CN114785780A - Lane service data processing method, apparatus, device, medium, and program product - Google Patents
Lane service data processing method, apparatus, device, medium, and program product Download PDFInfo
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Abstract
The application relates to the technical field of data processing, and provides a lane service data processing method, a lane service data processing device, lane service data processing computer equipment, a storage medium and a computer program product. The method and the system can improve the efficiency and convenience of function deployment, program updating and problem repairing of the lane service data processing system, and improve the efficiency and accuracy of lane service data processing. The method comprises the following steps: based on a Dapr distributed framework, a plurality of working nodes for processing corresponding lane service data are constructed and obtained, the working nodes are deployed in a k8s cluster in a container mode, the working nodes are mutually backed up to obtain a plurality of lane service data to be processed, the lane service data to be processed are respectively input to the corresponding working nodes in the k8s cluster to be processed, and a plurality of lane service data processing results corresponding to the lane service data to be processed are obtained.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for processing lane service data.
Background
With the development of urban construction, traffic becomes an important index for measuring the development degree of cities. In lanes such as expressways and the like, efficient processing of lane service data can be beneficial to avoiding congestion conditions caused by too many vehicles, and efficient convenience of traffic transportation is further improved.
The conventional technology generally performs lane service data processing through a single-frame lane system, but the lane service data processing efficiency is low through the technology.
Disclosure of Invention
In view of the above, it is necessary to provide a lane service data processing method, apparatus, computer device, computer readable storage medium and computer program product for the above technical problem.
In a first aspect, the present application provides a lane service data processing method. The method comprises the following steps:
constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on a Dapr distributed framework;
deploying a plurality of working nodes in a container mode in a k8s cluster; a plurality of working nodes are backups of each other;
and acquiring a plurality of lane service data to be processed, and respectively inputting the plurality of lane service data to be processed to corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the plurality of lane service data to be processed.
In one embodiment, constructing a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework includes:
and constructing a plurality of service modules for processing the lane service data into one working node for processing one corresponding lane service data based on the Dapr distributed framework aiming at each working node.
In one embodiment, the service module comprises a service publishing module and a service subscribing module; obtaining a plurality of lane service data processing results corresponding to a plurality of lane service data to be processed, including:
processing lane service data to be processed by using a service publishing module aiming at each working node, and sending a lane service data processing result corresponding to the lane service data to be processed to a service subscribing module through a publishing and subscribing mode;
and sending a lane service data processing result to the lane terminal by using the service subscription module.
In one embodiment, the service module comprises a plurality of service points; the service point is constructed and obtained based on an Actor model.
In one embodiment, deploying a plurality of working nodes in a container manner in a k8s cluster comprises:
deploying a plurality of working nodes in a container mode in a plurality of nodes in a k8s cluster;
one node in the k8s cluster is set as a control node, and each node in the k8s cluster is managed by the control node.
In one embodiment, acquiring a plurality of lane service data to be processed, and inputting the plurality of lane service data to be processed to corresponding work nodes in a k8s cluster respectively for processing, includes:
receiving vehicle types and license plates corresponding to a plurality of vehicles sent by a lane service data acquisition terminal;
and respectively inputting the vehicle types and the license plates corresponding to a plurality of vehicles as a plurality of lane service data to be processed into a corresponding work node in the k8s cluster for processing.
In a second aspect, the application further provides a lane service data processing device. The device comprises:
the working node construction module is used for constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework;
the working node deployment module is used for deploying the working nodes in a k8s cluster in a container mode; the plurality of working nodes are backups of each other;
and the processing result obtaining module is used for obtaining a plurality of lane service data to be processed, and respectively inputting the plurality of lane service data to be processed to the corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the plurality of lane service data to be processed.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:
constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework; deploying a plurality of working nodes in a k8s cluster in a container mode; a plurality of working nodes are backed up mutually; and acquiring a plurality of lane service data to be processed, and respectively inputting the plurality of lane service data to be processed to corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the plurality of lane service data to be processed.
In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework; deploying a plurality of working nodes in a k8s cluster in a container mode; a plurality of working nodes are backed up mutually; and acquiring a plurality of lane service data to be processed, and respectively inputting the plurality of lane service data to be processed to corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the plurality of lane service data to be processed.
In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:
constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on a Dapr distributed framework; deploying a plurality of working nodes in a container mode in a k8s cluster; a plurality of working nodes are backed up mutually; and acquiring a plurality of lane service data to be processed, and respectively inputting the plurality of lane service data to be processed to corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the plurality of lane service data to be processed.
The lane service data processing method, the lane service data processing device, the computer equipment, the storage medium and the computer program product are based on a Dapr distributed framework, a plurality of working nodes for processing corresponding lane service data are constructed and obtained, the working nodes are deployed in a k8s cluster in a container mode, the working nodes are mutually backed up to obtain a plurality of lane service data to be processed, the lane service data to be processed are respectively input to corresponding working nodes in the k8s cluster to be processed, and a plurality of lane service data processing results corresponding to the lane service data to be processed are obtained. The scheme is based on a Dapr distributed framework to construct a plurality of working nodes, the working nodes are used for processing corresponding lane service data, the working nodes are arranged in a k8s cluster in a container mode, the working nodes are mutually backup, namely when a certain working node has the condition of errors and the like and cannot process the lane service data, the k8s cluster is used for sending the lane service data needing to be processed by the error node to another normal working node in a k8s cluster for processing, and the processed lane service data result can be fed back to a lane terminal, so that the lane service data can be normally processed even if some working nodes have the condition of errors and the like and cannot process the lane service data, and the lane system structure can be used for improving the efficiency and convenience of function arrangement, program updating and problem repairing of a lane service data processing system, in practical application, a plurality of lane service data to be processed are obtained, and the lane service data to be processed are respectively input to corresponding work nodes in the k8s cluster for processing, for example, each work node processes the lane service data to be processed of one lane, and a plurality of lane service data processing results corresponding to the lane service data to be processed are obtained, so that the efficiency and the accuracy of lane service data processing are improved.
Drawings
FIG. 1 is a flow chart illustrating a lane service data processing method according to an embodiment;
FIG. 2 is a schematic structural diagram of a lane service data processing method according to an embodiment;
FIG. 3 is a schematic structural diagram of a working node in the lane service data processing method according to an embodiment;
FIG. 4 is a block diagram showing the structure of a lane service data processing apparatus according to an embodiment;
FIG. 5 is a diagram of the internal structure of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a lane service data processing method is provided, which is exemplified by being applied to a terminal or a server, and includes the following steps:
and S101, constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework.
In this step, the Dapr distributed framework may be a Dapr distributed application framework; the worker node may be a worker node in a k8s cluster, such as a Pod, Pod charging service as shown in FIG. 2.
For example, in some embodiments, the building of the plurality of working nodes for processing the corresponding lane service data based on the Dapr distributed framework in step S101 specifically includes: and constructing a plurality of service modules for processing the lane service data into one working node for processing one corresponding lane service data based on the Dapr distributed framework aiming at each working node.
In some embodiments, the service module includes a plurality of service points, and the service points are constructed based on the Actor model.
Specifically, the independent service points are determined according to the service functions, each service point is realized on the basis of an Actor model, when the function of a certain service point changes, only the current service point can be updated without influencing the operation of other service points, local updating is realized, each service module comprises a plurality of service points, as shown in fig. 3, the internal structure of a work node is based on a Dapr distributed application framework, the internal logics of service points are independent from each other, the service points communicate with each other by means of message agents of the framework, the service points cooperate with each other to jointly complete the whole lane service data processing flow, a plurality of service modules including a plurality of service points construct a work node for processing service data of a corresponding lane, and the efficiency and convenience of function deployment, program update and problem repair of the lane service data processing system are improved.
Optionally, each service point includes implementation of state storage and service invocation, and in the process of processing a service block in charge of each service point, some data generated by the current service may be stored using the state storage, and each service point may also access data of other service points or disclosed methods in a service invocation manner. The state storage can be a Redis database, an Azure SQL Server, or other storage media with similar functions.
Step S102, a plurality of working nodes are deployed in a k8S cluster in a container mode.
In this step, the plurality of working nodes back up each other, that is, when one working node crashes, the other normal working node is automatically switched to, for example, when a certain working node fails to process lane service data under the conditions of error or crash, the k8s cluster is used to send the lane service data required to be processed by the wrong working node to another normal working node in the k8s cluster for processing, and the processed lane service data result can be fed back to a lane terminal, so that even when some working nodes fail to process the lane service data under the conditions of error or the like, the lane service data can be normally processed.
For example, in some embodiments, the deploying the plurality of working nodes in the k8S cluster in the manner of a container in step S102 specifically includes: deploying a plurality of working nodes in a container mode in a plurality of nodes in a k8s cluster; one node in the k8s cluster is set as a control node, and each node in the k8s cluster is managed by the control node.
As shown in fig. 2, a plurality of nodes, such as node 001, node 002, node 003, etc., may be deployed in the k8s cluster, the node ports may be set to the same node port number, as 32123, one or more working nodes (Pod charging service) may be deployed in the node, the port numbers of the working nodes may be set to the same port number, e.g. 8080, the same node port number and the same port number are set so that when a certain working node fails to process lane service data due to a fault or crash, the k8s cluster is used to send the lane service data that needs to be processed by the wrong node to another normal working node in the k8s cluster for processing, and then setting one node in the k8s cluster as a control node, managing each node in the k8s cluster by using the control node, completing the scheduling of resources and the management of the cluster state, and realizing the improvement of the efficiency and the accuracy of lane service data processing.
Optionally, as shown in fig. 2 and fig. 3, the lane service data processing system (e.g., a distributed service cluster lane system) is disposed in a station server (Windows/Linux/MacOS … …), a k8s cluster is disposed in the lane service data processing system, and a micro-service framework (Dapr distributed application framework) based on a grid service is adopted to partition a control plane/a data plane/a service plane, so that a service code is not invaded by the framework, and is convenient for development and upgrade; the lane service data processing system reconstructed by the Actor model has the advantages that the reality and the virtualization are completely consistent, the real service logic can be visually realized in the system, the understanding and the processing of developers to complex services can be greatly simplified, actors are completely decoupled, and the function is conveniently upgraded; by adopting a containerization deployment technology, a mirror image warehouse can be established, one-key deployment/upgrading is realized, a whole set of lane service data processing system and a database can be deployed within one minute by a new machine pre-installed with Docker, and software upgrading is only required for several seconds; a K8S rolling upgrading mechanism can be adopted, and updating without stopping the vehicle can be realized; the data storage medium is mounted on the frame in the form of modules which can be plugged and unplugged, so that a wide data storage mode is supported; the realization of full compatibility of a trusted platform is supported; various hardware platforms such as Intel, AMD, spread-green, sea lights, dragon cores, soars and mega cores are supported; various operating systems such as Windows, Debian, Ubuntu, macOS, CentOS, Loongnix, kylin and the like are supported; and various deployment modes such as bare machine operation, Docker standalone, K8S cluster, edge node and the like are supported.
Step S103, obtaining a plurality of lane service data to be processed, respectively inputting the plurality of lane service data to be processed into the k8S cluster corresponding to the working nodes for processing, and obtaining a plurality of lane service data processing results corresponding to the plurality of lane service data to be processed.
For example, in some embodiments, the obtaining of the multiple lane service data processing results corresponding to the multiple lane service data to be processed in step S103 specifically includes: processing lane service data to be processed by using a service publishing module aiming at each working node, and sending a lane service data processing result corresponding to the lane service data to be processed to a service subscribing module through a publishing and subscribing mode; and sending a lane service data processing result to the lane terminal by using the service subscription module.
The service module includes a service publishing module and a service subscribing module, the service publishing module includes a hardware service module, a parameter service module, a charging service module, a transaction service module and/or a transaction flow service module (for example, corresponding to lane hardware service, lane parameter service, lane charging service, lane transaction service and/or lane transaction flow service shown in fig. 2, or corresponding to hardware service, parameter service, charging service, transaction service and/or transaction flow shown in fig. 3), and the service subscribing module includes a system UI module (for example, corresponding to lane UI service shown in fig. 2, or corresponding to UI service shown in fig. 3).
Specifically, as shown in fig. 2 and 3, the hardware service module is used for monitoring the state of the lane equipment, feeding back the health condition of each equipment in real time, and simultaneously taking charge of analyzing and processing the data acquired by the equipment and controlling the functions of the equipment; the parameter service module is used for issuing and dumping basic parameters required by the lane and is responsible for uploading the traffic data of the lane transaction; the charging service module obtains a lane service data processing result corresponding to the lane service data to be processed (for example, the high-speed traffic charge of the vehicle is calculated by combining a unified rate file) according to the lane service data to be processed (for example, information such as a vehicle driving path and the like); the transaction service module is used for acquiring a plurality of lane service data to be processed (such as the collection and processing of information such as vehicle types/license plates and the like), feeding back the lane service data processing state in real time and generating running water (such as the vehicle transaction state and generating vehicle transaction running water); the transaction pipelining service module is used for splicing the pipelining generated by the transaction service module into a final pipelining and storing the final pipelining into the database through data transmission (for example, the transaction pipelining generated by the transaction service module is spliced into a final pipelining which can be used for settlement and stored into the database); the system UI module is used for providing a visual and user-friendly charging interface, providing visual display of a real-time lane service data processing result and providing a more convenient and visual lane service data processing result query and summary function (such as a more convenient vehicle transaction data query and summary function and more visual real-time charging information), wherein the visual mode can be a static data form, a two-dimensional or three-dimensional dynamic thermodynamic diagram, and the display terminal can be a desktop end or a mobile end.
Optionally, as shown in fig. 2, a plurality of lane service data to be processed sent by a lane service data collecting terminal (e.g., a toll lane terminal, which may be a PC terminal or a mobile terminal and may include a hardware service client and a lane interface) are received, the lane service data to be processed are input into a k8s cluster for load balancing, and are input into a working node (Pod charging service) in the node for processing, and the lane service data to be processed may also be distributed by using a service of a k8s cluster, as shown in fig. 2 and fig. 3, for each working node, a service publishing module is used to process one lane service data to be processed, wherein the service module is connected with a Dapr Sidecar (Sidecar) through a Dapr API to perform operations such as tracking, logging, and indexing, and may include Application (licensing), and resource binding may be input and output through event scanning by using the Sidecar (resource binding may be through evenb, ev, or mobile terminal and lane interface) Kafka, AWS SQS, GCP pub/sub … …), status management by loading and saving status can be performed by using Sidecar (status management can be performed by AWS dynamos db, CosmosDB, Redis, cassandra … …), publish subscription can be performed by information transceiving by using Sidecar (publish subscription can be performed by NATS, RabbitMQ, Service Bus, Redis … …), the Sidecar can perform secure communication by mTLS, and then send a lane traffic data processing result corresponding to one lane traffic data to be processed to the traffic subscription module through a mode of publish subscription (for example, the hardware Service module publishes a device status message to the message relay station, the system UI module and the transaction Service module bind the device status subscription on the message relay station, the message relay station forwards the device status message copy to the system UI module and the transaction Service module, the system UI module and the transaction Service module receive and process the device status message from the subscription, this completes a complete publish-subscribe process), and sends a lane service data processing result to the lane terminal by using the service subscribe module.
In the lane service data processing method, a plurality of working nodes for processing corresponding lane service data are constructed and obtained based on a Dapr distributed framework, the plurality of working nodes are deployed in a k8s cluster in a container mode, the plurality of working nodes are mutually backed up to obtain a plurality of lane service data to be processed, the plurality of lane service data to be processed are respectively input to corresponding working nodes in the k8s cluster to be processed, and a plurality of lane service data processing results corresponding to the plurality of lane service data to be processed are obtained. The scheme is based on a Dapr distributed framework to construct a plurality of working nodes, the working nodes are used for processing corresponding lane service data, the working nodes are arranged in a k8s cluster in a container mode, the working nodes are mutually backup, namely when a certain working node has the condition of errors and the like and cannot process the lane service data, the lane service data required to be processed by the error node is sent to another normal working node in a k8s cluster by using a k8s cluster for processing, and the processed lane service data result can be fed back to a lane terminal, so that the lane service data can be normally processed even if some working nodes have the condition of errors and the like and cannot process the service data, the efficiency and the convenience of function arrangement, program updating and problem repairing of the lane service data processing system can be improved by using the lane system structure, in practical application, a plurality of lane service data to be processed are obtained, and the lane service data to be processed are respectively input to corresponding working nodes in the k8s cluster for processing, for example, each working node processes the lane service data to be processed of one lane, and a plurality of lane service data processing results corresponding to the lane service data to be processed are obtained, so that the efficiency and the accuracy of lane service data processing are improved.
In an embodiment, the acquiring the traffic data of the plurality of lanes to be processed in step S103, and respectively inputting the traffic data of the plurality of lanes to be processed to the corresponding work nodes in the k8S cluster to process specifically includes: receiving vehicle types and license plates corresponding to a plurality of vehicles sent by a lane service data acquisition terminal; and respectively inputting the vehicle models and the license plates corresponding to the vehicles as a plurality of lane service data to be processed into a corresponding working node in the k8s cluster for processing.
Specifically, as shown in fig. 2, vehicle types and license plates corresponding to multiple vehicles sent by a lane service data collection terminal (e.g., a lane terminal of a toll lane) are received, and the vehicle types and license plates corresponding to the multiple vehicles are respectively input to a corresponding work node in a k8s cluster as multiple lane service data to be processed for processing (the lane service data to be processed sent by each lane service data collection terminal can be sent to a corresponding work node for processing), so that efficiency and accuracy of lane service data processing are improved.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides a lane service data processing device for realizing the lane service data processing method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so specific limitations in one or more embodiments of the lane service data processing device provided below can be referred to the limitations of the lane service data processing method in the above, and details are not described here.
In one embodiment, as shown in fig. 4, there is provided a lane service data processing apparatus, and the apparatus 400 may include:
the working node constructing module 401 is configured to construct a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework;
a work node deployment module 402, configured to deploy the plurality of work nodes in a container manner in the k8s cluster; the plurality of working nodes are backups of each other;
a processing result obtaining module 403, configured to obtain multiple pieces of lane service data to be processed, and input the multiple pieces of lane service data to be processed to corresponding work nodes in the k8s cluster respectively for processing, so as to obtain multiple lane service data processing results corresponding to the multiple pieces of lane service data to be processed respectively.
In one embodiment, the working node constructing module 401 is further configured to construct, for each working node, a plurality of service modules for lane service data processing based on the Dapr distributed framework, to be a working node for processing a corresponding lane service data.
In one embodiment, the service module comprises a service publishing module and a service subscribing module; the processing result obtaining module 403 is further configured to, for each working node, process one lane service data to be processed by using the service publishing module, and send a lane service data processing result corresponding to the lane service data to be processed to the service subscribing module through a publishing and subscribing mode; and sending the lane service data processing result to a lane terminal by using the service subscription module.
In one embodiment, the service module comprises a plurality of service points; the service point is constructed and obtained based on an Actor model.
In one embodiment, the working node deploying module 402 is further configured to deploy the plurality of working nodes in a container manner in a plurality of nodes in the k8s cluster; and setting one node in the k8s cluster as a control node, and managing each node in the k8s cluster by using the control node.
In an embodiment, the processing result obtaining module 403 is further configured to receive vehicle types and license plates corresponding to multiple vehicles sent by the lane service data acquisition terminal; and respectively inputting the vehicle types and the license plates corresponding to the vehicles as the service data of the lanes to be processed into a corresponding work node in the k8s cluster for processing.
The modules in the lane service data processing device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing the traffic data of the lanes to be processed. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a lane service data processing method.
It will be appreciated by those skilled in the art that the configuration shown in fig. 5 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, carries out the steps in the method embodiments described above.
It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided herein can include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in the embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. A method of lane service data processing, the method comprising:
constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on a Dapr distributed framework;
deploying the plurality of worker nodes in a container manner in a k8s cluster; the plurality of working nodes are backups of each other;
and acquiring a plurality of lane service data to be processed, and respectively inputting the lane service data to be processed to corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the lane service data to be processed.
2. The method according to claim 1, wherein the constructing a plurality of working nodes for processing the corresponding lane service data based on the Dapr distributed framework comprises:
and constructing a plurality of service modules for lane service data processing into one working node for processing one corresponding lane service data based on the Dapr distributed framework aiming at each working node.
3. The method of claim 2, wherein the service module comprises a service publishing module and a service subscribing module; the obtaining of the multiple lane service data processing results corresponding to the multiple lane service data to be processed includes:
for each working node, processing lane service data to be processed by using the service publishing module, and sending a lane service data processing result corresponding to the lane service data to be processed to the service subscribing module through a publishing and subscribing mode;
and sending the lane service data processing result to a lane terminal by using the service subscription module.
4. The method of claim 2, wherein the service module comprises a plurality of service points; the service point is constructed and obtained based on the Actor model.
5. The method of claim 1, wherein the container-wise deploying the plurality of worker nodes in a k8s cluster comprises:
deploying the plurality of working nodes in a container manner in a plurality of nodes in a k8s cluster;
and setting one node in the k8s cluster as a control node, and managing each node in the k8s cluster by using the control node.
6. The method according to claim 1, wherein the obtaining a plurality of lane service data to be processed and inputting the plurality of lane service data to be processed into corresponding work nodes in the k8s cluster respectively for processing comprises:
receiving vehicle types and license plates corresponding to a plurality of vehicles sent by a lane service data acquisition terminal;
and respectively inputting the vehicle types and the license plates corresponding to the vehicles as the service data of the lanes to be processed into a corresponding work node in the k8s cluster for processing.
7. A lane service data processing apparatus, characterized in that the apparatus comprises:
the working node construction module is used for constructing and obtaining a plurality of working nodes for processing corresponding lane service data based on the Dapr distributed framework;
the working node deployment module is used for deploying the working nodes in a k8s cluster in a container mode; the plurality of working nodes are backups of each other;
and the processing result obtaining module is used for obtaining a plurality of lane service data to be processed, and respectively inputting the plurality of lane service data to be processed to the corresponding working nodes in the k8s cluster for processing to obtain a plurality of lane service data processing results respectively corresponding to the plurality of lane service data to be processed.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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