CN113590988A - Network data acquisition system - Google Patents
Network data acquisition system Download PDFInfo
- Publication number
- CN113590988A CN113590988A CN202111167751.9A CN202111167751A CN113590988A CN 113590988 A CN113590988 A CN 113590988A CN 202111167751 A CN202111167751 A CN 202111167751A CN 113590988 A CN113590988 A CN 113590988A
- Authority
- CN
- China
- Prior art keywords
- data
- request
- task
- dynamic parameter
- segment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/955—Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
- G06F16/9566—URL specific, e.g. using aliases, detecting broken or misspelled links
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
- G06F16/972—Access to data in other repository systems, e.g. legacy data or dynamic Web page generation
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention relates to a network data acquisition system, which realizes the step S1 of obtaining url parameters, request modes and request parameters corresponding to a network data acquisition task, generating a task dynamic parameter data body according to a dynamic parameter data structure and storing the task dynamic parameter data body into a dynamic parameter data section in a request processing data structure; step S2, calling a request processing function in the request processing data structure, and acquiring dynamic parameter data from the task dynamic parameter data body and filling the dynamic parameter data into the request main body data segment to generate a task request main body; and step S3, acquiring target network data based on the task request main body. The system provided by the invention can be suitable for data acquisition of a plurality of service scenes, reduces the development and maintenance cost of network data acquisition, and improves the efficiency of network data acquisition.
Description
Technical Field
The invention relates to the technical field of data acquisition, in particular to a network data acquisition system.
Background
In the prior art, when collecting network data, the steps generally used are determining url (Uniform Resource Locator), requesting header information, network requesting, extracting, storing, and the like, and when a plurality of data collection services are involved, the steps need to be repeatedly executed. One service requirement corresponds to one data acquisition program, when a plurality of data acquisition programs are constructed, the data acquisition programs are increased continuously along with the increase of service volume, and in the face of the plurality of data acquisition programs, the maintenance cost and the development cost of workers on the programs can be increased, and the problems of disordered programs, repeated development, low data acquisition efficiency and the like can also be caused. Therefore, how to reduce the development cost of network data acquisition and improve the network data acquisition efficiency becomes a technical problem to be solved urgently.
Disclosure of Invention
The invention aims to provide a network data acquisition system which can be suitable for data acquisition of a plurality of service scenes, reduce development and maintenance cost of network data acquisition and improve efficiency of network data acquisition.
According to one aspect of the present invention, a network data acquisition system is provided, which includes a preconfigured dynamic parameter data structure and a request processing data structure, a memory storing a computer program, and a processor, where the dynamic parameter data structure and the request processing data structure are both character string data structures, the dynamic parameter data structure includes a url parameter data segment, a request mode data segment, and at least one request parameter data segment, the url parameter data segment, the request mode data segment, and the request body parameter data segment are separated by a preset first separator, different request body parameter data segments are separated by a preset second separator, and the first separator and the second separator are different; the request processing data structure comprises a request processing function data section, a request main body data section and a dynamic parameter data section, the request processing function and the request main body data section are separated by a preset third separator, the request main body data section and the dynamic parameter data section are separated by a preset fourth separator, and the third separator and the fourth separator are different;
the processor, when executing the computer program, implements the steps of:
step S1, acquiring url parameters, request modes and request parameters corresponding to the network data acquisition task, generating a task dynamic parameter data body according to the dynamic parameter data structure, and storing the task dynamic parameter data body into a dynamic parameter data section in the request processing data structure;
step S2, calling a request processing function in the request processing data structure, and acquiring dynamic parameter data from the task dynamic parameter data body and filling the dynamic parameter data into the request main body data segment to generate a task request main body;
and step S3, acquiring target network data based on the task request main body.
Compared with the prior art, the invention has obvious advantages and beneficial effects. By means of the technical scheme, the network data acquisition system provided by the invention can achieve considerable technical progress and practicability, has wide industrial utilization value and at least has the following advantages:
the system converts complex logic codes into short request statement expression through the set dynamic parameter data structure and the request processing data structure in the form of character strings to acquire dynamic parameters and construct a task request main body for network data acquisition, and is suitable for data acquisition of a plurality of service scenes, development and maintenance cost of network data acquisition is reduced, and efficiency of network data acquisition is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
Fig. 1 is a schematic diagram of a network data acquisition system according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description will be given to a specific implementation and effects of a network data acquisition system according to the present invention with reference to the accompanying drawings and preferred embodiments.
The embodiment of the invention provides a network data acquisition system, which comprises a pre-configured dynamic parameter data structure, a request processing data structure, a memory and a processor, wherein the memory and the processor are used for storing computer programs, and the dynamic parameter data structure and the request processing data structure are both character string data structures. The dynamic parameter data structure comprises a url parameter data segment, a request mode data segment and at least one request parameter data segment, wherein the url parameter data segment, the request mode data segment and the request body parameter data segment are separated by a preset first separator, different request body parameter data segments are separated by a preset second separator, and the first separator and the second separator are different. The request processing data structure comprises a request processing function data section, a request main body data section and a dynamic parameter data section, wherein the request processing function and the request main body data section are separated by a preset third separator, and the request main body data section and the dynamic parameter data section are separated by a preset fourth separator. It should be noted that the separator may be a parallel slash, a single slash, or the like, the word of the present invention is not limited thereto, and different parameters are separated by setting different separators in the data structure, so that the parameter extraction and execution of the string expression are facilitated.
The processor, when executing the computer program, implements the steps of:
step S1, acquiring url parameters, request modes and request parameters corresponding to the network data acquisition task, generating a task dynamic parameter data body according to the dynamic parameter data structure, and storing the task dynamic parameter data body into a dynamic parameter data section in the request processing data structure;
it will be appreciated that each network data collection task corresponds to a dynamic parameter data structure and a request processing data structure.
Step S2, calling a request processing function in the request processing data structure, and acquiring dynamic parameter data from the task dynamic parameter data body and filling the dynamic parameter data into the request main body data segment to generate a task request main body;
and step S3, acquiring target network data based on the task request main body.
As an embodiment, the system further includes a pre-constructed decryption interface for decrypting the encryption parameter, the decryption interface may be specifically set as a flash interface constructed based on a flash framework, the flash is a lightweight Web application framework written by using Python in the prior art, the flash interface may be constructed based on the application framework in the prior art, and the specific construction process is not described herein again. The parameter processing is carried out by configuring the flash interface, the configuration can be carried out according to different data acquisition requirements, and the variable name or the field name does not need to be specially memorized when the parameter is called, so that the flexibility of the request main body and the reusability of the program are improved. The step S1 includes:
step S11, if the url link of the network data acquisition task is a fixed link, directly determining the url link character string as a corresponding url parameter, and filling the url parameter into the url parameter data segment; if the url link is a url keyword splicing link, acquiring a url keyword corresponding to the network data acquisition task, splicing the acquired url keyword, separating by using a preset fifth separator to generate a corresponding url parameter, and filling the url parameter into the url parameter data segment;
when the obtained url keywords are spliced, the url keywords can be compressed and then spliced.
Step S12, if the network data collection task is a GET task, configuring the request type data segment as a GET, and if the network data collection task is a POST request, configuring the request type data segment as a POST;
step S13, acquiring a request header of a network data acquisition task, if the request header comprises a request header encryption parameter, calling the decryption interface to decrypt, generating a request header parameter, and filling in the request body parameter data segment; if the request mode data segment is configured to be POST, acquiring form data of a network data acquisition task, if the form data comprises form encrypted data, calling the decryption interface to decrypt to generate form parameters, and filling the request body parameter data segment to generate the task dynamic parameter data body.
The steps S11 to S13 may be executed sequentially, in an alternative order, or in parallel. The encrypted parameters in the request header may specifically be cookies encrypted by js, encrypted forms encrypted by js may also exist in the form data, and the encrypted parameters are decrypted by the decryption interface and then dynamically configured. By way of example, the task dynamic parameter data volume obtained through the steps S11-S13 is < https:// www.XXX.com @ GET @ headers { }. } data {.
The string expression requesting processing of the data structure may be < request function:// request.url/param.url >, wherein the request function is a processing function of the data collection program and includes an execution path of the program, such as general divider. And// is a third separator, request.url is a request main body, param.url is a dynamic parameter, the dynamic parameter is filled in the request.url by calling a request function processing function in a request processing data structure, and the dynamic parameter can be separated from a plurality of dynamic parameters by using semicolons.
As an embodiment, the request body data segment includes a url location, a header location, and a form data location, and step S2 includes:
step S21, invoking the request processing function in the request processing data structure, determining the target data position according to the request mode from the task dynamic parameter data body, acquiring dynamic parameter data from the task dynamic parameter data body, and filling the dynamic parameter data into the corresponding target data position in the request main body, or replacing the information in the target data position, thereby generating a task request main body.
The request processing data structure is a character string expression, dynamic parameters and a request main body are combined through the character string expression, complex logic codes are converted into short statement expressions, and the requested dynamic parameters are filled and replaced into a request block of a corresponding target data position in the request main body according to a configured expression rule to construct a complete task request main body. The character string expression is used, and has the advantages that when the service types are various and the request amount is large, some idle low-frequency data acquisition programs still occupy server resources, so that resource waste is caused, and the system is not suitable for load balancing.
It should be noted that, the request body in the request processing data structure is pre-configured with fixed parameters, which can be multiplexed, for example, a user-agent (user agent) in the request header, thereby reducing the length of the dynamic parameter string expression. In step S2, the variable dynamic parameters are combined with the fixed parameters to generate a task request body.
As an embodiment, the system further includes a preconfigured response processing data structure, where the response processing data structure is a character string data structure and includes a data parsing function data segment and a parsing path data segment, the data parsing function data segment and the parsing path data segment are separated by a preset sixth separator, the data in the data parsing function data segment is preconfigured with a data parsing function, and when the network data collection task includes a single request, the step S3 includes:
step S31, determining task analysis path data based on the task request main body, and storing the task analysis path data in the analysis path data segment;
and step S32, calling a corresponding data analysis function in the data analysis function data segment to analyze the task analysis path data, and generating the target network data.
The data analysis function may be specifically set as an xpath analysis function re regular function, a Beautiful sound function, or the like. The above functions are all functions constructed by the existing functions or the existing application frameworks, and the specific construction process is not described herein again.
When the network data collection task comprises a single request, the target network data can be obtained by directly adopting the steps S31-S32, when the network data collection task is a continuous collection request, the current analysis data is required to be used as a parameter of the next request, the final target network data can be obtained through a plurality of requests, the plurality of continuous requests form a request chain, aiming at the application scene, the response processing data structure further comprises a response processing function path data segment and a temporary cache identification data segment, the response processing function path data segment is configured with a response processing function path in advance, and when the network data collection task comprises M requests { R }, the network data collection task comprises M requests1，R2，…RMAt this time, RmM is the M-th request and takes the value from 1 to M, M is an integer greater than or equal to 2, RmThe corresponding task request body is SmThe task request body generated in the step S2 is R1, and the step S3 includes:
step S301, initializing m =1, creating a corresponding temporary cache container for the network data acquisition task, and storing a corresponding temporary cache container identifier into the temporary cache identifier data segment;
the temporary cache container is used for constructing a temporary cache for the analysis result, and transmitting or storing the analysis result downwards. It can be understood that each of the network data collection tasks corresponds to a response processing data structure, and in step S301, the corresponding temporary buffer container identifier is stored in the temporary buffer identifier data segment in the response processing data structure corresponding to the network data collection task.
Step S302, based on RmDetermining the mth task analysis path data, and updating the mth task analysis path data into the analysis path data segment;
it should be noted that, if the current analysis path data segment is empty, the mth task analysis path data may be directly stored, and if the current analysis path data segment is not empty, the mth task analysis path data may be stored after the data currently stored in the analysis path data segment is deleted.
Step S303, calling a data analysis function corresponding to the data analysis function data segment to analyze the task analysis path data, generating an mth analysis result, calling a response processing function corresponding to the response processing function path to store the mth analysis result into a temporary cache container corresponding to the temporary cache identifier;
step S304, if M is smaller than M and the mth analysis result does not meet the preset acquisition ending condition, based on the mth analysis result and RmGeneration of Rm+1And setting m = m +1, returning to execute the step S302, otherwise, generating the target network data based on the data stored in the temporary cache container.
As an example, the response handling data structure is specifically arranged to
Expression, responsefunction representing the path of the processing function for calling the response processing function to store the parsing result in the temporary buffer, meta.key representing the temporary buffer container identification,
text is the name of the variable, xpath is the analytic function, (///. title/text ()) is the specific path for xpath analysis,
are separators.
The target network data may be an mth analysis result, or an mth analysis result and an analysis result corresponding to the intermediate request, and the target data generation condition may be configured based on a specific application scenario.
As an embodiment, the step S3 further includes the step S305, after the target network data is generated, emptying and deleting the temporary cache container. The system further comprises a global cache, wherein the global cache is used for storing global parameters in the running process of the system, and the global parameters comprise survival state, depth and total request quantity. It should be noted that the global sharing is used as much as possible in the whole process of the system operation, and the temporary cache is used in the process of executing the current network data acquisition task.
As an embodiment, the step S3 is followed by:
step S4, storing the target network data, including storing the target network data in a local file according to a preset file format, which may specifically adopt json, text, or the like, or forwarding and storing the target network data to a preset queue server for subsequent data analysis or other operations, or storing the target network data in a preset database for other applications to call.
The system provided by the embodiment of the invention converts complex logic codes into short request statement expression through the set dynamic parameter data structure and the request processing data structure in the form of character strings to acquire dynamic parameters and construct a task request main body for network data acquisition, and is suitable for data acquisition of a plurality of service scenes, so that the development and maintenance cost of network data acquisition is reduced, and the efficiency of network data acquisition is improved. The system provided by the embodiment of the invention can be particularly used for network data acquisition scenes such as common data acquisition, common parameter data acquisition, common data acquisition needing continuous requests, continuously requested parameter data acquisition, continuously requested vertical data acquisition, continuously requested parameter data acquisition and the like.
It should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. A network data acquisition system is characterized in that,
the dynamic parameter data structure and the request processing data structure are both character string data structures, the dynamic parameter data structure comprises a url parameter data segment, a request mode data segment and at least one request parameter data segment, the url parameter data segment, the request mode data segment and the request body parameter data segment are separated by a preset first separator, different request body parameter data segments are separated by a preset second separator, and the first separator and the second separator are different; the request processing data structure comprises a request processing function data section, a request main body data section and a dynamic parameter data section, the request processing function and the request main body data section are separated by a preset third separator, the request main body data section and the dynamic parameter data section are separated by a preset fourth separator, and the third separator and the fourth separator are different;
the processor, when executing the computer program, implements the steps of:
step S1, acquiring url parameters, request modes and request parameters corresponding to the network data acquisition task, generating a task dynamic parameter data body according to the dynamic parameter data structure, and storing the task dynamic parameter data body into a dynamic parameter data section in the request processing data structure;
step S2, calling a request processing function in the request processing data structure, and acquiring dynamic parameter data from the task dynamic parameter data body and filling the dynamic parameter data into the request main body data segment to generate a task request main body;
and step S3, acquiring target network data based on the task request main body.
2. The system of claim 1,
the system further includes a pre-constructed decryption interface for cracking the encryption parameters, and the step S1 includes:
step S11, if the url link of the network data acquisition task is a fixed link, directly determining the url link character string as a corresponding url parameter, and filling the url parameter into the url parameter data segment; if the url link is a url keyword splicing link, acquiring a url keyword corresponding to the network data acquisition task, splicing the acquired url keyword, separating by using a preset fifth separator to generate a corresponding url parameter, and filling the url parameter into the url parameter data segment;
step S12, if the network data acquisition task is a GET task, configuring the request mode data segment into a GET, and if the network data acquisition task is a POST request, configuring the request mode data segment into a POST;
step S13, acquiring a request header of a network data acquisition task, if the request header comprises a request header encryption parameter, calling the decryption interface to decrypt, generating a request header parameter, and filling in the request body parameter data segment; if the request mode data segment is configured to be POST, acquiring form data of a network data acquisition task, if the form data comprises form encrypted data, calling the decryption interface to decrypt to generate form parameters, and filling the request body parameter data segment to generate the task dynamic parameter data body.
3. The system of claim 2,
the decryption interface is a flash interface built based on a flash framework.
4. The system of claim 1,
the request body data segment includes a url location, a header location, and a form data location, and step S2 includes:
step S21, invoking the request processing function in the request processing data structure, determining the target data position according to the request mode from the task dynamic parameter data body, acquiring dynamic parameter data from the task dynamic parameter data body, and filling the dynamic parameter data into the corresponding target data position in the request main body, or replacing the information in the target data position, thereby generating a task request main body.
5. The system of claim 1,
the system further includes a preconfigured response processing data structure, where the response processing data structure is a character string data structure, and includes a data parsing function data segment and a parsing path data segment, where the data parsing function data segment and the parsing path data segment are separated by a preset sixth separator, and data in the data parsing function data segment is preconfigured with a data parsing function, and when the network data collection task includes a single request, the step S3 includes:
step S31, determining task analysis path data based on the task request main body, and storing the task analysis path data in the analysis path data segment;
and step S32, calling a corresponding data analysis function in the data analysis function data segment to analyze the task analysis path data, and generating the target network data.
6. The system of claim 5,
the response processing data structure further comprises a response processing function path data segment and a temporary cache identification numberThe data segment of the response processing function path is configured with a response processing function path in advance, and when the network data acquisition task comprises M requests { R }1，R2，…RMAt this time, RmM is the M-th request and takes the value from 1 to M, M is an integer greater than or equal to 2, RmThe corresponding task request body is SmThe task request body generated in the step S2 is R1, and the step S3 includes:
step S301, initializing m =1, creating a corresponding temporary cache container for the network data acquisition task, and storing a corresponding temporary cache container identifier into the temporary cache identifier data segment;
step S302, based on RmDetermining the mth task analysis path data, and updating the mth task analysis path data into the analysis path data segment;
step S303, calling a data analysis function corresponding to the data analysis function data segment to analyze the task analysis path data, generating an mth analysis result, calling a response processing function corresponding to the response processing function path to store the mth analysis result into a temporary cache container corresponding to the temporary cache identifier;
step S304, if M is smaller than M and the mth analysis result does not meet the preset acquisition ending condition, based on the mth analysis result and RmGeneration of Rm+1And setting m = m +1, returning to execute the step S302, otherwise, generating the target network data based on the data stored in the temporary cache container.
7. The system of claim 6,
the step S3 further includes the step S305 of emptying and deleting the temporary cache container after the target network data is generated.
8. The system of claim 1,
the system further comprises a global cache, wherein the global cache is used for storing global parameters in the running process of the system, and the global parameters comprise survival state, depth and total request quantity.
9. The system of claim 1,
the step S3 is followed by:
step S4, storing the target network data, including storing the target network data in a local file according to a preset file format, or forwarding and storing the target network data to a preset queue server, or storing the target network data in a preset database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111167751.9A CN113590988B (en) | 2021-10-08 | 2021-10-08 | Network data acquisition system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111167751.9A CN113590988B (en) | 2021-10-08 | 2021-10-08 | Network data acquisition system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113590988A true CN113590988A (en) | 2021-11-02 |
| CN113590988B CN113590988B (en) | 2021-12-14 |
Family
ID=78242900
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111167751.9A Active CN113590988B (en) | 2021-10-08 | 2021-10-08 | Network data acquisition system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113590988B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104111836A (en) * | 2014-07-14 | 2014-10-22 | 浪潮软件集团有限公司 | Method for collecting and processing asynchronous loading data by network |
| CN104881424A (en) * | 2015-03-13 | 2015-09-02 | 国家电网公司 | Regular expression-based acquisition, storage and analysis method of power big data |
| US10282479B1 (en) * | 2014-05-08 | 2019-05-07 | Google Llc | Resource view data collection |
| CN111934751A (en) * | 2020-08-28 | 2020-11-13 | 中南民族大学 | Agricultural environment data acquisition system and method based on Beidou short message |
| CN112182462A (en) * | 2020-08-28 | 2021-01-05 | 镇江智越智能科技有限公司 | Intelligent network information acquisition system and acquisition method |
-
2021
- 2021-10-08 CN CN202111167751.9A patent/CN113590988B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10282479B1 (en) * | 2014-05-08 | 2019-05-07 | Google Llc | Resource view data collection |
| CN104111836A (en) * | 2014-07-14 | 2014-10-22 | 浪潮软件集团有限公司 | Method for collecting and processing asynchronous loading data by network |
| CN104881424A (en) * | 2015-03-13 | 2015-09-02 | 国家电网公司 | Regular expression-based acquisition, storage and analysis method of power big data |
| CN111934751A (en) * | 2020-08-28 | 2020-11-13 | 中南民族大学 | Agricultural environment data acquisition system and method based on Beidou short message |
| CN112182462A (en) * | 2020-08-28 | 2021-01-05 | 镇江智越智能科技有限公司 | Intelligent network information acquisition system and acquisition method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113590988B (en) | 2021-12-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20230004434A1 (en) | Automated reconfiguration of real time data stream processing | |
| US8543539B2 (en) | Method and system for capturing change of data | |
| EP2954403B1 (en) | Cloud-based streaming data receiver and persister | |
| US9378053B2 (en) | Generating map task output with version information during map task execution and executing reduce tasks using the output including version information | |
| CN101202761B (en) | System of distributed resource scheduling and method thereof | |
| US20130124616A1 (en) | Methods for dynamically generating application interfaces for modeled entities and devices thereof | |
| CN112751845B (en) | Network protocol analysis method, system and device | |
| CN112379949B (en) | Data processing method, device, equipment and storage medium | |
| US20130212259A1 (en) | Service scripting framework | |
| CN108287894B (en) | Data processing method, device, computing equipment and storage medium | |
| WO2021203918A1 (en) | Method for processing model parameters, and apparatus | |
| CN103927314A (en) | Data batch processing method and device | |
| US10165036B1 (en) | Network resource remote process execution | |
| WO2016146009A1 (en) | Html page compression method and device | |
| AlShahwan et al. | Mobile cloud computing for providing complex mobile web services | |
| US9996344B2 (en) | Customized runtime environment | |
| US11861386B1 (en) | Application gateways in an on-demand network code execution system | |
| CN113590988B (en) | Network data acquisition system | |
| CN104503983A (en) | Method and device for providing website certification data for search engine | |
| CN114401262A (en) | RDMA-based big data transmission system, method, device, equipment and storage medium | |
| US20110055279A1 (en) | Application server, object management method, and object management program | |
| US11929933B2 (en) | Ephemeral data stream routing service | |
| JP7336161B2 (en) | Media processing method | |
| Mukherjee et al. | Automated deep learning model partitioning for heterogeneous edge devices | |
| CN112988806A (en) | Data processing method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |