CN115277579A - Warehouse video calling method and cloud platform - Google Patents
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- H—ELECTRICITY
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Abstract
The application provides a warehouse video calling method and a cloud platform, wherein the method comprises the following steps: the cluster server acquires a video calling task and a task priority of the video calling task, and adds the video calling task to a task queue according to the task priority; for each execution server, when the execution server is in an idle state, the execution server performs task preemption operation on the cluster server so as to preempt the execution permission of the video retrieval task corresponding to the highest priority in the task queue; the cluster server allocates the video calling task corresponding to the highest priority to an execution server with a task preemption success; and for each execution server, under the condition that the execution server is distributed with the video calling task, executing the distributed video calling task to download the warehouse video to be called from the equipment platform of the warehouse monitoring equipment. By adopting the method and the device, the average response time of the video frequency acquisition task can be shortened.
Description
Technical Field
The application relates to the technical field of warehouse management, in particular to a warehouse video calling method and a cloud platform.
Background
In e-commerce sales, in order to clear the state of commodities in the shipment link and provide after-sale services for customers, e-commerce sales enterprises can respectively install a plurality of warehouse monitoring devices in a warehouse and on a workbench to respectively shoot the warehouse and the workbench, so that warehouse videos can record the commodity state of the commodities in the shipment link.
When after-sale service is provided or the shipment condition of the commodity is traced back, the staff can call the warehouse video from the equipment platform of the warehouse monitoring equipment through the video call system so as to determine the commodity state of the shipment link of the commodity. However, the inventor researches and finds that in the prior art, when the warehouse video is called, the response time is too long, in other words, a worker needs to obtain the warehouse video after a long waiting time.
Disclosure of Invention
The object of the present application is to solve at least one of the above-mentioned technical drawbacks, in particular the technical drawback of the prior art of excessively long response times.
In a first aspect, an embodiment of the present application provides a warehouse video retrieval method, where the method is applied to a cloud platform, where the cloud platform includes a cluster server and multiple execution servers, and the method includes:
the cluster server acquires a video calling task and a task priority of the video calling task, and adds the video calling task to a task queue according to the task priority;
for each execution server, when the execution server is in an idle state, the execution server performs task preemption operation on the cluster server so as to preempt the execution permission of the video invoking task corresponding to the highest priority in the task queue;
the cluster server allocates the video calling task corresponding to the highest priority to an execution server with a task preemption success;
and for each execution server, under the condition that the execution server is distributed with the video calling task, executing the distributed video calling task to download the warehouse video to be called from the equipment platform of the warehouse monitoring equipment.
In one embodiment, for each execution server, the step of executing the allocated video retrieval task to download the warehouse video to be retrieved from the device platform of the warehouse monitoring device when the execution server is allocated with the video retrieval task includes:
for each execution server, under the condition that the execution server is allocated with a video calling task, acquiring an effective network connection from an SDK connection pool configured by the execution server, and sending a video downloading request to an equipment platform of the warehouse monitoring equipment through the effective network connection so as to enable the equipment platform to return the warehouse video to be called to the execution server;
the SDK connection pool is used for storing information of network connection between the cloud platform and the equipment platform.
In one embodiment, the cloud platform further comprises a cloud storage object server, and the method further comprises:
for each execution server, after downloading the warehouse video to be called, the execution server transcodes the warehouse video to be called to obtain the warehouse video in the H264 format, and uploads the warehouse video in the H264 format to the cloud storage object server.
In one embodiment, after the step of the execution server uploading the warehouse video in the H264 format to the cloud storage object server, the method further includes:
the cluster server allocates a temporary uniform resource locator to the playing device, so that the playing device obtains the warehouse video to be played from the cloud storage object server based on the temporary uniform resource locator.
In one embodiment, the step of acquiring the video retrieval task by the cluster server includes:
the cluster server receives a calling demand sent by a user, wherein the calling demand comprises a commodity ex-warehouse number and a link identification of an ex-warehouse link corresponding to a to-be-called warehouse video;
the cluster server acquires a commodity ex-warehouse log, and inquires the commodity ex-warehouse log according to the commodity ex-warehouse serial number and the link identification so as to determine an equipment identification of warehouse monitoring equipment for shooting the warehouse video to be called and a shooting time period corresponding to the warehouse video to be called;
and the cluster server generates the video calling task according to the equipment identification and the shooting time interval.
In one embodiment, the step of acquiring the task priority of the video retrieval task by the cluster server includes:
the cluster server determines a target user identity, wherein the target user identity is a user identity corresponding to the user sending the calling requirement;
the cluster server determines a target task priority corresponding to the target user identity from a preset mapping relation, the target task priority is used as a task priority of the video calling task, and the preset mapping relation is the mapping relation between the user identity and the task priority.
In one embodiment, the method further comprises: and the cluster server writes the video calling task into a task database.
In a second aspect, an embodiment of the present application provides a cloud platform, where the cloud platform includes a cluster server and multiple execution servers, where:
the cluster server is used for acquiring a video calling task and the task priority of the video calling task, and adding the video calling task to a task queue according to the task priority;
for each execution server, when the execution server is in an idle state, the execution server is used for performing task preemption operation on the cluster server so as to preempt the execution permission of the video retrieval task corresponding to the highest priority in the task queue;
the cluster server is used for distributing the video calling task corresponding to the highest priority to the execution server which is successful in task preemption;
and for each execution server, the execution server is used for executing the distributed video calling task under the condition that the video calling task is distributed, so as to download the warehouse video to be called from the equipment platform of the warehouse monitoring equipment.
In one embodiment, the cloud platform further comprises a cloud storage object server. And for each execution server, the execution server is further configured to, after downloading the warehouse video to be called, transcode the warehouse video to be called to obtain a warehouse video in an H264 format, and upload the warehouse video in the H264 format to the cloud storage object server.
In one embodiment, the cluster server is further configured to write the video retrieval task into a task database.
In the warehouse video calling method and the cloud platform provided by the embodiment of the application, the cloud platform can comprise a cluster server and a plurality of execution servers. The cluster server can acquire the video calling task and the task priority corresponding to the video calling task, and adds the acquired video calling task to the task queue according to the task priority. Each execution server in the idle state can perform task preemption operation on the cluster server to preempt the execution permission of the video retrieval task corresponding to the highest priority in the task queue. The cluster server may allocate a video retrieval task corresponding to the highest priority to the successfully preempted execution server, so as to download the warehouse video to be retrieved from the device platform of the warehouse monitoring device through the server resource of the successfully preempted execution server. Therefore, each video calling task in the task queue can be preempted according to the server dimension, different video calling tasks are executed through the multiple execution servers respectively, the multiple video calling tasks are executed concurrently, the response speed of the video calling tasks can be increased, the average response time of the video calling tasks is shortened, and user experience can be improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a schematic block diagram of a cloud platform in one embodiment;
FIG. 2 is a schematic flow chart diagram of a warehouse video retrieval method in one embodiment;
FIG. 3 is a flowchart illustrating a step of a cluster server acquiring a video retrieval task according to an embodiment;
fig. 4 is a flowchart illustrating a task priority step of acquiring a video retrieval task by a cluster server in an embodiment.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
As background art, the prior art has the problem of too long response time when a warehouse video is called. The inventor researches and finds that the problem is caused because the video calling system in the prior art is realized by a single machine. In other words, in the prior art, all video calling tasks are executed by a single server, so that simultaneous execution of multiple tasks is not supported, concurrency performance is poor, and expansibility is not strong.
Meanwhile, when a single video retrieval task is executed, the server needs to first establish a network connection between the server and the device platform of the warehouse monitoring device by using an SDK (Software Development Kit) provided by a device vendor of the warehouse monitoring device, and in the establishment process, steps such as initialization, login, downloading, link release, resource consumption release and the like need to be performed. After the network connection is established, the server downloads the warehouse video to be called from the equipment platform of the warehouse monitoring equipment through the network connection and transcodes the warehouse video to be called. Therefore, the server needs to consume a large amount of CPU (Central Processing Unit), memory and IO (Input/Output) resources when executing a single video retrieval task, the execution time of the single video retrieval task is long, and the average response time of each video retrieval task is further increased.
In order to solve the foregoing problems, embodiments of the present application provide a warehouse video retrieval method and a cloud platform, seize each video retrieval task in a task queue according to server dimensions, and execute different video retrieval tasks respectively through a plurality of execution servers, so as to implement concurrent and parallel execution of the plurality of video retrieval tasks, thereby increasing response speed of the video retrieval tasks, shortening average response time of the video retrieval tasks, and further improving user experience.
In one embodiment, the present application provides a cloud platform. As shown in fig. 1, the cloud platform includes a cluster server 102 and a plurality of execution servers 104, and it is understood that the specific number of execution servers 104 may be determined according to practical situations, and is not particularly limited in this application.
The cluster server 102 refers to a server having functions of task management and task allocation, and may be a Redis cluster server, or another server having a Redis cluster characteristic, which is not limited in this application. The execution server 104 refers to a server that can be used to execute a video retrieval task, and may have one or more threads running therein, and the execution server 104 may perform task preemption operations through the threads running thereon. The cluster servers 102 may be used to manage threads on each execution server 104 and to distribute tasks accordingly.
In one embodiment, the cloud platform may also include a cloud storage object server, such as an OSS (Operation Support Systems) cloud storage object server. The cloud storage object server may be configured to store the to-be-retrieved warehouse videos acquired by each execution server 104 after executing the video retrieval task, so as to implement mass video storage.
With respect to the cluster server 102, the execution server 104, and the cloud storage object server according to the foregoing embodiments, the execution steps of each server may be as described in any embodiment of the warehouse video retrieval method, and the foregoing embodiments may be understood in combination with any embodiment of the warehouse video retrieval method.
In one embodiment, the application provides a warehouse video retrieval method. As shown in fig. 2, the method specifically includes the following steps:
s202, the cluster server obtains a video calling task and the task priority of the video calling task, and adds the video calling task to a task queue according to the task priority.
The video calling task refers to a task for calling the warehouse video in the corresponding time period from the equipment platform of the warehouse monitoring equipment. In one embodiment, the video retrieval task may include an equipment identifier of a warehouse monitoring device used for shooting a warehouse video to be retrieved, and a shooting period corresponding to the warehouse video to be retrieved, so that the execution server performs video retrieval according to task information of the video retrieval task, and then completes the video retrieval task.
The video calling task may correspond to a task priority, and the task priority may be used to reflect a task execution order of the video calling task. The task queue may be configured to maintain video retrieval tasks, and when the task queue includes a plurality of video retrieval tasks, the video retrieval tasks are ordered according to task priority, for example, the video retrieval tasks may be ordered from high to low priority or ordered from low to high priority.
When the cluster server obtains the video calling task, the video calling task can be added to a corresponding position of a task queue according to the task priority of the video calling task, so that each video calling task can be arranged according to a preset priority order in the added task queue.
In one embodiment, the method further comprises: and the cluster server writes the video calling task into a task database. In other words, when the video calling task is acquired, the cluster server may perform double writing to add the video calling task to the task queue and write the video calling task to the task database, respectively. Therefore, each video calling task can be recorded through the task database, and task tracing can be conducted in the later stage conveniently.
And S204, aiming at each execution server, when the execution server is in an idle state, the execution server performs task preemption operation on the cluster server so as to preempt the execution permission of the video retrieval task corresponding to the highest priority in the task queue.
The idle state is a state in which the execution server has enough idle resources to execute the video retrieval task, and may be, for example, a state in which the execution server does not execute the task. When the task queue comprises at least one video calling task, for the video calling task corresponding to the highest priority in the task queue, each execution server in an idle state in the cloud platform performs task preemption on the video calling task so as to try to acquire the execution permission of the video calling task.
And S206, the cluster server allocates the video calling task corresponding to the highest priority to the execution server with the task preemption success.
In one embodiment, after the video retrieval task corresponding to the highest priority is allocated, the cluster server may delete the allocated video retrieval task from the task queue, so as to update the task queue in real time according to the task allocation condition, so that the execution server of the cloud platform continues to seize the next video retrieval task according to step S204 until the video retrieval task is not included in the task queue.
And S208, for each execution server, the execution server executes the distributed video calling task under the condition that the video calling task is distributed, so as to download the warehouse video to be called from the equipment platform of the warehouse monitoring equipment.
Specifically, when an execution server is allocated with the execution right of the video calling task, the execution server can execute the allocated video calling task through the resource of the execution server so as to acquire the warehouse video to be called from the equipment platform of the warehouse monitoring equipment.
According to the embodiment of the application, each video calling task in the task queue can be preempted according to the server dimension, different video calling tasks are executed through the multiple execution servers respectively, and the multiple video calling tasks are executed concurrently and parallelly, so that the response speed of the video calling tasks can be increased, the average response time of the video calling tasks is shortened, and further the user experience can be improved. In addition, the scheme of this application can be adopted to solve the issue efficiency inefficiency problem, promotes the fortune ability of maintaining certainly, promotes the performance.
In one embodiment, the step of, for each execution server, executing the allocated video retrieval task to download the warehouse video to be retrieved from the device platform of the warehouse monitoring device when the execution server is allocated with the video retrieval task, includes:
for each execution server, under the condition that the execution server is allocated with a video calling task, acquiring an effective network connection from an SDK connection pool configured by the execution server, and sending a video downloading request to an equipment platform of the warehouse monitoring equipment through the effective network connection so that the equipment platform returns the warehouse video to be called to the execution server;
the SDK connection pool is used for storing information of network connection between the cloud platform and the equipment platform.
Specifically, if the execution server directly uses the SDK provided by the equipment provider to construct the network connection between the execution server and the equipment platform of the warehouse monitoring equipment, the steps of initializing, logging in, downloading, releasing links, releasing consumed resources, and the like are required in the construction process, which takes a long time. Moreover, because the SDK provided by the device vendor is implemented based on C + +, and the execution server is implemented based on Java, the problem of incompatibility between C + + and Java will further increase the time consumption for constructing the network connection, thereby increasing the average response time of the video retrieval task.
In order to further accelerate the response speed of the video calling task and shorten the average response time of the video calling task, the network connection between the cloud platform and the equipment platform can be maintained through the SDK connection pool, and the multiplexing of the network connection is realized. When the execution server executes the video retrieval task, the execution server can directly acquire effective network connection from the SDK connection pool without the steps of initialization, login, link release and resource consumption, so that repeated login can be avoided, the parallelism of task execution is improved, the response speed of the video retrieval task can be further increased, and the average response time of the video retrieval task is shortened.
Specifically, the SDK connection pool may be configured in each execution server, and may be used to store information of network connections between the cloud platform and the device platform. The execution server can acquire an effective network connection from the SDK connection pool under the condition that the video calling task is distributed, and send a video downloading request to an equipment platform of the warehouse monitoring equipment through the acquired effective network connection, so that the equipment platform can receive the video downloading request. The device platform can respond to the video downloading request when receiving the request, and returns a corresponding warehouse video to the execution server sending the request, wherein the corresponding warehouse video is the warehouse video to be called.
In one embodiment, the cloud platform further comprises a cloud storage object server, the method further comprising: for each execution server, after downloading the warehouse video to be called, the execution server transcodes the warehouse video to be called to obtain the warehouse video in the H264 format, and uploads the warehouse video in the H264 format to the cloud storage object server.
The warehouse video to be called returned by the equipment platform is generally in an H265 format with high compression ratio. However, most of the mainstream players and video playing plug-ins do not support the H265 format, and cannot directly play the video in the format. Therefore, in order to enable the warehouse video to be called to be played in the playing device, after the execution server downloads the warehouse video to be called in the high compression ratio format from the device platform, the execution server needs to transcode the video to obtain the warehouse video in the H264 format. After the warehouse video in the H264 format is obtained, the execution server may upload the warehouse video in the H264 format to the cloud storage object server, so as to implement mass video storage through the cloud storage object server.
In one embodiment, after the step of uploading, by the execution server, the warehouse video in the H264 format to the cloud storage object server, the method further includes: the cluster server allocates a temporary uniform resource locator to the playing device, so that the playing device obtains the warehouse video to be played from the cloud storage object server based on the temporary uniform resource locator.
Specifically, after the execution server uploads the warehouse video in the H264 format to the cloud storage object server, the playing device may obtain the corresponding warehouse video from the cloud storage object server and play the warehouse video. At this time, the cluster server may allocate a temporary URL (Uniform Resource Locator) to the playback device, so that the playback device may pull the stream data from the cloud storage object server through the temporary URL to buffer the warehouse video to be played. Therefore, the video buffering time of the playing equipment can be shortened, and the video processing speed is further improved. In one embodiment, the playback device can play back the warehouse video through its configured H5 video playback plug-in.
In an embodiment, as shown in fig. 3, the step of acquiring the video retrieval task by the cluster server includes:
s302, the cluster server receives a calling requirement sent by a user, wherein the calling requirement comprises a commodity ex-warehouse number and a link identifier of an ex-warehouse link corresponding to a to-be-called warehouse video;
s304, the cluster server acquires a commodity ex-warehouse log, and inquires the commodity ex-warehouse log according to the commodity ex-warehouse number and the link identification so as to determine an equipment identification of warehouse monitoring equipment for shooting the warehouse video to be called and a shooting time period corresponding to the warehouse video to be called;
s306, the cluster server generates the video calling task according to the equipment identification and the shooting time interval.
Specifically, when a user has a warehouse video calling demand, the user can send a calling demand to the cluster server, and the calling demand can include a commodity ex-warehouse number and a link identifier of an ex-warehouse link corresponding to a warehouse video to be called, so that the cluster server can determine video information of the warehouse video to be called according to the link identifier. The commodity ex-warehouse number may be a unique number of the commodity in the ex-warehouse link, and may be an order number or a waybill number, for example. Due to the fact that the commodities need to pass through a plurality of links (such as a picking link, a packing link, a conveying link and the like) in the delivery process, time consumption is relatively long, and in some cases, a user only wants to determine the state of the commodities in one link or a plurality of links when calling videos, and does not need to obtain complete delivery videos. Therefore, the retrieval requirement may include a link identifier of an ex-warehouse link corresponding to the warehouse video to be retrieved, so as to retrieve a warehouse video segment corresponding to the link identifier, such as a warehouse video corresponding to a packaging link or a warehouse video corresponding to a picking link.
The cluster server can obtain a commodity export log, wherein the commodity export log records information corresponding to each commodity in each export link, such as a commodity export number, each link identification and a time period when the commodity corresponding to the commodity export number is in the corresponding export link. After the cluster server obtains the calling requirement, the commodity ex-warehouse number and the link identification can be extracted from the calling requirement, the commodity ex-warehouse number and the link identification are used as log query keywords, the equipment identification and the shooting time period corresponding to the warehouse video to be called are queried from the commodity ex-warehouse log, and a video calling task is generated according to the equipment identification and the shooting time period.
In one embodiment, the cluster server may determine the target workstation identifier according to the commodity export number and the link identifier, and determine the device identifier according to the target workstation identifier. The target workbench mark is the mark of the workbench of the commodity in the warehouse-out link corresponding to the to-be-called warehouse video.
In this embodiment, the cluster server may automatically determine, for the retrieval request sent by the user, the device identifier of the warehouse monitoring device of the warehouse video to be retrieved and the shooting period corresponding to the warehouse video to be retrieved, and generate the video retrieval task according to the device identifier and the shooting period, without requiring the user to manually determine the device identifier and the shooting period, so as to further increase the response speed of the video retrieval task and shorten the average response time of the video retrieval task.
In an embodiment, as shown in fig. 4, the step of the cluster server obtaining the task priority of the video retrieval task includes:
s402, the cluster server determines a target user identity, wherein the target user identity is a user identity corresponding to the user sending the calling requirement;
s404, the cluster server determines a target task priority corresponding to the target user identity from a preset mapping relation, and takes the target task priority as the task priority of the video calling task, wherein the preset mapping relation is the mapping relation between the user identity and the task priority.
Specifically, the cluster server may store mapping relationships between different user identifiers and task priorities corresponding to the user identifiers in advance. When the retrieval requirement sent by the user is acquired, the cluster server may determine, according to the user identity corresponding to the user sending the retrieval requirement, the task priority corresponding to the user identity from the pre-stored mapping relationship, and use the task priority as the task priority of the video retrieval task. For example, when the target user identity is a customer service person identity, the video calling task may correspond to the highest priority; when the target user identity is a quality control personnel identity, the video calling task can correspond to the next highest priority; when the target user identity is other related personnel identities, the video calling task may correspond to the lowest priority. Therefore, the task priority can be determined according to the user identity corresponding to the user sending the calling requirement, so that the user with high response requirement can be responded preferentially, and the user experience can be further improved.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element. As used herein, the terms "a," "an," "the," and "the" can also include the plural forms as well, unless the context clearly indicates otherwise. Plural means at least two, such as 2, 3, 5 or 8, etc. "and/or" includes any and all combinations of the associated listed items.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, the embodiments may be combined as needed, and the same and similar parts may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The warehouse video calling method is applied to a cloud platform, the cloud platform comprises a cluster server and a plurality of execution servers, and the method comprises the following steps:
the cluster server acquires a video calling task and a task priority of the video calling task, and adds the video calling task to a task queue according to the task priority;
for each execution server, when the execution server is in an idle state, the execution server performs task preemption operation on the cluster server so as to preempt the execution permission of the video retrieval task corresponding to the highest priority in the task queue;
the cluster server allocates the video calling task corresponding to the highest priority to an execution server with a task preemption success;
and for each execution server, under the condition that the execution server is distributed with the video calling task, executing the distributed video calling task to download the warehouse video to be called from the equipment platform of the warehouse monitoring equipment.
2. The warehouse video retrieval method according to claim 1, wherein the step of executing, for each execution server, the video retrieval task allocated to the execution server to download the warehouse video to be retrieved from the device platform of the warehouse monitoring device comprises:
for each execution server, under the condition that the execution server is allocated with a video calling task, acquiring an effective network connection from an SDK connection pool configured by the execution server, and sending a video downloading request to an equipment platform of the warehouse monitoring equipment through the effective network connection so as to enable the equipment platform to return the warehouse video to be called to the execution server;
the SDK connection pool is used for storing information of network connection between the cloud platform and the equipment platform.
3. The warehouse video retrieval method of claim 1, wherein the cloud platform further comprises a cloud storage object server, the method further comprising:
for each execution server, after downloading the warehouse video to be called, the execution server transcodes the warehouse video to be called to obtain the warehouse video in the H264 format, and uploads the warehouse video in the H264 format to the cloud storage object server.
4. The warehouse video retrieval method according to claim 3, further comprising, after the step of the executive server uploading the warehouse video in H264 format to the cloud storage object server:
the cluster server allocates a temporary uniform resource locator to the playing device, so that the playing device obtains the warehouse video to be played from the cloud storage object server based on the temporary uniform resource locator.
5. The warehouse video retrieval method of claim 1, wherein the step of the cluster server obtaining the video retrieval task comprises:
the cluster server receives a calling demand sent by a user, wherein the calling demand comprises a commodity ex-warehouse number and a link identification of an ex-warehouse link corresponding to a to-be-called warehouse video;
the cluster server acquires a commodity ex-warehouse log, and inquires the commodity ex-warehouse log according to the commodity ex-warehouse serial number and the link identification so as to determine an equipment identification of warehouse monitoring equipment for shooting the warehouse video to be called and a shooting time period corresponding to the warehouse video to be called;
and the cluster server generates the video calling task according to the equipment identification and the shooting time interval.
6. The warehouse video retrieval method according to claim 5, wherein the step of the cluster server obtaining the task priority of the video retrieval task includes:
the cluster server determines a target user identity, wherein the target user identity is a user identity corresponding to the user sending the calling requirement;
the cluster server determines a target task priority corresponding to the target user identity from a preset mapping relation, the target task priority is used as a task priority of the video calling task, and the preset mapping relation is the mapping relation between the user identity and the task priority.
7. The warehouse video retrieval method of any of claims 1 to 6, wherein the method further comprises:
and the cluster server writes the video calling task into a task database.
8. The cloud platform is characterized by comprising a cluster server and a plurality of execution servers, wherein:
the cluster server is used for acquiring a video calling task and the task priority of the video calling task, and adding the video calling task to a task queue according to the task priority;
aiming at each execution server, when the execution server is in an idle state, the execution server is used for performing task preemption operation on the cluster server so as to preempt the execution permission of the video calling task corresponding to the highest priority in the task queue;
the cluster server is used for distributing the video calling task corresponding to the highest priority to the execution server which is successful in task preemption;
and for each execution server, the execution server is used for executing the distributed video calling task under the condition that the video calling task is distributed, so as to download the warehouse video to be called from the equipment platform of the warehouse monitoring equipment.
9. The cloud platform of claim 8, wherein the cloud platform further comprises a cloud storage object server;
and for each execution server, the execution server is further configured to, after downloading the warehouse video to be called, transcode the warehouse video to be called to obtain a warehouse video in an H264 format, and upload the warehouse video in the H264 format to the cloud storage object server.
10. The cloud platform of claim 8, wherein the cluster server is further configured to write the video retrieval task to a task database.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140344415A1 (en) * | 2011-09-16 | 2014-11-20 | Tencent Technology (Shenzhen) Company Limited | Mobile multimedia real-time transcoding system, apparatus, storage medium and method |
| US20150244757A1 (en) * | 2012-11-27 | 2015-08-27 | Tencent Technology (Shenzhen) Company Limited | Transcoding Method and System, and Distributed File Apparatus |
| CN104954158A (en) * | 2014-03-27 | 2015-09-30 | 深圳市金蝶友商电子商务服务有限公司 | Connection management method and connection pool control equipment |
| CN109309646A (en) * | 2017-07-27 | 2019-02-05 | 贵州白山云科技股份有限公司 | A kind of multi-media transcoding method and system |
| CN109788315A (en) * | 2019-01-31 | 2019-05-21 | 湖南快乐阳光互动娱乐传媒有限公司 | video transcoding method, device and system |
| WO2020000944A1 (en) * | 2018-06-25 | 2020-01-02 | 星环信息科技（上海）有限公司 | Preemptive scheduling based resource sharing use method, system and |
| CN112162865A (en) * | 2020-11-03 | 2021-01-01 | 中国工商银行股份有限公司 | Server scheduling method and device and server |
| CN113596085A (en) * | 2021-06-24 | 2021-11-02 | 阿里云计算有限公司 | Data processing method, system and device |
| KR20220075250A (en) * | 2020-11-29 | 2022-06-08 | 박철우 | Logistics Agency Management System For Logistics Agency |
-
2022
- 2022-07-25 CN CN202210879694.5A patent/CN115277579B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140344415A1 (en) * | 2011-09-16 | 2014-11-20 | Tencent Technology (Shenzhen) Company Limited | Mobile multimedia real-time transcoding system, apparatus, storage medium and method |
| US20150244757A1 (en) * | 2012-11-27 | 2015-08-27 | Tencent Technology (Shenzhen) Company Limited | Transcoding Method and System, and Distributed File Apparatus |
| CN104954158A (en) * | 2014-03-27 | 2015-09-30 | 深圳市金蝶友商电子商务服务有限公司 | Connection management method and connection pool control equipment |
| CN109309646A (en) * | 2017-07-27 | 2019-02-05 | 贵州白山云科技股份有限公司 | A kind of multi-media transcoding method and system |
| WO2020000944A1 (en) * | 2018-06-25 | 2020-01-02 | 星环信息科技（上海）有限公司 | Preemptive scheduling based resource sharing use method, system and |
| CN109788315A (en) * | 2019-01-31 | 2019-05-21 | 湖南快乐阳光互动娱乐传媒有限公司 | video transcoding method, device and system |
| CN112162865A (en) * | 2020-11-03 | 2021-01-01 | 中国工商银行股份有限公司 | Server scheduling method and device and server |
| KR20220075250A (en) * | 2020-11-29 | 2022-06-08 | 박철우 | Logistics Agency Management System For Logistics Agency |
| CN113596085A (en) * | 2021-06-24 | 2021-11-02 | 阿里云计算有限公司 | Data processing method, system and device |
Non-Patent Citations (1)
| Title |
|---|
| 程雷: "基于HTTP协议的PACS系统设计与实现", 中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑, pages 42 - 44 * |
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