CN120086017B - Queue data processing methods - Google Patents
Queue data processing methodsInfo
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- CN120086017B CN120086017B CN202510136803.8A CN202510136803A CN120086017B CN 120086017 B CN120086017 B CN 120086017B CN 202510136803 A CN202510136803 A CN 202510136803A CN 120086017 B CN120086017 B CN 120086017B
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/50—Indexing scheme relating to G06F9/50
- G06F2209/5011—Pool
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/50—Indexing scheme relating to G06F9/50
- G06F2209/5018—Thread allocation
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/54—Indexing scheme relating to G06F9/54
- G06F2209/548—Queue
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Abstract
The application relates to a queue data processing method, a device, a computer device, a readable storage medium and a program product, wherein the method comprises the steps of asynchronously writing received data to be processed into a preset queue table as queue data; and respectively distributing the queue data to a corresponding thread pool according to the type of the queue data, and consuming the queue data in a consumption mode of the corresponding thread pool. The method can improve the efficiency of data processing while ensuring the data consumption sequence, thereby optimizing the overall system performance and improving the stability of service functions.
Description
Technical Field
The present application relates to the field of data processing technology, and in particular, to a queue data processing method, apparatus, computer device, computer readable storage medium, and computer program product.
Background
In modern computing systems, with rapid growth of data volume and increasing complexity of business scenarios, it is important to employ efficient queue data processing methods.
A common method of queue data consumption today is to process messages asynchronously through a thread pool. The use of multithreading can increase the throughput of data processing, but in practical applications this approach may result in the unordered consumption of queue data. Particularly in some business functions where processing order is critical, unordered consumption of queue data may result in data anomalies or business logic failures. For example, some businesses may rely on sequential event sequences for proper state updates, and the disruption in the order of consumption may not only increase the cost of subsequent data verification, but may also lead to system instability and degradation of user experience.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a queue data processing method, apparatus, computer device, computer readable storage medium, and computer program product.
In a first aspect, the present application provides a method for processing queue data. The method comprises the following steps:
asynchronously writing the received data to be processed into a preset queue table as queue data;
identifying each queue data in the queue list, and determining the type of each queue data;
And respectively distributing the queue data to corresponding thread pools according to the types of the queue data, and consuming the queue data in a consumption mode of the corresponding thread pools.
In one embodiment, the identifying each queue data in the queue table, and determining the type of each queue data includes:
Under the condition that the queue data do not have type identifiers, acquiring the document identifiers in the queue list, wherein the document identifiers are identifiers of documents corresponding to the queues to which each queue data belong;
And determining the type of each queue data according to the number of the queue data under each document identification.
In one embodiment, the determining the type of the queue data according to the number of the queue data under each document identification includes:
For each document identifier, determining the quantity of queue data under the document identifier in real time;
and under the condition that the number of the queue data under the document identification is detected to be larger than the preset number, marking all the queue data under the document identification as sequential queue data.
In one embodiment, the method further comprises:
After traversing the queue table, if the number of the queue data under the document identification is smaller than the preset number, marking the queue data under the document identification as unordered queue data.
In one embodiment, the identifying each queue data in the queue table, determining the type of each queue data, further includes:
And under the condition that each queue data has the type identifier, determining the type of each queue data according to the type identifier of each queue data.
In one embodiment, the allocating the respective queue data to the corresponding thread pool according to the type of the respective queue data includes:
For each queue data, if the type of the queue data is sequential queue data, the queue data is distributed to an ordered thread pool, wherein the ordered thread pool comprises a single thread;
And if the type of the queue data is unordered queue data, distributing the queue data to an unordered thread pool, wherein the unordered thread pool comprises a plurality of threads.
In a second aspect, the application further provides a queue data processing device. The device comprises:
the data writing module is used for asynchronously writing the received data to be processed into a preset queue table as queue data;
the type identification module is used for identifying each queue data in the queue list and determining the type of each queue data;
and the data distribution module is used for distributing the queue data to the corresponding thread pools according to the types of the queue data, and consuming the queue data in a consumption mode of the corresponding thread pools.
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 which when executing the computer program performs the steps of:
asynchronously writing the received data to be processed into a preset queue table as queue data;
identifying each queue data in the queue list, and determining the type of each queue data;
And respectively distributing the queue data to corresponding thread pools according to the types of the queue data, and consuming the queue data in a consumption mode of the corresponding thread pools.
In a fourth aspect, the present application also 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:
asynchronously writing the received data to be processed into a preset queue table as queue data;
identifying each queue data in the queue list, and determining the type of each queue data;
And respectively distributing the queue data to corresponding thread pools according to the types of the queue data, and consuming the queue data in a consumption mode of the corresponding thread pools.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:
asynchronously writing the received data to be processed into a preset queue table as queue data;
identifying each queue data in the queue list, and determining the type of each queue data;
And respectively distributing the queue data to corresponding thread pools according to the types of the queue data, and consuming the queue data in a consumption mode of the corresponding thread pools.
The queue data processing method, the device, the computer equipment, the storage medium and the computer program product asynchronously write the received data to be processed into a preset queue table by taking the received data to be processed as the queue data, identify each queue data in the queue table, determine the type of each queue data, respectively allocate each queue data to a corresponding thread pool according to the type of each queue data, and consume each queue data in a consumption mode of the corresponding thread pool. The method writes the queue data into the queue list, and reasonably distributes the queue data to the corresponding thread pool for consumption by identifying the type of the queue data, so that the method can flexibly adapt to the processing requirements of different data types, ensures that the data needing to be consumed sequentially is effectively processed, and simultaneously does not influence the concurrent consumption efficiency of other types of data, namely the efficiency of data processing can be improved while the data consumption sequency is ensured, thereby optimizing the performance of the whole system and improving the stability of service functions.
Drawings
FIG. 1 is a flow diagram of a method of processing queue data in one embodiment;
FIG. 2 is a flow chart of a method for processing queue data in another embodiment;
FIG. 3 is a flow chart of a method of processing queue data in yet another embodiment;
FIG. 4 is a block diagram of a queue data processing apparatus in one embodiment;
fig. 5 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, as shown in fig. 1, a queue data processing method is provided, where the method is applied to a terminal to illustrate the method, it is understood that the method may also be applied to a server, and may also be applied to a system including the terminal and the server, and implemented through interaction between the terminal and the server. The terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things equipment and portable wearable equipment, and the internet of things equipment can be smart speakers, smart televisions, smart air conditioners, smart vehicle-mounted equipment and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers. In this embodiment, the method includes the steps of:
Step S110, the received data to be processed is used as queue data, and asynchronously written into a preset queue table.
The queue is simply called a queue, is a linear table with limited operation, and only allows insertion at one end of the table and deletion at the other end of the table. Inserting elements into a queue is referred to as enqueuing or enqueuing, and deleting elements is referred to as dequeuing or dequeuing.
The queue table can adopt a database table, an in-memory data structure storage based on key value pairs or a document type database.
In a specific implementation, a database table may be established as a queue table, and the received data to be processed is written into the queue table in an asynchronous manner. The queue data in the queue table may correspond to a queue identifier, a document identifier corresponding to the queue, a method of operating the queue, a time of creating the queue, a type of the queue data, and the like, as shown in table 1 below, which is a schematic illustration of a structure of the queue table.
Table 1 queue table structure
Step S120, each queue data in the queue list is identified, and the type of each queue data is determined.
In particular implementations, when the queue data is written to the queue table, the field value of the fd_order (i.e., type identification) field in table 1 may be set to indicate the type of the queue data. When the queue data is distributed, if the queue data has a type identifier, the type of the queue data can be determined according to the type identifier. If the queue data has no type identification, the type of each queue data can be identified through a preset type identification algorithm.
Step S130, according to the types of the queue data, the queue data are respectively distributed to the corresponding thread pools, and the queue data are consumed in a consumption mode of the corresponding thread pools.
Wherein the thread pool is a management framework for creating a certain number of threads in advance. When the task arrives, the thread pool acquires threads from the pool to execute the task, and the threads are not destroyed after the task is ended and return to the pool for next use. The core idea of this mechanism is thread multiplexing, avoiding frequent creation and destruction of threads. The thread is the minimum unit of operation scheduling of the operating system. It is included in the process and is the actual unit of operation in the process. Multiple threads may be concurrent in a process, each thread executing a different task in parallel.
In a specific implementation, corresponding thread pools may be set according to the type of queue data, where each thread pool corresponds to a specific data type and consumption scenario. After the data type is identified, each queue data is assigned to a corresponding thread pool. For example, for queue data that needs to be consumed sequentially, it is allocated to an ordered thread pool. For data that can be processed in parallel, it is assigned to an unordered thread pool. And asynchronously consuming the queue data in a corresponding consumption mode through the respective thread pools. A message confirmation mechanism may be used during the consumption process to ensure that the data is successfully processed. And the consumption state is tracked in real time, success and failure of data consumption are recorded, and a feedback mechanism is provided, so that the system can adjust the processing strategy in time.
According to the queue data processing method, received data to be processed are used as queue data and asynchronously written into a preset queue table, each queue data in the queue table is identified, the type of each queue data is determined, each queue data is distributed to a corresponding thread pool according to the type of each queue data, and each queue data is consumed in a consumption mode of the corresponding thread pool. The method writes the queue data into the queue list, and reasonably distributes the queue data to the corresponding thread pool for consumption by identifying the type of the queue data, so that the method can flexibly adapt to the processing requirements of different data types, ensures that the data needing to be consumed sequentially is effectively processed, and simultaneously does not influence the concurrent consumption efficiency of other types of data, namely the efficiency of data processing can be improved while the data consumption sequency is ensured, thereby optimizing the performance of the whole system and improving the stability of service functions.
In an exemplary embodiment, the identifying each queue data in the queue table in step S120, and determining the type of each queue data includes:
In the first case, under the condition that each queue data has a type identifier, determining the type of each queue data according to the type identifier of each queue data.
Specifically, when the queue data is written into the queue table, the field value of the fd_order (i.e. type identifier) field in table 1 is set, and then when the allocation of the queue data is performed, the type of the queue data can be determined directly according to the corresponding relationship between the type identifier and the type. For example, the type identifier is set to 0-sequential queue data, 1-unordered queue data, and when the type identifier of a certain queue data is 0, it can be determined that it is sequential queue data.
And secondly, under the condition that each queue data has no type identifier, acquiring each document identifier in a queue list, wherein the document identifier is the identifier of a document corresponding to the queue to which each queue data belongs, and determining the type of each queue data according to the number of the queue data under each document identifier.
In a specific implementation, if the data in the queue table has no type identifier, the type of each queue data can be identified according to a preset type identification algorithm. In particular, each document identification in the acquisition queue table can be identified, and the document identification is used for distinguishing different data sources or services, so that the queue data under the same document identification can be set to be consumed sequentially. The number of queue data under each document identification can be determined, and based on the number, the type of the corresponding queue data can be determined.
In this embodiment, the type of each queue data is automatically determined by the provided type identification algorithm, so that the queue data is allocated, the type identification can be realized under the condition that each queue data has no type identifier, the unordered quick consumption or sequential consumption can be realized by the characteristics of the queue data, and the flexibility of queue consumption is provided.
In an exemplary embodiment, the step of determining the type of each queue data according to the number of the queue data under each document identification includes determining the number of the queue data under the document identification in real time for each document identification, and marking all the queue data under the document identification as sequential queue data when the number of the queue data under the document identification is detected to be greater than a preset number.
In a specific implementation, the number of queue data under each document identifier can be updated in real time, that is, each time a new queue data is identified, the number of queue data under the corresponding document identifier can be updated in real time. When the number of the queue data under a certain document identifier is detected to be larger than the preset number, the queue data under the document identifier is marked as sequential queue data, and when the subsequent other data which are not identified in the queue list are identified to belong to the document identifier, the queue data can be directly marked as sequential queue data without performing type identification again.
In practical application, the preset number may be 2, that is, when at least two queue data exist under a certain document identifier, it is indicated that there are multiple queues in the data under the document, and then the queue data under the document identifier may be marked as sequential queue data that needs to be consumed sequentially. The numerical value 2 is used as a basis for dividing the sequential queue and the unordered queue, so that the recognition efficiency can be improved on the basis of ensuring the accuracy of recognition results.
It should be noted that, in some other application scenarios, the preset number may also be determined according to the actual requirement, which is not particularly limited by the present application.
In the embodiment, by detecting and marking the data in real time, unnecessary repeated identification is avoided, the response speed of the system is improved, the logic of subsequent data processing can be simplified, the subsequent data can directly refer to the existing mark, and the complexity of the system is reduced.
In an exemplary embodiment, the method further comprises marking the queue data under the document identification as unordered queue data after traversing the queue table if the number of queue data under the document identification is less than a preset number.
In a specific implementation, when identifying each queue data in the queue table, if after traversing all queue data in the queue table, the number of queue data under a certain document identifier is smaller than a preset number, for example, smaller than 2, which indicates that the queue data under the document identifier does not need to be consumed sequentially, the queue data can be marked as unordered queue data.
In the embodiment, by adding the marking mechanism for marking that the number of the queue data under the document identification is smaller than the preset number, not only is the strict control on the sequential data realized, but also the proper classification on the unordered data is completed, and the accuracy and the efficiency of the data processing are ensured by the overall design.
In an exemplary embodiment, the step S130 allocates each queue data to a corresponding thread pool according to the type of each queue data, and specifically includes, for each queue data, allocating the queue data to an ordered thread pool if the type of the queue data is sequential queue data, where the ordered thread pool includes a single thread, allocating the queue data to an unordered thread pool if the type of the queue data is unordered queue data, and where the unordered thread pool includes a plurality of threads.
In the specific implementation, the queue data is distributed to a proper thread pool for processing according to the data type of each queue data, wherein if the queue data is sequential queue data, the queue data is distributed to a specially designed sequential thread pool, and a thread is created in the sequential thread pool to ensure the processing sequence. The ordered thread pool continuously circulates and consumes the queue data marked as the sequential consumption, and if no queue data is found to be consumable, the thread sleeps for a period of time, and idle running is reduced.
If the queue data is unordered queue data, the unordered queue data is distributed to an unordered thread pool, and a plurality of threads are created in the unordered thread pool so as to realize efficient concurrent processing. Since multithreaded execution is itself out of order, each thread only needs to consume out of order queue data all the time if there is queue data.
In the embodiment, in the data consumption process, the sequential queue data adopts a single-thread consumption mode, so that the data is ensured to be processed one by one according to a fixed sequence, and other queue data in the multithreading pool enjoy the high-efficiency operation brought by parallel consumption. Therefore, by means of the characteristic of the queue data, unordered quick consumption or sequential consumption can be carried out according to the requirements, and flexibility of queue consumption is provided.
Referring to fig. 2, a flow chart of a queue data processing method according to another embodiment is provided, and in this embodiment, the method includes the following steps:
Step S201, asynchronously writing received data to be processed into a preset queue table by taking the received data to be processed as queue data;
Step S202, identifying each queue data in the queue list, and determining the type of each queue data;
Step S203, under the condition that each queue data has a type identifier, determining the type of each queue data according to the type identifier of each queue data;
step S204, under the condition that the data of each queue has no type identifier, acquiring the identifier of each document in the queue list;
step S205, determining the number of queue data under the document identifications in real time for each document identification;
step S206, marking all the queue data under the document identification as sequential queue data under the condition that the number of the queue data under the document identification is detected to be larger than the preset number;
step S207, after traversing the queue table, if the number of the queue data under the document identification is smaller than the preset number, marking the queue data under the document identification as unordered queue data;
step S208, for each queue data, if the type of the queue data is sequential queue data, the queue data is distributed to an ordered thread pool, wherein the ordered thread pool comprises a single thread;
in step S209, if the queue data is of an unordered queue data type, the queue data is allocated to an unordered thread pool, and the unordered thread pool includes a plurality of threads.
The method writes the queue data into the queue list, and reasonably distributes the queue data to the corresponding thread pool for consumption by identifying the type of the queue data, so that the method can flexibly adapt to the processing requirements of different data types, ensures that the data needing to be consumed sequentially is effectively processed, and simultaneously does not influence the concurrent consumption efficiency of other types of data, namely the efficiency of data processing can be improved while the data consumption sequency is ensured, thereby optimizing the performance of the whole system and improving the stability of service functions. Through the provided type identification algorithm, the types of the queue data are automatically judged, so that the queue data are distributed, the type identification under the condition that the queue data have no type identification can be realized, the unordered quick consumption or sequential consumption can be realized through the characteristics of the queue data according to the requirements, and the flexibility of the queue consumption is provided.
In one embodiment, to facilitate understanding of embodiments of the application by those skilled in the art, a specific example will be described below in conjunction with the accompanying drawings. Referring to fig. 3, another flow diagram of a queue data processing method is shown, a database table is built as a queue table, service sending messages only need to asynchronously write data into the queue table, two sets of thread pools are started, one is an unordered thread pool, the other is an ordered thread pool, and the queue data are processed quickly or sequentially according to service requirements. The method specifically comprises the following steps:
(1) And (3) writing queue data, namely providing a addQueue interface for calling the writing data to a service side, wherein the queue can set a field fd_order of the table 1 as a sequence consuming queue or not, and can also not set a type recognition algorithm built in a hand-over program for calculation.
(2) Setting the queue data in the same document to be executed in sequence, and judging whether the data is the sequential queue data or not based on the database table and the corresponding sql to be executed.
2.1 Performing sql SELECT DISTINCT FD _doc_ id from queue where fd _order |=true, and acquiring the queue data of how many document ids are under the current queue table.
2.2 Through 2.1) the returned fd_doc_id set, and then performing paging sql according to each fd_doc_id, select fd_ id from queue where fd _doc_id= 'queue data processing' and fd_order |=true limit 2.
2.3 If the same document returns more than or equal to 2 pieces of queue data, the condition that a plurality of queues exist in the data under the document is indicated, the data under the document is marked as sequential queue data, and sql is performed, wherein update queue set fd _order=true window fd_doc_id= 'queue data processing'.
In the method, a calling party can provide identification for data whether to consume sequentially or not or calculate whether to consume sequentially through a built-in algorithm according to the needs of the calling party, then the data is inserted into a queue table, and the subsequent queue data consumption is automatically completed by a program.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a queue data processing device for realizing the above related queue data processing method. The implementation of the solution provided by the apparatus is similar to the implementation described in the above method, so the specific limitation of one or more embodiments of the queue data processing apparatus provided below may refer to the limitation of the queue data processing method hereinabove, and will not be repeated herein.
In one embodiment, as shown in FIG. 4, there is provided a queue data processing apparatus comprising a data writing module 410, a type identification module 420, and a data allocation module 430, wherein:
A data writing module 410, configured to asynchronously write the received data to be processed into a preset queue table as queue data;
a type identifying module 420, configured to identify each queue data in the queue table, and determine a type of each queue data;
the data distribution module 430 is configured to distribute each queue data to a corresponding thread pool according to the type of each queue data, and consume each queue data in a consumption manner of the corresponding thread pool.
In one embodiment, the type identifying module 420 is further configured to obtain, when each queue data has no type identifier, each document identifier in the queue table, where the document identifier is an identifier of a document corresponding to a queue to which each queue data belongs, and determine a type of each queue data according to the number of queue data under each document identifier.
In one embodiment, the type identifying module 420 is further configured to determine, for each document identifier, a number of queue data under the document identifier in real time, and mark all the queue data under the document identifier as sequential queue data when the number of queue data under the document identifier is detected to be greater than a preset number.
In one embodiment, the type identifying module 420 is further configured to mark the queue data under the document identifier as unordered queue data if the number of queue data under the document identifier is less than a preset number after traversing the queue table.
In one embodiment, the type identifying module 420 is further configured to determine, if each queue data has a type identifier, a type of each queue data according to the type identifier of each queue data.
In one embodiment, the data allocation module 430 is further configured to allocate, for each queue data, the queue data to an ordered thread pool if the type of the queue data is sequential queue data, the ordered thread pool including a single thread, allocate the queue data to an unordered thread pool if the type of the queue data is unordered queue data, and the unordered thread pool including a plurality of threads.
The various modules in the queue data processing apparatus described above may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device 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 and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program, when executed by a processor, implements a method of queue data processing. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may 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), magneto-resistive random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
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| CN116880990A (en) * | 2023-07-28 | 2023-10-13 | 重庆赛力斯新能源汽车设计院有限公司 | Task execution methods, devices, electronic equipment and computer-readable storage media |
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| US10133489B2 (en) * | 2014-09-16 | 2018-11-20 | Oracle International Corporation | System and method for supporting a low contention queue in a distributed data grid |
| US10244070B2 (en) * | 2016-01-26 | 2019-03-26 | Oracle International Corporation | In-memory message sequencing |
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| CN115563226A (en) * | 2022-09-14 | 2023-01-03 | 北京结慧科技有限公司 | Database-based data consumption method, control device and readable storage medium |
| CN116880990A (en) * | 2023-07-28 | 2023-10-13 | 重庆赛力斯新能源汽车设计院有限公司 | Task execution methods, devices, electronic equipment and computer-readable storage media |
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