of this application, since the summary data is unique, by analyzing the similarity between the summary data of the system batch data and the target historical system batch data, compared with directly calculating the similarity between the system batch data and the target historical system batch data, the amount of computation is less, which can improve the computational efficiency and thus improve the execution efficiency of the update operation.

[0114] According to embodiments of this application, the above method further includes: processing system time parameters associated with system batch data using a digest algorithm to obtain digest data of system batch data, wherein the system time parameters include at least one of the following: current batch time, batch time before adjustment, or time difference between the current batch time and a predetermined time, and the batch time before adjustment is the generation time of host batch data; processing historical system time parameters associated with target historical system batch data using a digest algorithm to obtain digest data of target historical system batch data, wherein the historical system time parameters include at least one of the following: historical batch time, historical batch time before adjustment, or time difference between the historical batch time and a predetermined time, and the historical batch time before adjustment is the generation time of historical host batch data corresponding to the target historical system batch data.

[0115] A hash algorithm is a class of functions that map input data of arbitrary length to a fixed-length output (a digest value or a hash value).

[0116] The current batch time can be determined based on the time when the host batch data was generated and the current system time zone.

[0117] The batch time before adjustment can be determined based on the generation time of the host batch data.

[0118] The scheduled time can be determined based on the time indicated by the time zone of the scheduled region.

[0119] The time difference between the current batch time and the predetermined time can be determined based on the difference between the current batch time and the time indicated by the time zone of the predetermined region.

[0120] Historical batch timestamps can be determined based on the generation time of historical host batch data and the updated historical system timezone.

[0121] The historical batch time before adjustment can be determined based on the generation time of historical host batch data.

[0122] The time difference between the historical batch time and the predetermined time can be determined based on the difference between the historical batch time and the time indicated by the time zone of the predetermined region.

[0123] After determining the system time parameters and historical system time parameters, a summary algorithm is used to calculate the summaries of the system time parameters and historical system time parameters, respectively, to obtain the summary data of the system time parameters and the summary data of the historical system time parameters.

[0124] In the process of summarizing, multiple parameters in the system time parameters and historical system time parameters can be concatenated into strings. When summarizing the system time parameters and historical system time parameters, the summarization can be performed on the strings of the system time parameters and historical system time parameters respectively. The concatenation method can be to combine them in a specified order to solve the problem of low reliability of the summary data due to the inconsistent order of multiple parameters.

[0125] According to the embodiments of this application, by acquiring multiple system time parameters and historical system time parameters, the input data of the summarization algorithm can be enriched during subsequent summarization calculation. This improves the reliability of the summarization data during subsequent similarity calculation, solves the problem of abnormal similarity calculation results caused by a single parameter, and thus obtains a more accurate similarity.

[0126] According to an embodiment of this application, the above method further includes: processing the batch data included in the system batch data using a digest algorithm to obtain digest data of the system batch data; and processing the target historical batch data included in the target historical system batch data using a digest algorithm to obtain digest data of the target historical system batch data.

[0127] Batch data can be the task data of the task indicated by the system batch data. Target historical batch data can be the target historical task data of the target historical task indicated by the target historical system batch data.

[0128] The batch data and the target historical batch data are processed separately using a digest algorithm. The batch data and the target historical batch data are converted into a set of fixed-length data respectively, resulting in digest data of the system batch data and digest data of the target historical system batch data.

[0129] After obtaining the summary data of the system batch data and the summary data of the target historical system batch data, the differences between the summary data of the system batch data and the summary data of the target historical system batch data can be determined based on their differences. This allows us to determine whether the task indicated by the system batch data has changed compared to the target historical task indicated by the target historical system batch data. Compared to summarizing multiple system time parameters and historical system time parameters, summarizing the batch data and the target historical batch data is more computationally intensive, but the similarity between the system batch data and the target historical system batch data is more accurate.

[0130] According to the embodiments of this application, by calculating the summary data of the batch data and the target historical batch data respectively, it is possible to directly calculate the similarity between the batch data and the target historical batch data, and solve the problem of high computational complexity caused by directly calculating the similarity between the batch data and the target historical batch data, thereby improving the efficiency of similarity calculation.

[0131] According to an embodiment of this application, the above-mentioned method of obtaining the similarity between the system batch data and the target historical system batch data based on the respective summary data of the system batch data and the target historical system batch data includes: when the summary data of the system batch data and the summary data of the target historical system batch data are inconsistent, obtaining that the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold.

[0132] Because summary data is unique, changes in the input data to the summary algorithm will alter the summary data. When the summary data of the system batch data differs from the summary data of the target historical system batch data, a discrepancy can be established between the two.

[0133] According to embodiments of this application, by determining whether the summary data of the system batch data is consistent with the summary data of the target historical system batch data, it is possible to directly determine whether the system batch data and the target historical system batch data are consistent. The comparison based on the summary data reduces the computational complexity, and the summary data is unique, which can improve the accuracy of the similarity between the system batch data and the target historical system batch data.

[0134] According to an embodiment of this application, when the system batch data includes multiple data sets, the method further includes: for any historical system batch data set in at least one historical system batch data set, if there is no batch identifier in the batch identifiers of the multiple system batch data sets that matches the historical batch identifier of the historical system batch data set, deleting the historical system batch data set.

[0135] If none of the batch identifiers of the batch data from multiple systems match the historical batch identifier of the historical batch data, then for the task indicated by the historical batch data, the host will no longer generate a new batch version, and the distributed system will not need to continue executing the task indicated by the historical batch data.

[0136] Since the system no longer needs to execute the task indicating the historical system batch data, the historical system batch data is deleted from the batch memory, and the system executor will no longer execute the task indicating the historical system batch data.

[0137] According to the embodiments of this application, by determining whether there is a batch identifier in the batch identifier of each of the multiple system batch data that matches the historical batch identifier of the historical system batch data, it is possible to determine the historical system batch data that will no longer be executed based on the determination result, thereby releasing the memory space of the batch memory and solving the problem of low execution efficiency caused by the system executing unnecessary tasks.

[0138] Figure 5 A schematic diagram of a batch data switching method according to an embodiment of this application is shown.

[0139] like Figure 5 As shown, in operation S510, a time zone synchronization operation is performed, adjusting the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system, thus obtaining the system batch data corresponding to the host batch data. In operation S520, it is determined whether the system batch data and historical batch data have the same batch identifier, thereby determining the target historical batch data corresponding to the system batch data. If the system batch data and historical batch data do not have the same batch identifier, then operation S570 is executed, updating the target historical system batch data based on the batch data included in the system batch data. If the system batch data and historical batch data have the same batch identifier, then operation S530 is executed. In operation S530, it is determined whether the system batch data is within the expected effective period. If it does not exist, then operation S570 is executed; if it exists, then operation S540 is executed, determining the system time parameter associated with the system batch data and the target historical time parameter associated with the target historical batch data. In operation S550, the summary data of the system batch data and the summary data of the target historical batch data are determined. In operation S560, determine whether the summary data of the system batch data matches the summary data of the target historical system batch data. If they do not match, the operation ends; if they match, proceed to operation S570. In operation S580, determine whether there is a matching historical batch identifier in the batch identifiers of the multiple system batch data. If not, the operation ends; if they do match, proceed to operation S590 to delete the target historical system batch data.

[0140] Based on the above-described batch data switching method, this application also provides a batch data switching device. The following will be combined with... Figure 6 The device is described in detail.

[0141] Figure 6 A structural block diagram of a batch data switching device according to an embodiment of this application is shown.

[0142] like Figure 6 As shown, the batch data switching device 600 of this embodiment includes a first adjustment module 610, a first analysis module 620 and a first update module 630.

[0143] The first adjustment module 610 is used to adjust the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system, thereby obtaining system batch data corresponding to the host batch data. The system batch data includes batch data, batch identifier, and batch time. The batch time is determined based on the generation time of the host batch data and the current system time zone. In one embodiment, the first adjustment module 610 can be used to perform the operation S210 described above, which will not be repeated here.

[0144] The first analysis module 620 is used to perform validity analysis on the system batch data based on the target historical system batch data and the expected effective period, when a historical batch identifier matching the batch identifier exists in the historical batch identifiers of at least one historical system batch data. The target historical system batch data is the historical system batch data corresponding to the historical batch identifier matching the batch identifier. In one embodiment, the first analysis module 620 can be used to perform the operation S220 described above, which will not be repeated here.

[0145] The first update module 630 is used to update the target historical system batch data based on the batch data included in the system batch data when the validity analysis results characterize that the batch data of the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, so as to realize the batch data switching operation. In one embodiment, the first update module 630 can be used to perform the operation S230 described above, which will not be repeated here.

[0146] According to the embodiments of this application, after obtaining the host batch data, the host time zone corresponding to the host batch data is adjusted to the current system time zone to obtain the system batch data corresponding to the host batch data. This solves the problem of update errors caused by time zone asynchrony during subsequent update operations. Furthermore, based on the target historical system batch data and the expected effective period, the system batch data is subjected to validity analysis to determine whether the batch time indicated by the system batch data is within the expected effective period to determine whether the system batch data is valid. This reduces the need to analyze unnecessary batch data, thereby improving the efficiency of validity analysis and thus improving the efficiency of update operations. Moreover, since it is determined whether the system batch data matches the target historical system batch data, the differences between the system batch data and the target historical system batch data can be accurately analyzed, thereby improving the reliability of update operations. Thus, the target historical system batch data can be updated based on the system batch data indicated by the validity analysis results, thereby improving both update efficiency and update accuracy.

[0147] According to an embodiment of this application, the first analysis module 620 includes a first obtaining submodule and a second obtaining submodule.

[0148] The first submodule is used to obtain the validity analysis result indicating whether the batch time is within the expected effective period based on the batch time and the expected effective period. The expected effective period is determined based on the generation time of the target historical host batch corresponding to the target historical system batch data, and the current system time zone, which serves as the time zone of the updated historical system.

[0149] The second submodule is used to obtain the validity analysis results, which characterize whether the system batch data matches the target historical system batch data, based on the similarity between the system batch data and the target historical system batch data.

[0150] According to an embodiment of this application, the first obtaining submodule includes a first obtaining unit.

[0151] The first obtaining unit is used to obtain the validity analysis result, which characterizes whether the system batch data matches the target historical system batch data, based on the similarity between the system batch data and the target historical system batch data, when the validity analysis result characterizes the batch time within the expected effective period.

[0152] According to an embodiment of this application, the first analysis module 620 includes a third obtaining submodule.

[0153] The third submodule is used to obtain the effectiveness analysis results characterizing the mismatch between the system batch data and the target historical system batch data when the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold.

[0154] According to an embodiment of this application, the first analysis module 620 includes a fourth obtaining submodule.

[0155] The fourth submodule is used to obtain the similarity between the system batch data and the target historical system batch data based on the respective summary data of the system batch data and the target historical system batch data.

[0156] According to an embodiment of this application, the first analysis module 620 includes a fifth obtaining submodule and a sixth obtaining submodule.

[0157] The fifth submodule is used to process the system time parameters associated with the system batch data using a digest algorithm to obtain the digest data of the system batch data. The system time parameters include at least one of the following: the current batch time, the batch time before adjustment, or the time difference between the current batch time and the predetermined time. The batch time before adjustment is the time when the host batch data was generated.

[0158] The sixth submodule is used to process the historical system time parameters associated with the target historical system batch data using a digest algorithm to obtain the digest data of the target historical system batch data. The historical system time parameters include at least one of the following: the historical batch time, the historical batch time before adjustment, or the time difference between the historical batch time and the predetermined time. The historical batch time before adjustment is the generation time of the historical host batch data corresponding to the target historical system batch data.

[0159] According to an embodiment of this application, the first analysis module 620 includes a seventh obtaining submodule and an eighth obtaining submodule.

[0160] The seventh submodule is used to process the batch data included in the system batch data using a digest algorithm to obtain the digest number of the system batch data.

[0161] The eighth submodule is used to process the target historical system batch data, including the target historical system batch data, using a digest algorithm to obtain the digest data of the target historical system batch data.

[0162] According to an embodiment of this application, the fourth obtaining submodule includes the second obtaining unit.

[0163] The second obtaining unit is used to determine that the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold when the summary data of the system batch data is inconsistent with the summary data of the target historical system batch data.

[0164] According to an embodiment of this application, the first analysis module 620 includes a first update submodule.

[0165] The first update submodule is used to update the target historical system batch data based on the batch data included in the system batch data when the validity analysis results characterize the batch time not being in the expected effective period.

[0166] According to an embodiment of this application, the batch data cutting device 600 includes a first deletion module.

[0167] The first deletion module is used to delete historical system batch data for any historical system batch data in at least one historical system batch data if there is no batch identifier in the batch identifiers of the multiple system batch data that matches the historical batch identifier of the historical system batch data.

[0168] According to an embodiment of this application, when there are multiple host batch data, the order in which update operations are performed based on the multiple host batch data is determined according to the regions to which the host and each of the multiple host batch data belong.

[0169] The batch data switching device 600 includes a second adjustment module.

[0170] The second adjustment module is used to adjust the host time zone corresponding to the host batch data to the current system time zone of the distributed system in response to the parameter indicated by the processing instruction being a predetermined update parameter, so as to obtain the system batch data corresponding to the host batch data.

[0171] According to an embodiment of this application, the first adjustment module 610 includes a first adjustment submodule.

[0172] The first adjustment submodule is used to adjust the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system using the acquisition interface.

[0173] According to an embodiment of this application, the updated historical system time zone is obtained by updating the historical system time zone based on the current system time zone when the historical system time zone indicated by the historical interface parameters of the acquisition interface is inconsistent with the current system time zone indicated by the current interface parameters of the acquisition interface.

[0174] According to embodiments of this application, any plurality of modules among the first adjustment module 610, the first analysis module 620, and the first update module 630 can be merged into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this application, at least one of the first adjustment module 610, the first analysis module 620, and the first update module 6300 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the first adjustment module 610, the first analysis module 620, and the first update module 630 can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0175] Figure 7 A block diagram of an electronic device suitable for implementing a batch data switching method according to an embodiment of this application is shown.

[0176] like Figure 7As shown, an electronic device 700 according to an embodiment of this application includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0177] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0178] According to embodiments of this application, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the input / output (I / O) interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0179] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0180] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this application, the computer-readable storage medium may include ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703 described above.

[0181] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to enable the computer system to implement the batch data switching method provided in the embodiments of this application.

[0182] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0183] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0184] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, it performs the functions defined in the system of this application embodiment. According to the embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0185] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0186] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0187] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

Claims

1. A method for batch data switching, characterized in that, include: The host time zone corresponding to the host batch data is adjusted to the current system time zone of the distributed system to obtain the system batch data corresponding to the host batch data. The system batch data includes batch data, batch identifier and batch time. The batch time is determined according to the generation time of the host batch data and the current system time zone. If, in the case that a historical batch identifier matching the batch identifier exists in the historical batch identifier of each of the historical system batch data, the system batch data is subjected to validity analysis based on the target historical system batch data and the expected effective period, wherein the target historical system batch data is the historical system batch data corresponding to the historical batch identifier matching the batch identifier; If the validity analysis results indicate that the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, the target historical system batch data is updated based on the batch data included in the system batch data to realize the batch data switching operation.

2. The method according to claim 1, characterized in that, The step of performing data validity analysis on the system batch data based on the target historical system batch data and the expected effective period includes: Based on the batch time and the expected effective period, an effectiveness analysis result is obtained to characterize whether the batch time is within the expected effective period. The expected effective period is determined based on the generation time of the target historical host batch corresponding to the target historical system batch data, and the current system time zone, which serves as the time zone of the updated historical system. Based on the similarity between the system batch data and the target historical system batch data, an effectiveness analysis result is obtained to characterize whether the system batch data and the target historical system batch data match.

3. The method according to claim 2, characterized in that, The validity analysis result, which characterizes whether the system batch data matches the target historical system batch data, is obtained based on the similarity between the system batch data and the target historical system batch data. This includes: If the validity analysis result indicates that the batch time is within the expected effective period, the validity analysis result indicating whether the system batch data matches the target historical system batch data is obtained based on the similarity between the system batch data and the target historical system batch data.

4. The method according to claim 2 or 3, characterized in that, The method further includes: When the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold, an effectiveness analysis result is obtained that characterizes the mismatch between the system batch data and the target historical system batch data.

5. The method according to any one of claims 2 to 4, characterized in that, The method further includes: Based on the summary data of the system batch data and the target historical system batch data, the similarity between the system batch data and the target historical system batch data is obtained.

6. The method according to claim 5, characterized in that, The method further includes: The system time parameters associated with the system batch data are processed using a digest algorithm to obtain digest data of the system batch data. The system time parameters include at least one of the following: the current batch time, the batch time before adjustment, or the time difference between the current batch time and a predetermined time. The batch time before adjustment is the generation time of the host batch data. The digest algorithm is used to process the historical system time parameters associated with the target historical system batch data to obtain the digest data of the target historical system batch data. The historical system time parameters include at least one of the following: the historical batch time, the historical batch time before adjustment, or the time difference between the historical batch time and a predetermined time. The historical batch time before adjustment is the generation time of the historical host batch data corresponding to the target historical system batch data.

7. The method according to claim 5, characterized in that, The method further includes: The system batch data is processed using a digest algorithm to obtain digest data of the system batch data; The target historical system batch data, including the target historical system batch data, is processed using the summarization algorithm to obtain the summary data of the target historical system batch data.

8. The method according to any one of claims 5 to 7, characterized in that, The step of obtaining the similarity between the system batch data and the target historical system batch data based on their respective summary data includes: If the summary data of the system batch data is inconsistent with the summary data of the target historical system batch data, the similarity between the system batch data and the target historical system batch data is less than or equal to a predetermined threshold.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: If the validity analysis results indicate that the batch time is not within the expected effective period, the target historical system batch data is updated based on the batch data included in the system batch data.

10. The method according to any one of claims 1 to 9, characterized in that, When the system's batch data includes multiple data sets, the method further includes: If, for any historical system batch data in at least one of the historical system batch data, there is no batch identifier in the batch identifiers of the multiple system batch data that matches the historical batch identifier of the historical system batch data, the historical system batch data is deleted.

11. The method according to any one of claims 1 to 10, characterized in that, When the host batch data includes multiple data sets, the order in which update operations are performed based on the multiple host batch data sets is determined according to the region to which each of the multiple host batch data sets belongs, as well as the data from the host.

12. The method according to any one of claims 1 to 11, characterized in that, The step of adjusting the host timezone corresponding to the host batch data from the host to the current system timezone of the distributed system to obtain the system batch data corresponding to the host batch data includes: In response to the processing instruction indicating that the parameter is a predetermined update parameter, the host time zone corresponding to the host batch data is adjusted to the current system time zone of the distributed system to obtain the system batch data corresponding to the host batch data.

13. The method according to any one of claims 2 to 11, characterized in that, The step of adjusting the host timezone corresponding to the host batch data from the host to the current system timezone of the distributed system includes: The host time zone corresponding to the batch data from the host is adjusted to the current system time zone of the distributed system using the acquisition interface.

14. The method according to claim 13, characterized in that, The updated historical system time zone is obtained by updating the historical system time zone according to the current system time zone when the historical system time zone indicated by the historical interface parameters of the acquisition interface is inconsistent with the current system time zone indicated by the current interface parameters of the acquisition interface.

15. A batch data switching device, characterized in that, The device includes: The first adjustment module is used to adjust the host time zone corresponding to the host batch data from the host to the current system time zone of the distributed system, so as to obtain the system batch data corresponding to the host batch data. The system batch data includes batch data, batch identifier and batch time. The batch time is determined according to the generation time of the host batch data and the current system time zone. The first analysis module is used to perform validity analysis on the system batch data based on the target historical system batch data and the expected effective period, when a historical batch identifier matching the batch identifier exists in the historical batch identifiers of at least one historical system batch data set; and the target historical system batch data is the historical system batch data corresponding to the historical batch identifier matching the batch identifier. The first update module is used to update the target historical system batch data based on the batch data included in the system batch data when the validity analysis results indicate that the system batch data does not match the target historical system batch data and the batch time is within the expected effective period, so as to realize the batch data switching operation.

16. An electronic device comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 14.

17. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 14.

18. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 14.

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