CN112650523A - Data distribution method, device and equipment for gray scale release - Google Patents
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Abstract
The application relates to the technical field of computers and discloses a data distribution method for gray scale publishing. The method comprises the following steps: acquiring a node serial number and a user data serial number; determining a node type corresponding to the node serial number; determining a user data type corresponding to the user data serial number; and carrying out data distribution according to the node type and the user data type. Determining a node type corresponding to the node serial number by acquiring the node serial number and the user data serial number, determining a user data type corresponding to the user data serial number, and then performing data distribution according to the node type and the user data type; therefore, data distribution is not needed to be carried out in a mode of manually configuring nodes in gray scale release, and the efficiency of data distribution is improved. The application also discloses a data shunting device and equipment for gray scale release.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a data splitting method, device, and apparatus for gray scale publishing.
Background
At present, more and more nodes are distributed in the distributed application, and the distribution is more and more frequent. To ensure the stability of the system and reduce the impact on the user, gray-scale distribution is usually used to update the nodes of the application one by one.
In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art: the existing gray level publishing technology needs to perform data distribution in a mode of manually configuring nodes, so that the data distribution efficiency is low.
Disclosure of Invention
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of such embodiments but rather as a prelude to the more detailed description that is presented later.
The embodiment of the disclosure provides a data distribution method, device and equipment for gray scale release, so as to improve the efficiency of data distribution.
In some embodiments, the data splitting method for gray scale distribution includes:
acquiring a node serial number and a user data serial number;
determining a node type corresponding to the node serial number;
determining a user data type corresponding to the user data serial number;
and carrying out data distribution according to the node type and the user data type.
In some embodiments, determining the node type corresponding to the node sequence number includes:
determining the node type corresponding to the node serial number meeting the first preset condition as a gray node; and/or the presence of a gas in the gas,
and determining the node type corresponding to the node serial number which does not meet the first preset condition as a non-gray node.
In some embodiments, the determining, as a gray node, a node type corresponding to a node sequence number that satisfies a first preset condition includes:
acquiring a gray release serial number;
and determining the node type corresponding to the node serial number which is the same as the gray release serial number as a gray node.
In some embodiments, the determining, as a non-grayscale node, a node type corresponding to a node sequence number that does not satisfy the first preset condition includes:
acquiring a gray release serial number;
and determining the node type corresponding to the node serial number different from the gray release serial number as a non-gray node.
In some embodiments, determining the user data type corresponding to the user data serial number includes:
determining the user data type corresponding to the user data serial number meeting the second preset condition as gray user data; and/or the presence of a gas in the gas,
and determining the user data type corresponding to the user data serial number which does not meet the second preset condition as non-gray user data.
In some embodiments, the determining, as the grayscale user data, the user data type corresponding to the user data serial number that satisfies the second preset condition includes:
acquiring a gray node serial number;
and determining the user data type corresponding to the user data serial number which is the same as the gray node serial number as gray user data.
In some embodiments, the determining, as the non-grayscale user data, the user data type corresponding to the user data serial number that does not satisfy the second preset condition includes:
acquiring a gray node serial number;
and determining the user data type corresponding to the user data serial number different from the gray node serial number as non-gray user data.
In some embodiments, the data splitting according to the node type and the user data type includes:
sending the gray-scale user data to the gray-scale nodes; and/or sending the non-grayscale user data to the non-grayscale node.
In some embodiments, the apparatus for data splitting for grayscale distribution includes a processor and a memory storing program instructions, and the processor is configured to execute the data splitting method for grayscale distribution described above when executing the program instructions.
In some embodiments, the apparatus includes the above-mentioned data splitting device for gray scale distribution.
The data distribution method, device and equipment for gray scale release provided by the embodiment of the disclosure can achieve the following technical effects: determining a node type corresponding to the node serial number by acquiring the node serial number and the user data serial number, determining a user data type corresponding to the user data serial number, and then performing data distribution according to the node type and the user data type; the data distribution is not needed to be carried out in a mode of manually configuring nodes in the gray level publishing process, the data distribution efficiency is improved, and the user experience in the gray level publishing process is improved.
The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.
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One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the accompanying drawings and not in limitation thereof, in which elements having the same reference numeral designations are shown as like elements and not in limitation thereof, and wherein:
fig. 1 is a schematic diagram of a data splitting method for gray scale distribution according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a method for determining grayscale and non-grayscale nodes provided by an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a method for automatically configuring a node according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a data splitting device for gray scale distribution according to an embodiment of the present disclosure.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The terms "first," "second," and the like in the description and in the claims, and the above-described drawings of embodiments of the present disclosure, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure described herein may be made. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions.
The term "plurality" means two or more unless otherwise specified.
In the embodiment of the present disclosure, the character "/" indicates that the preceding and following objects are in an or relationship. For example, A/B represents: a or B.
The term "and/or" is an associative relationship that describes objects, meaning that three relationships may exist. For example, a and/or B, represents: a or B, or A and B.
With reference to fig. 1, an embodiment of the present disclosure provides a data splitting method for gray scale distribution, including:
step S101, acquiring a node serial number and a user data serial number;
step S102, determining a node type corresponding to the node serial number;
step S103, determining a user data type corresponding to the user data serial number;
and step S104, carrying out data distribution according to the node type and the user data type.
By adopting the data distribution method for gray scale release provided by the embodiment of the disclosure, the node type corresponding to the node serial number is determined by acquiring the node serial number and the user data serial number, the user data type corresponding to the user data serial number is determined, and then data distribution is performed according to the node type and the user data type; the data distribution is not needed to be carried out in a mode of manually configuring nodes in the gray level publishing process, the data distribution efficiency is improved, and the user experience in the gray level publishing process is improved.
Optionally, the node sequence number is a sequence number of a node in the application; the node sequence numbers include a grayscale node sequence number and a non-grayscale node sequence number. The application involved in greyscale distribution is greyscale application.
Optionally, the user data refers to data that generates interaction through the application in the user terminal and the server; the user data sequence number is used to distinguish the user data into grayscale user data and non-grayscale user data. In one-time gray release, after part of nodes in an application are upgraded, user data needs to be shunted and guided into the upgraded application nodes and the un-upgraded application nodes, so that one part of users begin to experience a new version of the upgraded application and collect user satisfaction of the new version of the users, and the other part of users continue to use the old version; under the condition that the user satisfaction degree meets a third preset condition, nodes of the applications with the remained sanitation levels are upgraded, so that another part of users start to use the new version, and then the gray level release is finished; and when the user satisfaction does not meet the third preset condition, rolling back the new version to the old version, and finishing the gray release. Optionally, the third preset condition is that more than 90% of users using the new version are satisfied.
Optionally, determining a node type corresponding to the node sequence number includes: determining the node type corresponding to the node serial number meeting the first preset condition as a gray node; and/or determining the node type corresponding to the node serial number which does not meet the first preset condition as a non-gray node.
Optionally, the grayscale release sequence number and the node sequence number of the node to which the grayscale is applied are obtained by the server.
Optionally, the first preset condition is that the node serial number is the same as the gray release serial number; and when a first preset condition is met, namely the node type of the node corresponding to the node serial number is determined to be a gray node from a preset node set under the condition that the node serial number is the same as the gray release serial number. And the node type of the node corresponding to the node serial number is determined to be a non-gray node from a preset node set under the condition that the first preset condition is not met, namely the node serial number is not equal to the gray release serial number.
Optionally, determining a node type corresponding to the node serial number meeting the first preset condition as a gray node, including: acquiring a gray release serial number; and determining the node type corresponding to the node serial number which is the same as the gray release serial number as a gray node.
Optionally, the gray release sequence number is an identifier of the number of gray releases. For example: under the condition of carrying out gray release for the first time, the serial number of the gray release is 1; when the gray release is carried out for the second time, the gray release serial number is added with 1, namely the gray release serial number of the gray release for the second time is 2; when the gray scale is released for the third time, the serial number of the gray scale release is 3, and so on; the gray release serial number of each gray release is added with 1 on the basis of the last gray release serial number, so that each serial number mark corresponds to one gray release, and the gray release is more convenient for a user.
In some embodiments, if the gray release serial number is 5, and the node serial number of a certain node in the gray application is 5, the gray release serial number is the same as the node release number, and the node type of the node is determined to be a gray node.
Optionally, determining a node type corresponding to the node serial number that does not satisfy the first preset condition as a non-grayscale node, including: acquiring a gray release serial number; and determining the node type corresponding to the node serial number different from the gray release serial number as a non-gray node.
In some embodiments, if the gray release serial number is 5 and the node serial number of a node in the gray application is 4, and the gray release serial number is not the same as the node serial number, it is determined that the node type of the node is a non-gray node.
Optionally, determining the user data type corresponding to the user data serial number includes: determining the user data type corresponding to the user data serial number meeting the second preset condition as gray user data; and/or determining the user data type corresponding to the user data serial number which does not meet the second preset condition as non-gray user data.
Optionally, the user data serial number of the user data and the node serial number of the node of the grayscale application are obtained by the server.
Optionally, the second preset condition is that the user data serial number is the same as the gray node serial number; and meeting a first preset condition, namely determining the type of the user data corresponding to the user data serial number as gray level user data under the condition that the user data serial number is the same as the gray level node serial number. And the second preset condition is not met, namely the type of the user data corresponding to the user data serial number is determined to be non-gray level user data under the condition that the user data serial number is different from the gray level node serial number.
Optionally, determining the user data type corresponding to the user data serial number meeting the second preset condition as the grayscale user data, including: acquiring a gray node serial number; and determining the user data type corresponding to the user data serial number which is the same as the gray node serial number as the gray user data.
Optionally, after determining a gray node and a non-gray node in the gray application, a node serial number of the gray node, that is, a gray node serial number, is obtained by the server.
In some embodiments, if the gray node serial number is 5, and the user data serial number of a certain user data is 5, the user data serial number is the same as the gray node serial number, and the type of the user data is determined to be gray user data.
Optionally, determining the user data type corresponding to the user data serial number that does not satisfy the second preset condition as non-grayscale user data, including: acquiring a gray node serial number; and determining the user data type corresponding to the user data serial number different from the gray node serial number as non-gray user data.
In some embodiments, if the gray node serial number is 5 and the user data serial number of a certain user data is 4, and the user data serial number is not the same as the gray node serial number, it is determined that the type of the user data is non-gray user data.
Optionally, the data splitting is performed according to the node type and the user data type, and includes: sending the gray-scale user data to the gray-scale nodes; and/or transmitting non-grayscale user data to the non-grayscale nodes.
Optionally, the grayscale node and the non-grayscale node are tested through the test data, the test data is monitored after being sent to the grayscale node and the non-grayscale node, and the grayscale user data is sent to the grayscale node and the non-grayscale user data is sent to the non-grayscale node under the condition that the test data runs normally without errors.
In some embodiments, in a one-time gray release process, a user upgrades a certain application deployed in a server; upgrading a certain node in the application to a new version, and updating the node serial number of the upgraded node to ensure that the node serial number of the node is the same as the gray release serial number of the time; then, the server acquires a gray release serial number of the gray release, node serial numbers of all nodes and user data serial numbers of all user data, and determines gray nodes and non-gray nodes from a preset node set according to a first preset condition, namely, under the condition that the node serial number is the same as the gray release serial number, the type of the node corresponding to the node serial number is determined to be the gray node, and under the condition that the node serial number is not the same as the gray release serial number, the type of the node corresponding to the node serial number is determined to be the non-gray node; after determining which gray nodes and non-gray nodes from a preset node set, acquiring a gray node serial number of the gray nodes, and determining gray user data and non-gray user data according to a second preset condition, namely determining that the type of the user data corresponding to the user data serial number is gray user data under the condition that the user data serial number is the same as the gray node serial number, and determining that the type of the user data corresponding to the user data serial number is non-gray user data under the condition that the user data serial number is different from the gray node serial number. Then, the determined gray level user data is sent to the gray level nodes, so that the part of users can use the upgraded new version application; the determined non-grayscale user data is sent to the non-grayscale nodes so that the portion of users continues to use the old version of the application. Therefore, the nodes are divided into the gray-scale nodes and the non-gray-scale nodes through the node serial numbers, and the user data is divided into the gray-scale user data and the non-gray-scale user data through the user data serial numbers, so that the error rate of manually configuring the gray-scale nodes and the non-gray-scale nodes is reduced, the data distribution efficiency is improved, and the user experience in the gray-scale release process is also improved.
Optionally, whether the application is an application related to the current gray scale distribution is determined by judging whether node serial numbers of all nodes applied in the server are the same. Under the condition that the node serial numbers of all nodes in the application are the same, determining that the application is an application which is not involved in the gray scale release, namely a non-gray scale application; and under the condition that the node issuing numbers of all the nodes in the application have two different values, determining the application as the application related to the gray level issuing, namely the gray level application.
In some embodiments, after determining the grayscale application and the non-grayscale application, a grayscale release serial number, a user data serial number, and node serial numbers of all nodes in the grayscale application are obtained; for example: the gray release serial number is 24, the serial numbers of two kinds of user data are 23 and 24, and the serial numbers of two kinds of nodes are 23 and 24; comparing and judging the node serial numbers of all nodes applied by the gray scale with the gray scale release serial number; when the node serial number of a certain node is the same as the grayscale release serial number, for example: if the node release number of a certain node is 24 and the gray release serial number is 24, determining that the node type of the node corresponding to the node serial number is a gray node; in the case where the node sequence number is not the same as the grayscale issuance sequence number, for example: if the node serial number of a certain node is 23 and the gray release serial number is 24, determining that the node type of the node corresponding to the node serial number is a non-gray node. After determining gray level nodes and non-gray level nodes, acquiring gray level node serial numbers of the gray level nodes, and comparing and judging all user data serial numbers with gray level release serial numbers; in the case where the user data sequence number is the same as the grayscale node sequence number, for example: if the user data serial number is 24 and the gray node serial number is 24, determining that the type of the user data corresponding to the user data serial number is gray user data; in the case where the user data sequence number is not the same as the grayscale node sequence number, for example: and if the user data serial number is 23 and the gray node serial number is 24, determining that the type of the user data corresponding to the user data serial number is non-gray user data. And then the server sends different user data to different nodes for data distribution according to the judgment result, namely sending the gray-scale user data to the gray-scale nodes and sending the non-gray-scale data to the non-gray-scale nodes. Therefore, the nodes are divided into the gray-scale nodes and the non-gray-scale nodes through the node serial numbers, and the user data is divided into the gray-scale user data and the non-gray-scale user data through the user data serial numbers, so that the error rate of manually configuring the gray-scale nodes and the non-gray-scale nodes is reduced, the data distribution efficiency is improved, and the user experience in the gray-scale release process is also improved.
In some embodiments, after the server sends the grayscale user data to the grayscale node, the user satisfaction of the user to the upgraded new version application is obtained, and under the condition that the user satisfaction meets a third preset condition, the remaining non-grayscale nodes in the grayscale application are upgraded to complete the grayscale release. Optionally, the third preset condition is that the user satisfaction is more than 90% of the user satisfaction in the grayscale user data.
Optionally, when the user satisfaction does not meet the preset condition, rolling back the application of the upgraded new version to the old version, and waiting for the next gray release.
Gray scale distribution for internet products, online and offline are black and white, gray scale is understood from the literal meaning to be a smooth transition area between black and white, and a mode for realizing smooth transition of offline function is called gray scale distribution. Non-black, i.e. white, is never a common phenomenon, and from a color point of view, gray refers to unsaturated black, and if black is defined as a reference color, each gray object is an intermediate value from white (0%) to black (100%), and the middle 98% is gray. The Internet product has the characteristics of large user scale, frequent version updating and the like. Every time the new version of the application product is on line, the application product bears great pressure, and the risk is well avoided by gray release. The greyscale distribution product may extract a portion of the users in a number of forms, such as selecting VIP users, or selecting active users; the users are divided into two batches, wherein one batch delivers the application product of version A, and the other batch delivers the application product of version B. Collection and recording of various possible data is performed before delivery, so that user data feedback of two versions can be viewed after delivery, and determination of which version is used for delivery update is performed through extensive data analysis and investigation. Generally, a set of perfect gray scale distribution needs to perform necessary user identification, namely, user distinguishing; for example, the amount of payment or the area and the activity are differentiated, and the purpose of the differentiation is to perform data analysis more accurately.
Optionally, a complete set of gray level publishing mechanisms may include: user identification, target user screening or flow screening, real-time data monitoring, gray scale publishing or rollback. Wherein the user identification is: mainly distinguish users, and meanwhile assist data analysis; the target user screening or flow screening is as follows: the consistency of user characteristics, user flow, user range and user experience needs to be referred to, version iteration aims at all users or part of users, the low-flow test is used for screening users according to the sequence of internal users, seed users, active users and all users generally, the method is typical range control, and the experience consistency requires that whether the span of a new version and an old version is too large or not and whether the users can accept the new version and the old version are considered; monitoring real-time data: monitoring data such as stability of a new version, stability of a server, use times, use frequency and the like to be compared with original data; gray release or rollback: and determining to release the application product or rollback the application product from the data feedback result. By adopting a gray level release mode, the risk of online of the whole new version of the application product can be effectively avoided, and by adopting a small flow verification mode, the problems in the product can be found, adjusted and optimized in a gray level stage, and smooth iteration is realized, so that the updating of the application product can better meet the requirements of users; meanwhile, all relevant data are collected, such as the stability of a new version, the stability and the use times of a server, the use frequency and various data, so that the comparison with the original data can be conveniently carried out; the purpose of doing so is not only to know the truest user experience but also to effectively prevent the generation of a heavy BUG, which affects the system return or causes other unnecessary economic losses, so the gray release is an effective method for effectively avoiding the online risk of the new version, and the test work can be performed through a small flow to help the new version to complete the smooth iteration.
With reference to fig. 2, an embodiment of the present disclosure provides a method for determining a gray node and a non-gray node, including:
step S201, acquiring a gray release serial number and node serial numbers of all nodes in application;
step S202, judging whether the gray release serial number is the same as the node serial number; if yes, namely the gray level issuing serial number is the same as the node serial number, executing step S203; if not, namely the gray level issuing serial number is not the same as the node serial number, executing the step S204;
step S203, determining the node type of the node corresponding to the node serial number as a gray node;
step S204, determining the node type of the node corresponding to the node serial number as a non-gray node.
Optionally, judging all nodes in the application through a first preset condition, and determining a gray node and a non-gray node from a preset node set of the application; the user data type which meets the first preset condition is gray-scale user data, and the user data type which does not meet the first preset condition is non-gray-scale user data; the first preset condition is as follows: the gray release sequence number is the same as the node sequence number.
By dividing the nodes into the gray nodes and the non-gray nodes, a small part of users can use the upgraded new version application first, and the rest of users continue to use the old version, so that the user flow pressure born by the nodes is reduced, the upgraded new version application can effectively avoid the risk of the new version application on line in full, and the new version of the application can be smoothly iterated.
With reference to fig. 3, an embodiment of the present disclosure provides a method for automatically configuring a node, including:
step S301, acquiring a gray node serial number and a user data serial number;
step S302, judging whether the user data serial number is the same as the gray node serial number, if so, executing step S303, namely, if the user data serial number is the same as the gray node serial number; if not, the user data serial number is not the same as the gray node serial number, then step S304 is executed;
step S303, determining the user data type corresponding to the user data serial number as gray level user data, and sending the gray level user data to a gray level node;
step S304, determining the user data type corresponding to the user data serial number as non-gray user data, and sending the non-gray user data to a non-gray node.
Determining a gray scale node and a non-gray scale node through a first preset condition, determining gray scale user data and non-gray scale user data through a second preset condition, and sending the gray scale user data to the gray scale node and sending the non-gray scale user data to the non-gray scale node; therefore, the gray level nodes and the non-gray level nodes are judged, the user data distribution is automatically completed, the whole gray level issuing process does not need manual participation, the data distribution efficiency is improved, the error probability of the gray level issuing is reduced, and the user experience in the gray level issuing process is improved.
As shown in fig. 4, an apparatus for implementing gray scale issue according to an embodiment of the present disclosure includes a processor (processor)100 and a memory (memory)101 storing program instructions. Optionally, the apparatus may also include a Communication Interface (Communication Interface)102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other via a bus 103. The communication interface 102 may be used for information transfer. The processor 100 may call program instructions in the memory 101 to perform the data splitting method for grayscale distribution of the above-described embodiments.
Further, the program instructions in the memory 101 may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product.
The memory 101, which is a computer-readable storage medium, may be used for storing software programs, computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 100 executes functional applications and data processing, i.e., implements the data splitting method for gray scale distribution in the above-described embodiments, by executing program instructions/modules stored in the memory 101.
The memory 101 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. In addition, the memory 101 may include a high-speed random access memory, and may also include a nonvolatile memory.
According to the data distribution device for gray scale release provided by the embodiment of the disclosure, by acquiring the node serial number, the user data serial number and the gray scale release serial number, the node type corresponding to the node serial number is determined according to the gray scale release serial number, the user data type corresponding to the user data serial number is determined according to the node serial number, and then data distribution is performed according to the node type and the user data type; the data distribution is not needed to be carried out in a mode of manually configuring nodes in the gray level publishing process, the data distribution efficiency is improved, and the user experience in the gray level publishing process is improved.
The device provided by the embodiment of the disclosure comprises the data shunting device for gray scale distribution.
Optionally, the device is a server, a computer, or the like.
The device provided by the embodiment of the disclosure determines a node type corresponding to a node serial number by acquiring the node serial number and a user data serial number, determines a user data type corresponding to the user data serial number, and then performs data distribution according to the node type and the user data type; the data distribution is not needed to be carried out in a mode of manually configuring nodes in the gray level publishing process, the data distribution efficiency is improved, and the user experience in the gray level publishing process is improved.
The disclosed embodiments provide a computer-readable storage medium storing computer-executable instructions configured to perform the above-described method for data streaming provision for grayscale publishing.
The present disclosure provides a computer program product including a computer program stored on a computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to execute the above-described data splitting method for gray scale distribution.
The computer-readable storage medium described above may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.
The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium comprising: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes, and may also be a transient storage medium.
The above description and drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising an …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosures, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.
Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units may be merely a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to implement the present embodiment. In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (10)
1. A data distribution method for gray scale release is characterized by comprising the following steps:
acquiring a node serial number and a user data serial number;
determining a node type corresponding to the node serial number;
determining a user data type corresponding to the user data serial number;
and carrying out data distribution according to the node type and the user data type.
2. The method of claim 1, wherein determining the node type corresponding to the node sequence number comprises:
determining the node type corresponding to the node serial number meeting the first preset condition as a gray node; and/or the presence of a gas in the gas,
and determining the node type corresponding to the node serial number which does not meet the first preset condition as a non-gray node.
3. The method according to claim 2, wherein the determining the node type corresponding to the node sequence number satisfying the first preset condition as a gray node comprises:
acquiring a gray release serial number;
and determining the node type corresponding to the node serial number which is the same as the gray release serial number as a gray node.
4. The method according to claim 2, wherein the determining the node type corresponding to the node sequence number that does not satisfy the first preset condition as a non-gray node comprises:
acquiring a gray release serial number;
and determining the node type corresponding to the node serial number different from the gray release serial number as a non-gray node.
5. The method of claim 2, wherein determining the user data type corresponding to the user data sequence number comprises:
determining the user data type corresponding to the user data serial number meeting the second preset condition as gray user data; and/or the presence of a gas in the gas,
and determining the user data type corresponding to the user data serial number which does not meet the second preset condition as non-gray user data.
6. The method according to claim 5, wherein the determining the user data type corresponding to the user data serial number satisfying the second preset condition as the grayscale user data comprises:
acquiring a gray node serial number;
and determining the user data type corresponding to the user data serial number which is the same as the gray node serial number as gray user data.
7. The method according to claim 5, wherein the determining the user data type corresponding to the data sequence number that does not satisfy the second preset condition as the non-grayscale user data comprises:
acquiring a gray node serial number;
and determining the user data type corresponding to the user data serial number different from the gray node serial number as non-gray user data.
8. The method of claim 5, wherein the data splitting according to the node type and the user data type comprises:
sending the gray-scale user data to the gray-scale nodes; and/or sending the non-grayscale user data to the non-grayscale node.
9. A data splitting apparatus for gray scale distribution, comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the data splitting method for gray scale distribution according to any one of claims 1 to 8 when executing the program instructions.
10. An apparatus comprising the data splitting device for gray scale distribution according to claim 9.
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