CN112115154A - Data processing and data query method, device, equipment and computer readable medium - Google Patents
Data processing and data query method, device, equipment and computer readable medium Download PDFInfo
- Publication number
- CN112115154A CN112115154A CN202011034773.3A CN202011034773A CN112115154A CN 112115154 A CN112115154 A CN 112115154A CN 202011034773 A CN202011034773 A CN 202011034773A CN 112115154 A CN112115154 A CN 112115154A
- Authority
- CN
- China
- Prior art keywords
- target
- data
- index
- real
- time
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000012545 processing Methods 0.000 title claims abstract description 39
- 238000004458 analytical method Methods 0.000 claims abstract description 38
- 230000004044 response Effects 0.000 claims abstract description 21
- 238000004590 computer program Methods 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000007619 statistical method Methods 0.000 claims description 4
- 238000004141 dimensional analysis Methods 0.000 claims description 2
- 238000003672 processing method Methods 0.000 abstract description 14
- 238000010586 diagram Methods 0.000 description 16
- 230000006870 function Effects 0.000 description 8
- 238000004891 communication Methods 0.000 description 6
- 230000003287 optical effect Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000000644 propagated effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
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
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
- G06F16/2372—Updates performed during offline database operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
- G06F16/2365—Ensuring data consistency and integrity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
Abstract
The embodiment of the disclosure discloses a data processing method, a data processing device, an electronic device and a computer readable medium. One embodiment of the method comprises: controlling the target data query index to point to a target real-time index which is created in advance; within the target time period, the following data processing steps are performed: in response to receiving the real-time data, updating the target real-time index based on the real-time data and storing the real-time data; after the end time of the target time period, analyzing the target offline data to obtain an analysis result, and creating an index of the analysis result to obtain a target offline index, wherein the target offline data is obtained by storing real-time data received in at least one sub-time period of the target time period; and controlling the target data query index to point to the target offline index. The embodiment realizes unified processing of real-time data and offline data.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a data processing and data query method, apparatus, device, and computer-readable medium.
Background
With the on-line of various services, more and more network information is also present. Such information data is typically generated in real time. These real-time generated data are then typically stored for later use. Such a piece of data will have two states, real-time data and offline data. In the related technology, when data processing is performed at different occasions or by different users, the processing results are incompatible and inconsistent.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose data processing methods, apparatuses, devices and computer readable media to solve the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a data processing method, including: controlling the target data query index to point to a target real-time index which is created in advance; within the target time period, the following data processing steps are performed: in response to receiving real-time data, updating the target real-time index based on the real-time data and storing the real-time data; after the end time of the target time period, analyzing target offline data to obtain an analysis result, and creating an index of the analysis result to obtain a target offline index, wherein the target offline data is obtained by storing real-time data received in at least one sub-time period of the target time period; and controlling the target data query index to point to the target offline index.
In a second aspect, some embodiments of the present disclosure provide a data processing apparatus comprising: a first control unit configured to control the target data query index to point to a pre-created target real-time index; an update and storage unit configured to perform the following data processing steps during a target time period: in response to receiving real-time data, updating the target real-time index based on the real-time data and storing the real-time data; an analysis and index creation unit configured to analyze target offline data after the end time of the target time period to obtain an analysis result, and create an index of the analysis result to obtain a target offline index, the target offline data being obtained by storing real-time data received in at least one sub-time period of the target time period; and the second control unit is configured to control the target data query index to point to the target offline index.
In a third aspect, some embodiments of the present disclosure provide a data query method, including: in response to receiving a data query request, determining a target query index in a query index group, wherein the data query request comprises a target query index name; and determining the data in the index pointed by the target query index as target data.
In a fourth aspect, some embodiments of the present disclosure provide a data query apparatus, including: a first determining unit configured to determine a target query index in a query index group in response to receiving a data query request, the data query request including a target query index name; and the second determining unit is configured to determine the data in the index pointed by the target query index as the target data.
In a fifth aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method as described in any of the implementations of the first aspect.
In a sixth aspect, some embodiments of the disclosure provide a computer readable medium having a computer program stored thereon, where the program when executed by a processor implements a method as described in any of the implementations of the first aspect.
One of the above-described various embodiments of the present disclosure has the following advantageous effects: when data processing is carried out at different time or different users, the processing result can be ensured to be more consistent. Specifically, the inventors have found that the reason why the related art cannot guarantee the consistency of the results of the processing is that one of real-time data or offline data cannot be used adaptively and selectively according to the current environment. Based on the scheme, the switching of the real-time data index and the off-line data index in different time periods is realized by introducing the data query index. Specifically, when the target time period is not over, the data query index is controlled to point to the real-time data index. That is, the object of data processing is real-time data. And after the target time period is ended, controlling the data query index to point to the target offline data index. That is, the object of data processing is offline data. Therefore, the method provided by the scheme can better ensure the consistency of the data processing results in different environments.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
FIG. 1 is a schematic diagram of one application scenario of a data processing method of some embodiments of the present disclosure;
FIG. 2 is a schematic diagram of an application scenario of a data query method of some embodiments of the present disclosure;
FIG. 3 is a flow diagram of some embodiments of a data processing method according to the present disclosure;
FIG. 4 is a flow diagram of further embodiments of a data processing method according to the present disclosure;
FIG. 5 is a flow diagram of some embodiments of a data query method according to the present disclosure;
FIG. 6 is a schematic block diagram of some embodiments of a data processing apparatus according to the present disclosure;
FIG. 7 is a schematic block diagram of some embodiments of a data query device according to the present disclosure;
FIG. 8 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 shows a schematic diagram of one application scenario in which the data processing method of some embodiments of the present disclosure may be applied.
In the application scenario shown in fig. 1, the computing device 101 may first control the target data query index 102 to point to the pre-created target real-time index 103. Then, in response to receiving the real-time data 104 within the target time period, the target real-time index 103 is updated based on the real-time data 104 and the real-time data 104 is stored. In this application scenario, the target time period is "26 days at 5 months in 2020". On this basis, the names of the target query index and the target real-time index are "2020/05/26". In the application scenario, a total of 4 pieces of real-time data are received in the target time period, and the content is "09: 05 watch for 15 seconds", "13: 10 watch for 20 seconds", "16: 15 watch for 20 seconds", and "21: 20 watch for 15 seconds", respectively. Each piece of data represents a time node and a watching time length of each time when the corresponding user starts to watch the target content in the target time period. After the end time of the target time period, the target offline data 105 is analyzed to obtain an analysis result 106. In the present application scenario, the content of the analysis result 106 is "viewed 14 times for 5 seconds in total". Then, an index of the analysis result 106 is created to obtain a target offline index 107. The target offline data 105 is obtained by storing the real-time data 104 received in at least one sub-period of the target period. Finally, the computing device 101 controls the target data query index 102 to point to the target offline index 107.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of a plurality of servers or electronic devices, or may be implemented as a single server or a single electronic device. When the computing device is embodied as software, it may be implemented as multiple pieces of software or software modules, for example, to provide distributed services, or as a single piece of software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices 101 in FIG. 1 is merely illustrative. There may be any number of computing devices 101, as desired for implementation.
With continued reference to fig. 2, fig. 2 is a schematic diagram of an application scenario of a data query method of some embodiments of the present disclosure.
In the application scenario illustrated in fig. 2, in response to receiving a data query request 202, the computing device 201 may determine a target query index 204 in the query index group 203, where the data query request 202 includes a target query index name. In the present application scenario, the query index set includes 6 query indexes. After the name of the target query index is "2019/02/10", the data 206 in the index pointed to by the target query index 205 is determined as the target data. In the present application scenario, the target data is "total viewing 17 times for 5 seconds". The corresponding user is characterized in that the corresponding user watches the target content for 17 times and for 5 seconds in the time period of '2 months and 10 days in 2019'.
The computing device 201 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of a plurality of servers or electronic devices, or may be implemented as a single server or a single electronic device. When the computing device is embodied as software, it may be implemented as multiple pieces of software or software modules, for example, to provide distributed services, or as a single piece of software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices 201 in FIG. 2 is merely illustrative. There may be any number of computing devices 201, as implementation needs dictate.
With continued reference to fig. 3, a flow 300 of some embodiments of a data processing method according to the present disclosure is shown. The data processing method comprises the following steps:
In some embodiments, the target data query index may be a query index in any query interface format. As an example, the target data query index described above may be a query index in the form of a search box. As yet another example, the target data query index may also be a query index in the form of a mouse selection interface.
In some embodiments, the target real-time index may be an index stored in a file of any format. As an example, the target real-time index may be an index stored in a database file. As yet another example, the target real-time index may also be an index stored in a table file.
In some embodiments, the execution subject of the data processing method may control the target data query index to point to a pre-created target real-time index by determining a storage address of the target real-time index in the target storage space as an index value of the target data query index.
In some embodiments, the target real-time index may be an index that points to a contiguous storage space. On this basis, the execution body may update the target real-time index by storing the real-time data in the continuous storage space.
In some optional implementations of some embodiments, the target real-time index stores at least one real-time statistic of the real-time data. On this basis, the execution subject may update the at least one real-time statistic by performing at least one dimensional analysis on the real-time data to update the target real-time index. By way of example, the at least one dimension may include, but is not limited to: the total number of real-time data, the average value of a certain field value in the real-time data, the maximum value of a certain field in the real-time data, and the sum of a certain field in the real-time data.
In some embodiments, the target offline data is obtained by storing real-time data received during at least one sub-period of the target time period.
In some embodiments, the execution subject may obtain the analysis result by performing a statistical analysis on the target offline data. As an example, the execution subject may count the total number of the target offline data. As another example, the execution subject may also perform statistics by averaging an average value of a certain field value in the target offline data.
In some embodiments, the execution subject may further obtain the analysis result by screening the target offline data. For example, whether to screen out target offline data is determined according to the generation time of real-time data corresponding to the target offline data.
In some embodiments, the target offline index may be an index stored in a file of any format. As an example, the target offline index may be an index stored in a database file. As yet another example, the target offline index described above may also be an index stored in a table file.
In some embodiments, the names of the target real-time index and the target offline index may be sequence numbers.
In some optional implementations of some embodiments, the names of the target real-time index and the target offline index may be further generated according to information related to the target time period. With the embodiments of the present implementation, by using information naming related to the target time period, querying the target index by using the time period is easier to implement.
According to the method provided by some embodiments of the disclosure, switching between real-time data indexing and offline data indexing in different time periods is realized by introducing the data query index. Therefore, the consistency of data processing results in different environments can be better ensured.
With continued reference to fig. 4, a flow 400 of some embodiments of a data processing method according to the present disclosure is shown. The data processing method comprises the following steps:
In some embodiments, the specific implementation of step 401 and the technical effect thereof may refer to step 301 in the embodiment corresponding to fig. 3, which is not described herein again.
And step 404, updating the target real-time index based on the real-time data and storing the real-time data.
In some embodiments, the specific implementation of steps 404 and 406 and the technical effects thereof can refer to steps 302 and 304 in the embodiment corresponding to fig. 3, which are not described herein again.
As can be seen from fig. 4, compared with the description of some embodiments corresponding to fig. 3, the flow 400 of the data processing method in some embodiments corresponding to fig. 4 embodies the step of performing field processing on real-time data. Thus, the schemes described by these embodiments save storage space by deleting unnecessary fields in the real-time data. By introducing the field which is actually needed, the statistical result can meet the actual requirement.
With further reference to fig. 5, a flow 500 of some embodiments of a data query method is illustrated. The process 500 of the data query method includes the following steps:
In some embodiments, the execution body may compare, in the index group, whether a name of a currently queried index is the same as the target index name in a certain order. As an example, the target index may be queried in a front-to-back order of indexes in the secondary index set. As yet another example, the indexes in the index set are ordered according to an attribute value of the index name, and the target index is queried in the secondary index set by using a binary search method. The attribute value may be in the form of a value of a date represented by the index name. The attribute value may be a dash of the index name.
In some embodiments, the index pointed to by the target query index may include: at least one of a target real-time index or a target offline index.
According to the method provided by some embodiments of the disclosure, switching between real-time data indexing and offline data indexing in different time periods is realized by introducing the data query index. Therefore, the consistency of data processing results in different environments can be better ensured.
With further reference to fig. 6, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a data processing apparatus, which correspond to those shown in fig. 3, and which may be applied in particular to various electronic devices.
As shown in fig. 6, the data processing apparatus 600 of some embodiments includes: a first control unit 601, an update and storage unit 602, an analysis and creation index unit 603, and a second control unit 604. The first control unit 601 is configured to control the target data query index to point to a target real-time index created in advance; an update and storage unit 602 configured to perform the following data processing steps during a target time period: in response to receiving real-time data, updating the target real-time index based on the real-time data and storing the real-time data; an analyzing and indexing unit 603 configured to analyze target offline data after the end time of the target time period to obtain an analysis result, and create an index of the analysis result to obtain a target offline index, wherein the target offline data is obtained by storing real-time data received in at least one sub-time period of the target time period; the second control unit 604 is configured to control the target data query index to point to the target offline index.
In an optional implementation of some embodiments, the apparatus 600 further comprises: the sorting unit is configured to perform field sorting on the real-time data, wherein the field sorting comprises deleting a first target field and performing numerical calculation on a second target field to obtain a new field; and the updating unit is configured to update the real-time data.
In an optional implementation manner of some embodiments, at least one piece of real-time statistical information of the real-time data is stored in the target real-time index; and the update and storage unit 602 is further configured to: and analyzing the real-time data in at least one dimension to update the at least one piece of real-time statistical information, and storing the real-time data.
In an optional implementation of some embodiments, the analysis and creation indexing unit 603 is further configured to: and performing at least one-dimensional statistical analysis on the target offline data to obtain at least one piece of offline statistical information of the target offline data as the analysis result.
In an optional implementation manner of some embodiments, the index names of the target real-time index and the target offline index are generated according to information related to the target time period.
It will be understood that the elements described in the apparatus 600 correspond to various steps in the method described with reference to fig. 3. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 600 and the units included therein, and are not described herein again.
With further reference to fig. 7, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a data query apparatus, which correspond to those shown in fig. 4, and which may be applied in various electronic devices.
As shown in fig. 7, the data processing apparatus 700 of some embodiments includes: a first determination unit 701 and a second determination unit 702. The first determining unit 701 is configured to determine a target query index in a query index group in response to receiving a data query request, where the data query request includes a target query index name; a second determining unit 702, configured to determine the data in the index pointed by the target query index as the target data.
It will be understood that the units described in the apparatus 700 correspond to the various steps in the method described with reference to fig. 4. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 700 and the units included therein, and will not be described herein again.
Referring now to FIG. 8, a block diagram of an electronic device (e.g., the computing device of FIG. 1) 800 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device in some embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle-mounted terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 8, an electronic device 800 may include a processing means (e.g., central processing unit, graphics processor, etc.) 801 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage means 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data necessary for the operation of the electronic apparatus 800 are also stored. The processing apparatus 801, the ROM 802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
Generally, the following devices may be connected to the I/O interface 805: input devices 806 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 807 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage 808 including, for example, magnetic tape, hard disk, etc.; and a communication device 809. The communication means 809 may allow the electronic device 800 to communicate wirelessly or by wire with other devices to exchange data. While fig. 8 illustrates an electronic device 800 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 8 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through communications device 809, or installed from storage device 808, or installed from ROM 802. The computer program, when executed by the processing apparatus 801, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: controlling the target data query index to point to a target real-time index which is created in advance; within the target time period, the following data processing steps are performed: in response to receiving the real-time data, updating the target real-time index based on the real-time data and storing the real-time data; after the end time of the target time period, analyzing the target offline data to obtain an analysis result, and creating an index of the analysis result to obtain a target offline index, wherein the target offline data is obtained by storing real-time data received in at least one sub-time period of the target time period; and controlling the target data query index to point to the target offline index.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first control unit, an update and storage unit, an analysis and creation index unit, and a second control unit. Where the names of these units do not in some cases constitute a limitation on the units themselves, for example, the first control unit may also be described as a "unit controlling the target data query index to point to a pre-created target real-time index".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
According to one or more embodiments of the present disclosure, there is provided a data processing method including: controlling the target data query index to point to a target real-time index which is created in advance; within the target time period, the following data processing steps are performed: in response to receiving the real-time data, updating the target real-time index based on the real-time data and storing the real-time data; after the end time of the target time period, analyzing the target offline data to obtain an analysis result, and creating an index of the analysis result to obtain a target offline index, wherein the target offline data is obtained by storing real-time data received in at least one sub-time period of the target time period; and controlling the target data query index to point to the target offline index.
According to one or more embodiments of the present disclosure, before the updating the target real-time index based on the real-time data and storing the real-time data, the method further includes: performing field arrangement on the real-time data, wherein the field arrangement comprises deleting a first target field and performing numerical calculation on a second target field to obtain a new field; and updating the real-time data.
According to one or more embodiments of the present disclosure, at least one real-time statistic information of the real-time data is stored in the target real-time index; and the updating the target real-time index based on the real-time data includes: and analyzing the real-time data in at least one dimension to update the at least one piece of real-time statistical information.
According to one or more embodiments of the present disclosure, analyzing target offline data to obtain an analysis result includes: and performing at least one-dimensional statistical analysis on the target offline data to obtain at least one piece of offline statistical information of the target offline data as the analysis result.
According to one or more embodiments of the present disclosure, the index names of the target real-time index and the target offline index are generated according to information related to the target time period.
According to one or more embodiments of the present disclosure, there is provided a data processing apparatus including: a first control unit configured to control the target data query index to point to a pre-created target real-time index; an update and storage unit configured to perform the following data processing steps during a target time period: in response to receiving real-time data, updating the target real-time index based on the real-time data and storing the real-time data; an analysis and index creation unit configured to analyze target offline data after the end time of the target time period to obtain an analysis result, and create an index of the analysis result to obtain a target offline index, the target offline data being obtained by storing real-time data received in at least one sub-time period of the target time period; and the second control unit is configured to control the target data query index to point to the target offline index.
According to one or more embodiments of the present disclosure, there is provided a data query method including: in response to receiving a data query request, determining a target query index in a query index group, wherein the data query request comprises a target query index name; and determining the data in the index pointed by the target query index as target data.
According to one or more embodiments of the present disclosure, there is provided a data query apparatus including: a first determining unit configured to determine a target query index in a query index group in response to receiving a data query request, the data query request including a target query index name; and the second determining unit is configured to determine the data in the index pointed by the target query index as the target data.
According to one or more embodiments of the present disclosure, there is provided an electronic device including: one or more processors; a storage device having one or more programs stored thereon which, when executed by one or more processors, cause the one or more processors to implement a method as in any above.
According to one or more embodiments of the present disclosure, a computer-readable medium is provided, on which a computer program is stored, wherein the program, when executed by a processor, implements the method as any one of the above.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. A method of data processing, comprising:
controlling the target data query index to point to a target real-time index which is created in advance;
within the target time period, the following data processing steps are performed:
in response to receiving real-time data, updating the target real-time index based on the real-time data and storing the real-time data;
after the end time of the target time period, analyzing target offline data to obtain an analysis result, and creating an index of the analysis result to obtain a target offline index, wherein the target offline data is obtained by storing real-time data received in at least one sub-time period of the target time period;
and controlling the target data query index to point to the target offline index.
2. The method of claim 1, wherein prior to the updating the target real-time index based on the real-time data and storing the real-time data, the method further comprises:
performing field arrangement on the real-time data, wherein the field arrangement comprises deleting a first target field and performing numerical calculation on a second target field to obtain a new field;
and updating the real-time data.
3. The method of claim 1, wherein the target real-time index has at least one real-time statistic of the real-time data stored therein; and
the updating the target real-time index based on the real-time data includes:
performing at least one dimensional analysis on the real-time data to update the at least one real-time statistic.
4. The method of claim 1, wherein analyzing the target offline data to obtain an analysis result comprises:
and performing statistical analysis of at least one dimension on the target offline data to obtain at least one piece of offline statistical information of the target offline data as the analysis result.
5. The method of claim 1, wherein index names of the target real-time index and the target offline index are generated from information related to the target time period.
6. A method of data query, comprising:
in response to receiving a data query request, determining a target query index in a query index group, wherein the data query request comprises a target query index name;
and determining the data in the index pointed by the target query index as target data.
7. A data processing apparatus comprising:
a first control unit configured to control the target data query index to point to a pre-created target real-time index;
an update and storage unit configured to perform the following data processing steps during a target time period:
in response to receiving real-time data, updating the target real-time index based on the real-time data and storing the real-time data;
an analysis and creation index unit configured to analyze target offline data after an end time of the target time period to obtain an analysis result, and create an index of the analysis result to obtain a target offline index, the target offline data being obtained by storing real-time data received in at least one sub-time period of the target time period;
a second control unit configured to control the target data query index to point to the target offline index.
8. A data query apparatus, comprising:
a first determining unit configured to determine a target query index in a query index group in response to receiving a data query request, the data query request including a target query index name;
a second determining unit configured to determine data in the index pointed to by the target query index as target data.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011034773.3A CN112115154A (en) | 2020-09-27 | 2020-09-27 | Data processing and data query method, device, equipment and computer readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011034773.3A CN112115154A (en) | 2020-09-27 | 2020-09-27 | Data processing and data query method, device, equipment and computer readable medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112115154A true CN112115154A (en) | 2020-12-22 |
Family
ID=73797009
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011034773.3A Pending CN112115154A (en) | 2020-09-27 | 2020-09-27 | Data processing and data query method, device, equipment and computer readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112115154A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112800074A (en) * | 2021-01-27 | 2021-05-14 | 北京字跳网络技术有限公司 | Offline data management method, device, terminal equipment, system and readable medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184222A (en) * | 2011-05-05 | 2011-09-14 | 杭州安恒信息技术有限公司 | Quick searching method in large data volume storage |
| CN106162675A (en) * | 2015-03-25 | 2016-11-23 | 中兴通讯股份有限公司 | A kind of data processing method based on call reminding, Apparatus and system |
| CN107707487A (en) * | 2017-09-20 | 2018-02-16 | 杭州安恒信息技术有限公司 | The real-time retrieval system and real-time search method of a kind of network service traffic |
| CN108694188A (en) * | 2017-04-07 | 2018-10-23 | 腾讯科技（深圳）有限公司 | A kind of newer method of index data and relevant apparatus |
| CN108804594A (en) * | 2018-05-28 | 2018-11-13 | 国家计算机网络与信息安全管理中心 | A kind of construction method and device of news content full-text search engine |
-
2020
- 2020-09-27 CN CN202011034773.3A patent/CN112115154A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184222A (en) * | 2011-05-05 | 2011-09-14 | 杭州安恒信息技术有限公司 | Quick searching method in large data volume storage |
| CN106162675A (en) * | 2015-03-25 | 2016-11-23 | 中兴通讯股份有限公司 | A kind of data processing method based on call reminding, Apparatus and system |
| CN108694188A (en) * | 2017-04-07 | 2018-10-23 | 腾讯科技（深圳）有限公司 | A kind of newer method of index data and relevant apparatus |
| CN107707487A (en) * | 2017-09-20 | 2018-02-16 | 杭州安恒信息技术有限公司 | The real-time retrieval system and real-time search method of a kind of network service traffic |
| CN108804594A (en) * | 2018-05-28 | 2018-11-13 | 国家计算机网络与信息安全管理中心 | A kind of construction method and device of news content full-text search engine |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112800074A (en) * | 2021-01-27 | 2021-05-14 | 北京字跳网络技术有限公司 | Offline data management method, device, terminal equipment, system and readable medium |
| CN112800074B (en) * | 2021-01-27 | 2023-09-15 | 北京字跳网络技术有限公司 | Offline data management method, device, terminal equipment, system and readable medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111581563A (en) | Page response method and device, storage medium and electronic equipment | |
| CN110781373B (en) | List updating method and device, readable medium and electronic equipment | |
| CN110909521A (en) | Synchronous processing method and device for online document information and electronic equipment | |
| CN115757400A (en) | Data table processing method and device, electronic equipment and computer readable medium | |
| CN111857720A (en) | Method and device for generating user interface state information, electronic equipment and medium | |
| CN115357350A (en) | Task configuration method and device, electronic equipment and computer readable medium | |
| CN113190517A (en) | Data integration method and device, electronic equipment and computer readable medium | |
| CN112115154A (en) | Data processing and data query method, device, equipment and computer readable medium | |
| CN111756953A (en) | Video processing method, device, equipment and computer readable medium | |
| CN111241137A (en) | Data processing method and device, electronic equipment and storage medium | |
| CN111262907A (en) | Service instance access method and device and electronic equipment | |
| CN112507676B (en) | Method and device for generating energy report, electronic equipment and computer readable medium | |
| CN112100211B (en) | Data storage method, apparatus, electronic device, and computer readable medium | |
| CN114490718A (en) | Data output method, data output device, electronic equipment and computer readable medium | |
| CN111143355B (en) | Data processing method and device | |
| CN114428925A (en) | Page rendering method and device, electronic equipment and computer readable medium | |
| CN112100205A (en) | Data processing method, device, equipment and computer readable medium | |
| CN112100159A (en) | Data processing method and device, electronic equipment and computer readable medium | |
| CN111580890A (en) | Method, apparatus, electronic device, and computer-readable medium for processing features | |
| CN112799863A (en) | Method and apparatus for outputting information | |
| CN111291254A (en) | Information processing method and device | |
| CN111857879B (en) | Data processing method, device, electronic equipment and computer readable medium | |
| CN111294321B (en) | Information processing method and device | |
| CN114428823B (en) | Data linkage method, device, equipment and medium based on multidimensional variable expression | |
| CN116880909A (en) | Offline device identification method, device, electronic device and computer readable medium |
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 |