Method and device for optimizing large concurrent scheduling, equipment and medium

Abstract

The invention relates to a method and device for optimizing large concurrency scheduling, equipment and a medium. The method for optimizing the large concurrency scheduling comprises the following steps: in response to a scheduling request, performing request warehousing processing through a first-level scheduler; creating a hash index corresponding to the scheduling request through the first-level scheduler; performing cluster scheduling processing through a secondary scheduler according to the Hash index to obtain a corresponding processing result; and returning a corresponding scheduling result under the condition that the processing result is scheduling success. According to the embodiment of the invention, large-concurrency scheduling requests can be completed through a hierarchical scheduling mode, and resource conflicts are reduced.

Description

Technical Field

[0001] This disclosure relates to the field of virtual machine technology, and in particular to a method, apparatus, device and medium for optimizing high-concurrency scheduling. Background Technology

[0002] When virtual machines are created concurrently, the bottleneck mainly lies in the virtual machine scheduling module, which can lead to a backlog in the scheduling queue and severely restrict the platform's throughput.

[0003] In related technologies, increasing the number of scheduling nodes increases scheduling concurrency. However, when the number of scheduling nodes increases, since each scheduling node retains its own resource view, it is very easy for the memory resource views of all nodes to become inconsistent, thus leading to frequent resource conflicts. Summary of the Invention

[0004] To address the aforementioned technical problems, this disclosure provides an optimized method, apparatus, device, and medium for high-concurrency scheduling.

[0005] Firstly, this disclosure provides an optimized method for high-concurrency scheduling, including:

[0006] In response to scheduling requests, the requests are processed for database entry through the primary scheduler;

[0007] The first-level scheduler creates a hash index corresponding to the scheduling request.

[0008] The cluster scheduling process is performed by the secondary scheduler based on the hash index to obtain the corresponding processing result;

[0009] If the processing result is a successful scheduling, the corresponding scheduling result is returned.

[0010] Secondly, this disclosure provides an optimized high-concurrency scheduling device, comprising:

[0011] The first processing module is used to respond to scheduling requests and process the requests for database entry through the first-level scheduler;

[0012] An index creation module is used to create a hash index corresponding to the scheduling request through the first-level scheduler;

[0013] The second processing module is used to perform cluster scheduling processing based on the hash index through the secondary scheduler to obtain the corresponding processing result.

[0014] The result return module is used to return the corresponding scheduling result if the processing result is that the scheduling is successful.

[0015] Thirdly, this disclosure provides an optimized high-concurrency scheduling device, including:

[0016] processor;

[0017] Memory, used to store executable instructions;

[0018] The processor is used to read executable instructions from memory and execute the executable instructions to implement the optimized high-concurrency scheduling method of the first aspect.

[0019] Fourthly, this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the optimized high-concurrency scheduling method of the first aspect.

[0020] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0021] The optimized high-concurrency scheduling method, apparatus, device, and medium of this disclosure are capable of responding to scheduling requests by performing request storage processing through a primary scheduler; creating a hash index corresponding to the scheduling request through the primary scheduler; performing cluster scheduling processing based on the hash index through a secondary scheduler to obtain the corresponding processing result; and returning the corresponding scheduling result if the processing result is successful. Thus, high-concurrency scheduling requests are completed through hierarchical scheduling, reducing resource conflicts. Attached Figure Description

[0022] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0023] Figure 1 A flowchart illustrating an optimized high-concurrency scheduling method provided in this embodiment of the disclosure;

[0024] Figure 2 A flowchart illustrating another optimized high-concurrency scheduling method provided in this embodiment of the disclosure;

[0025] Figure 3 A flowchart illustrating yet another optimized high-concurrency scheduling method provided in this embodiment of the disclosure;

[0026] Figure 4 A flowchart illustrating another optimized high-concurrency scheduling method provided in this embodiment of the disclosure;

[0027] Figure 5 This is a schematic diagram of the structure of an optimized high-concurrency scheduling device provided in an embodiment of the present disclosure;

[0028] Figure 6This is a schematic diagram of the structure of an optimized high-concurrency scheduling device provided in an embodiment of this disclosure. Detailed Implementation

[0029] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0030] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0031] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0032] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0033] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0034] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0035] To address the aforementioned problems, this disclosure provides an optimized method, apparatus, device, and medium for high-concurrency scheduling. The following is a detailed description... Figures 1-4 The optimized high-concurrency scheduling method provided in the embodiments of this disclosure will be described in detail.

[0036] Figure 1 A flowchart illustrating an optimized high-concurrency scheduling method provided in an embodiment of this disclosure is shown.

[0037] In this embodiment of the disclosure, the optimized high-concurrency scheduling method can be executed by an electronic device. The electronic device may include, but is not limited to, devices such as computer equipment, cloud servers, or cloud server clusters.

[0038] like Figure 1 As shown, this optimized high-concurrency scheduling method may include the following steps.

[0039] S110. In response to the scheduling request, the request is processed for database entry through the first-level scheduler.

[0040] In this embodiment of the disclosure, the electronic device can respond to a scheduling request and perform request entry processing through a primary scheduler.

[0041] Optionally, a scheduling request is a request used to schedule virtual machine resources.

[0042] Optionally, the primary scheduler can be the process that requests data entry in response to scheduling requests.

[0043] Alternatively, the request to be entered into the database can be processed by entering the scheduling request into the database.

[0044] Specifically, when you want to create a virtual machine, you need to schedule virtual machine resources. Electronic devices can respond to scheduling requests and process the scheduling request by a primary scheduler.

[0045] S120. Create a hash index corresponding to the scheduling request through the first-level scheduler.

[0046] In this embodiment of the disclosure, the electronic device can create a hash index corresponding to the scheduling request through the primary scheduler.

[0047] Alternatively, a hash index can be an index structure based on a hash table, which locates data rows by calculating the hash code of the index column.

[0048] Specifically, after the electronic device performs request entry processing on the scheduling request, it can create a hash index corresponding to the scheduling request through the primary scheduler.

[0049] S130. The secondary scheduler performs cluster scheduling based on the hash index to obtain the corresponding processing result.

[0050] In this embodiment of the disclosure, the electronic device can perform cluster scheduling processing based on the hash index through a secondary scheduler to obtain the corresponding processing result.

[0051] Optionally, the secondary scheduler can be a process that performs virtual machine cluster resource scheduling in response to scheduling requests.

[0052] Alternatively, cluster scheduling can be performed on a cluster-by-cluster basis to schedule virtual machine resources.

[0053] Optionally, the processing result can be a result used to characterize whether the scheduling was successful.

[0054] Specifically, after obtaining the hash index, the electronic device can perform cluster scheduling processing based on the hash index through the secondary scheduler, that is, perform virtual machine resource scheduling on a cluster basis, thereby obtaining the corresponding processing result.

[0055] S140. If the processing result is that the scheduling is successful, return the corresponding scheduling result.

[0056] In this embodiment of the disclosure, the electronic device can return the corresponding scheduling result if the processing result is a successful scheduling.

[0057] Optionally, the scheduling result can be a result used to characterize resource scheduling.

[0058] Specifically, after the electronic devices perform cluster scheduling processing through the secondary scheduler, if the processing result is that the scheduling is successful, the corresponding scheduling result can be returned.

[0059] Therefore, in this embodiment of the disclosure, in response to a scheduling request, the primary scheduler performs request storage processing; the primary scheduler creates a hash index corresponding to the scheduling request; the secondary scheduler performs cluster scheduling processing based on the hash index to obtain the corresponding processing result; and if the processing result is a successful scheduling, the corresponding scheduling result is returned. Thus, high-concurrency scheduling requests are completed through hierarchical scheduling, reducing resource conflicts.

[0060] Figure 2 A flowchart illustrating another optimized high-concurrency scheduling method provided in an embodiment of this disclosure is shown.

[0061] like Figure 2 As shown, the electronic device can respond to the scheduling request (api-server), process the request into the database through the first-level scheduler, and create a hash index corresponding to the scheduling request through the first-level scheduler. Then, the second-level scheduler (worker) performs cluster scheduling processing based on the hash index to obtain the corresponding processing result. If the processing result is that the scheduling is successful, the corresponding scheduling result is returned; if the processing result is that the scheduling is unsuccessful, rescheduling is performed.

[0062] Optionally, S120 may specifically include: according to preset sharding rules, performing sharding processing on the scheduling request through the first-level scheduler to obtain multiple sharded requests; and performing request storage processing on the multiple sharded requests through the first-level scheduler.

[0063] In this embodiment of the disclosure, the electronic device can perform fragmentation processing on the scheduling request through the first-level scheduler according to the preset fragmentation rules to obtain multiple fragmentation requests.

[0064] Optionally, the preset sharding rules can be sharding rules defined according to different logical management units. The preset sharding rules include at least one of the following: average division, priority sales, flat sales, and best matching.

[0065] Alternatively, fragmentation can be used to split scheduling requests.

[0066] Specifically, after receiving a scheduling request, which may correspond to multiple logical management units, the electronic device can shard the scheduling request according to preset sharding rules through the primary scheduler to obtain multiple sharded requests. For example, when a scheduling request corresponds to multiple logical management units, the scheduling request is split according to different logical management units to obtain corresponding logical management unit clusters. Furthermore, if the cluster size is too large (tens of thousands of computing nodes), it may cause certain backtracking, graph-based, or recursive algorithms to take too long or consume too many resources. Therefore, the logical management unit clusters are further logically split, such as dividing a logical management unit cluster into 50 computing nodes to obtain multiple sharded requests. The preset sharding rules include: average partitioning: the number of virtual machines in the scheduling request is evenly distributed among the logical management unit clusters under the same cluster; priority selling: configure priority selling logical unit clusters, and when the resources of the priority logical unit are insufficient, the request is scheduled to other units; even selling: according to the idle resource weight of each logical unit cluster, the more idle resources, the higher the priority, so as to balance the selling of resources among the logical unit clusters; optimal matching: virtual machines create a specified logical unit cluster.

[0067] Furthermore, the electronic device can perform the request entry processing on multiple fragmented requests through a primary scheduler.

[0068] Optionally, S120 may specifically include: creating corresponding hash indexes for multiple shard requests through the first-level scheduler.

[0069] In this embodiment of the disclosure, the electronic device can create corresponding hash indexes for multiple shard requests through the primary scheduler.

[0070] Optionally, a hash index may include at least one of time indexes, cluster indexes, cell indexes, and other indexes.

[0071] Specifically, electronic devices can create corresponding hash indexes for multiple shard requests through a primary scheduler. For example, hash indexes can include: a time index: scheduling batch processing requests use timestamps as the scheduling basis; a tick-tock will retrieve the current time window and previous (mainly rescheduling) requests for scheduling processing; a cluster index: based on the scheduling request, a corresponding index is established to ensure cluster partitioning; a unit index: a subset of the cluster index; when the cluster belongs to the same scheduling management unit, this index is equivalent to the cluster index; if the cluster size is too large (tens of thousands of computing nodes), it may cause certain backtracking, graph-based, or recursive algorithms to take too long or consume too many resources, so the cluster will be further logically partitioned; other indexes: mainly for meeting special scheduling needs, such as special large packages, special NUMA layouts, special hardware (such as GPUs, FPGAs, 100G network cards, etc.), etc., to quickly implement special hardware to meet the requirements.

[0072] Optionally, S130 may specifically include: based on preset cluster scheduling rules, performing cluster scheduling processing through a secondary scheduler according to the hash index to obtain the corresponding processing result.

[0073] In this embodiment of the disclosure, the electronic device can perform cluster scheduling processing based on the hash index through a secondary scheduler according to the preset cluster scheduling rules, and obtain the corresponding processing result.

[0074] Optionally, the preset cluster scheduling rules include at least one of the following: multi-cluster priority scheduling rules, cluster-oriented scheduling rules, and cluster redirection scheduling rules.

[0075] Specifically, electronic devices can perform cluster scheduling processing based on the hash index through a secondary scheduler according to preset cluster scheduling rules, and obtain the corresponding processing results. For example, the preset cluster scheduling rules include: Multi-cluster priority scheduling rules: Add a default `priority_clusters` configuration item to specify the list of priority clusters to be scheduled. Scheduling is performed in order. For example, if the rule sets the priority cluster to X6-EBS, and the underlying cluster list is X6-EBS, S6-EBS, {"X6-EBS":["X6-EBS","S6-EBS"]}, then the scheduler will schedule both X6-EBS and S6-EBS clusters together, prioritizing X6-EBS. When X6-EBS resources are insufficient, scheduling will move to the S6-EBS cluster. Cluster-directed scheduling rules: Configure a direction policy example: {"cluster":"X6"}, then the scheduler will allocate virtual machines to the underlying X6 cluster. Cluster redirection scheduling rules: Configure a redirection policy example: {"cluster":"X6"}->{"redirect cluster":"S6"}, then the scheduler will redirect virtual machines requested by X6 to the underlying S6 cluster.

[0076] Figure 3 A flowchart illustrating another optimized high-concurrency scheduling method provided in this disclosure embodiment is shown.

[0077] like Figure 3 As shown, after receiving a scheduling request (api-server), the electronic device can use a primary scheduler (master) to perform sharding processing on the scheduling request according to preset sharding rules, resulting in multiple sharded requests. The primary scheduler then processes these multiple sharded requests by storing them in the database and creates a hash index corresponding to each scheduling request. Next, a secondary scheduler (worker) performs cluster scheduling processing based on the hash index to obtain the corresponding processing result. If the processing result is a successful scheduling, the corresponding scheduling result is returned; if the processing result is a failed scheduling, rescheduling is performed.

[0078] Figure 4 A flowchart illustrating another optimized high-concurrency scheduling method provided in an embodiment of this disclosure is shown.

[0079] like Figure 4As shown, electronic devices can process requests for database entry through a primary scheduler. Then, a corresponding hash index is constructed using hash buckets, including at least one of time index, cluster index, cell index, and other indexes. Based on preset sharding rules, the primary scheduler shards the scheduling request, resulting in multiple sharded requests. The preset sharding rules include at least one of average partitioning, priority selling, flat selling, and best matching. Based on preset cluster scheduling rules, a secondary scheduler performs cluster scheduling processing according to the hash index, obtaining the corresponding processing result. The preset cluster scheduling rules include at least one of multi-cluster priority scheduling rules, cluster-oriented scheduling rules, and cluster redirection scheduling rules. If the processing result is a successful scheduling, the corresponding scheduling result is returned. If the processing result is a failed scheduling, rescheduling is performed if the retry count has not been exceeded; otherwise, the scheduling ends.

[0080] Figure 5 A schematic diagram of an optimized high-concurrency scheduling device provided in an embodiment of this disclosure is shown.

[0081] like Figure 5 As shown, the optimized high-concurrency scheduling device 500 may include a first processing module 510, an index creation module 520, a second processing module 530, and a result return module 540.

[0082] The first processing module 510 can be used to respond to scheduling requests and perform request entry processing through a first-level scheduler.

[0083] The index creation module 520 can be used to create a hash index corresponding to the scheduling request through the first-level scheduler.

[0084] The second processing module 530 can be used to perform cluster scheduling processing based on the hash index through a secondary scheduler to obtain the corresponding processing result.

[0085] The result return module 540 can be used to return the corresponding scheduling result if the processing result is a successful scheduling.

[0086] Therefore, in this embodiment of the disclosure, in response to a scheduling request, the primary scheduler performs request storage processing; the primary scheduler creates a hash index corresponding to the scheduling request; the secondary scheduler performs cluster scheduling processing based on the hash index to obtain the corresponding processing result; and if the processing result is a successful scheduling, the corresponding scheduling result is returned. Thus, high-concurrency scheduling requests are completed through hierarchical scheduling, reducing resource conflicts.

[0087] In some embodiments of this disclosure, the first processing module 510 may specifically include a first processing unit and a second processing unit.

[0088] The first processing unit can be used to perform sharding processing on the scheduling request through the first-level scheduler according to the preset sharding rules, so as to obtain multiple sharding requests.

[0089] The second processing unit can be used to perform the request entry processing on multiple shard requests through the first-level scheduler.

[0090] In some embodiments of this disclosure, the preset sharding rule can be a sharding rule formulated according to different logical management units, and the preset sharding rule can include at least one of average division, priority sales, flat sales, and best matching.

[0091] In some embodiments of this disclosure, the index creation module 520 may be specifically used to create corresponding hash indexes for multiple shard requests through the first-level scheduler.

[0092] In some embodiments of this disclosure, a hash index may include at least one of a time index, a cluster index, a cell index, and other indexes.

[0093] In some embodiments of this disclosure, the second processing module 530 can be specifically used to perform cluster scheduling processing based on preset cluster scheduling rules, through a secondary scheduler according to the hash index, to obtain the corresponding processing result.

[0094] In some embodiments of this disclosure, the preset cluster scheduling rules may include at least one of multi-cluster priority scheduling rules, cluster-oriented scheduling rules, and cluster redirection scheduling rules.

[0095] It should be noted that, Figure 5 The optimized high-concurrency scheduling device 500 shown can execute... Figures 1-4 The various steps in the method embodiment shown are implemented. Figures 1-4 The various processes and effects in the method embodiments shown are not elaborated here.

[0096] Figure 6 A schematic diagram of the structure of an optimized high-concurrency scheduling device provided in an embodiment of this disclosure is shown.

[0097] In some embodiments of this disclosure, Figure 6 The optimized high-concurrency scheduling device shown can be an electronic device. Specifically, the electronic device can include, but is not limited to, devices such as computer equipment, cloud servers, or cloud server clusters.

[0098] like Figure 6As shown, the optimized high-concurrency scheduling device may include a processor 601 and a memory 602 storing computer program instructions.

[0099] Specifically, the processor 601 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0100] Memory 602 may include a large-capacity storage for information or instructions. For example, and not limitingly, memory 602 may include a hard disk drive (HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 602 may include removable or non-removable (or fixed) media. Where appropriate, memory 602 may be internal or external to the integrated gateway device. In a particular embodiment, memory 602 is a non-volatile solid-state memory. In a particular embodiment, memory 602 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (Electrically Programmable ROM, EPROM), an electrically erasable programmable PROM (EEPROM), an electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0101] The processor 601 performs the steps of the optimized high-concurrency scheduling method provided in the embodiments of this disclosure by reading and executing computer program instructions stored in the memory 602.

[0102] In one example, the optimized high-concurrency scheduling device may also include a transceiver 603 and a bus 604. Wherein, as Figure 6 As shown, the processor 601, memory 602 and transceiver 603 are connected via bus 604 and communicate with each other.

[0103] Bus 604 includes hardware, software, or both. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 604 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0104] This disclosure also provides a computer-readable storage medium that can store a computer program that, when executed by a processor, enables the processor to implement the optimized high-concurrency scheduling method provided in this disclosure.

[0105] The aforementioned storage medium may, for example, include a memory 602 containing computer program instructions, which can be executed by a processor 601 of an optimized high-concurrency scheduling device to complete the optimized high-concurrency scheduling method provided in this embodiment. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), compact disc ROM (CD-ROM), magnetic tape, floppy disk, and optical data storage device.

[0106] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0107] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An optimized large concurrency scheduling method, characterized in that, The method comprises the following steps: In response to a scheduling request, performing request entry storage processing through a primary scheduler; Creating a hash index corresponding to the scheduling request through the primary scheduler; Performing cluster scheduling processing according to the hash index through a secondary scheduler to obtain a corresponding processing result; In the case that the processing result is scheduling success, returning a corresponding scheduling result.

2. The method of claim 1, wherein, The request entry storage processing through the primary scheduler comprises the following steps: According to a preset sharding rule, performing sharding processing on the scheduling request through the primary scheduler to obtain a plurality of sharding requests; Performing the request entry storage processing on the plurality of sharding requests through the primary scheduler.

3. The method of claim 2, wherein, The preset sharding rule is a sharding rule formulated according to different logical management units, and the preset sharding rule comprises at least one of average division, preferential selling, flat selling and best matching.

4. The method of claim 2, wherein, The creating of the hash index corresponding to the scheduling request through the primary scheduler comprises the following steps: Creating a corresponding hash index for the plurality of sharding requests through the primary scheduler.

5. The method of claim 1, wherein, The hash index comprises at least one of a time index, a cluster index, a unit index and other indexes.

6. The method of claim 1, wherein, The performing of the cluster scheduling processing according to the hash index through the secondary scheduler to obtain a corresponding processing result comprises the following steps: Based on a preset cluster scheduling rule, performing cluster scheduling processing according to the hash index through the secondary scheduler to obtain a corresponding processing result.

7. The method of claim 6, wherein, The preset cluster scheduling rule comprises at least one of a multi-cluster preferential scheduling rule, a cluster directional scheduling rule and a cluster redirection scheduling rule.

8. An optimized high-concurrency scheduling device, characterized in that, The method comprises the following steps: A first processing module is configured to perform request entry storage processing through a primary scheduler in response to a scheduling request; An index creating module is configured to create a hash index corresponding to the scheduling request through the primary scheduler; A second processing module is configured to perform cluster scheduling processing according to the hash index through a secondary scheduler to obtain a corresponding processing result; A result returning module is configured to return a corresponding scheduling result in the case that the processing result is scheduling success.

9. An optimized mass-concurrent scheduling device, comprising: The method comprises the following steps: A processor; A memory is configured to store executable instructions; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the optimization large concurrent scheduling method in any one of claims 1-7.

10. A non-transitory computer readable storage medium, comprising: The storage medium stores a computer program, and when the computer program is executed by the processor, the processor implements the optimization large concurrent scheduling method in any one of claims 1-7.

Images