CN113568917B - Data ranking method and device, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure provides a data ranking method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The data ranking method comprises the following steps: acquiring user area position information and user initial data; generating user ranking list coding data based on the user area position information, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data; and responding to the selection operation of the idle node list, establishing a ranking list data pulling process, and acquiring user ranking data through the ranking list data pulling process so as to return the user ranking data to the client. According to the technical scheme, reading and writing of the ranking list data can be separated, ranking efficiency of initial data of a user and reading efficiency of ranking data of the user are improved, and reliability of a server is improved.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a data ranking method, a data ranking apparatus, an electronic device, and a computer-readable storage medium.
Background
With the rapid development of the internet, electronic athletic activities are increasingly abundant. In various electronic athletic activities, it is necessary to rank the user initial data according to different administrative region levels, and how to provide an efficient and reliable region ranking method becomes a problem to be solved in the current electronic athletic activities.
In the related regional ranking method, regional ranking is performed based on either single server nodes or distributed server nodes. However, for the conventional single-server node, the user initial data is regional ranked through a single process of the server side, so that the operation amount of the server is large, and the efficiency of ranking the user initial data and the reliability of the server are low due to the limited memory of the server. For the distributed server node, ranking is needed to be performed on initial data of a user through a ranking list center process, ranking list data is fed back to a client where the user is located, load burden of the ranking list center process is large, probability of failure of the ranking list center process is high, and data reading and writing efficiency is low.
It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
An object of the embodiments of the present disclosure is to provide a data ranking method, a data ranking apparatus, an electronic device, and a computer readable storage medium, so as to overcome the problems of a higher load of a ranking list process and lower data reading and writing efficiency to at least a certain extent.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to a first aspect of embodiments of the present disclosure, there is provided a data ranking method, including: acquiring user area position information and user initial data; generating user ranking list coding data based on the user area position information, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data; generating an idle node list and sending the idle node list to a client; and responding to the selection operation of the idle node list, establishing a ranking list data pulling process, and acquiring the user ranking data through the ranking list data pulling process so as to return the user ranking data to the client.
In some example embodiments of the present disclosure, based on the foregoing, the generating the user leaderboard encoded data based on the user area location information includes: obtaining a standard region coding statistical table, and matching a user region position code corresponding to the user region position information from the standard region coding statistical table; acquiring a historical ranking list data table of the user area position codes through the ranking list data pulling process, and determining a historical period number corresponding to the user area position codes based on the historical ranking list data table; and calculating the current period number of the user area position code based on the historical period number, and generating the user ranking list coding data based on the user area position code and the current period number.
In some example embodiments of the present disclosure, based on the foregoing, the user ranking data is obtained by ordering the user initial data in a skip list data structure in the key value database table.
In some example embodiments of the present disclosure, based on the foregoing solution, the user initial data includes user identification data, and the obtaining the user ranking data through the leaderboard data pulling process includes: analyzing the user ranking list coding data through the ranking list data pulling process to obtain the user region position code and the current period number corresponding to the user ranking list coding data; if the leaderboard data pulling process detects a cache leaderboard data table corresponding to the user area position code and the current period number, acquiring current time data and life period data of the cache leaderboard data table; and if the ranking list data pulling process detects that the current time data is smaller than or equal to the life cycle data, matching the user ranking data corresponding to the user identification data from the cache ranking list data table.
In some example embodiments of the disclosure, based on the foregoing scheme, the method further comprises: and if the cache ranking list data table does not exist, acquiring the ranking list data table corresponding to the user ranking list coding data from the key value database, and caching the ranking list data table.
In some example embodiments of the disclosure, based on the foregoing scheme, the method further comprises: acquiring a target time stamp of the updated ranking list data table; in response to receiving the leaderboard data table update request, detecting whether a timestamp of the received update request is equal to or greater than the target timestamp; if the timestamp is detected to be equal to or larger than the target timestamp, calculating a target period number of the user area position code, and updating the user ranking list code data according to the target period number to obtain target user ranking list code data; and inserting the user update data in the update request into a key value database table corresponding to the target user ranking list coding data, and ranking the user update data in the key value database table to realize the update of the user ranking data.
In some example embodiments of the disclosure, based on the foregoing scheme, the method further comprises: generating an idle node set in real time, and detecting whether a fault node set exists in the idle node set; if the fault node set exists in the idle node set, deleting the fault node set from the idle node set to obtain a target idle node set; and updating the idle node list according to the target idle node set.
According to a second aspect of embodiments of the present disclosure, there is provided a data ranking apparatus comprising:
the data acquisition module is used for acquiring the user area position information and the user initial data; the ranking list coding data generation module is used for generating user ranking list coding data based on the user area position information, inserting the user initial data into a key value database table corresponding to the user ranking list coding data, and ranking the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data; the system comprises an idle node list sending module, a client and a server, wherein the idle node list sending module is used for generating an idle node list and sending the idle node list to the client; and the data pulling process establishing module is used for responding to the selection operation of the idle node list, establishing a ranking list data pulling process, and acquiring the user ranking data through the ranking list data pulling process so as to return the user ranking data to the client.
In some example embodiments of the present disclosure, based on the foregoing solution, the chart code data generating module further includes a chart code generating unit, where the chart code generating unit is configured to obtain a standard area code statistics table, and match a user area position code corresponding to the user area position information from the standard area code statistics table; acquiring a historical ranking list data table of the user area position codes through the ranking list data pulling process, and determining a historical period number corresponding to the user area position codes based on the historical ranking list data table; and calculating the current period number of the user area position code based on the historical period number, and generating the user ranking list coding data based on the user area position code and the current period number.
In some example embodiments of the present disclosure, based on the foregoing solution, the ranking list encoding data generating module further includes a data inserting unit, where the data inserting unit is configured to insert the user initial data into the key value database table to obtain the user ranking data; user ranking data is obtained by ordering the user initial data in the key value database table in a skip list data structure.
In some example embodiments of the present disclosure, based on the foregoing solutions, the data ranking apparatus further includes a user ranking data obtaining module, where the user ranking data obtaining module is configured to parse the user ranking list encoded data through the ranking list data pulling process to obtain the user region position code and the current period number corresponding to the user ranking list encoded data; if the leaderboard data pulling process detects a cache leaderboard data table corresponding to the user area position code and the current period number, acquiring current time data and life period data of the cache leaderboard data table; and if the ranking list data pulling process detects that the current time data is smaller than or equal to the life cycle data, matching the user ranking data corresponding to the user identification data from the cache ranking list data table.
In some example embodiments of the present disclosure, based on the foregoing solution, the data pulling process building module further includes a data detection unit, where the data detection unit is configured to detect, by the leaderboard pulling node, whether the cached leaderboard data table exists, and if the leaderboard data pulling process detects that the cached leaderboard data table does not exist, obtain, from the key database, a leaderboard data table corresponding to the user leaderboard encoded data, and cache the leaderboard data table.
In some example embodiments of the present disclosure, based on the foregoing, the data ranking apparatus further includes a user ranking data updating module for obtaining a target timestamp to update the leaderboard data table; in response to receiving the leaderboard data table update request, detecting whether a timestamp of the received update request is equal to or greater than the target timestamp; if the timestamp is detected to be equal to or larger than the target timestamp, calculating a target period number of the user area position code, and updating the user ranking list code data according to the target period number to obtain target user ranking list code data; and inserting the user update data in the update request into a key value database table corresponding to the target user ranking list coding data, and ranking the user update data in the key value database table to realize the update of the user ranking data.
In some example embodiments of the present disclosure, based on the foregoing solution, the data ranking apparatus further includes an idle node update module, where the idle node update module is configured to generate an idle node set in real time, and detect whether a faulty node set exists in the idle node set; if the fault node set exists in the idle node set, deleting the fault node set from the idle node set to obtain a target idle node set; and updating the idle node list according to the target idle node set.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory having stored thereon computer readable instructions that when executed by the processor implement the data ranking method of any one of the above.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a data ranking method according to any one of the above.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
the data ranking method in the example embodiment of the disclosure obtains user area location information and user initial data; generating user ranking list coding data based on the user area position information, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data; generating an idle node list, and sending the idle node list to a client; and responding to the selection operation of the idle node list, establishing a ranking list data pulling process, and acquiring user ranking data through the ranking list data pulling process so as to return the user ranking data to the client. On one hand, by generating the user ranking list coding data and inserting the user initial data of different area positions into the key value database table corresponding to the user ranking list coding data, the scattered ranking of the user initial data is realized, the aggregation ranking of the user initial data through a single process is avoided, the load burden of a server is relieved, and the reliability of the server is improved; on the other hand, ranking the user initial data through a key value database table corresponding to the user ranking list coding data, so that parallel ranking of the user initial data at different region positions is realized, and ranking efficiency of the user initial data is improved; in still another aspect, the user initial data is written into the key value database table through the server process corresponding to the user login client, and the user ranking data is read through the ranking list data pulling process, so that the data reading and writing separation is realized, and the computing capacity of the server and the data redundancy capacity are improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort. In the drawings:
FIG. 1 schematically illustrates a schematic diagram of a data ranking method flow according to some embodiments of the present disclosure;
FIG. 2 schematically illustrates a schematic diagram of a user leaderboard encoding data generation method flow according to some embodiments of the present disclosure;
FIG. 3 schematically illustrates a schematic diagram of a user ranking data acquisition method flow according to some embodiments of the present disclosure;
FIG. 4 schematically illustrates a schematic diagram of a user ranking data updating method flow according to some embodiments of the present disclosure;
FIG. 5 schematically illustrates a schematic diagram of a free node list update method flow according to some embodiments of the present disclosure;
FIG. 6 schematically illustrates a schematic diagram of a data ranking apparatus according to some embodiments of the present disclosure;
FIG. 7 schematically illustrates a structural schematic diagram of a computer system of an electronic device, in accordance with some embodiments of the present disclosure;
fig. 8 schematically illustrates a schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure.
In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
Moreover, the drawings are only schematic illustrations and are not necessarily drawn to scale. The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
In the present exemplary embodiment, a data ranking method is first provided, which may be applied to a distributed server cluster. Fig. 1 schematically illustrates a schematic diagram of a data ranking method flow according to some embodiments of the present disclosure. Referring to fig. 1, the data ranking method may include the steps of:
step S110, obtaining user area position information and user initial data;
step S120, generating user ranking list coding data based on the user area position information, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data;
Step S130, an idle node list is generated and sent to a client; and
step S140, in response to the selection operation on the free node list, establishes a ranking list data pulling process, and obtains the user ranking data through the ranking list data pulling process, so as to return the user ranking data to the client.
According to the data ranking method in the present exemplary embodiment, on one hand, by generating the user ranking list coding data, the user initial data in different areas are inserted into the key value database table corresponding to the user ranking list coding data, so that the scattered ranking of the user initial data is realized, the aggregation ranking of the user initial data through a single process is avoided, the load burden of the server is reduced, and the reliability of the server is improved; on the other hand, ranking the user initial data through a key value database table corresponding to the user ranking list coding data, so that parallel ranking of the user initial data in different areas is realized, and the ranking efficiency of the user initial data is improved; in still another aspect, the user initial data is written into the key value database table through the server process corresponding to the user login client, and the user ranking data is read through the ranking list data pulling process, so that the data reading and writing separation is realized, and the computing capacity of the server and the data redundancy capacity are improved.
Next, a data ranking method in the present exemplary embodiment will be further described.
In step S110, user area location information and user initial data are acquired.
In an example embodiment of the present disclosure, the user area location information may refer to area location information of a user participating in a game play, for example, the user area location information may be area geographical location information of a user logging in a game page, or may be target area location information of a user applying for game ranking, for example, after the user participates in the game play in area a to obtain a game score, the user applies for querying ranking data of the game score in area B, and of course, the user area location information may also be area location information of other users participating in the game play, where this embodiment is not limited in particular.
The user initial data may refer to data related to the user game play, for example, the user initial data may be account data and game score of the user, nickname of the user, game level data, virtual gold coin data of the user, virtual energy data of the user, or other data related to the user game play, such as virtual equipment data, which is not limited in this embodiment.
After a user logs in a game account and enters a game state, acquiring user area position information through an LBS SDK (Lacation Based Service Soft Development Kit, software development kit based on position service) on a user interface, and sending the user area position information to a server, wherein the server converts the user area position information into user area position code data corresponding to the user position information according to a national unified standard area code statistical table; the server may refer to a server that establishes communication connection with a client that a user logs in. Of course, the user area location information may be converted into the user area location code data corresponding to the user location information at the client according to the national unified standard area code statistics table, which is not limited in this embodiment.
In step S120, user ranking list encoding data is generated based on the user region position information, and the user initial data is inserted into a key value database table corresponding to the user ranking list encoding data, so that the user initial data is ranked in the key value database table, and user ranking data corresponding to the user initial data is obtained.
In an example embodiment of the present disclosure, the user ranking list encoding data may refer to encoding data for distinguishing between different user area location codes and game play ranking periods, for example, the user ranking list encoding data may be encoding data composed of a user area location code and a game play ranking period number, or the user ranking list encoding data may be encoding data composed of a user area location code, a game play ranking period number, and a game name, although the user ranking list encoding data may also be encoding data composed of other data for distinguishing between different user area location codes and game play ranking periods, which is not particularly limited in this example embodiment.
The key-value database table may refer to a database table for storing user initial data of the same user area location code, for example, the key-value database table may be a key-value database based on Redis (remote dictionary service), a key-value database based on Nosql (non-relational database), a key-value database based on Riak (distributed database), or a database table based on other database designs, which is not limited in this embodiment. The user ranking data may refer to the user's ranking data.
The server sends a request for obtaining a key value database table corresponding to the user ranking list coding data to the distributed server cluster, the distributed server cluster can inquire whether the key value database table corresponding to the user ranking list coding data exists from a respective database or a memory after receiving the request, if the key value database table corresponding to the user ranking list coding data exists, the key value database table is returned to the server, the server caches the key value database table, inserts user initial data into the key value database table, and ranks the user initial data. Because different users log in different clients, the corresponding servers of the different clients all cache the key value database table, thereby realizing the duplication of the key value database table and improving the disaster recovery capability of the initial data and the ranking list data table of the users.
In step S130, a free node list is generated and sent to the client.
In an example embodiment of the present disclosure, the free node list may refer to a list for counting free node information in the distributed service cluster, for example, the free node list may be a list for recording identification data of the free node, the free node list may also be a list for recording an available memory size of the free node, and the free node list may also be a list for recording information such as a first address and a length of an available memory of the free node.
The server side can acquire idle node information in the distributed server cluster in real time and update an idle node list; and if the fault node exists in the idle node list, deleting the fault node in the idle node list, and sending the idle node list containing the idle nodes in a normal state to the client so that a user can select one idle node from the idle node list. After the idle node selected by the user is detected, a ranking list data pulling process is established, so that user ranking data is obtained from a cache or a key value database table through the ranking list data pulling process, the reading efficiency of the user ranking data is improved, and the utilization rate of the idle node in the distributed service cluster is also improved.
In step S140, in response to the selection operation on the free node list, a ranking list data pulling process is established, and the user ranking data is obtained through the ranking list data pulling process, so as to return the user ranking data to the client.
In one example embodiment of the present disclosure, the leaderboard data pulling process may refer to a process for reading a leaderboard data table corresponding to user leaderboard encoded data. The idle node list can be sent to the client, when the selection operation of the user on the idle node list is detected, a target idle node is obtained by matching from the idle node list, a ranking list data pulling process is established based on the target idle node according to the available memory information of the target idle node in the idle node list, so that a ranking list data table is obtained from a cache or a key value database corresponding to user ranking list coding data through the ranking list data pulling process, and user ranking data corresponding to a user account is obtained by matching from the ranking list data table according to the identification data of the user such as the user account.
The method comprises the steps of generating an idle node list, sending the idle node list to a client to detect selection operation of a user on the idle node list, determining a target idle node from the idle node list, and establishing a ranking list data pulling process according to memory information and the like of the target idle node in the idle node list so as to read a ranking list data table from a cache of a server or a key value database corresponding to user ranking list coding data; the possibility that different users select the same idle node is reduced, the capacity bottleneck of the idle node is avoided, the high availability of the idle node is guaranteed, a plurality of users are supported to acquire user ranking data in parallel, and online capacity expansion for reading the user ranking data is realized.
Fig. 2 schematically illustrates a schematic diagram of a user leaderboard coded data generation method flow according to some embodiments of the present disclosure. Referring to fig. 2, the method for generating user leaderboard coded data may include the steps of:
in step S210, a standard region coding statistical table is obtained, and a user region position code corresponding to the user region position information is matched from the standard region coding statistical table;
In step S220, a history ranking list data table of the user area position code is obtained through the ranking list data pulling process, and a history period number corresponding to the user area position code is determined based on the history ranking list data table;
in step S230, a current period number of the user area position code is calculated based on the history period number, and the user leaderboard code data is generated based on the user area position code and the current period number.
The standard region coding statistics table may refer to a standard mapping table between region position information and region position coding data. The user region position code may refer to a region position code corresponding to the user region position information in the standard region code statistics table. The historical ranking list data table may refer to a ranking list data table for counting the histories corresponding to the same user ranking list code data, for example, the historical ranking list data table may be a ranking list data table of ranking list data with a smaller settlement period number than that of the current settlement period number for the same game play corresponding to the same user ranking list code data, for example, the current settlement period number of the game play is 3, the historical ranking list data table may be ranking list data with a settlement period number of 2 for the game play, and of course, the historical ranking list data table may also be ranking list data tables corresponding to a plurality of other historical settlement period numbers corresponding to the same user ranking list code data under the condition of the same game play.
The history period number may refer to a settlement period number corresponding to the history ranking list data table, for example, the history period number may be a settlement period number corresponding to a season of the history game play, or may be a settlement period number corresponding to a session of the history game play, or may be any other settlement period number corresponding to the history ranking list data table, which is not particularly limited in this embodiment. The current period number may refer to a period number for settling the leaderboard data of the current game play.
Preferably, the pulling process of the ranking list data table can query a historical ranking list data table corresponding to the user area position code from the key value database table according to the user area position code, further obtain a historical period number corresponding to the historical ranking list data table, calculate the current period number based on the historical period number when detecting that the historical period number is the latest period number of the history, if adding one on the basis of the historical period number to obtain the current period number, thereby determining the current user game ranking list code data based on the user area position code and the current period number, inserting the user initial data into the key value database table corresponding to the user ranking list code data to rank the user initial data, or obtain the ranking list data table from the key value database table or a cache of a node corresponding to the ranking list data pulling process according to the ranking list code data after game competition is finished, and match the user ranking list data from the ranking list data table according to the user identification data.
Alternatively, the current cycle number may be calculated by formula (1).
n＝(t n -t 0 )/h (1)
Wherein n may represent the current period number, t n Can represent the current period start time stamp, t 0 The reference period start time stamp may be represented and h may represent time interval data of a single game play settlement period.
For example, the single-shot settlement period of a game play is 1 hour, i.e., the user ranking of the game play is settled every 1 hour, and the reference period start time stamp of the game play is 00:00:00 each day, and the current period start time stamp is 02:00:00. Meanwhile, the current cycle start time stamp can be converted into a time stamp in seconds, for example, the time interval between 02:00:00 and 00:00:00 is 7200 seconds, and the time interval corresponding to the user ranking every 1 hour is 3600 seconds, and the current cycle number is 2 can be calculated according to the above formula (1). Furthermore, the user ranking list coding data can be obtained through the current period number and the user area position coding, so that the user initial data can be inserted into the key value database table to rank the user initial data according to the user ranking list coding data, and the user ranking data of the current user can be queried according to the user ranking list coding data after the user initial data is ranked.
In example embodiments of the present disclosure, user initial data may be inserted into a key-value database table corresponding to user leaderboard coded data, and user ranking data may be obtained by sorting the user initial data in a skip list data structure in the key-value database table.
The user initial data can be inserted into the key value database table corresponding to the user ranking list coding data, and the user initial data is sorted and stored in a skip list structure, so that the situation that the whole key value database table needs to be traversed when the user ranking data is queried is avoided, and the query efficiency of the user ranking data is improved.
For example, the user initial data may be stored and ranked in a Zset structure based on the Redis database, for example, the user initial data of the same user ranking list encoded data is inserted into the same key value database table, and the inserted user initial data, for example, the user game scores, are arranged in order from small to large to obtain a data set S, and s= {20, 25, 33, 45, 66, 74, 76, 85, 96, 125, 130}, the node index of each element in the S set is established, and the nodes are randomly extracted from the S set to be used as a first-layer sparse index, for example, the node corresponding to 25, 74, 85, 125 is extracted from the S set to be used as a first-layer sparse index, and the node corresponding to 25, 85 is extracted from the first-layer sparse index to be used as a node corresponding to a second-layer sparse index, that is, the current key value database table may be a database containing two-layer sparse indexes and one-layer original data. If the user game score is 66, the data interval between 25 and 85 of the 66 can be obtained by searching in the second layer sparse index, the data interval between 25 and 74 of the 66 can be obtained by entering the first layer sparse index, and then the index of 66 can be found in the user score sorting of the base layer, and further the ranking data of 66 can be obtained.
Fig. 3 schematically illustrates a schematic diagram of a user ranking data acquisition method flow according to some embodiments of the present disclosure. Referring to fig. 3, the user ranking data acquiring method may include the steps of:
in step S310, the user ranking list coding data is parsed by the ranking list data pulling process, so as to obtain the user region position code and the current period number corresponding to the user ranking list coding data;
in step S320, if the leaderboard data pulling process detects a cache leaderboard data table corresponding to the user area position code and the current period number, current time data and life period data of the cache leaderboard data table are obtained;
in step S330, if the leaderboard data pulling process detects that the current time data is less than or equal to the life cycle data, the user ranking data corresponding to the user identification data is obtained by matching from the cache leaderboard data table.
The current time data may refer to time data of the current server. The lifecycle data may refer to time data corresponding to an effective cache of the leaderboard data table. The ranking list data table may refer to ranking list data corresponding to the same user ranking list encoding data, for example, the ranking list data table may be a data table containing user ranking data corresponding to the same user ranking list encoding data, and of course, the ranking list data table may also be a data table containing other information of the user, which is not limited in particular in this embodiment. The user identification data may refer to identification data for distinguishing different user identities, for example, the user identification data may be account data of a user or nickname data of the user, and of course, the user identification data may also be other identification data for distinguishing different user identities, which is not limited in particular in this embodiment.
Analyzing the user ranking list coding data through the ranking list data pulling process to obtain a user region position code and a current period number, inquiring whether a caching ranking list data table corresponding to the user region position code and the current period number exists in the ranking list pulling process according to the user region position code and the current period number, detecting whether the caching ranking list data table is out of date if the caching ranking list data table corresponding to the user region position code and the current period number exists in the ranking list data pulling process, and if the effective caching deadline corresponding to the caching ranking list data table is longer than the current time data, the caching ranking list data table is not out of date, and obtaining user ranking data by matching the caching ranking list data table according to user identification data. If the user ranking list is out of date with the ranking list data table, the cache ranking list data table can be deleted, the ranking list data table is obtained from the key value database table according to the user ranking list coding data, and the ranking list data table is cached in the memory again, so that other users can quickly obtain the user ranking data after selecting the same ranking list pulling process, and the load burden of the server is relieved by separating the uploading user initial data from the obtaining user ranking data.
In one example embodiment of the present disclosure, if the leaderboard data pulling process detects that there is no cached leaderboard data table, a leaderboard data table corresponding to the user leaderboard encoded data is obtained from the key value database table, and the leaderboard data table is cached.
The cache ranking list data table corresponding to the user area position code and the current period number can be detected through the ranking list data pulling process, if no cache ranking list data table exists, the ranking list data table corresponding to the user area position code and the current period number can be obtained from the key value database table according to the user area position code and the current period number, and the ranking list data table is cached into the memory corresponding to the ranking list pulling process, so that after other users select the same ranking list pulling process, the ranking list data of the users can be quickly obtained, the memory consumption of the server side for obtaining the initial data of the users is saved, and the running efficiency and reliability of the server side where the users are located are improved.
Fig. 4 schematically illustrates a schematic diagram of a user ranking data updating method flow according to some embodiments of the present disclosure. Referring to fig. 4, the user ranking data updating method may include the steps of:
In step S410, a target timestamp of updating the leaderboard data table is acquired;
in step S420, in response to receiving the leaderboard data table update request, detecting whether a timestamp of receiving the update request is equal to or greater than the target timestamp;
in step S430, if the timestamp is detected to be equal to or greater than the target timestamp, calculating a target period number of the user region position code, and updating the user ranking list code data according to the target period number to obtain target user ranking list code data;
in step S440, the user update data in the update request is inserted into a key value database table corresponding to the target user ranking list coding data, and the user update data is ranked in the key value database table, so as to update the user ranking data.
Wherein the target timestamp may refer to a timestamp that triggers an update of the leaderboard data table. The target period number data may refer to updated period code data, for example, the current period number is 2, the target period number may be a period number updated by the current period number, for example, a period number of period number 3, and of course, the target period number may also be a period number obtained by updating other period numbers.
The target user ranking list encoding data may refer to updated user ranking list encoding data, for example, the target user ranking list data may be user ranking list encoding data corresponding to the target period number, and of course, the target user ranking list encoding data may also be other updated user ranking list encoding data. The user update data may refer to updated user initial data, for example, the user update data may be a game score updated by the user, or may be data of a new client logged in by the user re-querying the ranking data, and of course, the user update data may also be other data updated by the user, for example, data corresponding to the location information of the area updated by the user, which is not limited in this embodiment.
The timer for updating the ranking list data table at fixed time can be set at the server, when the target time stamp is reached, the ranking list data table is triggered to be updated, and the target time stamp can correspond to time interval data of a single game play settlement period of the game play. When a leaderboard data table update request is received, determining whether a timestamp corresponding to the received leaderboard data table update request is equal to or greater than a target timestamp. If the time stamp corresponding to the ranking list data table updating request is equal to or greater than the target time stamp, calculating a target period number, updating the user ranking list coding data corresponding to the current ranking list data table based on the target period number, and inserting the user updating data into a key value database table corresponding to the target user ranking list coding data. If the timestamp of the update request of the ranking list data table is received, the user ranking list coding data corresponding to the current ranking list data table is not required to be updated, the original user initial data is only required to be removed from the key value database table corresponding to the current ranking list data table according to the user identification data, and the user update data is re-ranked, so that the real-time update of the ranking list data table and the user ranking data is realized, and the ranking accuracy of the user initial data is improved.
If the user update data contains the update of the user area position information, recoding the user area position information to obtain a target user area position code, detecting whether the timestamp corresponding to the received ranking list data table update request is equal to or greater than a target timestamp, if the timestamp corresponding to the ranking list data table update request is equal to or greater than the target timestamp, calculating a target period number, updating the user ranking list code data based on the target user area position code and the target period number to obtain target user ranking list code data, inserting the user update data into a key value database table corresponding to the target user ranking list code data, and re-ranking the user update data, thereby improving the real-time performance of the updated user ranking data and the authenticity of the user ranking data.
Fig. 5 schematically illustrates a schematic diagram of a free node list update method flow according to some embodiments of the present disclosure. Referring to fig. 5, the free node list updating method may include the steps of:
in step S510, an idle node set is generated in real time, and whether a fault node set exists in the idle node set is detected;
In step S520, if it is detected that a faulty node set exists in the idle node set, deleting the faulty node set from the idle node set to obtain a target idle node set;
in step S530, the list of idle nodes is updated according to the target set of idle nodes.
The idle node set may refer to a set corresponding to a stateless node in the distributed server cluster. A failed node set may refer to a set of nodes in a distributed server cluster that cannot respond to a client request. The target idle node set may refer to an idle node set obtained after the failure node set is removed from the idle node set.
Because each server in the distributed server cluster can communicate through a point-to-point protocol or a master-slave architecture, the acquisition of the idle node set in the distributed server cluster is convenient. After obtaining the idle node set, the server can detect whether a fault node set exists in the idle node set, if the fault node set exists in the idle node set, the fault node set in the idle node set is deleted to obtain a target idle node set, and the current idle node list is updated according to the target idle node set, so that real-time update of the idle node list is realized.
The method comprises the steps that a real-time updated idle node list is sent to a client side, so that the client side can select a target idle node from the idle node list, and a process is established based on the target idle node and used for pulling a ranking list data table. Because a plurality of idle nodes exist in the idle node list, the ranking list data pulling process is based on multi-node deployment, and the idle nodes in the idle node list are fault-free nodes, so that the client can acquire user ranking data in parallel and in real time, and the reliability of acquiring the user ranking data by the user is improved.
It should be noted that although the steps of the methods of the present disclosure are illustrated in the accompanying drawings in a particular order, this does not require or imply that the steps must be performed in that particular order or that all of the illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
In addition, in the present exemplary embodiment, a data ranking apparatus is also provided. Referring to fig. 6, the data ranking apparatus 600 includes: the system comprises a data acquisition module 610, a ranking list coding data generation module 620, an idle node list sending module 630 and a data pulling process establishment module 640. Wherein: a data acquisition module 610 for acquiring user area location information and user initial data; the ranking list encoding data generating module 620 generates user ranking list encoding data based on the user region position information, and inserts the user initial data into a key value database table corresponding to the user ranking list encoding data, so as to rank the user initial data in the key value database table, and obtain user ranking data corresponding to the user initial data; the idle node list sending module 630 generates an idle node list and sends the idle node list to the client; and the data pulling process establishing module 640 is used for establishing a ranking list data pulling process in response to the selection operation of the idle node list, and acquiring the user ranking data through the ranking list data pulling process so as to return the user ranking data to the client.
In some example embodiments of the present disclosure, based on the foregoing solution, the chart code data generating module 620 further includes a chart code generating unit, where the chart code generating unit is configured to obtain a standard area code statistics table, and match a user area position code corresponding to the user area position information from the standard area code statistics table; acquiring a historical ranking list data table of the user area position codes through the ranking list data pulling process, and determining a historical period number corresponding to the user area position codes based on the historical ranking list data table; and calculating the current period number of the user area position code based on the historical period number, and generating the user ranking list coding data based on the user area position code and the current period number.
In some example embodiments of the present disclosure, based on the foregoing solution, the ranking list encoding data generating module 620 further includes a data inserting unit, where the data inserting unit is configured to insert the user initial data into the key value database table to obtain the user ranking data; user ranking data is obtained by ordering the user initial data in the key value database table in a skip list data structure.
In some example embodiments of the present disclosure, based on the foregoing solution, the data ranking apparatus 600 further includes a user ranking data obtaining module, configured to parse the user ranking list encoded data through the ranking list data pulling process to obtain the user region position code and the current period number corresponding to the user ranking list encoded data; if the leaderboard data pulling process detects a cache leaderboard data table corresponding to the user area position code and the current period number, acquiring current time data and life period data of the cache leaderboard data table; and if the ranking list data pulling process detects that the current time data is smaller than or equal to the life cycle data, matching the user ranking data corresponding to the user identification data from the cache ranking list data table.
In some example embodiments of the present disclosure, based on the foregoing solution, the data pulling process establishing module 630 further includes a data detecting unit, where the data detecting unit is configured to detect, by the leaderboard pulling node, whether the cached leaderboard data table exists, and if the leaderboard data pulling process detects that the cached leaderboard data table does not exist, acquire, from the key database, the leaderboard data table corresponding to the user leaderboard encoded data, and cache the leaderboard data table.
In some example embodiments of the present disclosure, based on the foregoing, the data ranking apparatus 600 further includes a user ranking data updating module for obtaining a target timestamp of updating the ranking list data table; in response to receiving the leaderboard data table update request, detecting whether a timestamp of the received update request is equal to or greater than the target timestamp; if the timestamp is detected to be equal to or larger than the target timestamp, calculating a target period number of the user area position code, and updating the user ranking list code data according to the target period number to obtain target user ranking list code data; and inserting the user update data in the update request into a key value database table corresponding to the target user ranking list coding data, and ranking the user update data in the key value database table to realize the update of the user ranking data.
In some example embodiments of the present disclosure, based on the foregoing solution, the data ranking apparatus 600 further includes an idle node updating module, where the idle node updating module is configured to generate an idle node set in real time, and detect whether a faulty node set exists in the idle node set; if the fault node set exists in the idle node set, deleting the fault node set from the idle node set to obtain a target idle node set; and updating the idle node list according to the target idle node set.
The specific details of each module of the above data ranking device are described in detail in the corresponding data ranking method, so that the details are not repeated here.
It should be noted that although several modules or units of the data ranking apparatus are mentioned in the above detailed description, this division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above data ranking method is also provided.
Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.
An electronic device 700 according to such an embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is merely an example and should not be construed as limiting the functionality and scope of use of the disclosed embodiments.
As shown in fig. 7, the electronic device 700 is embodied in the form of a general purpose computing device. Components of electronic device 700 may include, but are not limited to: the at least one processing unit 710, the at least one storage unit 720, a bus 730 connecting the different system components (including the storage unit 720 and the processing unit 710), and a display unit 740.
Wherein the storage unit stores program code that is executable by the processing unit 710 such that the processing unit 710 performs steps according to various exemplary embodiments of the present disclosure described in the above-described "exemplary methods" section of the present specification. For example, the processing unit 710 may perform step S110 shown in fig. 1 to acquire user area location information and user initial data; step S120, generating user ranking list coding data based on the user area position information, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data; step S130, an idle node list is generated and sent to a client; step S140 establishes a leaderboard data pulling process in response to the selection operation on the free node list, and obtains the user ranking data through the leaderboard data pulling process, so as to return the user ranking data to the client.
The memory unit 720 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 721 and/or cache memory 722, and may further include Read Only Memory (ROM) 723.
The storage unit 720 may also include a program/utility 724 having a set (at least one) of program modules 725, such program modules 725 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 730 may be a bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 700 may also communicate with one or more external devices 770 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 700, and/or any device (e.g., router, modem, etc.) that enables the electronic device 700 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 750. Also, electronic device 700 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 760. As shown, network adapter 760 communicates with other modules of electronic device 700 over bus 730. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 700, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, a computer-readable storage medium having stored thereon a program product capable of implementing the method described above in the present specification is also provided. In some possible embodiments, the various aspects of the present disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.
Referring to fig. 8, a program product 800 for implementing the above-described data ranking method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
Furthermore, the above-described figures are only schematic illustrations of processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (9)
1. A method of ranking data, comprising:
acquiring user area position information and user initial data;
obtaining a standard region coding statistical table, and matching a user region position code corresponding to the user region position information from the standard region coding statistical table;
acquiring a historical ranking list data table of the user area position codes through a ranking list data pulling process, and determining a historical period number corresponding to the user area position codes based on the historical ranking list data table;
calculating the current period number of the user area position code based on the historical period number, generating user ranking list coding data based on the user area position code and the current period number, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data;
Generating an idle node list and sending the idle node list to a client; and
and responding to the selection operation of the idle node list, establishing a ranking list data pulling process, and acquiring the user ranking data through the ranking list data pulling process so as to return the user ranking data to the client.
2. The data ranking method of claim 1 wherein the user ranking data is obtained by ordering the user initial data in a skip list data structure in the key value database table.
3. The data ranking method of claim 1, wherein the user initial data comprises user identification data, the obtaining the user ranking data by the leaderboard data pulling process comprises:
analyzing the user ranking list coding data through the ranking list data pulling process to obtain the user region position code and the current period number corresponding to the user ranking list coding data;
if the leaderboard data pulling process detects a cache leaderboard data table corresponding to the user area position code and the current period number, acquiring current time data and life cycle data of the cache leaderboard data table;
And if the ranking list data pulling process detects that the current time data is smaller than or equal to the life cycle data, matching the user ranking data corresponding to the user identification data from the cache ranking list data table.
4. A data ranking method according to claim 3, characterized in that the method further comprises:
and if the cache ranking list data table does not exist, acquiring the ranking list data table corresponding to the user ranking list coding data from the key value database, and caching the ranking list data table.
5. The data ranking method of claim 1, wherein the method further comprises:
acquiring a target time stamp of the updated ranking list data table;
in response to receiving the leaderboard data table update request, detecting whether a timestamp of the received update request is equal to or greater than the target timestamp;
if the timestamp is detected to be equal to or larger than the target timestamp, calculating a target period number of the user area position code, and updating the user ranking list code data according to the target period number to obtain target user ranking list code data;
And inserting the user update data in the update request into a key value database table corresponding to the target user ranking list coding data, and ranking the user update data in the key value database table to realize the update of the user ranking data.
6. The data ranking method of claim 1, wherein the method further comprises:
generating an idle node set in real time, and detecting whether a fault node set exists in the idle node set;
if the fault node set exists in the idle node set, deleting the fault node set from the idle node set to obtain a target idle node set;
and updating the idle node list according to the target idle node set.
7. A data ranking apparatus, comprising:
the data acquisition module is used for acquiring the user area position information and the user initial data;
the ranking list coding data generation module is used for acquiring a standard region coding statistical table and matching a user region position code corresponding to the user region position information from the standard region coding statistical table; acquiring a historical ranking list data table of the user area position codes through a ranking list data pulling process, and determining a historical period number corresponding to the user area position codes based on the historical ranking list data table; calculating the current period number of the user area position code based on the historical period number, generating user ranking list coding data based on the user area position code and the current period number, and inserting the user initial data into a key value database table corresponding to the user ranking list coding data so as to rank the user initial data in the key value database table to obtain user ranking data corresponding to the user initial data;
The system comprises an idle node list sending module, a client and a server, wherein the idle node list sending module is used for generating an idle node list and sending the idle node list to the client; and
and the data pulling process establishing module is used for responding to the selection operation of the idle node list, establishing a ranking list data pulling process, and acquiring the user ranking data through the ranking list data pulling process so as to return the user ranking data to the client.
8. An electronic device, comprising:
a processor; and
a memory having stored thereon computer readable instructions which, when executed by the processor, implement the data ranking method of any one of claims 1 to 6.
9. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the data ranking method of any one of claims 1 to 6.
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