CN114124968B - Load balancing method, device, equipment and medium based on market data - Google Patents

Abstract

The invention relates to the field of Internet, and provides a load balancing method, a device, equipment and a medium based on market data, which can calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of a target client, obtaining a target pre-occupied bandwidth of each server, obtaining a pre-configured bandwidth threshold, obtaining the server with the target pre-occupied bandwidth smaller than the bandwidth threshold from each server as a candidate server, obtaining a client type corresponding to the target client, selecting a target server from the candidate servers according to the client type, accessing the target client to the target server, and further, load balancing based on market data is achieved from multiple dimensions of the server, the client and the client, service performance of the server cluster is improved, resource allocation is optimized, and robustness of the server cluster is guaranteed.

Description

Load balancing method, device, device and medium based on market data

technical field

The present invention relates to the field of Internet technologies, and in particular, to a method, device, device and medium for load balancing based on market data.

Background technique

In the field of financial quotations, TCP (Transmission Control Protocol, Transmission Control Protocol) long connection is usually used to issue quotations subscribed by Internet clients. In order to ensure more efficient and accurate data transmission between the server and the client, the Internet quotation The subscription push business needs to use load balancing technology to ensure maximum resource utilization.

In the field of financial quotations, since the number of quotations subscribed by different clients is dynamically changed, and the magnitude is large, the changes in the occupied resources are also large. In the prior art, the general load balancing strategy is either based on only one dimension, or It cannot be applied to the scenario of dynamic market subscription, resulting in poor load balancing effect.

SUMMARY OF THE INVENTION

In view of the above content, it is necessary to provide a load balancing method, device, device and medium based on market data, aiming at solving the problem of load balancing for market data.

A load balancing method based on market data, the load balancing method based on market data comprising:

In response to the access request triggered by the target client, calculating the pre-requested bandwidth of the target client;

Collect resource information of each server in the server cluster, and determine the current pre-occupied bandwidth of each server according to the resource information of each server;

Calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client respectively, and obtain the target pre-occupied bandwidth of each server;

Obtaining a preconfigured bandwidth threshold, and obtaining a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server;

Obtain the client type corresponding to the target client, and select a target server from the candidate servers according to the client type;

Connect the target client to the target server.

According to a preferred embodiment of the present invention, the calculating the pre-requested bandwidth of the target client includes:

Obtain the bandwidth occupied by each snapshot quotation code subscribed by the target client, the number of subscribed snapshot quotation codes, the bandwidth occupied by each entrusted quotation code of each subscription, the number of subscribed entrusted quotation codes, each subscribed quotation code The bandwidth occupied by the tick-by-ticket quotation codes, the number of subscribed tick-by-tick quotation codes, and the flow control value obtained from the target client;

Calculate the product of the bandwidth occupied by each snapshot quotation code and the number of the snapshot quotation code to obtain the first value;

Calculate the product of the bandwidth occupied by each entrusted quotation code and the number of the entrusted quotation codes to obtain the second value;

Calculate the product of the bandwidth occupied by each tick-by-tick quotation code and the number of the tick-by-tick quotation codes to obtain a third value;

calculating the sum of the first numerical value, the second numerical value and the third numerical value to obtain the pre-used bandwidth of the target client;

The flow control value is compared with the size of the pre-used bandwidth, and the smaller value is determined as the pre-requested bandwidth.

According to a preferred embodiment of the present invention, the determining of the current pre-occupied bandwidth of each server according to the resource information of each server includes:

Determine the client currently connected to each server according to the resource information of each server;

Get the pre-requested bandwidth for each client;

Calculate the sum of the pre-requested bandwidths of the clients currently connected to each server to obtain the current pre-occupied bandwidth of each server.

According to a preferred embodiment of the present invention, the selecting a target server from the candidate servers according to the client type includes:

When the client type is the first type, in order from small to large, sort each candidate server according to the target pre-occupied bandwidth of each candidate server to obtain a target sequence;

The first candidate server is extracted from the target sequence as the target server.

According to a preferred embodiment of the present invention, the selecting a target server from the candidate servers according to the client type further includes:

When the client type is the second type, obtain the client currently connected to each candidate server;

determining the client type of the client currently connected to each candidate server;

Obtaining the client type of the client currently connected to each candidate server is the client of the second type, and as the first client corresponding to each candidate server;

Calculate the number of first clients corresponding to each candidate server respectively, and obtain the first number corresponding to each candidate server;

Sort each candidate server according to the first quantity in ascending order;

The first candidate server is obtained as the target server.

According to a preferred embodiment of the present invention, the method further includes:

When the client type is the second type, and no server with the target pre-occupied bandwidth less than the bandwidth threshold is obtained from each server as the candidate server, it is determined that the client is currently connected to each server. The client type of the client on the server side;

Obtaining the client type of the client currently connected to each server is the client of the first type, and as the second client corresponding to each server;

Obtain the occupied bandwidth of the second client corresponding to each server;

Calculate the sum of the occupied bandwidth of the second client corresponding to each server respectively, and use it as the releasable bandwidth of each server;

Select a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client from each server as at least one candidate server;

Obtain the currently pre-occupied bandwidth of each alternative server in the at least one alternative server;

Sort each candidate server according to the current pre-occupied bandwidth of each candidate server in descending order;

Get the top-ranked alternative server as the pending server;

Controlling the to-be-processed server to disconnect from a preset number of the second clients, and to connect the target client to the to-be-processed server;

The preset number is the number of disconnected second clients when the sum of the occupied bandwidth of the disconnected second clients is greater than or equal to the pre-requested bandwidth of the target client. minimum value.

According to a preferred embodiment of the present invention, the method further includes:

When a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client is not selected from each server, an alarm message for prompting the server cluster to be fully loaded is sent, and an alarm message is sent to the A request for expansion of the server cluster.

A load balancing device based on market data, the load balancing device based on market data comprising:

a computing unit, configured to calculate the pre-requested bandwidth of the target client in response to the access request triggered by the target client;

a determining unit, configured to collect resource information of each server in the server cluster, and determine the current pre-occupied bandwidth of each server according to the resource information of each server;

The computing unit is further configured to calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, and obtain the target pre-occupied bandwidth of each server;

an acquiring unit, configured to acquire a preconfigured bandwidth threshold, and acquire a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server;

a selection unit, configured to obtain a client type corresponding to the target client, and select a target server from the candidate servers according to the client type;

An access unit, configured to access the target client to the target server.

A computer device comprising:

a memory that stores at least one instruction; and

The processor executes the instructions stored in the memory to implement the market data-based load balancing method.

A computer-readable storage medium, where at least one instruction is stored, the at least one instruction is executed by a processor in a computer device to implement the market data-based load balancing method.

It can be seen from the above technical solutions that the present invention can respond to the access request triggered by the target client, calculate the pre-request bandwidth of the target client, collect the resource information of each server in the server cluster, and calculate the bandwidth of each server according to the information of each server. The resource information determines the current pre-occupied bandwidth of each server, respectively calculates the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, obtains the target pre-occupied bandwidth of each server, and obtains the pre-configured bandwidth threshold. , obtain a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server, obtain the client type corresponding to the target client, and select a server from the candidate server according to the client type Select the target server, connect the target client to the target server, and then realize load balancing based on market data from multiple dimensions of the server, the client and the client, improve the service performance of the server cluster, and optimize The resource configuration is guaranteed to ensure the robustness of the server cluster.

Description of drawings

FIG. 1 is a flow chart of a preferred embodiment of a load balancing method based on market data of the present invention.

FIG. 2 is a functional block diagram of a preferred embodiment of the market data-based load balancing device of the present invention.

FIG. 3 is a schematic structural diagram of a computer device according to a preferred embodiment of the present invention for implementing a load balancing method based on market data.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

As shown in FIG. 1 , it is a flow chart of a preferred embodiment of the method for load balancing based on market data of the present invention. According to different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted.

The load balancing method based on market data is applied to one or more computer devices, and the computer device is a device that can automatically perform numerical calculation and/or information processing according to pre-set or stored instructions. Including but not limited to microprocessors, application specific integrated circuits (ASICs), programmable gate arrays (Field-Programmable Gate Arrays, FPGAs), digital processors (Digital Signal Processors, DSPs), embedded devices, and the like.

The computer device can be any electronic product that can interact with the user, such as a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), a game console, an interactive network TV ( Internet Protocol Television, IPTV), smart wearable devices, etc.

The computer equipment may also include network equipment and/or user equipment. Wherein, the network device includes, but is not limited to, a single network server, a server group formed by multiple network servers, or a cloud formed by a large number of hosts or network servers based on cloud computing (Cloud Computing).

The server can be an independent server, or can provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (Content Delivery Network) , CDN), and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms.

Among them, artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. .

The basic technologies of artificial intelligence generally include technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation/interaction systems, and mechatronics. Artificial intelligence software technology mainly includes computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning/deep learning.

The network where the computer equipment is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (Virtual Private Network, VPN), and the like.

S10, in response to the access request triggered by the target client, calculate the pre-requested bandwidth of the target client.

In at least one embodiment of the present invention, the target client may be a client of any user, and the target client requests to access the server so as to subscribe to financial market data.

In at least one embodiment of the present invention, the calculating the pre-requested bandwidth of the target client includes:

Obtain the bandwidth occupied by each snapshot quotation code subscribed by the target client, the number of subscribed snapshot quotation codes, the bandwidth occupied by each entrusted quotation code of each subscription, the number of subscribed entrusted quotation codes, each subscribed quotation code The bandwidth occupied by the tick-by-ticket quotation codes, the number of subscribed tick-by-tick quotation codes, and the flow control value obtained from the target client;

Calculate the product of the bandwidth occupied by each snapshot quotation code and the number of the snapshot quotation code to obtain the first value;

Calculate the product of the bandwidth occupied by each entrusted quotation code and the number of the entrusted quotation codes to obtain the second value;

Calculate the product of the bandwidth occupied by each tick-by-tick quotation code and the number of the tick-by-tick quotation codes to obtain a third value;

calculating the sum of the first numerical value, the second numerical value and the third numerical value to obtain the pre-used bandwidth of the target client;

The flow control value is compared with the size of the pre-used bandwidth, and the smaller value is determined as the pre-requested bandwidth.

Wherein, the bandwidth occupied by each snapshot quotation code, the bandwidth occupied by each transaction-by-transaction quotation code, and the bandwidth occupied by each transaction-by-transaction quotation code can be tested and evaluated according to the actual situation, which is not limited in the present invention.

The flow control value of the target client may be configured according to the account corresponding to the target client.

Through the foregoing implementation manner, the pre-requested bandwidth of the target client can be determined based on multiple dimensions, so that the determined pre-requested bandwidth of the target client is more accurate.

S11: Collect resource information of each server in the server cluster, and determine the currently pre-occupied bandwidth of each server according to the resource information of each server.

In this embodiment, the server cluster includes at least one server for providing market data to connected clients.

In at least one embodiment of the present invention, the resource information of each server may include, but is not limited to, a combination of one or more of the following information:

The clients currently connected to each server, the subscription status of clients connected to each server, and the limit of client subscriptions.

In at least one embodiment of the present invention, the determining the current pre-occupied bandwidth of each server according to the resource information of each server includes:

Determine the client currently connected to each server according to the resource information of each server;

Get the pre-requested bandwidth for each client;

Calculate the sum of the pre-requested bandwidths of the clients currently connected to each server to obtain the current pre-occupied bandwidth of each server.

The manner of calculating the pre-requested bandwidth of each client is similar to the manner of calculating the pre-requested bandwidth of the target client, and details are not described herein.

S12: Calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, respectively, to obtain the target pre-occupied bandwidth of each server.

In the above embodiment, the sum of the pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client is used as the target pre-occupied bandwidth of each server, and this is used as a comparison basis to ensure access to the target client. After the server is installed, the corresponding server can meet the load.

S13: Acquire a preconfigured bandwidth threshold, and acquire a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server.

In this embodiment, the bandwidth threshold may be custom configured according to actual requirements, which is not limited in the present invention.

Through the above embodiment, the candidate server can be selected in combination with the resource occupancy of the server and the resource occupancy of the client at the same time.

S14: Acquire a client type corresponding to the target client, and select a target server from the candidate servers according to the client type.

In at least one embodiment of the present invention, the customer types may include, but are not limited to: VIP customers, non-VIP customers (premium customers, ordinary customers, free customers), and the like.

In at least one embodiment of the present invention, the selecting a target server from the candidate servers according to the client type includes:

When the client type is the first type, in order from small to large, sort each candidate server according to the target pre-occupied bandwidth of each candidate server to obtain a target sequence;

The first candidate server is extracted from the target sequence as the target server.

Wherein, the first type may include a non-VIP client type.

In the above embodiment, for non-key clients, a server with low bandwidth occupation is selected as a target server to serve.

In at least one embodiment of the present invention, the selecting a target server from the candidate servers according to the client type further includes:

When the client type is the second type, obtain the client currently connected to each candidate server;

determining the client type of the client currently connected to each candidate server;

Obtaining the client type of the client currently connected to each candidate server is the client of the second type, and as the first client corresponding to each candidate server;

Calculate the number of first clients corresponding to each candidate server respectively, and obtain the first number corresponding to each candidate server;

Sort each candidate server according to the first quantity in ascending order;

The first candidate server is obtained as the target server.

Wherein, the second type may include a VIP client type.

In the above embodiment, for key customers, the server with the least number of connected key customers is selected as the target server, so as to provide better services to key customers.

Through the above-mentioned embodiments, on the basis of the server-side dimension and the client-side dimension, the customer dimension can be further integrated to achieve load balancing, so that the attributes of the market data can be more satisfied.

S15, connect the target client to the target server.

Through the above embodiments, the load balancing for market data delivery services is realized in combination with the server dimension, the client dimension and the customer dimension, which improves the service quality and the processing capability of network data, reduces the delay for the client to receive data, and at the same time can Make full use of the resources of the server cluster to improve the overall service performance.

In at least one embodiment of the present invention, the method further includes:

When the client type is the second type, and no server with the target pre-occupied bandwidth less than the bandwidth threshold is obtained from each server as the candidate server, it is determined that the client is currently connected to each server. The client type of the client on the server side;

Obtaining the client type of the client currently connected to each server is the client of the first type, and as the second client corresponding to each server;

Obtain the occupied bandwidth of the second client corresponding to each server;

Calculate the sum of the occupied bandwidth of the second client corresponding to each server respectively, and use it as the releasable bandwidth of each server;

Select a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client from each server as at least one candidate server;

Obtain the currently pre-occupied bandwidth of each alternative server in the at least one alternative server;

Sort each candidate server according to the current pre-occupied bandwidth of each candidate server in descending order;

Get the top-ranked alternative server as the pending server;

Controlling the to-be-processed server to disconnect from a preset number of the second clients, and to connect the target client to the to-be-processed server;

The preset number is the number of disconnected second clients when the sum of the occupied bandwidth of the disconnected second clients is greater than or equal to the pre-requested bandwidth of the target client. minimum value.

Specifically, when controlling the to-be-processed server to disconnect from the preset number of the second clients, a client with a longer connection time may be selected from the second clients to perform the disconnection operation , you can also select the client with higher resource consumption from the second client to perform the disconnection operation, or arbitrarily select the client from the second client to perform the disconnection operation, so that the bandwidth released after disconnection is just right. It is sufficient to satisfy the pre-requested bandwidth of the target client.

Through the above implementation, in the case of limited resources, the clients of non-key customers are disconnected, so that key customers can use server resources preferentially and stably, and on the premise of ensuring service reliability, flexible and differentiated load balancing can be achieved .

In at least one embodiment of the present invention, the method further includes:

When a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client is not selected from each server, an alarm message for prompting the server cluster to be fully loaded is sent, and an alarm message is sent to the A request for expansion of the server cluster.

Through the above implementation, a full load warning can be issued when there are no available resources in the server cluster, and capacity expansion can be requested, so as to ensure that the server cluster can resume normal services in time and avoid affecting customer service experience.

In this embodiment, when there is no target server that can be accessed, a notification of request failure may be sent to the target client in time, or a reconnection prompt may also be sent to the target client at the same time, so as to avoid client long wait.

It can be seen from the above technical solutions that the present invention can respond to the access request triggered by the target client, calculate the pre-request bandwidth of the target client, collect the resource information of each server in the server cluster, and calculate the bandwidth of each server according to the information of each server. The resource information determines the current pre-occupied bandwidth of each server, respectively calculates the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, obtains the target pre-occupied bandwidth of each server, and obtains the pre-configured bandwidth threshold. , obtain a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server, obtain the client type corresponding to the target client, and select a server from the candidate server according to the client type Select the target server, connect the target client to the target server, and then realize load balancing based on market data from multiple dimensions of the server, the client and the client, improve the service performance of the server cluster, and optimize The resource configuration is guaranteed to ensure the robustness of the server cluster.

As shown in FIG. 2 , it is a functional block diagram of a preferred embodiment of the market data-based load balancing device of the present invention. The market data-based load balancing device 11 includes a calculation unit 110 , a determination unit 111 , an acquisition unit 112 , a selection unit 113 , and an access unit 114 . The modules/units referred to in the present invention refer to a series of computer program segments that can be executed by the processor 13 and can perform fixed functions, and are stored in the memory 12 . In this embodiment, the functions of each module/unit will be described in detail in subsequent embodiments.

The calculating unit 110 calculates the pre-requested bandwidth of the target client in response to the access request triggered by the target client.

In at least one embodiment of the present invention, the target client may be a client of any user, and the target client requests to access the server so as to subscribe to financial market data.

In at least one embodiment of the present invention, the calculating unit 110 calculating the pre-requested bandwidth of the target client includes:

Obtain the bandwidth occupied by each snapshot quotation code subscribed by the target client, the number of subscribed snapshot quotation codes, the bandwidth occupied by each entrusted quotation code of each subscription, the number of subscribed entrusted quotation codes, each subscribed quotation code The bandwidth occupied by the tick-by-ticket quotation codes, the number of subscribed tick-by-tick quotation codes, and the flow control value obtained from the target client;

Calculate the product of the bandwidth occupied by each snapshot quotation code and the number of the snapshot quotation code to obtain the first value;

Calculate the product of the bandwidth occupied by each entrusted quotation code and the number of the entrusted quotation codes to obtain the second value;

Calculate the product of the bandwidth occupied by each tick-by-tick quotation code and the number of the tick-by-tick quotation codes to obtain a third value;

calculating the sum of the first numerical value, the second numerical value and the third numerical value to obtain the pre-used bandwidth of the target client;

The flow control value is compared with the size of the pre-used bandwidth, and the smaller value is determined as the pre-requested bandwidth.

Wherein, the bandwidth occupied by each snapshot quotation code, the bandwidth occupied by each transaction-by-transaction quotation code, and the bandwidth occupied by each transaction-by-transaction quotation code can be tested and evaluated according to the actual situation, which is not limited in the present invention.

The flow control value of the target client may be configured according to the account corresponding to the target client.

Through the foregoing implementation manner, the pre-requested bandwidth of the target client can be determined based on multiple dimensions, so that the determined pre-requested bandwidth of the target client is more accurate.

The determining unit 111 collects resource information of each server in the server cluster, and determines the currently pre-occupied bandwidth of each server according to the resource information of each server.

In this embodiment, the server cluster includes at least one server for providing market data to connected clients.

In at least one embodiment of the present invention, the resource information of each server may include, but is not limited to, a combination of one or more of the following information:

The clients currently connected to each server, the subscription status of clients connected to each server, and the limit of client subscriptions.

In at least one embodiment of the present invention, the determining unit 111 determining the currently pre-occupied bandwidth of each server according to the resource information of each server includes:

Determine the client currently connected to each server according to the resource information of each server;

Get the pre-requested bandwidth for each client;

Calculate the sum of the pre-requested bandwidths of the clients currently connected to each server to obtain the current pre-occupied bandwidth of each server.

The manner of calculating the pre-requested bandwidth of each client is similar to the manner of calculating the pre-requested bandwidth of the target client, and details are not described herein.

The calculating unit 110 calculates the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, respectively, to obtain the target pre-occupied bandwidth of each server.

In the above embodiment, the sum of the pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client is used as the target pre-occupied bandwidth of each server, and this is used as a comparison basis to ensure access to the target client. After the server is installed, the corresponding server can meet the load.

The acquiring unit 112 acquires a preconfigured bandwidth threshold, and acquires a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server.

In this embodiment, the bandwidth threshold may be custom configured according to actual requirements, which is not limited in the present invention.

Through the above embodiment, the candidate server can be selected in combination with the resource occupancy of the server and the resource occupancy of the client at the same time.

The selecting unit 113 acquires a client type corresponding to the target client, and selects a target server from the candidate servers according to the client type.

In at least one embodiment of the present invention, the customer types may include, but are not limited to: VIP customers, non-VIP customers (premium customers, ordinary customers, free customers), and the like.

In at least one embodiment of the present invention, the selecting unit 113 selecting a target server from the candidate servers according to the client type includes:

When the client type is the first type, in order from small to large, sort each candidate server according to the target pre-occupied bandwidth of each candidate server to obtain a target sequence;

The first candidate server is extracted from the target sequence as the target server.

Wherein, the first type may include a non-VIP client type.

In the above embodiment, for non-key clients, a server with low bandwidth occupation is selected as a target server to serve.

In at least one embodiment of the present invention, the selecting unit 113 selecting a target server from the candidate servers according to the client type further includes:

When the client type is the second type, obtain the client currently connected to each candidate server;

determining the client type of the client currently connected to each candidate server;

Obtaining the client type of the client currently connected to each candidate server is the client of the second type, and as the first client corresponding to each candidate server;

Calculate the number of first clients corresponding to each candidate server respectively, and obtain the first number corresponding to each candidate server;

Sort each candidate server according to the first quantity in ascending order;

The first candidate server is obtained as the target server.

Wherein, the second type may include a VIP client type.

In the above embodiment, for key customers, the server with the least number of connected key customers is selected as the target server, so as to provide better services to key customers.

Through the above-mentioned embodiments, on the basis of the server-side dimension and the client-side dimension, the customer dimension can be further integrated to achieve load balancing, so that the attributes of the market data can be more satisfied.

The access unit 114 accesses the target client to the target server.

Through the above-mentioned embodiments, the load balancing for the market data delivery service is realized by combining the server dimension, the client dimension and the customer dimension, which improves the service quality and the processing capability of network data, reduces the time delay for the client to receive data, and at the same time can Make full use of the resources of the server cluster to improve the overall service performance.

In at least one embodiment of the present invention, when the client type is the second type, and no server whose target pre-occupied bandwidth is less than the bandwidth threshold is obtained from each server as the candidate When the server is used, determine the client type of the client currently connected to each server;

Obtaining the client type of the client currently connected to each server is the client of the first type, and as the second client corresponding to each server;

Obtain the occupied bandwidth of the second client corresponding to each server;

Calculate the sum of the occupied bandwidth of the second client corresponding to each server respectively, and use it as the releasable bandwidth of each server;

Select a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client from each server as at least one candidate server;

Obtain the currently pre-occupied bandwidth of each alternative server in the at least one alternative server;

Sort each candidate server according to the current pre-occupied bandwidth of each candidate server in descending order;

Get the top-ranked alternative server as the pending server;

Controlling the to-be-processed server to disconnect from a preset number of the second clients, and to connect the target client to the to-be-processed server;

The preset number is the number of disconnected second clients when the sum of the occupied bandwidth of the disconnected second clients is greater than or equal to the pre-requested bandwidth of the target client. minimum value.

Specifically, when controlling the to-be-processed server to disconnect from the preset number of the second clients, a client with a longer connection time may be selected from the second clients to perform the disconnection operation , you can also select the client with higher resource consumption from the second client to perform the disconnection operation, or arbitrarily select the client from the second client to perform the disconnection operation, so that the bandwidth released after disconnection is just right. It is sufficient to satisfy the pre-requested bandwidth of the target client.

Through the above implementation, in the case of limited resources, the clients of non-key customers are disconnected, so that key customers can use server resources preferentially and stably, and on the premise of ensuring service reliability, flexible and differentiated load balancing can be achieved .

In at least one embodiment of the present invention, when a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client is not selected from each server, a message is sent to prompt the server cluster full-load alarm information, and issue a capacity expansion request for the server cluster.

Through the above implementation, a full load warning can be issued when there are no available resources in the server cluster, and capacity expansion can be requested, so as to ensure that the server cluster can resume normal services in time and avoid affecting customer service experience.

In this embodiment, when there is no target server that can be accessed, a notification of request failure may be sent to the target client in time, or a reconnection prompt may also be sent to the target client at the same time, so as to avoid client long wait.

It can be seen from the above technical solutions that the present invention can respond to the access request triggered by the target client, calculate the pre-request bandwidth of the target client, collect the resource information of each server in the server cluster, and calculate the bandwidth of each server according to the information of each server. The resource information determines the current pre-occupied bandwidth of each server, respectively calculates the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, obtains the target pre-occupied bandwidth of each server, and obtains the pre-configured bandwidth threshold. , obtain a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server, obtain the client type corresponding to the target client, and select a server from the candidate server according to the client type Select the target server, connect the target client to the target server, and then realize load balancing based on market data from multiple dimensions of the server, the client and the client, improve the service performance of the server cluster, and optimize The resource configuration is guaranteed to ensure the robustness of the server cluster.

As shown in FIG. 3 , it is a schematic structural diagram of a computer device according to a preferred embodiment of the present invention to implement the method for load balancing based on market data.

The computer device 1 may include a memory 12, a processor 13 and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a load balancing program based on market data.

Those skilled in the art can understand that the schematic diagram is only an example of the computer device 1, and does not constitute a limitation on the computer device 1. The computer device 1 can be either a bus-type structure or a star-shaped structure. The device 1 may also include more or less other hardware or software than shown, or a different arrangement of components, for example, the computer device 1 may also include input and output devices, network access devices, and the like.

It should be noted that the computer equipment 1 is only an example. If other existing or future electronic products can be adapted to the present invention, they should also be included within the protection scope of the present invention, and are incorporated herein by reference. .

Wherein, the memory 12 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. . The memory 12 may be an internal storage unit of the computer device 1 in some embodiments, such as a removable hard disk of the computer device 1 . In other embodiments, the memory 12 may also be an external storage device of the computer device 1 , such as a pluggable mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) equipped on the computer device 1 . Cards, Flash Cards, etc. Further, the memory 12 may also include both an internal storage unit of the computer device 1 and an external storage device. The memory 12 can not only be used to store application software installed in the computer device 1 and various types of data, such as code of a load balancing program based on market data, etc., but also can be used to temporarily store data that has been output or will be output.

The processor 13 may be composed of integrated circuits in some embodiments, for example, may be composed of a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units. CPU (Central Processing Unit, CPU), microprocessor, digital processing chip, graphics processor and combination of various control chips, etc. The processor 13 is the control core (Control Unit) of the computer device 1, and uses various interfaces and lines to connect the various components of the entire computer device 1, and by running or executing the program or module stored in the memory 12 (for example, executing A load balancing program based on market data, etc.), and calling the data stored in the memory 12 to execute various functions of the computer device 1 and process data.

The processor 13 executes the operating system of the computer device 1 and various installed application programs. The processor 13 executes the application program to implement the steps in each of the foregoing embodiments of the load balancing method based on market data, for example, the steps shown in FIG. 1 .

Exemplarily, the computer program may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 12 and executed by the processor 13 to complete the present invention. invention. The one or more modules/units may be a series of computer-readable instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device 1 . For example, the computer program may be divided into a calculation unit 110 , a determination unit 111 , an acquisition unit 112 , a selection unit 113 , and an access unit 114 .

The above-mentioned integrated units implemented in the form of software functional modules may be stored in a computer-readable storage medium. The above-mentioned software function modules are stored in a storage medium, and include several instructions to enable a computer device (which may be a personal computer, a computer device, or a network device, etc.) or a processor (processor) to execute the based on the various embodiments of the present invention. Part of the load balancing method for market data.

If the modules/units integrated in the computer device 1 are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments, and can also be completed by instructing relevant hardware devices through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above method embodiments can be implemented.

Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory) , random access memory, etc.

Further, the computer-readable storage medium may mainly include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required by at least one function, and the like; Use the created data, etc.

The blockchain referred to in the present invention is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm. Blockchain, essentially a decentralized database, is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information to verify its Validity of information (anti-counterfeiting) and generation of the next block. The blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.

The bus may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (extended industry standard architecture, EISA for short) bus or the like. The bus can be divided into address bus, data bus, control bus and so on. For ease of representation, only one straight line is shown in FIG. 3, but it does not mean that there is only one bus or one type of bus. The bus is arranged to enable connection communication between the memory 12 and at least one processor 13 and the like.

Although not shown, the computer device 1 may also include a power supply (such as a battery) for supplying power to various components, preferably, the power supply may be logically connected to the at least one processor 13 through a power management device, so as to be implemented by the power management device Charge management, discharge management, and power management functions. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and any other components. The computer device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

Further, the computer device 1 may also include a network interface, optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used in the computer device 1 Establish a communication connection with other computer equipment.

Optionally, the computer device 1 may further include a user interface, and the user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, and the like. The display, which may also be appropriately called a display screen or a display unit, is used for displaying information processed in the computer device 1 and for displaying a visual user interface.

It should be understood that the embodiments are only used for illustration, and are not limited by this structure in the scope of the patent application.

FIG. 3 only shows the computer device 1 having the components 12-13. Those skilled in the art can understand that the structure shown in FIG. 3 does not constitute a limitation on the computer device 1, and may include less than illustrated Or more components, or a combination of certain components, or a different arrangement of components.

1, the memory 12 in the computer device 1 stores multiple instructions to implement a load balancing method based on market data, and the processor 13 can execute the multiple instructions to implement:

In response to the access request triggered by the target client, calculating the pre-requested bandwidth of the target client;

Collect resource information of each server in the server cluster, and determine the current pre-occupied bandwidth of each server according to the resource information of each server;

Calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client respectively, and obtain the target pre-occupied bandwidth of each server;

Obtaining a preconfigured bandwidth threshold, and obtaining a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server;

Obtain the client type corresponding to the target client, and select a target server from the candidate servers according to the client type;

Connect the target client to the target server.

Specifically, for the specific implementation method of the above-mentioned instruction by the processor 13, reference may be made to the description of the relevant steps in the embodiment corresponding to FIG. 1 , which is not repeated here.

It should be noted that the data involved in this case were obtained legally.

In the several embodiments provided by the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division manners in actual implementation.

The present invention can be used in numerous general purpose or special purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, including A distributed computing environment for any of the above systems or devices, and the like. The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

The modules described as separate components may or may not be physically separated, and components shown as modules may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware, or can be implemented in the form of hardware plus software function modules.

It will be apparent to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, but that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics of the invention.

Therefore, the embodiments are to be regarded in all respects as illustrative and not restrictive, and the scope of the invention is to be defined by the appended claims rather than the foregoing description, which are therefore intended to fall within the scope of the claims. All changes within the meaning and range of the equivalents of , are included in the present invention. Any reference signs in the claims shall not be construed as limiting the involved claim.

Furthermore, it is clear that the word "comprising" does not exclude other units or steps and the singular does not exclude the plural. A plurality of units or devices stated in the present invention may also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to denote names and do not denote any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be Modifications or equivalent substitutions can be made without departing from the spirit and scope of the technical solutions of the present invention.

Claims (8)

1. a load balancing method based on market data, characterized in that the load balancing method based on market data comprises: In response to the access request triggered by the target client, calculating the pre-request bandwidth of the target client, wherein the calculating the pre-request bandwidth of the target client includes: acquiring the occupation of each snapshot quotation code subscribed by the target client Bandwidth, the number of subscribed snapshot quotation codes, the bandwidth occupied by each subscribed tick quotation code, the number of subscribed tick quotation codes, the bandwidth occupied by each subscribed tick quotation code, the subscribed tick quotations The number of codes, and obtain the flow control value of the target client; calculate the product of the bandwidth occupied by each snapshot quotation code and the number of the snapshot quotation codes to obtain the first value; calculate the bandwidth occupied by each commissioned quotation code and the The product of the number of the quotation codes of the one-by-one entrustment is obtained, and the second value is obtained; the product of the bandwidth occupied by each transaction-by-transaction quotation code and the number of the transaction-by-transaction quotation codes is calculated to obtain the third numerical value; the calculation of the first value, the sum of the second value and the third value to obtain the pre-used bandwidth of the target client; compare the size of the flow control value and the pre-used bandwidth, and determine the smaller value as the the pre-requested bandwidth; Collect resource information of each server in the server cluster, and determine the current pre-occupied bandwidth of each server according to the resource information of each server; Calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client respectively, and obtain the target pre-occupied bandwidth of each server; Obtaining a preconfigured bandwidth threshold, and obtaining a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server; Acquiring a client type corresponding to the target client, and selecting a target server from the candidate servers according to the client type, wherein the selecting a target server from the candidate servers according to the client type includes: When the client type is the first type, sort each candidate server according to the target pre-occupied bandwidth of each candidate server in order from small to large to obtain a target sequence; extract the ranking from the target sequence The candidate server in the first place serves as the target server; Connect the target client to the target server. 2. The load balancing method based on market data as claimed in claim 1, wherein the determining the current pre-occupied bandwidth of each server according to the resource information of each server comprises: Determine the client currently connected to each server according to the resource information of each server; Get the pre-requested bandwidth for each client; Calculate the sum of the pre-requested bandwidths of the clients currently connected to each server to obtain the current pre-occupied bandwidth of each server. 3. The load balancing method based on market data according to claim 1, wherein the selecting a target server from the candidate servers according to the client type further comprises: When the client type is the second type, obtain the client currently connected to each candidate server; determining the client type of the client currently connected to each candidate server; Obtaining the client type of the client currently connected to each candidate server is the client of the second type, and as the first client corresponding to each candidate server; Calculate the number of first clients corresponding to each candidate server respectively, and obtain the first number corresponding to each candidate server; Sort each candidate server according to the first quantity in ascending order; The first candidate server is obtained as the target server. 4. The load balancing method based on market data as claimed in claim 3, wherein the method further comprises: When the client type is the second type, and no server with the target pre-occupied bandwidth less than the bandwidth threshold is obtained from each server as the candidate server, it is determined that the client is currently connected to each server. The client type of the client of the server; Obtaining the client type of the client currently connected to each server is the client of the first type, and as the second client corresponding to each server; Obtain the occupied bandwidth of the second client corresponding to each server; Calculate the sum of the occupied bandwidth of the second client corresponding to each server respectively, and use it as the releasable bandwidth of each server; Select a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client from each server as at least one candidate server; Obtain the currently pre-occupied bandwidth of each alternative server in the at least one alternative server; Sort each candidate server according to the current pre-occupied bandwidth of each candidate server in descending order; Get the top-ranked alternative server as the pending server; Controlling the to-be-processed server to disconnect from a preset number of the second clients, and to connect the target client to the to-be-processed server; The preset number is equal to the number of the disconnected second clients when the sum of the occupied bandwidth of the disconnected second clients is greater than or equal to the pre-requested bandwidth of the target client minimum value. 5. The load balancing method based on market data as claimed in claim 4, wherein the method further comprises: When a server whose releasable bandwidth is greater than or equal to the pre-requested bandwidth of the target client is not selected from each server, an alarm message for prompting the server cluster to be fully loaded is sent, and an alarm message is sent to the A request for expansion of the server cluster. 6. A load balancing device based on market data, wherein the load balancing device based on market data comprises: A computing unit, configured to calculate the pre-requested bandwidth of the target client in response to the access request triggered by the target client, wherein the calculating the pre-requested bandwidth of the target client includes: acquiring every subscribed bandwidth of the target client Bandwidth occupied by only snapshot quotation codes, number of subscribed snapshot quotation codes, bandwidth occupied by each subscribed tick-by-tick quotation code, number of subscribed tick-by-tick quotation codes, bandwidth occupied by each subscribed tick-by-transaction quotation code, subscription The number of transaction quotation codes, and obtain the flow control value of the target client; calculate the product of the bandwidth occupied by each snapshot quotation code and the number of the snapshot quotation codes to obtain the first value; calculate each transaction entrustment The product of the bandwidth occupied by the quotation code and the number of the quotation codes of the order-by-transaction entrustment is obtained, and the second numerical value is obtained; the product of the bandwidth occupied by the quotation code of each per-transaction transaction and the number of the quotation code of the transaction-by-transaction is calculated to obtain the third numerical value; Calculate the sum of the first value, the second value and the third value to obtain the pre-used bandwidth of the target client; compare the size of the flow control value and the pre-used bandwidth, and set the smaller value The value of is determined as the pre-requested bandwidth; a determining unit, configured to collect resource information of each server in the server cluster, and determine the current pre-occupied bandwidth of each server according to the resource information of each server; The computing unit is also used to calculate the sum of the current pre-occupied bandwidth of each server and the pre-requested bandwidth of the target client, and obtain the target pre-occupied bandwidth of each server; an acquiring unit, configured to acquire a preconfigured bandwidth threshold, and acquire a server whose target pre-occupied bandwidth is less than the bandwidth threshold from each server as a candidate server; A selection unit, configured to obtain the client type corresponding to the target client, and select a target server from the candidate servers according to the client type, wherein the selection from the candidate servers according to the client type The target server includes: when the client type is the first type, in order from small to large, sort each candidate server according to the target pre-occupied bandwidth of each candidate server, and obtain a target sequence; Extracting the top candidate server from the target sequence as the target server; An access unit, configured to access the target client to the target server. 7. A computer device, characterized in that the computer device comprises: a memory that stores at least one instruction; and The processor executes the instructions stored in the memory to implement the market data-based load balancing method according to any one of claims 1 to 5. 8. A computer-readable storage medium, characterized in that: the computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in a computer device to implement the methods described in claims 1 to 5. Any one of the load balancing methods based on market data.

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