CN108268594B - Data query method and device - Google Patents
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- CN108268594B CN108268594B CN201711340837.0A CN201711340837A CN108268594B CN 108268594 B CN108268594 B CN 108268594B CN 201711340837 A CN201711340837 A CN 201711340837A CN 108268594 B CN108268594 B CN 108268594B
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- G06F16/10—File systems; File servers
- G06F16/17—Details of further file system functions
- G06F16/176—Support for shared access to files; File sharing support
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
- G06F9/5016—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals the resource being the memory
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Abstract
The invention provides a method and a device for querying data, wherein the method comprises the following steps: receiving a Python data query request, wherein the Python data query request comprises a target parameter; calling a Cython data query interface according to the Python data query request, wherein the Cython data query interface is packaged with a C language data query method; calling a C language data query method through a Cython data query interface, and transmitting a target parameter to the C language data query method; and querying target data corresponding to the target parameters in the shared memory by using a C language data query method carrying the target parameters, wherein a preset file stored in the shared memory has a C language data structure, and the C language data structure comprises a parameter index table and a preset file with an index address. The invention can improve the data query efficiency, improve the utilization rate of memory resources and reduce the memory occupation.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a data query method and apparatus.
Background
When a plurality of processes access the same large file at the same time, when each process needs to access data, the large file needs to be allocated with a memory, so that a large amount of memory resources are repeatedly occupied, and the problem of low memory resource utilization rate is caused; in addition, when a process accesses a large file, if a plurality of query fields (i.e., query parameters) are provided, the large file needs to be traversed for a plurality of times according to different fields, and this sequential query method is time-consuming and low in query efficiency.
The inventor finds that when multiple processes carry out multi-field concurrent query on the same file, the problems of low memory resource utilization rate and low data query efficiency obviously exist.
Disclosure of Invention
The invention provides a data query method and a data query device, which are used for solving the problems of low utilization rate of memory resources and low data query efficiency when multiple processes perform multi-field concurrent query on the same file in the prior art.
In order to solve the above problem, according to an aspect of the present invention, there is disclosed a data query method including:
receiving a Python data query request, wherein the Python data query request comprises a target parameter;
calling a Cython data query interface according to the Python data query request, wherein the Cython data query interface is packaged with a C language data query method;
calling the C language data query method through the Cython data query interface, and transmitting the target parameter to the C language data query method;
and querying target data corresponding to the target parameter in a shared memory by using the C language data query method carrying the target parameter, wherein a preset file stored in the shared memory has a C language data structure, and the C language data structure comprises a parameter index table and a preset file with an index address.
According to another aspect of the present invention, the present invention also discloses a data query apparatus, including:
the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is used for receiving a Python data query request, and the Python data query request comprises target parameters;
the first calling module is used for calling a Cython data query interface according to the Python data query request, wherein the Cython data query interface is packaged with a C language data query method;
the second calling module is used for calling the C language data query method through the Cython data query interface and transmitting the target parameter to the C language data query method;
and the query module is used for querying the target data corresponding to the target parameter in the shared memory by using the C language data query method carrying the target parameter, wherein the preset file stored in the shared memory has a C language data structure, and the C language data structure comprises a parameter index table and a preset file with an index address.
Compared with the prior art, the invention has the following advantages:
according to the embodiment of the invention, the data structure with the parameter index table in the C language is set for the preset file, so that when a plurality of Python data queries are performed and a plurality of fields are queried, the query efficiency can be improved by using the parameter index table, and the preset file is stored in the shared memory, so that the utilization rate of memory resources is improved, and the memory occupation is reduced.
Drawings
FIG. 1 is a schematic diagram of one embodiment of a data query system of the present invention;
FIG. 2 is a flow chart of steps of an embodiment of a data query method of the present invention;
fig. 3 is a block diagram of an embodiment of a data query apparatus according to the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
When multiple processes access the same large file concurrently, in order to improve the utilization rate of memory resources, the embodiment of the invention can store the large file into the shared memory, so that the multiple processes can access the same large file conveniently;
in addition, due to the characteristic of fast development of the Python language, in order to improve a code development period, a software developer generally uses the Python language to develop a business processing flow, but the operating efficiency of the Python language is low, so that when a large file is accessed by multiple processes concurrently, the system reaction is slow and the response speed is low.
However, since the development language of the business logic for sending the data query request and returning the query data is still Python, in order to realize the interface between the Python language and the C language, as shown in fig. 1, a schematic diagram of the data processing system according to the embodiment of the present invention is shown. Therefore, the data query and write-in method part of the large file is developed by using the C language, so that the efficiency of multi-process concurrent data access is improved, and the service processing flow is developed by using the Python language, so that the code development efficiency is improved, and the development is simpler.
Referring to fig. 2 in conjunction with fig. 1, fig. 2 shows a flowchart of steps of an embodiment of a data query method of the present invention, which may specifically include the following steps:
for example, in the embodiment of the present invention, a video website (or a video application program) may be stored in a shared memory in different dimensions (the dimensions may include, but are not limited to, a platform, a region, a channel, and a gender from high to low, where the platform includes, but is not limited to, IOS, Windows, Android, and the like, the region includes, but is not limited to, cities or areas in beijing, shanghai, Chongqing, and the like, the channel includes, but is not limited to, movies, television shows, synthesis, cartoons, and the gender includes males and females), and an entirety of data of the number of active users in the different dimensions forms a large file, that is, the preset file in the embodiment of the present invention, and the preset file refers to a file whose file size is larger than a preset file size threshold value.
The number of active users of the video website which a plurality of advertisers want to access under the respectively set dimension condition.
The query request of the active user initiated by each advertiser corresponds to a process, wherein the advertiser can input the query condition of the query request, namely the dimension data, and one dimension data is used as a target parameter. For example, advertiser 1 wants to query the number of male active users on channel 1 in zone 1 under platform 1, the target parameters of the query request include platform 1, zone 1, channel 1, and male.
In addition, by utilizing the characteristic of fast development of the Python language, the interaction between the data storage side and the user side is still developed by adopting the Python language, so that the method provided by the embodiment of the invention can receive a Python data query request initiated by a certain advertiser; when multiple advertisers initiate query requests of active users at the same time, optionally, the number of the Python data query requests of the embodiment of the present invention may be multiple. Of course, it should be noted that the target parameters of different Python data query requests have no relationship, and may be the same or different, depending mainly on the query requirements of the advertiser who wants to query the data.
As shown in fig. 1, a method according to an embodiment of the present invention may receive one or more Python data query requests.
in order to realize the interaction between the Python language and the C language, as shown in fig. 1, a Cython middleware, that is, a Cython interface, is provided in the embodiment of the present invention, and the Cython interface encapsulates the method for developing the C language, wherein, since the C language can develop a plurality of different methods, for the convenience of identification, the name of a certain method for developing the C language is the same as the name of the Cython interface encapsulating the C language method, that is, as shown in fig. 1, the Cython interface calls the homonymic function of the C language.
Therefore, the Cython data query interface encapsulates the data query method developed for the C language, and in addition, the Cython interface can also comprise a data writing interface, and the corresponding C language homonymous function is the data writing method. The Cython data write interface and the C language data write method are used for writing data into a shared memory or updating the written data, and the specific write and update method is similar to the data query method in the embodiment of the invention and is not described herein again.
as described above, the Cython data query interface may be used to call a corresponding C language function with the same name, that is, a C language data query function, and in addition, when the C language data query function is called, the Cython data query interface may transfer the target parameters (including platform 1, region 1, channel 1 and male) to the C language data query function, thereby facilitating subsequent data query.
In the conventional technology, when data of multiple fields (i.e., multiple target parameters) is queried, traversal query is performed on different fields one by one, so that all data of the large file needs to be traversed for each data query request, and the query efficiency of the sequential query method is very low. Therefore, when the method of the embodiment of the present invention stores the large file in the shared memory, a C language data structure is set for a data query logic portion of the large file, as shown in fig. 1, the C language data structure includes a parameter index portion (i.e., a parameter index table) and a sequential query portion (i.e., a large file with an index address), so that when querying target data (i.e., the number of active users that meet the target parameter), an index can be queried in the parameter index table according to the target parameter, and then the corresponding target data can be sequentially queried in a preset file by using the index, which greatly saves data query time.
Optionally, in one embodiment, when step 204 is executed, it may be implemented by:
querying the parameter index table in the shared memory by using the C language data query method carrying the target parameter, and determining a target index address corresponding to the target parameter;
optionally, the parameter in the parameter index table is a parameter whose query frequency is higher than a preset frequency threshold.
For example, in the embodiment of the present invention, some high-frequency parameters (that is, parameters whose query frequency is higher than a preset frequency threshold) with higher query frequency may be selected from all parameters (platform, region, channel, and gender) of a large file in advance, and a parameter index table is compiled for the parameters, for example, the two parameters with the highest query frequency are the platform and the region, so that the platform and the region may be compiled into a two-dimensional index table as shown in table 1, and the start-stop line numbers in the sequential lookup structure of the embodiment of the present invention are correspondingly stored.
TABLE 1
For example, the target parameters of a data query include platform 1, region 1, channel 1, and male.
Then, by looking up the two-dimensional index table shown in table 1, the storage data of the 1 st to 2 nd rows of the target index addresses corresponding to the platform 1 and the region 1 can be determined.
Determining the target range data pointed by the target index address according to the target index address in the preset file with the index address;
| line number | Channel with a plurality of channels | Sex | Number of active users |
| 1 | 1 | For male | 1000 |
| 2 | 1 | Woman | 5000 |
| 3 | 2 | Woman | 5000 |
| 4 | 2 | For male | 3000 |
| 5 | 2 | Woman | 4000 |
| 6 | 3 | Woman | 2000 |
TABLE 2
As shown in table 2, the preset file with the index address indicates that, according to table 2, the data in a range pointed by the 1 st to 2 nd rows, that is, the two records, are the number of active users of channel 1 male and the number of active users of channel 1 female, respectively;
and searching target data corresponding to the target parameters in the target range data.
The two searched records can be respectively searched in sequence according to the channel and the gender, and then the target data with the number of 1000 male active users of the platform 1, the region 1 and the channel 1 can be searched.
Optionally, the target data queried by the Python data query requests are selected from the same preset file.
That is to say, a large file is concurrently queried by a plurality of data query requests, and the method of the embodiment of the invention can improve the data query efficiency and improve the utilization rate of memory resources.
With reference to fig. 1, after the target data is queried by using the C language data query function from the shared memory, the sequential query part returns the target data to the C language homonymy function (here, the C language data query function) of the cotton interface, the C language data query function returns the target data to the cotton interface, the cotton interface returns the target data to the data query module shown in fig. 1, and finally, the data query module returns the target data to the advertiser.
That is, the process of returning the target data to the user side is similar to the query process of the data, but the data flow direction is opposite, and a Cythton interface is also required as an intermediary to realize data interaction between Python and C language.
Similarly, when data of a large file is written or updated into the shared memory, the process is similar to the data query process, and specific reference is made to fig. 1, which is not described herein again.
By means of the technical scheme of the embodiment of the invention, the data structure with the parameter index table in the language C is set for the preset file, so that when a plurality of Python data queries are performed and a plurality of fields are queried, the invention can improve the query efficiency by using the parameter index table, and the preset file is stored in the shared memory, thereby improving the utilization rate of memory resources and reducing the memory occupation.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
Corresponding to the method provided by the above embodiment of the present invention, referring to fig. 3, a block diagram of a data query apparatus according to an embodiment of the present invention is shown, which may specifically include the following modules:
a receiving module 31, configured to receive a Python data query request, where the Python data query request includes a target parameter;
the first calling module 32 is configured to call a Cython data query interface according to the Python data query request, where the Cython data query interface encapsulates a C language data query method;
the second calling module 33 is configured to call the C language data query method through the Cython data query interface, and transfer the target parameter to the C language data query method;
the query module 34 is configured to query, by using the C language data query method with the target parameter, target data corresponding to the target parameter in a shared memory, where a preset file stored in the shared memory has a C language data structure, and the C language data structure includes a parameter index table and a preset file with an index address.
Optionally, the query module 34 includes:
the query submodule is used for querying the parameter index table in the shared memory by using the C language data query method carrying the target parameter and determining a target index address corresponding to the target parameter;
the determining submodule is used for determining the target range data pointed by the target index address according to the target index address in the preset file with the index address;
and the searching submodule is used for searching the target data corresponding to the target parameter in the target range data.
Optionally, the parameter in the parameter index table is a parameter whose query frequency is higher than a preset frequency threshold.
Optionally, the number of the Python data query requests is multiple.
Optionally, the target data queried by the Python data query requests are selected from the same preset file.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, 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 terminal 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 terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The data query method and the data query device provided by the invention are described in detail above, and the principle and the implementation mode of the invention are explained by applying specific examples, and the description of the above examples is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (6)
1. A method for querying data, comprising:
receiving a Python data query request, wherein the Python data query request comprises a target parameter;
calling a Cython data query interface in a Cython interface according to the Python data query request, wherein the Cython data query interface is packaged with a C language data query method with the same name as the Cython data query interface;
calling the C language data query method which is the same as the Cython data query interface through the Cython data query interface, and transmitting the target parameter to the C language data query method;
querying target data corresponding to the target parameter in a shared memory by using the C language data query method carrying the target parameter, wherein a preset file stored in the shared memory has a C language data structure, and the C language data structure comprises a parameter index table and a preset file with an index address;
returning the inquired target data to the C language data inquiry method with the same name as the Cython data inquiry interface, returning the inquired target data to the Cython interface by the C language data inquiry method, and returning the inquired target data by the Cython interface;
the Python data query request is a plurality of concurrent query requests; when the Python data query request is a plurality of concurrent query requests, a plurality of target data queried by the Python data query requests are selected from the same preset file.
2. The method according to claim 1, wherein the querying the target data corresponding to the target parameter in the shared memory by using the C-language data query method with the target parameter includes:
querying the parameter index table in the shared memory by using the C language data query method carrying the target parameter, and determining a target index address corresponding to the target parameter;
determining target range data pointed by the target index address in the preset file with the index address according to the target index address;
and searching target data corresponding to the target parameters in the target range data.
3. The method according to claim 1 or 2, wherein the parameter in the parameter index table is a parameter with a query frequency higher than a preset frequency threshold.
4. A data query apparatus, comprising:
the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is used for receiving a Python data query request, and the Python data query request comprises target parameters;
the first calling module is used for calling a Cython data query interface in the Cython interface according to the Python data query request, wherein the Cython data query interface is packaged with a C language data query method with the same name as the Cython data query interface;
the second calling module is used for calling the C language data query method which is the same as the Cython data query interface through the Cython data query interface and transmitting the target parameter to the C language data query method;
the query module is used for querying target data corresponding to the target parameter in a shared memory by using the C language data query method carrying the target parameter, wherein a preset file stored in the shared memory has a C language data structure, and the C language data structure comprises a parameter index table and a preset file with an index address; returning the inquired target data to the C language data inquiry method with the same name as the Cython data inquiry interface, returning the inquired target data to the Cython interface by the C language data inquiry method, and returning the inquired target data by the Cython interface;
the Python data query request is a plurality of concurrent query requests; when the Python data query request is a plurality of concurrent query requests, a plurality of target data queried by the Python data query requests are selected from the same preset file.
5. The apparatus of claim 4, wherein the query module comprises:
the query submodule is used for querying the parameter index table in the shared memory by using the C language data query method carrying the target parameter and determining a target index address corresponding to the target parameter;
the determining submodule is used for determining target range data pointed by the target index address in the preset file with the index address according to the target index address;
and the searching submodule is used for searching the target data corresponding to the target parameter in the target range data.
6. The apparatus according to claim 4 or 5, wherein the parameter in the parameter index table is a parameter with a query frequency higher than a preset frequency threshold.
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| Publication number | Priority date | Publication date | Assignee | Title |
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Non-Patent Citations (5)
| Title |
|---|
| "pyx文件 生成pyd 文件用于 cython调用;dy9776;《https://www.cnblogs.com/nucdy/p/7736155.html》;20171016;第1-5页 * |
| MUSER海量数据预处理关键技术研究;梅盈;《中国优秀硕士学位论文全文数据库 基础科学辑》;20160115(第1期);正文第33-45页 * |
| python - 如何从 python 处理程序输入并发 查询到函数，并将输出重定向回 python？;Sravan;《https://kb.kutu66.com/python/post_2131247》;20170709;第1-3页 * |
| python性能优化;xvbaby;《https://www.cnblogs.com/xybaby/p/6510941.html》;20170307;第1-7页 * |
| 利用ctypes给python加速;thesby;《https://blog.csdn.net/thesby/article/details/76283807》;20170728;第1-2页 * |
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