CN112015732A - Sorting method, sorting device, electronic equipment and storage medium - Google Patents
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Abstract
The invention relates to a sorting method, a sorting device, electronic equipment and a storage medium, wherein the method comprises the following steps: the method comprises the steps of obtaining first dimension data of a plurality of objects to be sorted based on a first preset dimension, obtaining second dimension data of the plurality of objects to be sorted based on a second preset dimension, combining the first dimension data and the second dimension data of each object to be sorted to obtain a reference score corresponding to each object to be sorted, and sorting the plurality of objects to be sorted according to the reference scores. The embodiment of the invention can realize the sequencing of the objects to be sequenced based on the dimension data corresponding to the multiple preset dimensions, and the data of one dimension of the reference score is obtained by combining the first dimension data and the second dimension data of the multiple dimensions, so that the sequencing of the objects to be sequenced based on the reference score can be realized conveniently by utilizing a redis ordered set, the sequencing speed is high, and the requirement of high-concurrency row layout is met.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a sorting method and apparatus, an electronic device, and a storage medium.
Background
With the development of the internet, the ranking list function is applied to various services at present. For the functional requirements of the ranking list, storage is generally implemented by using Remote Dictionary service (Remote Dictionary Server, Redis) and the like, and the ordered set (sorted set) in the Redis can quickly implement the ranking list function based on the score (score) of the ranking object.
At present, many leaderboards may need to be ranked based on multiple dimensions, but the ordered set of redis cannot be ranked for multiple dimensions. The relational database can quickly realize the sequencing of multiple dimensions by using the index, but the response speed of the database relative to a data structure memory based on a memory such as redis is much slower, and the database is not suitable for high concurrent ranking list requirements.
Disclosure of Invention
In order to solve the technical problem or at least partially solve the technical problem, the application provides a sorting method, a sorting device, an electronic device and a storage medium.
In a first aspect, the present application provides a ranking method, including:
acquiring first dimension data of a plurality of objects to be sorted based on a first preset dimension;
acquiring second dimension data of a plurality of objects to be sorted based on a second preset dimension, wherein the first preset dimension is different from the second preset dimension;
for each object to be sorted, combining the first dimensional data and the second dimensional data to obtain a reference score corresponding to each object to be sorted;
and sequencing the plurality of objects to be sequenced according to the reference scores.
Optionally, the combining, for each object to be sorted, the first dimensional data and the second dimensional data to obtain a reference score corresponding to each object to be sorted includes:
determining priorities corresponding to the first preset dimension and the second preset dimension according to a preset corresponding relationship of the dimension priorities;
if the priority of the first preset dimension is higher than that of the second preset dimension, determining the first dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the second dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score; or if the priority of the first preset dimension is lower than the priority of the second preset dimension, determining the second dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the first dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score;
and respectively calculating the reference scores corresponding to the objects to be sorted based on the high-order data and the low-order data for each object to be sorted.
Optionally, the calculating, for each object to be sorted, the reference score corresponding to the object to be sorted based on the high-order data and the low-order data includes:
determining a first sorting order of first dimension data of a plurality of objects to be sorted and a second sorting order of second dimension data of the plurality of objects to be sorted;
determining whether the first sort order and the second sort order are the same;
if the first sorting sequence is the same as the second sorting sequence, shifting the high-order data according to a preset offset to obtain a first intermediate score;
and adding the first intermediate score and the low-level data to obtain the reference score.
Optionally, the calculating, for each object to be sorted, the reference score corresponding to the object to be sorted based on the high-order data and the low-order data further includes:
if the first sorting sequence is different from the second sorting sequence, shifting the high-order data according to a preset offset to obtain a first intermediate score;
subtracting a preset maximum value of the low bit data from the low bit data to obtain a second intermediate fraction;
and adding the first intermediate score and the second intermediate score to obtain the reference score.
Optionally, the method further includes:
judging whether the first dimension data and the second dimension data are both of digital types;
if the first dimension data and the second dimension data are both of a digital type, a step of combining the first dimension data and the second dimension data for each object to be sorted to obtain a reference score corresponding to each object to be sorted is executed;
if the first dimension data and/or the second dimension data are not in a digital type, converting the first dimension data and/or the second dimension data into the digital type according to a preset rule, and executing a step of combining the first dimension data and the second dimension data aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted.
Optionally, the converting the first dimension data and/or the second dimension data into a digital type according to a preset rule includes:
searching a numerical value corresponding to the first dimensional data or the second dimensional data in a preset corresponding relation between the dimensional data and the numerical value;
determining the value as the new first dimension data or the second dimension data.
Optionally, the converting the first dimension data and/or the second dimension data into a digital type according to a preset rule includes:
extracting one or more reference elements from a plurality of elements contained in the first dimension data and/or the second dimension data;
searching a numerical value corresponding to the reference element in a preset corresponding relationship of element numerical values to obtain a numerical value corresponding to one or more reference elements;
calculating one or more numerical values according to a preset operation mode to obtain a calculation result;
and determining the calculation result as the new first dimension data or the second dimension data.
In a second aspect, the present application provides a sorting apparatus comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring first dimension data of a plurality of objects to be sorted based on a first preset dimension;
the second acquisition module is used for acquiring second dimension data of a plurality of objects to be sorted based on a second preset dimension, wherein the first preset dimension is different from the second preset dimension;
the combination module is used for combining the first dimensional data and the second dimensional data aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted;
and the sorting module is used for sorting the plurality of objects to be sorted according to the reference scores.
Optionally, the combination module includes:
a first determining unit, configured to determine priorities corresponding to the first preset dimension and the second preset dimension according to a preset dimension priority correspondence;
a second determining unit, configured to determine the first dimension data as high-order data corresponding to a plurality of preset high-order data bits of the reference score and determine the second dimension data as low-order data corresponding to a plurality of preset low-order data bits of the reference score if the priority of the first preset dimension is higher than the priority of the second preset dimension; or if the priority of the first preset dimension is lower than the priority of the second preset dimension, determining the second dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the first dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score;
and the first calculation unit is used for calculating the reference scores corresponding to the objects to be sorted respectively based on the high-order data and the low-order data for each object to be sorted.
Optionally, the first computing unit includes:
the first determining subunit is used for determining a first ordering order of first dimension data of a plurality of objects to be ordered and a second ordering order of second dimension data of the plurality of objects to be ordered;
a second determining subunit operable to determine whether the first sorting order and the second sorting order are the same;
the first shifting subunit is configured to shift the high-order data according to a preset offset to obtain a first intermediate score if the first sorting order is the same as the second sorting order;
and the first summation subunit is used for adding the first intermediate score and the low-level data to obtain the reference score.
Optionally, the first computing unit further includes:
the second shifting subunit is used for shifting the high-order data according to a preset offset to obtain a first intermediate score if the first sorting order is different from the second sorting order;
the difference making subunit is used for making a difference between a preset low-order maximum value and the low-order data to obtain a second intermediate fraction;
and the second summation subunit is used for adding the first intermediate score and the second intermediate score to obtain the reference score.
Optionally, the apparatus further comprises:
the judging module is used for judging whether the first dimension data and the second dimension data are both of digital types;
the execution module is used for combining the first dimension data and the second dimension data aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted if the first dimension data and the second dimension data are of a digital type;
and the conversion execution module is used for converting the first dimension data and/or the second dimension data into a digital type according to a preset rule if the first dimension data and/or the second dimension data are not in the digital type, and executing a step of combining the first dimension data and the second dimension data for each object to be sorted to obtain a reference score corresponding to each object to be sorted.
Optionally, the conversion executing module includes:
the first searching unit is used for searching a numerical value corresponding to the first dimensional data or the second dimensional data in a preset corresponding relation between the dimensional data and the numerical value;
a third determining unit, configured to determine the value as the new first dimension data or the second dimension data.
Optionally, the conversion executing module includes:
an extracting unit, configured to extract one or more reference elements from a plurality of elements included in the first dimension data and/or the second dimension data;
the second searching unit is used for searching a numerical value corresponding to the reference element in a preset corresponding relation of the numerical values of the elements to obtain a numerical value corresponding to one or more reference elements;
the second calculation unit is used for calculating one or more numerical values according to a preset operation mode to obtain a calculation result;
a fourth determining unit, configured to determine the calculation result as the new first dimension data or the second dimension data.
In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete mutual communication through the communication bus;
a memory for storing a computer program;
a processor configured to implement the sorting method according to any one of the first aspect when executing a program stored in a memory.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a sorting method program which, when executed by a processor, implements the steps of the sorting method of any one of the first aspects.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages:
according to the embodiment of the invention, first dimension data of a plurality of objects to be sorted can be obtained based on a first preset dimension, second dimension data of the plurality of objects to be sorted can be obtained based on a second preset dimension, the first preset dimension is different from the second preset dimension, the first dimension data and the second dimension data are combined aiming at each object to be sorted, a reference score corresponding to each object to be sorted is obtained, and finally the plurality of objects to be sorted can be sorted according to the reference scores.
According to the embodiment of the invention, the first dimension data and the second dimension data are combined, and the objects to be sorted are sorted according to the reference scores obtained after combination, so that the objects to be sorted are sorted based on the dimension data corresponding to a plurality of preset dimensions, and the data of one dimension of the reference scores is obtained by combining the first dimension data and the second dimension data of a plurality of dimensions, so that the objects to be sorted based on the reference scores can be sorted conveniently by utilizing a redis ordered set, the sorting speed is high, and the requirement of high-concurrence row layout is met.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a flowchart of a sorting method according to an embodiment of the present application;
FIG. 2 is a flowchart of step S103 in FIG. 1;
FIG. 3 is a flowchart of step S203 in FIG. 2;
fig. 4 is another flowchart of a sorting method according to an embodiment of the present application;
FIG. 5 is a flowchart of step S403 in FIG. 4;
FIG. 6 is a flowchart of step S403 in FIG. 4;
fig. 7 is a structural diagram of a sorting apparatus according to an embodiment of the present application;
fig. 8 is a block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
At present, many leaderboards may need to be ranked based on multiple dimensions, but the ordered set of redis cannot be ranked for multiple dimensions. The relational database can quickly realize the sequencing of multiple dimensions by using the index, but the response speed of the database relative to a data structure memory based on a memory such as redis is much slower, and the database is not suitable for high concurrent ranking list requirements. To this end, an embodiment of the present invention provides a sorting method, an apparatus, an electronic device, and a storage medium, where the sorting method may be applied in a server, as shown in fig. 1, and the sorting method may include the following steps:
step S101, acquiring first dimension data of a plurality of objects to be sorted based on a first preset dimension;
in the embodiment of the present invention, the first preset dimension may refer to one of two dimensions for sorting, such as: integration and the like, the object to be sorted is the object needing sorting, such as: user name, topic, etc., the first dimension data may refer to first dimension data of the object to be sorted, corresponding to a first preset dimension, such as: if the integral of the user 001 is 99, the first dimension data of the user 001 is 99;
in this step, first dimension data of a plurality of objects to be sorted about a first preset dimension may be acquired, such as: first dimension data "99" of "user 001" with respect to "integral" of a first preset dimension is acquired, "first dimension data" 97 "of" user 002 "with respect to" integral "of the first preset dimension is acquired," first dimension data "90" … … of "user 003" with respect to "integral" of the first preset dimension is acquired.
In practical application, a database table for storing and recording first dimension data of a plurality of objects to be sorted may be obtained, and the first dimension data of the plurality of objects to be sorted is extracted from the database table.
Step S102, second dimension data of a plurality of objects to be sorted are obtained based on a second preset dimension, and the first preset dimension is different from the second preset dimension;
in the embodiment of the present invention, the second preset dimension may refer to the other dimension of the two dimensions for sorting, such as: amount of consumption, etc., and the second dimension data may refer to second dimension data of the object to be sorted corresponding to a second preset dimension, such as: if the consumption amount of the user 001 is 500, the second-dimension data of the user 001 is 500;
in this step, second dimension data of a plurality of objects to be sorted about a second preset dimension may be obtained, such as: second-dimension data "500" of "user 001" with respect to "spending amount" in the second preset dimension is acquired, "second-dimension data" 300 "of" user 002 "with respect to" spending amount "in the second preset dimension is acquired," second-dimension data "200" … … of "user 003" with respect to "spending amount" in the second preset dimension is acquired.
In practical application, a database table for storing and recording second dimension data of a plurality of objects to be sorted may be obtained, and the second dimension data of the plurality of objects to be sorted is extracted from the database table.
Step S103, aiming at each object to be sorted, combining the first dimensional data and the second dimensional data to obtain a reference score corresponding to each object to be sorted;
in the embodiment of the present invention, the first dimension data and the second dimension data may be combined into one data, and the combined data is the reference score.
For example: the first dimension data is 97, the second dimension data is 300, and the data obtained by combining the first dimension data and the second dimension data can be 97300 in one case, so that 97300 is the reference score.
And step S104, sequencing the objects to be sequenced according to the reference scores.
In this step, the plurality of objects to be sorted may be sorted according to the order of the reference scores, for example, the corresponding relationship pair formed by the reference scores and the objects to be sorted may be stored in a redis ordered set, the reference scores may be sorted by using a sorting mechanism of the redis ordered set, and then, the objects to be sorted corresponding to the reference scores may be sorted.
For example: if the reference score of the object 01 to be sorted is 87600, the reference score of the object 02 to be sorted is 69343, and the reference score of the object 03 to be sorted is 99999, then the objects to be sorted are sorted in the descending order of the reference scores: object to be sorted 03 → object to be sorted 01 → object to be sorted 02; the sequencing objects are sequenced from small to large according to the reference scores as follows: object to be sorted 02 → object to be sorted 01 → object to be sorted 03.
According to the embodiment of the invention, first dimension data of a plurality of objects to be sorted can be obtained based on a first preset dimension, second dimension data of the plurality of objects to be sorted can be obtained based on a second preset dimension, the first preset dimension is different from the second preset dimension, the first dimension data and the second dimension data are combined aiming at each object to be sorted, a reference score corresponding to each object to be sorted is obtained, and finally the plurality of objects to be sorted can be sorted according to the reference scores.
According to the embodiment of the invention, the first dimension data and the second dimension data are combined, and the objects to be sorted are sorted according to the reference scores obtained after combination, so that the objects to be sorted are sorted based on the dimension data corresponding to a plurality of preset dimensions, and the data of one dimension of the reference scores is obtained by combining the first dimension data and the second dimension data of a plurality of dimensions, so that the objects to be sorted based on the reference scores can be sorted conveniently by utilizing a redis ordered set, the sorting speed is high, and the requirement of high-concurrence row layout is met.
Based on the foregoing embodiment, since there is a certain difference between the influence of the high data and the low data on the value of the reference score, and the influence of the high data on the value of the reference score is greater than the influence of the low data on the value of the reference score, in another embodiment of the present invention, as shown in fig. 2, the step S103 may include the following steps:
step S201, determining priorities corresponding to the first preset dimension and the second preset dimension according to a preset dimension priority corresponding relation;
in the embodiment of the present invention, a corresponding relationship between preset dimensions and priorities may be preset, the preset dimension that needs to have a greater influence on the reference score in actual application is set as a high priority, and the preset dimension that has a smaller influence on the reference score is set as a low priority, for example, the corresponding relationship between the dimensions and priorities may be as shown in table 1 below:
TABLE 1
| Predetermined dimension | Priority (in order from high to low hereinafter) |
| Integration | 3 |
| Amount of consumption | 2 |
| Occupation of the world | 1 |
In this step, a priority corresponding to the first preset dimension and a priority corresponding to the second preset dimension may be respectively looked up in table 1.
For example: if the first preset dimension is the integral, the priority corresponding to the first preset dimension is 3, if the second preset dimension is the consumption amount, the priority corresponding to the second preset dimension is 2, and if the 3-degree is higher than the 2-degree, the priority of the first preset dimension is higher than the priority of the second preset dimension.
Step S202, if the priority of the first preset dimension is higher than the priority of the second preset dimension, determining the first dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the second dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score; or if the priority of the first preset dimension is lower than the priority of the second preset dimension, determining the second dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the first dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score;
in the embodiment of the present invention, a high data bit range and a low data bit range may be divided in advance for the reference score setting, the high data bit range includes a plurality of high data bits, the low data bit range includes a plurality of low data bits, data corresponding to the high data bit range is determined as high data bits, and data corresponding to the low data bit range is determined as low data bits.
In practical application, the score type of Redis adopts double, 64-bit double precision floating point number with 52-bit significant number, which can accurately express the integer range of-2 ^53 to 2^53, and can only express 16 decimal integers at most, so that 16 data bits can be divided in advance to obtain a high data bit range and a low data range, such as: the high 8 bits are high data bit range, the low 8 bits are low data bit range, the data corresponding to the high 8 bits are high data, and the data corresponding to the low 8 bits are low data; such as: the upper 6 bits are high data bit range, the lower 10 bits are low data bit range, the data corresponding to the upper 6 bits are high data, and the data corresponding to the lower 10 bits are low data.
In this step, dimension data corresponding to a preset dimension with a higher priority among the first preset dimension and the second preset dimension is determined as higher data, and dimension data corresponding to a preset dimension with a lower priority among the first preset dimension and the second preset dimension is determined as lower data.
Step S203, for each object to be sorted, calculating the reference score corresponding to the object to be sorted based on the high-order data and the low-order data, respectively.
In this step, the high-order data and the low-order data of each object to be sorted may be calculated to obtain a reference score of each object to be sorted.
According to the embodiment of the invention, through the priority levels, the dimensional data which needs to have a large influence on the reference score is determined as the high-order data, and the dimensional data which has a relatively small influence on the reference score is determined as the low-order data, so that the finally determined reference score can be ensured to be more accurate and is closer to the actual requirement.
In another embodiment of the present invention, as shown in fig. 3, the step S203 may include the steps of:
step S301, determining a first sorting order of first dimension data of a plurality of objects to be sorted and a second sorting order of second dimension data of the plurality of objects to be sorted;
in practical applications, the first dimension data and the second dimension data of a plurality of objects to be sorted stored in the database table are generally arranged according to a certain order, such as: the order of the first dimension data and the second dimension data of the plurality of objects to be sorted extracted from the database table can be determined in this step.
For example, a plurality of first dimension data corresponding to a plurality of objects to be sorted in a database table may be sequentially read, the first read first dimension data is compared with the second read first dimension data, if the first read first dimension data is greater than the second read first dimension data, it may be determined that the plurality of objects to be sorted are sorted in a descending order, and the first sorting order is descending;
if the first read-out first dimension data is smaller than the second read-out first dimension data, then the plurality of objects to be sorted can be determined to be sorted from small to large, and the first sorting order is from small to large;
if the first read-out dimension data is equal to the second read-out dimension data, the third first dimension data can be continuously read, the second read-out dimension data is compared with the third read-out dimension data, the first sorting order is obtained by referring to the comparison rule, and similarly, the second sorting order can be obtained.
Step S302, determining whether the first sorting order and the second sorting order are the same;
if the first sorting order is from small to large and the second sorting order is from large to small, it can be determined that the first sorting order is different from the second sorting order;
if the first sorting order and the second sorting order are both from small to large, or the first sorting order and the second sorting order are both from large to small, it may be determined that the first sorting order is the same as the second sorting order.
Step S303, if the first sorting order is the same as the second sorting order, shifting the high-order data according to a preset offset to obtain a first intermediate score;
in the embodiment of the present invention, a preset offset may be preset, where the preset offset may be calculated according to the number of preset low data bits, and the number of the preset low data bits is the number of low data bits included in the low data bit range, for example: if the number of the predetermined low data bits is 4 bits, the predetermined offset is 10^4 ^ 10000, and if the number of the predetermined low data bits is 8 bits, the predetermined offset is 10^8 ^ 100000000.
If the upper data bit 432 has a predetermined offset of 10000, the first intermediate score is 432 × 10000, which is 4320000.
Step S304, adding the first intermediate score to the low-level data to obtain the reference score.
If the low data is 9876, 4320000+9876 is 4329876.
According to the embodiment of the invention, the reference score can be calculated under the condition that the first sequencing sequence is the same as the second sequencing sequence, the calculation process is simple and quick, and the reference score can be conveniently and quickly obtained.
In another embodiment of the present invention, as shown in fig. 3, the step S203 may further include the steps of:
step S305, if the first sorting sequence is different from the second sorting sequence, shifting the high-order data according to a preset offset to obtain a first intermediate score;
illustratively, if the upper data bit 432 has a predetermined offset of 10000, the first intermediate score is 432 × 10000 — 4320000.
Step S306, subtracting a preset low-order maximum value from the low-order data to obtain a second intermediate fraction;
in the embodiment of the present invention, the preset offset may be reduced by one, so as to obtain the preset lower maximum value, for example, the preset offset is 10000, and the preset lower maximum value is 9999.
In this step, the low data may be directly subtracted from the preset maximum low data to obtain the second intermediate score.
Illustratively, assuming the predetermined lower maximum value is 9999 and the lower data bits are 3762, the second intermediate score is 6237.
Step S307, adding the first intermediate score and the second intermediate score to obtain the reference score.
Illustratively, 4320000+6237 is 4326237, and 4326237 is the calculated reference score.
According to the embodiment of the invention, the reference score can be calculated under the condition that the first sorting sequence is different from the second sorting sequence, the calculation process is simple, and the reference score can be conveniently and quickly obtained.
In yet another embodiment of the present invention, as shown in fig. 4, the method further comprises:
step S401, judging whether the first dimension data and the second dimension data are both digital types;
if the first dimensional data and the second dimensional data are both of a digital type, step S402, a step of combining the first dimensional data and the second dimensional data for each object to be sorted to obtain a reference score corresponding to each object to be sorted;
if the first dimension data and/or the second dimension data are not in a digital type, step S403, converting the first dimension data and/or the second dimension data into a digital type according to a preset rule, and executing a step of combining the first dimension data and the second dimension data for each object to be sorted to obtain a reference score corresponding to each object to be sorted.
According to the embodiment of the invention, when the first dimension data and the second dimension data are both in a digital type, the first dimension data and the second dimension data can be automatically combined, and when the first dimension data and/or the second dimension data are not in the digital type, the first dimension data and/or the second dimension data which are not in the digital type can be automatically converted into the digital type, so that the first dimension data and the second dimension data can be conveniently combined to obtain the reference score, the method is suitable for more application scenes, the conversion process is simple, and the reference score can be quickly and accurately obtained in more application scenes.
In practical applications, the first dimension data or the second dimension data may be names of people, professions, interests, levels of examination results, or names of things, and the like, and since the first dimension data and the second dimension data cannot be directly combined to obtain the reference score, as shown in fig. 5, in another embodiment of the present invention, the step S403 includes:
step S501, searching a numerical value corresponding to the first dimensional data or the second dimensional data in a preset corresponding relation between the dimensional data and the numerical value;
in the embodiment of the present invention, the corresponding relationship between the dimension data and the numerical value may be preset as shown in the following tables 2 and 3:
TABLE 2
TABLE 3
| Name (R) | Numerical value |
| A+ | 100 |
| A | 99 |
| A- | 98 |
For example, the first dimension data of the objects to be sorted is not a number type, where the name of a certain object to be sorted 1111 is lie four, the value 10 may be found in the corresponding relationship of table 2, and then 10 may be combined with the second dimension data (assumed as a number type) of the object to be sorted 1111.
For another example, the second dimension data of the objects to be sorted is not a number type, wherein the name of the examination result level of a certain object to be sorted 1222 is a +, then the value 100 can be found in the corresponding relationship of table 3, and then 100 and the first dimension data (assumed as a number type) of the object to be sorted can be combined.
When the first dimension data and the second dimension data are not in the digital type, the corresponding numerical values can be searched in the corresponding relations respectively according to the above modes, and the two numerical values are combined.
Step S502, determining the value as the new first dimension data or the second dimension data.
According to the embodiment of the invention, when the dimension data is of a non-digital type, the numerical values corresponding to the dimension data are searched in the corresponding relation, so that the numerical values can be automatically combined to obtain the reference score, the conversion process is simple, and the reference score can be quickly and accurately obtained in more application scenes.
In practical applications, the first dimension data or the second dimension data may be names of people, professions, interests, levels of examination results, or names of things, and the like, and since the first dimension data and the second dimension data cannot be directly combined to obtain the reference score, as shown in fig. 6, in another embodiment of the present invention, the step S403 includes:
step S601, extracting one or more reference elements from a plurality of elements included in the first dimension data and/or the second dimension data;
in this embodiment of the present invention, the first dimension data may include a plurality of elements, and the second dimension data may also include a plurality of elements, for example: when the first dimension data is a name, each word in the name is an element.
In this step, one or more reference elements may be extracted in the first dimension data and/or the second dimension data that are not of the numeric type.
Such as: if the first dimension data is not of a numeric type and the second dimension data is of a numeric type, one or more reference elements may be extracted from the first dimension data, such as: the first dimension data is 'Wangwu-Wuyi', and reference elements 'Wang' can be extracted from 'Wangwu-Wuyi', and reference elements 'Wang', 'Wu' and 'one' can also be extracted.
Such as: if the first dimension data is of a numeric type and the second dimension data is not of a numeric type, one or more reference elements may be extracted from the second dimension data, such as: the second dimension data is "Zhao Liu III", and reference elements "three" can be extracted from "Zhao Liu III", and also reference elements "Zhao", and "six" can be extracted, and the like.
Such as: if the first dimension data is not of a numeric type and the second dimension data is not of a numeric type, one or more reference elements may be extracted from the first dimension data and the second dimension data, respectively, such as: the first dimension data is 'Wangwu-one', the reference element 'Wang' can be extracted from 'Wangwu-one', and the reference elements 'Wang', 'five' and 'one' can also be extracted; the second dimension data is "Zhao Liu III", and reference elements "three" can be extracted from "Zhao Liu III", and also reference elements "Zhao", and "six" can be extracted, and the like.
Step S602, searching a numerical value corresponding to the reference element in a preset element numerical value corresponding relation to obtain a numerical value corresponding to one or more reference elements;
in this step, the correspondence between the elements and the numerical values may be set in advance as shown in table 4 below:
TABLE 4
| Element(s) | Numerical value |
| King (Chinese character of 'Wang') | 16 |
| Zhao (Zhao) | 78 |
| III | 43 |
Step S603, calculating one or more numerical values according to a preset operation mode to obtain a calculation result;
in the embodiment of the present invention, the preset operation manner may be a calculation manner such as summation.
Step S604, determining the calculation result as the new first dimension data or the second dimension data.
According to the embodiment of the invention, when the dimension data is of a non-digital type, the reference elements are extracted, and the numerical values corresponding to the reference elements are searched in the corresponding relation, so that the numerical values can be automatically combined to obtain the reference score, the conversion process is simple, and the reference score can be quickly and accurately obtained in more application scenes.
In still another embodiment of the present invention, there is also provided a sorting apparatus, as shown in fig. 7, including:
the first obtaining module 11 is configured to obtain first dimension data of a plurality of objects to be sorted based on a first preset dimension;
a second obtaining module 12, configured to obtain second dimension data of a plurality of objects to be sorted based on a second preset dimension, where the first preset dimension is different from the second preset dimension;
the combination module 13 is configured to combine the first dimensional data and the second dimensional data for each object to be sorted, so as to obtain a reference score corresponding to each object to be sorted;
and the sorting module 14 is configured to sort the plurality of objects to be sorted according to the reference scores.
Optionally, the combination module includes:
a first determining unit, configured to determine priorities corresponding to the first preset dimension and the second preset dimension according to a preset dimension priority correspondence;
a second determining unit, configured to determine the first dimension data as high-order data corresponding to a plurality of preset high-order data bits of the reference score and determine the second dimension data as low-order data corresponding to a plurality of preset low-order data bits of the reference score if the priority of the first preset dimension is higher than the priority of the second preset dimension; or if the priority of the first preset dimension is lower than the priority of the second preset dimension, determining the second dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the first dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score;
and the first calculation unit is used for calculating the reference scores corresponding to the objects to be sorted respectively based on the high-order data and the low-order data for each object to be sorted.
Optionally, the first computing unit includes:
the first determining subunit is used for determining a first ordering order of first dimension data of a plurality of objects to be ordered and a second ordering order of second dimension data of the plurality of objects to be ordered;
a second determining subunit operable to determine whether the first sorting order and the second sorting order are the same;
the first shifting subunit is configured to shift the high-order data according to a preset offset to obtain a first intermediate score if the first sorting order is the same as the second sorting order;
and the first summation subunit is used for adding the first intermediate score and the low-level data to obtain the reference score.
Optionally, the first computing unit further includes:
the second shifting subunit is used for shifting the high-order data according to a preset offset to obtain a first intermediate score if the first sorting order is different from the second sorting order;
the difference making subunit is used for making a difference between a preset low-order maximum value and the low-order data to obtain a second intermediate fraction;
and the second summation subunit is used for adding the first intermediate score and the second intermediate score to obtain the reference score.
Optionally, the apparatus further comprises:
the judging module is used for judging whether the first dimension data and the second dimension data are both of digital types;
the execution module is used for combining the first dimension data and the second dimension data aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted if the first dimension data and the second dimension data are of a digital type;
and the conversion execution module is used for converting the first dimension data and/or the second dimension data into a digital type according to a preset rule if the first dimension data and/or the second dimension data are not in the digital type, and executing a step of combining the first dimension data and the second dimension data for each object to be sorted to obtain a reference score corresponding to each object to be sorted.
Optionally, the conversion executing module includes:
the first searching unit is used for searching a numerical value corresponding to the first dimensional data or the second dimensional data in a preset corresponding relation between the dimensional data and the numerical value;
a third determining unit, configured to determine the value as the new first dimension data or the second dimension data.
Optionally, the conversion executing module includes:
an extracting unit, configured to extract one or more reference elements from a plurality of elements included in the first dimension data and/or the second dimension data;
the second searching unit is used for searching a numerical value corresponding to the reference element in a preset corresponding relation of the numerical values of the elements to obtain a numerical value corresponding to one or more reference elements;
the second calculation unit is used for calculating one or more numerical values according to a preset operation mode to obtain a calculation result;
a fourth determining unit, configured to determine the calculation result as the new first dimension data or the second dimension data.
In another embodiment of the present invention, an electronic device is further provided, which includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the sorting method in the embodiment of the method when executing the program stored in the memory.
In the electronic device provided by the embodiment of the invention, the processor executes the program stored in the memory to realize that first dimension data of a plurality of objects to be sorted is obtained based on a first preset dimension, second dimension data of the plurality of objects to be sorted is obtained based on a second preset dimension, the first preset dimension is different from the second preset dimension, the first dimension data and the second dimension data are combined aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted, and finally the plurality of objects to be sorted can be sorted according to the reference scores. The first dimension data and the second dimension data are combined, the objects to be sorted are sorted according to the reference scores obtained after combination, the objects to be sorted are sorted based on the dimension data corresponding to a plurality of preset dimensions, and the data of one dimension of the reference scores are obtained by combining the first dimension data and the second dimension data of the plurality of dimensions, so that the objects to be sorted based on the reference scores can be sorted conveniently by utilizing a redis ordered set, the sorting speed is high, and the requirement of high-concurrency row layout is met.
The communication bus 1140 mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
The communication interface 1120 is used for communication between the electronic device and other devices.
The memory 1130 may include a Random Access Memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The processor 1110 may be a general-purpose processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the integrated circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components.
In a further embodiment of the present invention, a computer-readable storage medium is also provided, on which a sorting method program is stored, which, when executed by a processor, implements the steps of the sorting method described in the method embodiment.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of sorting, comprising:
acquiring first dimension data of a plurality of objects to be sorted based on a first preset dimension;
acquiring second dimension data of a plurality of objects to be sorted based on a second preset dimension, wherein the first preset dimension is different from the second preset dimension;
for each object to be sorted, combining the first dimensional data and the second dimensional data to obtain a reference score corresponding to each object to be sorted;
and sequencing the plurality of objects to be sequenced according to the reference scores.
2. The sorting method according to claim 1, wherein the combining the first dimensional data and the second dimensional data for each object to be sorted to obtain a reference score corresponding to each object to be sorted comprises:
determining priorities corresponding to the first preset dimension and the second preset dimension according to a preset corresponding relationship of the dimension priorities;
if the priority of the first preset dimension is higher than that of the second preset dimension, determining the first dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the second dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score; or if the priority of the first preset dimension is lower than the priority of the second preset dimension, determining the second dimension data as high-order data of a plurality of preset high-order data bits corresponding to the reference score, and determining the first dimension data as low-order data of a plurality of preset low-order data bits corresponding to the reference score;
and respectively calculating the reference scores corresponding to the objects to be sorted based on the high-order data and the low-order data for each object to be sorted.
3. The sorting method according to claim 2, wherein the calculating, for each object to be sorted, the reference score corresponding to the object to be sorted based on the high-order data and the low-order data respectively comprises:
determining a first sorting order of first dimension data of a plurality of objects to be sorted and a second sorting order of second dimension data of the plurality of objects to be sorted;
determining whether the first sort order and the second sort order are the same;
if the first sorting sequence is the same as the second sorting sequence, shifting the high-order data according to a preset offset to obtain a first intermediate score;
and adding the first intermediate score and the low-level data to obtain the reference score.
4. The sorting method according to claim 3, wherein the calculating, for each object to be sorted, the reference score corresponding to the object to be sorted based on the high-order data and the low-order data, respectively, further comprises:
if the first sorting sequence is different from the second sorting sequence, shifting the high-order data according to a preset offset to obtain a first intermediate score;
subtracting a preset maximum value of the low bit data from the low bit data to obtain a second intermediate fraction;
and adding the first intermediate score and the second intermediate score to obtain the reference score.
5. The sorting method according to claim 1, wherein the method further comprises:
judging whether the first dimension data and the second dimension data are both of digital types;
if the first dimension data and the second dimension data are both of a digital type, a step of combining the first dimension data and the second dimension data for each object to be sorted to obtain a reference score corresponding to each object to be sorted is executed;
if the first dimension data and/or the second dimension data are not in a digital type, converting the first dimension data and/or the second dimension data into the digital type according to a preset rule, and executing a step of combining the first dimension data and the second dimension data aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted.
6. The sorting method according to claim 5, wherein the converting the first dimension data and/or the second dimension data into a numerical type according to a preset rule comprises:
searching a numerical value corresponding to the first dimensional data or the second dimensional data in a preset corresponding relation between the dimensional data and the numerical value;
determining the value as the new first dimension data or the second dimension data.
7. The sorting method according to claim 5, wherein the converting the first dimension data and/or the second dimension data into a numerical type according to a preset rule comprises:
extracting one or more reference elements from a plurality of elements contained in the first dimension data and/or the second dimension data;
searching a numerical value corresponding to the reference element in a preset corresponding relationship of element numerical values to obtain a numerical value corresponding to one or more reference elements;
calculating one or more numerical values according to a preset operation mode to obtain a calculation result;
and determining the calculation result as the new first dimension data or the second dimension data.
8. A sequencing apparatus, comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring first dimension data of a plurality of objects to be sorted based on a first preset dimension;
the second acquisition module is used for acquiring second dimension data of a plurality of objects to be sorted based on a second preset dimension, wherein the first preset dimension is different from the second preset dimension;
the combination module is used for combining the first dimensional data and the second dimensional data aiming at each object to be sorted to obtain a reference score corresponding to each object to be sorted;
and the sorting module is used for sorting the plurality of objects to be sorted according to the reference scores.
9. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the sorting method according to any one of claims 1 to 7 when executing a program stored in a memory.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a sorting method program which, when executed by a processor, carries out the steps of the sorting method according to any one of claims 1-7.
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