CN112650523B - Data distribution method, device and equipment for gray level release - Google Patents
Data distribution method, device and equipment for gray level release Download PDFInfo
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Abstract
The application relates to the technical field of computers and discloses a data distribution method for gray level release. 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. Determining a node type corresponding to the node sequence number by acquiring the node sequence number and the user data sequence number, determining a user data type corresponding to the user data sequence number, and carrying out data distribution according to the node type and the user data type; the gray level release is enabled to avoid data distribution in a mode of manually configuring nodes, and the data distribution efficiency is improved. The application also discloses a data distribution device and equipment for gray level release.
Description
Technical Field
The present invention relates to the field of computer technologies, and for example, to a data distribution method, device and equipment for gray level distribution.
Background
The nodes in the distributed application are more and more, and the distribution is more and more frequent. To ensure system stability, reduce impact on users, gray scale publishing is typically used to update nodes of an 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 release 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, and is intended to neither identify key/critical elements nor delineate the scope of such embodiments, but is intended as a prelude to the more detailed description that follows.
The embodiment of the disclosure provides a data distribution method, a data distribution device and data distribution equipment for gray level distribution, so that the data distribution efficiency can be improved.
In some embodiments, the data splitting method for gray scale distribution includes:
acquiring a node serial number and a user data serial number;
determining the 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 number of the groups of groups,
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 the gray node, the node type corresponding to the node serial number that satisfies the first preset condition includes:
acquiring a gray level 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 the non-gray node, the node type corresponding to the node serial number that does not satisfy the first preset condition includes:
acquiring a gray level release serial number;
and determining the node type corresponding to the node serial number which is 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 sequence 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 number of the groups of groups,
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 gray-scale user data, the user data type corresponding to the user data sequence 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-gray scale user data, the user data type corresponding to the user data sequence 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 which is different from the gray node serial number as non-gray user data.
In some embodiments, splitting data according to the node type and user data type comprises:
transmitting the gray scale user data to the gray scale node; and/or transmitting the non-gray scale user data to the non-gray scale node.
In some embodiments, the apparatus for gray scale distribution data distribution includes a processor and a memory storing program instructions, the processor being configured to perform the above-described data distribution method for gray scale distribution when executing the program instructions.
In some embodiments, the apparatus comprises the above-mentioned device for data splitting for gray scale distribution.
The data distribution method, the data distribution device and the data distribution equipment for gray level distribution, which are provided by the embodiment of the disclosure, can realize the following technical effects: determining a node type corresponding to the node sequence number by acquiring the node sequence number and the user data sequence number, determining a user data type corresponding to the user data sequence number, and carrying out data distribution according to the node type and the user data type; the data distribution is not needed in a mode of manually configuring the nodes, the data distribution efficiency is improved, and the user experience in the gray distribution 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 and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which like reference numerals refer to similar elements, and in which:
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 gray nodes and non-gray nodes provided by an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a method for automatically configuring a node provided by 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 techniques of the disclosed embodiments can be understood in more detail, a more particular description of the embodiments of the disclosure, briefly summarized below, may be had by reference to the appended drawings, which are not intended to be limiting of the embodiments of the disclosure. 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 still be practiced without these details. In other instances, well-known structures and devices may be shown simplified in order to simplify the drawing.
The terms first, second and the like in the description and in the claims of the embodiments of the disclosure and in the above-described figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe embodiments of the present disclosure. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion.
The term "plurality" means two or more, unless otherwise indicated.
In the embodiment of the present disclosure, the character "/" indicates that the front and rear objects are an or relationship. For example, A/B represents: a or B.
The term "and/or" is an associative relationship that describes an object, meaning that there may be three relationships. For example, a and/or B, represent: a or B, or, A and B.
Referring to fig. 1, an embodiment of the present disclosure provides a data splitting method for gray scale distribution, including:
step S101, obtaining 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 the user data type corresponding to the user data serial number;
step S104, data distribution is carried out according to the node type and the user data type.
By adopting the data distribution method for gray level release, which is provided by the embodiment of the invention, 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 carried out according to the node type and the user data type; the data distribution is not needed in a mode of manually configuring the nodes, the data distribution efficiency is improved, and the user experience in the gray distribution process is improved.
Optionally, the node serial number is the serial number of the node in the application; the node sequence numbers include gray node sequence numbers and non-gray node sequence numbers. The application to which the gradation release relates is a gradation application.
Optionally, the user data refers to data that generates interactions by the user terminal and the application in the server; the user data sequence number is used to distinguish the user data into greyscale user data and non-greyscale user data. In one-time gray level release, after upgrading part of nodes in the application, user data are required to be shunted and imported into the upgraded application nodes and the non-upgraded application nodes, so that one part of users start to experience the new version of the upgraded application and collect user satisfaction degree of the users on the new version, and the other part of users continue to use the old version; under the condition that the user satisfaction meets a third preset condition, upgrading the nodes of the rest sanitary-level applications so that another part of users also start to use the new version, and then ending the gray level release; and under the condition that the user satisfaction degree does not meet a third preset condition, rolling back the new version to the old version, and ending the gray release. Optionally, the third preset condition is satisfaction of more than 90% of users who use the new version.
Optionally, determining the node type corresponding to the node serial 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 publishing serial number and the node serial number of the node of the grayscale application are obtained by a server.
Optionally, the first preset condition is that the node serial number is the same as the gray release serial number; and (3) meeting a first preset condition, namely determining that the node type of the node corresponding to the node serial number is a gray level node from a preset node set under the condition that the node serial number is the same as the gray level release serial number. And if the first preset condition is not met, namely, if the node serial number is not equal to the gray release serial number, determining that the node type of the node corresponding to the node serial number is a non-gray node from a preset node set.
Optionally, determining the node type corresponding to the node serial number satisfying the first preset condition as the gray node includes: acquiring a gray level 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 scale release serial number is an identification of the number of gray scale release times. For example: in the case of gray level release for the first time, the gray level release serial number is 1; when the gray level release is carried out for the second time, adding 1 to the gray level release serial number, namely, the gray level release serial number of the second time gray level release is 2; when the gray level release is performed for the third time, the gray level release serial number 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 users.
In some embodiments, the gray release sequence number is 5, and if the node sequence number of a certain node in the gray application is 5, the gray release sequence 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 the node type corresponding to the node serial number that does not meet the first preset condition as a non-gray node includes: acquiring a gray level release serial number; and determining the node type corresponding to the node serial number which is different from the gray release serial number as a non-gray node.
In some embodiments, the gray release sequence number is 5, and if the node sequence number of a certain node in the gray application is 4, the gray release sequence number is different from the node sequence number, and the node type of the node is determined to be a non-gray node.
Optionally, determining the user data type corresponding to the user data sequence 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 sequence number of the user data and the node sequence number of the node of the greyscale application are obtained by a server.
Optionally, the second preset condition is that the user data sequence number is the same as the gray node sequence number; and (3) meeting a first preset condition, namely determining the type of the user data corresponding to the user data serial number as gray-scale user data under the condition that the user data serial number is the same as the gray-scale node serial number. And if the second preset condition is not met, namely, if the user data serial number is different from the gray node serial number, determining that the type of the user data corresponding to the user data serial number is non-gray user data.
Optionally, determining the user data type corresponding to the user data sequence number satisfying the second preset condition as gray user data 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.
Optionally, after determining the gray node and the non-gray node in the gray application, the node serial number of the gray node, that is, the gray node serial number, is obtained by the server.
In some embodiments, the gray node sequence number is 5, and if the user data sequence number of a certain user data is 5, the user data sequence number is the same as the gray node sequence 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 sequence number that does not meet the second preset condition as non-gray scale user data includes: acquiring a gray node serial number; and determining the user data type corresponding to the user data serial number which is different from the gray node serial number as non-gray user data.
In some embodiments, the gray node sequence number is 5, the user data sequence number of a certain user data is 4, the user data sequence number is different from the gray node sequence number, and the type of the user data is determined to be non-gray user data.
Optionally, the data splitting is performed according to the node type and the user data type, including: transmitting the gray user data to the gray node; and/or transmitting the non-gray scale user data to the non-gray scale node.
Optionally, the gray node and the non-gray node are tested through the test data, after the test data are sent to the gray node and the non-gray node, the test data are monitored, and the gray user data are sent to the gray node and the non-gray user data are sent to the non-gray node under the condition that the test data are normally operated without errors.
In some embodiments, a user upgrades a certain application deployed in a server during one gray level publication; firstly, upgrading a certain node in the application to a new version, and updating the node serial number of the upgraded node to enable the node serial number of the node to be the same as the gray release serial number of the current time; then the server obtains the gray release sequence number of the gray release, the node sequence numbers of all nodes and the user data sequence 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 sequence numbers are the same as the gray release sequence numbers, the type of the node corresponding to the node sequence numbers is determined to be the gray nodes, and under the condition that the node sequence numbers are different from the gray release sequence numbers, the type of the node corresponding to the node sequence numbers is determined to be the non-gray nodes; after determining which gray nodes and non-gray nodes from a preset node set, acquiring gray node serial numbers 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 gray level nodes, so that the part of users can use the updated new version application; and sending the determined non-gray scale user data to the non-gray scale nodes so that the part of users continue to use the old version application. In this way, the nodes are divided into the gray level nodes and the non-gray level nodes through the node serial numbers, and the user data is divided into the gray level user data and the non-gray level user data through the user data serial numbers, so that the error rate of manually configuring the gray level nodes and the non-gray level nodes is reduced, the data distribution efficiency is improved, and the user experience in the gray level release process is also improved.
Optionally, whether the application is the application related to the gray release is determined by judging whether the node serial numbers of all the nodes of the application in the server are the same. Under the condition that node serial numbers of all nodes in the application are the same, determining the application as the application which is not involved in the gray release at the time, namely, the non-gray application; in case the node release numbers of all nodes in the application have two different values, the application is determined to be the application involved in the present gray release, i.e. the gray application.
In some embodiments, after determining the gray application and the non-gray application, acquiring a gray release sequence number, a user data sequence number, and node sequence numbers of all nodes in the gray application; for example: gray release serial number 24, two user data serial numbers 23 and 24, two node serial numbers 23 and 24; comparing and judging the node serial numbers of all nodes of the gray application with the gray release serial numbers; in the case where the node serial number of a certain node is the same as the gradation release serial number, for example: the node release number of a certain node is 24, and the gray release serial number is 24, and the node type of the node corresponding to the node serial number is determined to be a gray node; in the case where the node serial number is not identical to the gradation release serial number, for example: and 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 the gray node and the non-gray node are determined, gray node serial numbers of the gray node are obtained, and all user data serial numbers are compared with the gray release serial numbers for judgment; in the case where the user data sequence number is the same as the gray node sequence number, for example: the user data serial number is 24, and the gray node serial number is 24, determining the type of the user data corresponding to the user data serial number as gray user data; in the case that the user data sequence number is not identical to the gray 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 transmits different user data to different nodes for data distribution according to the judging result, namely, gray user data is transmitted to gray nodes and non-gray data is transmitted to non-gray nodes. In this way, the nodes are divided into the gray level nodes and the non-gray level nodes through the node serial numbers, and the user data are divided into the gray level user data and the non-gray level user data through the user data serial numbers, so that the error rate of manually configuring the gray level nodes and the non-gray level nodes is reduced, the data distribution efficiency is improved, and the user experience in the gray level release process is also improved.
In some embodiments, after the server sends the gray level user data to the gray level node, user satisfaction of the user for the updated new version application is obtained, and under the condition that the user satisfaction meets a third preset condition, the rest non-gray level nodes in the gray level application are updated, so that the gray level release is completed. Optionally, the third preset condition is that the user satisfaction is satisfied by more than 90% of users in the gray scale user data.
Optionally, under the condition that the user satisfaction degree does not meet the preset condition, rolling back the updated new version application to the old version, and waiting for the next gray level release.
For internet products, gray level distribution is a division of black and white between online and offline, gray level is literally understood to be a smooth transition region between black and white, and one way to achieve smooth transition of offline function is called gray level distribution. Non-black, i.e. white, is never a common phenomenon, and from a color perspective, 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 98% of this intermediate value is gray. Because the Internet product has the characteristics of large user scale, frequent version update and the like. Each time a new version of an application product is put on line, the application product bears extremely high pressure, and gray level release well avoids the risk. Gray release products can extract a portion of users in a number of forms, such as selecting VIP users, or selecting active users; these users are divided into two batches, one batch for release A version of the application product and the other batch for release B version of the application product. The record work is collected for various possible data before the delivery, so that two versions of user data feedback can be checked after the delivery, and a large amount of data analysis and investigation are used for determining which version to use finally for the delivery update. In general, a complete set of gray level release is needed to identify the necessary user, i.e. distinguish the users; such as from the number of payments or the region and the activity level, and the aim of such differentiation is to allow a more accurate analysis of the data.
Optionally, a complete set of gray scale distribution mechanisms would include: user identification, target user screening or traffic screening, real-time data monitoring, gray scale publishing or rollback. Wherein the user identification: the method mainly distinguishes users and assists in data analysis at the same time; target user screening or traffic screening is: the consistency of user characteristics, user flow, user range and user experience is required to be referred, version iteration is carried out on all users or part of users, and a small flow test is carried out through re-discharge, so that users are generally screened according to the sequence of internal users, seed users, active users and all users, and the method is typical range control, and the experience consistency requirement considers whether the span of new and old versions is overlarge or not and whether the users can accept or not; and (3) real-time data monitoring: monitoring data such as stability of a new version, stability of a server, use times, use frequency and the like, and comparing the data with original data; gray scale release or rollback: and issuing the application product or rolling back the application product according to the data feedback result. By adopting a gray level release mode, the risk of full online of new version of an application product can be effectively avoided, and the problems in the product can be found, adjusted and optimized in a gray level stage by adopting a small flow verification mode, so that smooth iteration is realized, and the update of the application product can be more in line with the requirements of users; meanwhile, all relevant data are collected, such as stability of a new version, stability and use times of a server, use frequency and various data, so that comparison with original data can be facilitated; the aim of the method is to know the most realistic user experience, effectively prevent the generation of major BUG, influence system gear return or cause more unnecessary economic losses, so that gray release is an effective method for effectively avoiding the online risk of a new version, test work can be performed through small flow, and smooth iteration of the new version is helped.
As shown in connection with fig. 2, an embodiment of the present disclosure provides a method of 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 an application;
step S202, judging whether the gray release serial number is the same as the node serial number; if yes, the gray release serial number is the same as the node serial number, then executing step S203; if not, that is, the gray release serial number is different from the node serial number, executing 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 gray nodes and non-gray nodes from a preset node set of the application; gray user data satisfying the first preset condition, and user data types not satisfying the first preset condition are non-gray user data; the first preset condition is: the grayscale distribution sequence number is the same as the node sequence number.
By dividing the nodes into gray nodes and non-gray nodes, a small part of users can use the updated 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 updated new version application can effectively avoid the risk of full online of the new version application, and the new version of the application can be iterated smoothly.
As shown in conjunction with fig. 3, an embodiment of the present disclosure provides a method for automatically configuring a node, including:
step S301, a gray node serial number and a user data serial number are obtained;
step S302, judging whether the user data serial number is the same as the gray node serial number, if so, namely, if so, executing step S303; if not, executing step S304 if the user data sequence number is different from the gray node sequence number;
step S303, determining the user data type corresponding to the user data serial number as gray user data, and sending the gray user data to a gray node;
step S304, the user data type corresponding to the user data serial number is determined to be non-gray user data, and the non-gray user data is sent to the non-gray node.
Determining gray level nodes and non-gray level nodes according to a first preset condition, determining gray level user data and non-gray level user data according to a second preset condition, and sending the gray level user data to the gray level nodes and the non-gray level user data to the non-gray level nodes; therefore, the gray level nodes and the non-gray level nodes are judged, the user data are distributed automatically, the whole gray level distribution process does not need to be manually participated, the data distribution efficiency is improved, the error probability of gray level distribution is reduced, and the user experience in the gray level distribution process is improved.
As shown in connection with fig. 4, an embodiment of the present disclosure provides an apparatus for implementing gray scale distribution, including a processor (processor) 100 and a memory (memory) 101 storing program instructions. Optionally, the apparatus may further comprise 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 the bus 103. The communication interface 102 may be used for information transfer. The processor 100 may call the program instructions in the memory 101 to perform the data splitting method for gray scale distribution of the above-described embodiment.
Further, the program instructions in the memory 101 described above may be implemented in the form of software functional units and sold or used as a separate product, and may be stored in a computer-readable storage medium.
The memory 101 is a computer readable storage medium that can be used to store a software program, a computer executable program, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 100 executes the functional application and the data processing by executing the program instructions/modules stored in the memory 101, i.e., implements the data distribution method for gradation distribution in the above-described embodiment.
The memory 101 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created according to the use of the terminal device, etc. Further, 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 level distribution, the node type corresponding to the node sequence number is determined according to the gray level distribution sequence number by acquiring the node sequence number, the user data sequence number and the gray level distribution sequence number, the user data type corresponding to the user data sequence number is determined according to the node sequence number, and data distribution is performed according to the node type and the user data type; the data distribution is not needed in a mode of manually configuring the nodes, the data distribution efficiency is improved, and the user experience in the gray distribution process is improved.
The embodiment of the disclosure provides a device, which comprises the data distribution device for gray scale release.
Alternatively, the device is a server, computer, or the like.
The device provided by the embodiment of the disclosure determines the node type corresponding to the node sequence number by acquiring the node sequence number and the user data sequence number, determines the user data type corresponding to the user data sequence number, and performs data distribution according to the node type and the user data type; the data distribution is not needed in a mode of manually configuring the nodes, the data distribution efficiency is improved, and the user experience in the gray distribution 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 splitting provision for gray scale distribution.
The disclosed embodiments provide a computer program product comprising a computer program stored on a computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the data distribution method for grey scale distribution described above.
The computer readable storage medium may be a transitory computer readable storage medium or a non-transitory computer readable storage medium.
Embodiments of the present disclosure may be embodied in a software product stored on a storage medium, including one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of a method according to embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium including: a plurality of media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or a transitory storage medium.
The above description and the drawings illustrate embodiments of the disclosure sufficiently to enable those skilled in the art to practice them. Other embodiments may involve structural, logical, electrical, process, and other changes. The embodiments represent only 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. Moreover, the terminology used in the present application is for the purpose of describing embodiments only and is not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a," "an," and "the" (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, when used in this application, the terms "comprises," "comprising," and/or "includes," and variations thereof, mean that the stated features, integers, steps, operations, elements, and/or components are present, but that the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof is not precluded. Without further limitation, an element defined by the phrase "comprising one …" does not exclude the presence of other like elements in a process, method or apparatus comprising such elements. In this context, each embodiment may be described with emphasis on the differences from the other embodiments, and the same similar parts between the various embodiments may be referred to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method sections disclosed in the embodiments, the description of the method sections may be referred to for relevance.
Those of skill in the art will 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 depends upon the particular application and design constraints imposed on the solution. The skilled artisan may use different methods for each particular application to achieve the described functionality, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the embodiments disclosed herein, the disclosed methods, articles of manufacture (including but not limited to devices, apparatuses, etc.) may be practiced in other ways. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the units may be merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form. The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to implement the present embodiment. In addition, each functional unit in the embodiments of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The flowcharts 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 that disclosed in the description, and sometimes no specific order exists between different operations or steps. For example, two consecutive operations or steps may actually be performed substantially in parallel, they may sometimes be performed in reverse order, which may be dependent on the functions involved. Each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (3)
1. A data distribution method for gray scale distribution, comprising:
acquiring a node serial number and a user data serial number;
determining the node type corresponding to the node serial number;
determining a user data type corresponding to the user data serial number;
performing data distribution according to the node type and the user data type;
determining the node type corresponding to the node serial number comprises the following steps: acquiring a gray level release serial number; determining the node type corresponding to the node serial number which is the same as the gray release serial number as a gray node; determining the node type corresponding to the node serial number which is different from the gray release serial number as a non-gray node;
determining the user data type corresponding to the user data serial number comprises the following steps: acquiring a gray node serial number; 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; determining the user data type corresponding to the user data serial number which is different from the gray node serial number as non-gray user data;
and carrying out data distribution according to the node type and the user data type, wherein the data distribution comprises the following steps: transmitting the gray scale user data to the gray scale node; and/or transmitting the non-gray scale user data to the non-gray scale node.
2. A data splitting device for grey scale distribution comprising a processor and a memory storing program instructions, wherein the processor is configured to perform the data splitting method for grey scale distribution of claim 1 when executing the program instructions.
3. A data distribution device for gradation distribution, characterized by comprising the data distribution apparatus for gradation distribution as claimed in claim 2.
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