CN115480903A - Data batch processing method, device, equipment and storage medium - Google Patents
Data batch processing method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to a data processing technology, and discloses a data batch processing method, which comprises the following steps: acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operation environment of the data to be processed, and configuring a data processing node in the data operation environment according to the data processing task; distributing the data processing tasks to the data processing nodes by using a preset task scheduling tool to obtain a distribution log of the data tasks; based on the distribution log, running the data processing task through the data processing node to record a running log of the data processing task in the running process; and integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed. The invention can improve the efficiency of data batch processing.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for batch processing of data.
Background
Data batching is the collection, storage, retrieval, processing, transformation and transmission of batches of data by which valuable and meaningful data is extracted and derived from large, possibly chaotic, unintelligible amounts of data for certain individuals.
At present, data batch processing is usually realized by adopting a timing execution database technology, an execution program is compiled by using Java, and the same operation is repeatedly executed, but in an actual service scene, a large amount of data to be processed often exists, the data types are complex and changeable, components required by the timing execution database technology are numerous and complicated, the requirement on hardware resources is high, and the functions of supporting data log tracking, manual scheduling/retrying of pages, dynamic configuration of scheduling tasks, process management of task execution and the like are not provided, so that the efficiency of data batch processing is low.
Disclosure of Invention
The invention provides a data batch processing method, a device, equipment and a storage medium, and mainly aims to improve the efficiency of data batch processing.
In order to achieve the above object, the present invention provides a data batch processing method, including:
acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operation environment of the data to be processed, and configuring a data processing node in the data operation environment according to the data processing task;
distributing the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain distribution logs of the data tasks;
running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process;
and integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
Optionally, the configuring a data processing task of the data to be processed includes:
analyzing the service scene of the data to be processed;
identifying the data processing requirement of the data to be processed according to the service scene;
and constructing the processing task according to the data processing requirement.
Optionally, the configuring, according to the data processing task, a data processing node in the data execution environment includes:
analyzing the operation steps of the data processing tasks, and combing out operation logic according to the operation steps;
and configuring a data processing node in the data operation environment according to the operation logic.
Optionally, the allocating the data processing task to a data processing node by using a preset task scheduling tool to obtain an allocation log of the data task includes:
analyzing the task type of the data processing task by using the task scheduling tool;
determining a scheduling mode of the task scheduling tool according to the task type;
distributing the data tasks to the data processing nodes by using the task scheduling tool through the scheduling mode to obtain data task nodes;
and recording the complete operation record of the data task node from the acquisition of the node address to the acquisition of the distribution log.
Optionally, the running, by the data processing node, the data processing task based on the distribution log includes:
inquiring the mapping relation between each node in the data processing nodes and each task in the data processing tasks according to the distribution log;
loading each processing task in the data processing tasks into a corresponding running node in the data processing nodes based on the mapping relation;
and constructing a processing logic of the processing task in the running node, and running the processing task through the running node according to the processing logic.
Optionally, the integrating the distribution log and the operation log to obtain the data processing log of the to-be-processed data includes:
unifying the log format standards of the distribution log and the operation log to obtain a standard distribution log and a standard operation log;
carrying out log combination on the standard distribution log and the standard operation log to obtain a unified log;
and carrying out data combing on the unified log to obtain the data processing log.
Optionally, the performing data combing on the unified log to obtain the data processing log includes:
deleting the data illegal data of the unified log to obtain a legal data log;
deleting invalid data from the legal data log to obtain a valid data log;
and sorting the effective data logic to obtain the data processing log.
In order to solve the above problem, the present invention further provides a data batch processing apparatus, including:
the node configuration module is used for acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operation environment of the data to be processed, and configuring a data processing node in the data operation environment according to the data processing task;
the task allocation module is used for allocating the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain an allocation log of the data tasks;
the log recording module is used for running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process;
and the log integration module is used for integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
In order to solve the above problem, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the batch processing method of data as described above.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the data batch processing method described above.
The embodiment of the invention can clarify the processing requirement of the data to be processed and improve the processing efficiency of the data to be processed by acquiring the data to be processed and configuring the data processing task of the data to be processed, and the embodiment of the invention allocates the data processing task to the data processing node by utilizing a preset task scheduling tool, so that the allocation log of the data task can be used for timely tracking and solving any problem in the allocation process of the data processing task and ensuring the data processing efficiency through the allocation log, wherein the embodiment of the invention can automatically process the data processing task through the data processing node by obtaining the data processing result through the data processing node based on the allocation log, thereby reducing the labor cost and improving the batch processing efficiency of the data; in addition, the data processing log of the data to be processed is obtained by integrating the distribution log and the operation log, and the functions of dynamically configuring and scheduling the task and managing the task execution process of the data to be processed can be guaranteed to the maximum extent through data log tracking, so that the data batch processing efficiency is improved. Therefore, the data batch processing method, device, equipment and storage medium provided by the embodiment of the invention can improve the efficiency of data batch processing.
Drawings
FIG. 1 is a flow chart illustrating a data batch processing method according to an embodiment of the present invention;
FIG. 2 is a functional block diagram of a data batch processing apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the data batch processing method according to an embodiment of the present invention.
The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
The embodiment of the application provides a data batch processing method. In this embodiment of the present application, an execution subject of the data batch processing method includes, but is not limited to, at least one of electronic devices that can be configured to execute the method provided in this embodiment of the present application, such as a server and a terminal. In other words, the data batch processing method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Fig. 1 is a schematic flow chart of a data batch processing method according to an embodiment of the present invention. In this embodiment, the data batch processing method includes steps S1 to S5:
s1, acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operation environment of the data to be processed, and configuring a data processing node in the data operation environment according to the data processing task.
According to the embodiment of the invention, the processing requirement of the data to be processed can be clarified by acquiring the data to be processed and configuring the data processing task of the data to be processed, so that the processing efficiency of the data to be processed is improved, wherein the data to be processed refers to the data which needs to be processed.
The processing task refers to where data operation needs to be performed on the data to be processed, such as deletion, submission, modification and the like of the data to be processed.
Further, as an embodiment of the present invention, the configuring a data processing task of the to-be-processed data includes: analyzing the service scene of the data to be processed; identifying the data processing requirement of the data to be processed according to the service scene; and constructing the processing task according to the data processing requirement.
The service scene refers to an environment background where the data to be processed is located, for example, an e-commerce scene, a payment scene, a trip scene, a medical scene and the like; the data processing requirement refers to extracting useful information from the data to be processed;
further, in an optional embodiment of the present invention, the analyzing the service scenario of the to-be-processed data may be performed by using a Power BI data analysis visualization tool.
Further, in an optional embodiment of the present invention, the data processing requirement for identifying the data to be processed according to the service scenario may be implemented by a FineReport application data analysis tool.
Further, in an optional embodiment of the present invention, the constructing the processing task according to the data processing requirement may be implemented by backward derivation.
According to the embodiment of the invention, by creating the data operation environment of the data to be processed and configuring the data processing nodes in the data operation environment according to the data processing task, the operation environment and the processing nodes for processing the data to be processed in batch can be built in advance, so that the efficiency of data batch processing is further improved; the data operating environment refers to an operating system for processing the data to be processed, such as operating systems of DotNet, directX and the like, which are built; the data processing node refers to a tool kit for processing the data to be processed. As an embodiment of the present invention, the data execution environment for creating the to-be-processed data may be written in Java language.
Further, as an embodiment of the present invention, the configuring a data processing node in the data execution environment according to the data processing task includes: analyzing the operation steps of the data processing tasks, and combing out operation logic according to the operation steps; and configuring a data processing node in the data operation environment according to the operation logic.
The operation steps refer to operation flows required for realizing the data processing tasks, for example, in a travel scene, a car calling action needs to be performed, and the operation flows can be that a destination is selected first, a car using type is selected, and finally, a search is clicked; the operation logic refers to a collection of implementation logic of each step of the operation flow.
And S2, distributing the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain a distribution log of the data tasks.
In the embodiment of the invention, the data processing task is distributed to the data processing nodes by utilizing the preset task scheduling tool, and the distribution log of the data processing task is obtained, so that any problem in the distribution process of the data processing task can be solved and the data processing efficiency can be ensured by timely tracking the distribution log; the preset task scheduling tool refers to a tool for performing data task allocation scheduling, such as a QUARTZ tool; the distribution log refers to an operation record of the whole process of distributing the data processing task to the data processing node through the task scheduling tool.
As an embodiment of the present invention, the allocating the data processing task to a data processing node by using a preset task scheduling tool to obtain an allocation log of the data processing task includes: analyzing the task type of the data processing task by using the task scheduling tool; determining a scheduling mode of the task scheduling tool according to the task type; distributing the data tasks to the data processing nodes by using the task scheduling tool through the scheduling mode to obtain data task nodes; and recording the complete operation record from the acquisition of the node address to the acquisition of the data task node to obtain the distribution log.
The task type refers to different types of tasks divided by the data processing task according to different processing modes, such as a statistic type, a screening type and the like; the scheduling mode refers to a scheduling mode adopted by the task scheduling tool to allocate the data processing tasks to the data processing nodes, for example, the data processing tasks are scheduled according to months, and the tasks are executed every 5 minutes in the time period from 14 pm to 14 pm and from 18 pm to 18 pm in 2022; the data task node refers to the data processing node which has acquired the data processing task.
Further, in an optional embodiment of the present invention, the establishing of the data transmission channel between the data task and the data processing node may be performed by a WebRTC component.
Further, in an optional embodiment of the present invention, the allocating, by using the task scheduling tool, the data task to the data processing node to obtain a data task node includes: acquiring the node address of the data processing node by utilizing the address layer of the task scheduling tool; establishing a data transmission channel of the task scheduling tool and the data processing node by utilizing a channel layer of the task scheduling tool according to the node address; and transmitting the data task to the data processing node by utilizing a transmission layer of the task scheduling tool according to the data transmission channel.
And S3, running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process.
According to the embodiment of the invention, the data processing task is operated through the data processing node based on the distribution log, the obtained data processing result can be automatically processed through the data processing node, the labor cost is reduced, and the data batch processing efficiency is improved.
As an embodiment of the present invention, the executing the data processing task by the data processing node based on the distribution log includes: and inquiring a mapping relation between each node in the data processing nodes and each task in the data processing tasks according to the distribution logs, loading each processing task in the data processing tasks into a corresponding running node in the data processing nodes based on the mapping relation, constructing a processing logic of the processing tasks in the running nodes, and running the processing tasks through the running nodes according to the processing logic.
The mapping relation is used for representing the corresponding relation between each processing node in the data processing nodes and each processing task in the data processing tasks, the processing logic is used for determining the processing rule adopted by the subsequent processing nodes when the processing tasks are run, for example, a new transformation is created and stored in a local path, for example, the new transformation is stored under D:/etlst, the file name is EtltTrans, and the suffix name is ktr after the key default transformation file is stored; creating a new job, saving the job to a local path, for example, saving the job file with the filename Etlestest Job under D:/etltest, and saving the job file with the filename kjb after the job file is saved by default in a keytle; identifying common conversion link names, converting the transformation and other rules.
Further, in an optional embodiment of the present invention, a mapping relationship between each of the data processing nodes and each of the tasks in the data processing task may be queried through a query statement, for example, an SQL query statement, a processing logic of the processing task may be constructed through a program language, for example, JAVA, and the operation of the processing task may be implemented through a thread pool.
Furthermore, by recording the running log of the data processing task in the running process, the embodiment of the invention can ensure that the problems encountered in the data processing task in the processing process can be tracked and solved through the running log; the running log refers to a running record of the whole process of the data processing result obtained by the data processing node running the data processing task. Optionally, the recording of the running log of the data processing task in the running process is realized by building an Nxlog running environment, installing fluntd curl-L in a database, and restarting the service after modifying a configuration file of the Nxlog.
And S4, integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
According to the embodiment of the invention, the distribution log and the operation log are integrated to obtain the data processing log of the data to be processed, and the functions of dynamically configuring and scheduling the task and managing the task execution process of the data to be processed can be ensured to the maximum extent through data log tracking, so that the batch processing efficiency of the data is improved.
As an embodiment of the present invention, the integrating the distribution log and the operation log to obtain the data processing log of the to-be-processed data includes: unifying the log format standards of the distribution log and the operation log to obtain a standard distribution log and a standard operation log; merging the logs of the standard distribution log and the standard operation log to obtain a unified log; and carrying out data combing on the unified log to obtain the data processing log.
The standard distribution log and the standard operation log refer to the distribution log and the operation log which pass through a unified format; the unified log is a new log formed by log merging the standard distribution log and the standard operation log.
Further, in an optional embodiment of the present invention, the log format standards of the distribution log and the operation log are unified, and the obtaining of the standard distribution log and the standard operation log may be completed by restarting the server after modifying the log configuration file in the database by using a logback tool.
Further, in an optional embodiment of the present invention, the data combing is performed on the unified log to obtain the data processing log, including; deleting illegal data of the unified log to obtain a legal data log; deleting invalid data from the legal data log to obtain a valid data log; and sorting the effective data logic to obtain the data processing log.
Furthermore, the processing log is loaded into the webpage end to obtain the visual processing view of the data to be processed, so that the visual display of the processing process of the data to be processed is realized, and the user can be helped to know the data processing process of the data to be processed more clearly, wherein the webpage end can be known as a carrier for providing the view display for the user, such as a browser, and optionally the loading of the processing log can be realized through a loading tool, and the loading tool can be compiled through a JS language.
The embodiment of the invention can clarify the processing requirement of the data to be processed and improve the processing efficiency of the data to be processed by acquiring the data to be processed and configuring the data processing task of the data to be processed, and the embodiment of the invention allocates the data processing task to the data processing node by utilizing a preset task scheduling tool, so that the allocation log of the data task can be used for timely tracking and solving any problem in the allocation process of the data processing task and ensuring the data processing efficiency through the allocation log, wherein the embodiment of the invention can automatically process the data processing task through the data processing node by obtaining the data processing result through the data processing node based on the allocation log, thereby reducing the labor cost and improving the batch processing efficiency of the data; in addition, the data processing log of the data to be processed is obtained by integrating the distribution log and the operation log, and the functions of dynamically configuring and scheduling the task and managing the task execution process of the data to be processed can be guaranteed to the maximum extent through data log tracking, so that the data batch processing efficiency is improved. Therefore, the data batch processing method provided by the embodiment of the invention can improve the efficiency of data batch processing.
Fig. 2 is a functional block diagram of a data batch processing apparatus according to an embodiment of the present invention.
The data batch processing device 100 of the present invention can be installed in an electronic device. According to the implemented functions, the data batch processing apparatus 100 may include a node configuration module 101, a task allocation module 102, a log recording module 103, and a log integration module 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the node configuration module 101 is configured to acquire data to be processed, configure a data processing task of the data to be processed, create a data operating environment of the data to be processed, and configure a data processing node in the data operating environment according to the data processing task;
the task allocation module 102 is configured to allocate the data processing task to a data processing node by using a preset task scheduling tool, so as to obtain an allocation log of the data task;
the log recording module 103 is configured to run the data processing task through the data processing node based on the distribution log, so as to record a running log of the data processing task in a running process;
the log integration module 104 is configured to integrate the distribution log and the operation log to obtain a processing log of the to-be-processed data, and load the processing log into a web page end to obtain a visual processing view of the to-be-processed data.
In detail, when the modules in the data batch processing apparatus 100 in the embodiment of the present application are used, the same technical means as the data batch processing method described in fig. 1 are adopted, and the same technical effects can be produced, and no further description is given here.
Fig. 3 is a schematic structural diagram of an electronic device 1 for implementing a data batch processing method according to an embodiment of the present invention.
The electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may further include a computer program, such as a data batch processing method program, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device 1, connects various components of the whole electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (for example, a program for executing a data batch processing method, etc.) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, and the like. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only to store application software installed in the electronic device and various types of data, such as codes of a data batch processing method program, but also to temporarily store data that has been output or is to be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device 1 and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit, such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
Fig. 3 only shows an electronic device with components, and it will be understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or a combination of certain components, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The data batch processing method program stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, and when running in the processor 10, can realize:
acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operating environment of the data to be processed, and configuring a data processing node in the data operating environment according to the data processing task;
distributing the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain distribution logs of the data tasks;
running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process;
and integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
Specifically, the specific implementation method of the instruction by the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to the drawings, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operation environment of the data to be processed, and configuring a data processing node in the data operation environment according to the data processing task;
distributing the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain distribution logs of the data tasks;
running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process;
and integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it will be obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A method for batch processing of data, the method comprising:
acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operating environment of the data to be processed, and configuring a data processing node in the data operating environment according to the data processing task;
distributing the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain distribution logs of the data tasks;
running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process;
and integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
2. The batch processing method of data according to claim 1, wherein the configuring the data processing task of the data to be processed comprises:
analyzing the service scene of the data to be processed;
identifying the data processing requirement of the data to be processed according to the service scene;
and constructing the data processing task according to the data processing requirement.
3. The data batch processing method of claim 2, wherein said configuring data processing nodes in said data execution environment according to said data processing tasks comprises:
analyzing the operation steps of the data processing tasks, and combing out operation logic according to the operation steps;
and configuring a data processing node in the data operation environment according to the operation logic.
4. The data batch processing method of claim 1, wherein the allocating the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain an allocation log of the data tasks comprises:
analyzing the task type of the data processing task by using the task scheduling tool;
determining a scheduling mode of the task scheduling tool according to the task type;
distributing the data tasks to the data processing nodes by using the task scheduling tool through the scheduling mode to obtain data task nodes;
and recording the complete operation record of the data task node from the acquisition of the node address to the acquisition of the distribution log.
5. The data batch processing method of claim 1, wherein the running of the data processing task by the data processing node based on the allocation log comprises:
inquiring the mapping relation between each node in the data processing nodes and each task in the data processing tasks according to the distribution log;
loading each processing task in the data processing tasks into a corresponding running node in the data processing nodes based on the mapping relation;
and constructing a processing logic of the processing task in the running node, and running the processing task through the running node according to the processing logic.
6. The data batch processing method of claim 1, wherein the integrating the distribution log and the operation log to obtain the data processing log of the data to be processed comprises:
unifying the log format standards of the distribution log and the operation log to obtain a standard distribution log and a standard operation log;
carrying out log combination on the standard distribution log and the standard operation log to obtain a unified log;
and carrying out data combing on the unified log to obtain the data processing log.
7. The data batch processing method of claim 1, wherein the performing data combing on the unified log to obtain the data processing log comprises:
deleting illegal data of the unified log to obtain a legal data log;
deleting invalid data of the legal data log to obtain an effective data log;
and sorting the effective data logic to obtain the data processing log.
8. An apparatus for batch processing of data, the apparatus comprising:
the node configuration module is used for acquiring data to be processed, configuring a data processing task of the data to be processed, creating a data operation environment of the data to be processed, and configuring a data processing node in the data operation environment according to the data processing task;
the task allocation module is used for allocating the data processing tasks to data processing nodes by using a preset task scheduling tool to obtain an allocation log of the data tasks;
the log recording module is used for running the data processing task through the data processing node based on the distribution log so as to record a running log of the data processing task in the running process;
and the log integration module is used for integrating the distribution log and the operation log to obtain a processing log of the data to be processed, and loading the processing log into a webpage end to obtain a visual processing view of the data to be processed.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and (c) a second step of,
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of data batching as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out a method of data batching as claimed in any one of the claims 1 to 7.
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| CN202211208587.6A CN115480903A (en) | 2022-09-30 | 2022-09-30 | Data batch processing method, device, equipment and storage medium |
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