CN115357400B - Resource warehousing method and system based on Kubernetes recording and broadcasting manufacturers - Google Patents
Resource warehousing method and system based on Kubernetes recording and broadcasting manufacturers Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/5038—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the execution order of a plurality of tasks, e.g. taking priority or time dependency constraints into consideration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
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- G06F9/5083—Techniques for rebalancing the load in a distributed system
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/54—Interprogram communication
- G06F9/546—Message passing systems or structures, e.g. queues
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
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Abstract
The invention relates to a resource warehousing method and a resource warehousing system based on Kubernets recording and broadcasting manufacturers, wherein the resource warehousing method comprises a recording and broadcasting manufacturer, a recording and broadcasting manufacturer management platform, a scheduling platform, a Celery and a K8s Job; the recording and broadcasting manufacturer is used for recording and temporarily storing the teaching contents generated by the school; the recording and broadcasting manufacturer management platform is used for managing information of multiple recording and broadcasting manufacturers and issuing warehousing tasks; the scheduling platform is used for receiving the warehousing task request and detecting the running state of the task; celery is used for realizing the circulation, the scheduling and the persistence of tasks; and the K8s Job is used for executing mirroring for the task, is responsible for judging the resource type and executing direct downloading and warehousing or transcoding and warehousing. The invention issues tasks through the intelligent scheduling platform, issues different processing tasks according to different task judgment conditions, and realizes the issuing and detection of large-scale tasks based on the Kubernetes task scheduling, thereby ensuring the possibility of warehousing of mass data.
Description
Technical Field
The invention relates to the technical field of data resource storage, in particular to a resource warehousing method and system based on Kubernetes recording and broadcasting manufacturers.
Background
Along with the popularization of online education, more and more teaching recorded broadcast video resources are generated, and the requirement for unified warehousing management of the teaching recorded broadcast video resources is derived. The teaching recorded broadcast video resources can be produced by equipment of different manufacturers and stored in different storage equipment; this creates the following difficulties for resource unified warehousing management: 1. resource dispersion: resources are scattered in different hardware carriers, such as channels of recording and broadcasting hosts, file storage, object storage, recording and broadcasting platforms and the like, and a user cannot realize unified learning among different manufacturers, different carriers and different platforms; 2. the formats are different: the instructional recorded video assets generated by the various vendors' equipment may have different formats or packages (some of them even sliced video assets). If the output of a traditional manufacturer based on monitoring is mostly avi, the recording format of the intelligent camera is mostly mp4, the manufacturer based on cloud recording and broadcasting equipment is mostly m3u8, and how to store the resources in a unified format is a key point for resource storage and unified management; 3. content inconsistency: among different manufacturers, there are audio-free video formats with no surveillance camera and with ACC, and there are encoding formats for H264, VP9, VP8, and the like. How to identify whether the warehousing resource meets the warehousing requirement, how to determine the resource which does not meet the requirement to perform the next step and the like are key problems.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a resource warehousing method and a system based on Kubernetes recording and broadcasting manufacturers, and solves the defects in the conventional resource warehousing management.
The purpose of the invention is realized by the following technical scheme: a resource warehousing system based on Kubernetes recording and broadcasting manufacturers comprises recording and broadcasting manufacturers, a recording and broadcasting manufacturer management platform, a scheduling platform, a Celery, a K8s Job and a resource library; the recording and broadcasting manufacturer is used for recording and temporarily storing teaching contents generated by schools; the recording and broadcasting manufacturer management platform is used for managing information of multiple recording and broadcasting manufacturers, and integrating and executing warehouse entry task issuing of recording and broadcasting data; the scheduling platform is used for receiving the warehousing task request and detecting the running state of the task; the Celery is used for realizing the circulation, the scheduling and the persistence of tasks; the K8s Job is used for executing mirroring for the task, and is responsible for judging the resource type and executing direct downloading and warehousing or transcoding and warehousing; the resource library is used for centralized management of educational resources.
The dispatching platform comprises a dispatching platform Service and a dispatching platform Worker; the scheduling platform Service is responsible for receiving the warehousing task request, maintaining task information and pushing the task information into a queue; and the scheduling platform Worker is responsible for taking out task information from the task queue to execute and detecting the running state of the task.
A method of a resource warehousing system based on a Kubernetes recording and broadcasting manufacturer, the method comprising:
managing and accessing by a recording and broadcasting manufacturer: the platform provides the management of a recording and broadcasting manufacturer and access API specification, and supports data docking in a mode of SDK (software development kit) of the recording and broadcasting manufacturer or a mode reported by standard HTTP (hyper text transport protocol);
recording and broadcasting resource data issuing step: the recording and broadcasting manufacturer management platform initiates a request to the scheduling platform Service to realize the issuing of the recording and broadcasting resource task, the scheduling platform Service creates and records task information, and the task information flow is transferred to the scheduling platform Worker through the Celery task queue;
scheduling and executing the recorded and broadcast warehousing task; after receiving the task information, the scheduling platform worker calls a K8s interface, creates a task Job, and then packages the task Job and executes the operations of a video detection instruction, a download instruction and a video transcoding task;
recording, broadcasting and warehousing task state detection and pushing steps: and polling the state of the task Job, then performing resource warehousing, recording a response result of the resource warehousing, and pushing the response result to a message queue.
The scheduling and executing steps of the recording, broadcasting and warehousing task specifically comprise:
after receiving task information, the scheduling platform worker calls an interface of K8s to create a task Job, and by labeling the Job or adding node tolerance, the utilization of the K8s self scheduling logic is realized, and the purposes of load balancing among the nodes of the multiple hosts and specific node avoidance are achieved;
and performing operations of a video detection command, a download command and a video transcoding task based on the encapsulation of the functions of the MPC and the FFmpeg in the task Job container.
The recording, broadcasting and warehousing task state detection and pushing step specifically comprises the following steps:
the dispatching platform Worker polls the state of the task Job through a K8s interface, and calls a warehousing interface of the resource library to perform resource warehousing when the state is successful;
and the scheduling platform Worker records the response result of resource warehousing and pushes the response result into a message queue.
In the recording and broadcasting manufacturer management and access step, the binding relationship between the course and the recording and broadcasting manufacturer is established based on the relationship binding between the course and the teaching classroom and the relationship binding between the classroom and the recording and broadcasting, so as to serve the course resource warehousing.
The invention has the following advantages: a resource warehousing method and a resource warehousing system based on Kubernetes recording and broadcasting manufacturers are characterized in that tasks are issued through an intelligent scheduling platform, different processing tasks are issued according to different task judgment conditions, and large-scale tasks are issued and detected based on Kubernetes task scheduling, so that the possibility of warehousing of mass data is guaranteed.
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FIG. 1 is a schematic flow diagram of the process of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings, but the scope of the invention is not limited to the following.
The invention provides a solution to the problems of inconsistent video formats, inconsistent sources, inconsistent contents and the like among different recording and broadcasting manufacturers of the intelligent classroom; the intelligent scheduling platform is used for issuing tasks, different processing tasks are issued according to different task judgment conditions, and the issuing and detection of large-scale tasks are realized based on Kubernets task scheduling, so that the possibility of warehousing of mass data is guaranteed. The method specifically comprises the following steps:
recording and broadcasting manufacturers: the system is responsible for recording and temporarily storing the teaching contents (namely original resources) produced by schools; recording and broadcasting manufacturer management platform: the system is responsible for managing information of multiple recording and broadcasting manufacturers, and integrating and executing the storage task issuing of the recording and broadcasting data; scheduling platform Service: the system is responsible for receiving the warehousing task request, storing task information and pushing the task information to enter a queue; celery: the task queue component based on the RabbitMQ or the Redis is responsible for the circulation, the scheduling, the persistence and the like of the tasks; a dispatching platform Worker: the system is responsible for taking out and executing the task information from the task queue and detecting the running state of the task; k8s Job: calling a K8s task interface by a scheduling platform Worker to initiate, executing mirror image for a specific task, judging the resource type and executing direct downloading and warehousing or transcoding and warehousing; resource pool: a centralized management platform of educational resources and a terminal point of resource circulation.
As shown in fig. 1, the flow of the present invention is as follows:
managing and accessing by recording and broadcasting manufacturers: the platform provides the management of the recording and broadcasting manufacturer and the specification of the access API, and supports the data docking in the SDK mode or standard HTTP reporting mode of the recording and broadcasting manufacturer. Establishing a binding relationship between the course and the recording and broadcasting manufacturer based on the binding relationship between the course and the teaching classroom and the binding relationship between the classroom and the recording and broadcasting, and serving course resource warehousing;
and (3) issuing recorded broadcast resource data: the recording and broadcasting manufacturer management platform sends a request to the scheduling platform Service to realize the issuing of the recording and broadcasting resource task; the Service of the dispatching platform creates and records task information, and transfers the task information flow to the Worker of the dispatching platform through the Celery task queue;
further, encapsulating the task image, the image supporting receiving parameters: the method comprises the steps of obtaining a source file URL and an output path, judging whether transcoding is needed or not based on the type of the source file by using an MPC (multimedia personal computer), carrying out transcoding downloading or direct downloading, and finally storing the file to the specified output path;
the recording and broadcasting manufacturer management Service takes a source file URL and metadata of a video as parameters, and initiates a request to a scheduling platform Service through a RESTful API (application programming interface);
scheduling a recording, broadcasting and warehousing task: after receiving the task information, the scheduling platform Worker calls an interface of K8s to create a task Job; through labeling Job or adding node tolerance, the utilization of the self scheduling logic of K8s is realized, and the purposes of load balance among multiple host nodes and avoidance of specific nodes are achieved;
and (4) executing the recording, broadcasting and warehousing task: basic operations such as a video detection instruction, a download instruction, a video transcoding task and the like are executed in the task Job container based on the function encapsulation of the MPC and the FFmpeg;
and (3) recording, broadcasting and warehousing task state detection: the scheduling platform Worker polls the state of the task Job through a K8s interface, and calls a warehousing interface of the resource library to perform resource warehousing when the state is successful;
and (3) pushing the recorded and broadcast warehousing task result: and the dispatching platform Worker records the response result of resource warehousing, pushes the response result into a message queue and takes the response result by a related party with a demand.
Furthermore, the scheduling platform Service receives information such as a source file URL and metadata of the video, checks and records the information, uses the information as task information, pushes the task information to a Celery task queue, and then responds to the recording and broadcasting manufacturer management Service;
taking out task information from the Celery task queue by a scheduling platform Worker, generating an output path corresponding to the task according to a format agreed with a resource library, and calling an API of K8s to create a K8s Job together with a source file URL in the task information as a parameter; one scheduling platform Worker can simultaneously manage a plurality of K8s Job (the quantity can be adjusted according to the performance of a host machine); and the dispatching platform Service and the Worker run based on K8s stateless Service, and support the transverse expansion.
The created K8s Job runs a task container based on the task mirror image packaged in the first step, and the task container and the resource library are mounted with the same storage; judging a format according to an expected flow, transcoding to download or directly downloading the resource to a specified path (if an error occurs, an exception is thrown, and the K8s Job sets the state as a failure after a plurality of retries);
the scheduling platform Worker regularly detects the status of the created K8s Job. If the state is successful, taking the output path and the metadata as parameters, calling a warehousing interface of the resource platform for warehousing, and taking the response of the warehousing interface as a task result; if the state is failure, setting the task result as failure;
the scheduling platform Worker records the task results and pushes the task results to a message queue (such as Kafka or RabbitMQ) for self-subscription for retrieval by the interested party.
The foregoing is illustrative of the preferred embodiments of the present invention, and it is to be understood that the invention is not limited to the precise form disclosed herein and is not to be construed as limited to the exclusion of other embodiments, and that various other combinations, modifications, and environments may be used and modifications may be made within the scope of the concepts described herein, either by the above teachings or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. A method of a resource warehousing system based on Kubernetes recording and broadcasting manufacturers is characterized in that:
a resource warehousing system based on a Kubernetes recording and broadcasting manufacturer: the system comprises a recording and broadcasting manufacturer, a recording and broadcasting manufacturer management platform, a scheduling platform, a Celery, a K8s Job and a resource library; the recording and broadcasting manufacturer is used for recording and temporarily storing teaching contents generated by schools; the recording and broadcasting manufacturer management platform is used for managing information of multiple recording and broadcasting manufacturers, and integrating and executing warehouse entry task issuing of recording and broadcasting data; the scheduling platform is used for receiving the warehousing task request and detecting the running state of the task; the Celery is used for realizing the circulation, the scheduling and the persistence of tasks; the K8s Job is used for executing mirroring for the task, and is responsible for judging the resource type and executing direct downloading and warehousing or transcoding and warehousing; the resource library is used for centralized management of educational resources;
the method comprises the following steps:
recording and broadcasting manufacturer management and access steps: the platform provides the management and access API specification of the recording and broadcasting manufacturer, and supports data docking in the SDK mode of the recording and broadcasting manufacturer or the standard HTTP reporting mode;
and (3) recording and broadcasting resource data issuing: the recording and broadcasting manufacturer management platform initiates a request to the scheduling platform Service to realize the issuing of the recording and broadcasting resource task, the scheduling platform Service creates and records task information, and the task information flow is transferred to the scheduling platform Worker through the Celery task queue;
scheduling and executing the recorded and broadcast warehousing task; after receiving the task information, the scheduling platform worker calls a K8s interface, creates a task Job, and then packages the task Job and executes the operations of a video detection instruction, a downloading instruction and a video transcoding task;
recording, broadcasting and warehousing task state detection and pushing steps: and polling the state of the task Job, then performing resource warehousing, recording a response result of the resource warehousing, and pushing the response result to a message queue.
2. The method of the resource warehousing system based on the Kubernetes recording and broadcasting manufacturer according to claim 1, characterized in that: the dispatching platform comprises a dispatching platform Service and a dispatching platform Worker; the scheduling platform Service is responsible for receiving the warehousing task request, maintaining task information and pushing the task information into a queue; and the scheduling platform Worker is responsible for taking out task information from the task queue to execute and detecting the running state of the task.
3. The method of the resource warehousing system based on the kubernets recording and broadcasting manufacturer according to claim 1 or 2, characterized in that: the recording, broadcasting and warehousing task scheduling and executing step specifically comprises the following steps:
after receiving the task information, the scheduling platform worker calls an interface of K8s to create a task Job, and realizes utilization of the scheduling logic of the K8s by labeling the Job or adding node tolerance, so that the purposes of load balancing among the multiple host nodes and avoiding of specific nodes are achieved;
and performing operations of a video detection command, a download command and a video transcoding task based on the encapsulation of the functions of the MPC and the FFmpeg in the task Job container.
4. The method of claim 3, wherein the resource warehousing system comprises: the recording, broadcasting and warehousing task state detection and pushing step specifically comprises the following steps:
the scheduling platform Worker polls the state of the task Job through a K8s interface, and calls a warehousing interface of the resource library to perform resource warehousing when the state is successful;
and the dispatching platform Worker records the response result of resource warehousing and pushes the response result to the message queue.
5. The method of claim 4 for a resource warehousing system based on Kubernets recording and broadcasting manufacturers, characterized in that: in the recording and broadcasting manufacturer management and access step, the binding relationship between the course and the recording and broadcasting manufacturer is established based on the relationship binding between the course and the teaching classroom and the relationship binding between the classroom and the recording and broadcasting, so as to serve the course resource warehousing.
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