CN107341084B - Data processing method and device - Google Patents
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Abstract
The application discloses a data processing method and device, in the method, after a first system in a first machine room obtains streaming data, Map processing can be carried out on the streaming data, a first processing result is obtained, then the first processing result obtained by the first system is sent to a second system in a second machine room, and therefore the second system can obtain a second processing result according to the obtained first processing result sent by the first system. The first system processes the acquired streaming data to obtain a first processing result, and compared with the acquired streaming data, the data volume is greatly reduced, so that the data transmission volume across the machine room can be greatly reduced, the time consumed in data transmission across the machine room is shortened, and the data processing efficiency is improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for data processing.
Background
With the continuous development of big data technology, people can analyze and process massive data through the big data technology to obtain a relatively accurate analysis result, and perform activities such as business analysis and market conditions conjecture by using the obtained analysis result, thereby bringing instructive information for subsequent production and life of people.
Currently, when people perform streaming processing by using a big data technology, generally, mass streaming data acquired in multiple machine rooms are collected into one machine room, and then the mass streaming data are processed by the machine room collecting the mass streaming data, and the processed result is output, as shown in fig. 1.
Fig. 1 is a schematic diagram of streaming processing of big data provided by the prior art.
Assuming that operation and maintenance personnel need to count a service in real time through streaming processing, mass streaming data of the service can be acquired in real time through the machine rooms 1-4, and then the operation and maintenance personnel need to transmit and collect the mass streaming data acquired in real time in the machine rooms 1-4 to the machine room 5 through a network, and each server in the machine room 5 can store the collected mass streaming data in respective data queues. For each server in the computer room 5, the server may process the massive streaming data in its data queue in a preset data processing manner, and obtain a corresponding processing result. Each server in the computer room 5 (i.e. the server that obtains the mass streaming data) may send the processing result obtained by itself to one server in the computer room 5, so that the server may further process each collected processing result to obtain and output the final processing result.
However, the data amount transmitted from the machine rooms 1 to 4 to the machine room 5 is too large, and due to the fact that data are transmitted across the machine rooms, network delay is large, in the prior art, in the process of collecting massive streaming data in one machine room for data processing, time consumed for data transmission across the machine rooms is long, data transmission efficiency is low, and accordingly efficiency of streaming data processing is low.
Disclosure of Invention
The embodiment of the application provides a data processing method, which is used for solving the problem of low efficiency in cross-machine room flow data processing in the prior art.
The embodiment of the application provides a data processing method, which comprises the following steps:
a first system acquires and stores streaming data, wherein the first system is positioned in a first machine room;
map processing is carried out on the stored streaming data to obtain a first processing result, and the data volume of the first processing result is smaller than that of the streaming data;
and sending the first processing result to a second system so that the second system obtains a second processing result according to the first processing result, wherein the second system is positioned in a second machine room.
The embodiment of the application provides a data processing system, which is used for solving the problem of low efficiency in cross-machine room flow type data processing in the prior art.
An embodiment of the present application provides a data processing system, including: the system comprises at least one business server, at least one storage server and at least one first processing server, wherein the system is positioned in a first machine room;
the service server acquires streaming data;
the storage server acquires the streaming data from the service server and stores the streaming data;
and the first processing server performs Map processing on the streaming data stored by the storage server to obtain a first processing result.
The embodiment of the application provides a data processing method, which is used for solving the problem of low efficiency in cross-machine room flow data processing in the prior art.
The embodiment of the application provides a data processing method, which comprises the following steps:
a second system obtains a first processing result obtained by at least one first system, wherein the second system is positioned in a second machine room;
and performing Reduce processing on the obtained first processing result to obtain a second processing result.
The embodiment of the application provides a data processing system, which is used for solving the problem of low efficiency in cross-machine room flow type data processing in the prior art.
An embodiment of the present application provides a data processing system, including: the system comprises at least one acquisition server and at least one second processing server, wherein the system is positioned in a second machine room;
the acquisition server acquires a first processing result obtained by at least one first system;
and the second processing server performs Reduce processing on the first processing result acquired by the at least one acquisition server to acquire a second processing result.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
in this embodiment of the application, after acquiring streaming data, a first system in a first machine room may perform Map processing on the streaming data, obtain a first processing result, and then send the first processing result obtained by the first system to a second system in a second machine room, so that the second system may obtain a second processing result according to the obtained first processing result sent by the first system. The first system processes the acquired streaming data to obtain a first processing result, and compared with the acquired streaming data, the data volume is greatly reduced, so that the data transmission volume across the machine room can be greatly reduced, the time consumed in data transmission across the machine room is shortened, and the data processing efficiency is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic diagram of streaming big data provided by the prior art;
FIG. 2 is a schematic diagram of a data processing process provided in an embodiment of the present application;
fig. 3 is a schematic architecture diagram of a first system according to an embodiment of the present application;
fig. 4 is a schematic architecture diagram of a second system according to an embodiment of the present application;
fig. 5 is a schematic diagram illustrating that a plurality of first systems collect respective first processing results into one second system for processing according to the embodiment of the present application.
Detailed Description
In the embodiment of the application, the whole data processing process can be summarized as that the Map processing is performed on the streaming data acquired in real time, and the Reduce processing is further performed on the result obtained by the Map processing, so that the final processing result is obtained. The obtaining of the streaming data and the Map processing of the streaming data may be completed by the first system, and the result obtained by the Map processing may be further subjected to Reduce processing, and the final processing result may be completed by the second system. In other words, the data processing process described in this embodiment of the present application may be split into two parts by taking Map processing as a boundary, where the former part (i.e., Map processing is performed on the obtained streaming data to obtain a first processing result) may be performed by a first system, and the latter part (i.e., obtaining the first processing result, and performing Reduce processing on the obtained first processing result to obtain a second processing result) may be performed by a second system, where the first system and the second system may be different systems, and accordingly, the first system and the second system may be located in different machine rooms. In the embodiment of the present application, a machine room including the first system may be referred to as a first machine room, and a machine room including the second system may be referred to as a second machine room.
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 2 is a schematic diagram of a data processing process provided in an embodiment of the present application, which specifically includes the following steps:
s201: the first system acquires and stores streaming data.
In this embodiment of the application, when an operation and maintenance person needs to perform operations such as monitoring and analysis on at least one service in real time in a streaming processing manner, streaming data generated by the at least one service may be acquired through the first system. In practical application, a plurality of first systems for executing a plurality of service processing jobs may exist and be located in different machine rooms. For example, in practical application, one service platform corresponds to a plurality of first systems, and these systems may be divided into first rooms belonging to different areas and are responsible for processing a plurality of services belonging to the areas.
The first system may obtain streaming data generated by at least one service, and may also process the obtained streaming data to obtain a first processing result, where a specific processing procedure will be specifically described in subsequent steps.
In this embodiment, the first system may acquire the streaming data from a service processing process of a user. Specifically, during the service processing, the user may send the service information to the first system in the first computer room, and the first system may use the service information sent by the user as streaming data.
The user can also send the service information to the first system, and after the first system obtains the service information sent by the user, the first system can perform corresponding service processing according to the service information sent by the user, obtain a service log, and further use the obtained service log as streaming data. Of course, the streaming data mentioned here may also be other forms of data, and in the embodiment of the present application, the specific manner by which the streaming data is determined may be determined by the specific real-time operation to be performed by the operation and maintenance personnel on at least one service.
In an embodiment of the present application, the first system in the first computer room may be composed of a plurality of servers, in which different classes of servers have different task responsibilities, as shown in fig. 3.
Fig. 3 is a schematic architecture diagram of a first system according to an embodiment of the present application.
In fig. 3, the servers included in the first system may be roughly divided into three types, one type of server may be referred to as a service server, and the service server is responsible for acquiring streaming data, one type of server may be referred to as a storage server, and the storage server may store the streaming data acquired by the service server, and the other type of server may be referred to as a first processing server, and such a server may acquire the streaming data stored by the storage server from the storage server and perform data processing on the acquired streaming data to obtain a first processing result.
The storage server may store the streaming data acquired by the service server in a form of a data queue, so that a subsequent first processing server may acquire the streaming data from the data queue of the storage server. Of course, the storage server may also store the streaming data acquired by the service server by using other caching methods, which is not illustrated herein.
In this embodiment of the application, the storage server may store the streaming data acquired by the service server in the form of a data queue, because in addition to ensuring that the streaming data can be acquired and processed by the first processing server in real time, no matter whether the storage server in the first system actively sends the streaming data in the data queue to the first processing server or the first processing server actively acquires the streaming data in the data queue from the storage server, once the streaming data is acquired by the first processing server, the streaming data will be removed from the data queue. Therefore, other first processing servers in the first system cannot acquire the streaming data from the data queue of the storage server, so that the situation that each first processing server in the first system repeatedly acquires the streaming data from the same data queue is avoided, and the accurate and effective second processing result can be obtained through a second system of a second machine room subsequently.
Of course, if the storage server in the first system does not use the form of the data queue to cache the streaming data, it is necessary to ensure that each first processing server in the first system does not acquire the same streaming data.
If the storage server in the first system actively sends the streaming data to the first processing server, for a part of the streaming data stored by the storage server, if the storage server has already successfully sent the part of the streaming data to one first processing server, the storage server cannot send the part of the streaming data to other first processing servers. In other words, when the storage server actively sends the streaming data to the first processing server, one streaming data can only be correspondingly sent to one first processing server.
If the first processing server actively acquires the streaming data from the storage server, the storage server may lock the streaming data acquired by the first processing server, so that when other first processing servers in the first system acquire the streaming data from the storage server, the other first processing servers find that the streaming data is already in a locked state, and thus it may be determined that the streaming data has already been acquired by other first processing servers, and further, the streaming data is not acquired any more.
The method for locking the streaming data acquired by the first processing server by the storage server may be as follows: when the storage server determines that the streaming data stored by the storage server is acquired by a certain first processing server, the storage server may add identification information to the streaming data. In this way, when the other first processing server finds that the streaming data stored in the storage server has been added with the identification information, it can be determined that the streaming data has been acquired by the other first processing server, and thus the streaming data will not be acquired any more. Of course, there are many ways for the storage server to lock the streaming data that the first processing server has acquired, and this is not necessarily illustrated here.
It should be noted that, the first system may include, in addition to the service server, the storage server and the first processing server described above, other software and hardware devices, such as a gateway, a router, a load balancing device, and the like, which may be used for data communication between the cross-machine room and between the servers in the machine room. For example, the first system may not be divided into a storage server and a first processing server, and the two tasks of storing the streaming data and processing the streaming data to obtain the first processing result may be performed by one server.
S202: and performing Map processing on the stored streaming data to obtain a first processing result, wherein the data volume of the first processing result is smaller than that of the streaming data.
For each first system, after the storage server included in the first system stores the streaming data acquired by the service server, the first processing server in the first system may acquire the part of the streaming data from the storage server.
For each storage server included in the first system, when the storage server actively sends the streaming data stored in the storage server to the first processing server in the first system, one (or more) first processing servers may be randomly selected from the first processing servers included in the first system, and the stored streaming data is actively sent to the first processing server. The storage server may also select one (or more) first processing servers from the first processing servers included in the first system in a load balancing manner, and further actively send the streaming data stored in the storage server to the selected first processing server.
Of course, for each first processing server in the first system, when the first processing server actively acquires streaming data from the storage server in the first system, one (or more) storage servers may be randomly selected, and the streaming data may be acquired from the selected storage server. Of course, the first processing server may also select one (or more) storage servers from the storage servers included in the first system by means of load balancing, and further obtain streaming data from the selected storage servers.
In addition, a mapping relationship may be pre-established between each storage server and each first processing server in the first system. For example, for each storage server in the first system, the mapping relation specifies which first processing servers in the first system the storage server needs to actively send its own stored streaming data to. Similarly, for each first processing server in the first system, the mapping relation specifies which storage servers included in the first system the first processing server can obtain the streaming data from.
After the first processing server in the first system acquires the streaming data from one storage server (or multiple storage servers), Map processing may be performed on the acquired streaming data, and a corresponding first processing result is obtained.
For example, it is assumed that streaming data acquired by the service server in the first system is log information of a user sending a red packet, and in practical applications, the user can send the red packet in 4 service scenarios, so that each streaming data acquired by the service server includes the log information of the user sending the red packet in the 4 service scenarios.
After the service server in the first system acquires the streaming data in real time, the storage server in the first system may store the streaming data acquired in the service server in a data queue included in the storage server. When the first processing server in the first system acquires the streaming data from one or more storage servers included in the first system, Map processing may be performed on the acquired streaming data, so that a field that identifies each service scene included in the streaming data is used as a Key, and the number of times each streaming data appears is used as a Value, so as to obtain each Key-Value pair (Key-Value). Each key value pair obtained here may be referred to as a first processing result obtained by Map processing of the acquired streaming data by the first processing server, and the content included in the first processing result may be as shown in the following table.
| Key Value pair (Key-Value) |
| (service scenarios 1, 1) |
| (service scenarios 2, 1) |
| (service scenarios 1, 1) |
| (service scenarios 3, 1) |
| (service scenarios 4, 1) |
| (service scenarios 2, 1) |
| (service scenarios 1, 1) |
| …… |
TABLE 1
In this embodiment of the application, the data size of the first processing result obtained by Map processing performed by the first processing server on the obtained streaming data is much smaller than that of the obtained streaming data, because the first processing server can remove redundant fields in the streaming data during the Map processing performed on the streaming data, only keep fields required for executing the real-time operation (i.e., processing the streaming data obtained in real time), and then obtain the first processing result according to the required fields. In practical applications, the fields required for real-time operations only occupy a small portion of the entire streaming data, so the first processing result obtained by the first processing server will be much smaller in data size than the obtained streaming data.
Correspondingly, when the first processing server subsequently sends the first processing result to the second system of the second machine room across the machine room, although the situation of large delay of data transmission across the machine room still occurs, compared with the prior art, the data volume of the first processing result sent to the second system by the first processing server is greatly reduced, so that the transmission time consumed by the first processing server to send the first processing result to the second system is also greatly reduced, the transmission efficiency of data transmission across the machine room is greatly improved, and the efficiency of data processing is improved to a certain extent.
S203: and sending the first processing result to a second system so that the second system obtains and outputs a second processing result according to the first processing result, wherein the second system is positioned in a second machine room.
The first system (located in the first machine room) may send the first processing result obtained by the first processing server to the second system through a data transmission manner across machine rooms, where the first processing server is included in the first system. However, the second system may be configured by a plurality of servers, and servers of different types may have different task responsibilities, as shown in fig. 4.
Fig. 4 is a schematic architecture diagram of a second system according to an embodiment of the present application.
In fig. 4, servers included in the second system of the second machine room may be roughly divided into two types, one type of server may be used to obtain the first processing result sent by the first processing server of the first system, and this type of server may be referred to as an obtaining server; another type of server may be configured to perform Reduce processing on the first processing result obtained by the obtaining server to obtain a second processing result, and for this type of server, this type of server may be referred to as a second processing server.
In this embodiment of the application, the second system may obtain, through a plurality of obtaining servers included in the second system, the first processing result sent by each first system (each first system may be located in a different first machine room), and directly send each obtained first processing result to one second processing server to perform Reduce processing, so as to obtain and output a second processing result. Or after the first processing result is processed to a certain extent, the intermediate processing result obtained after the first processing result is processed is finally collected into the second processing server for Reduce processing, and then the second processing result is obtained and output.
Continuing from the above, it is assumed that the first processing results respectively sent by one acquisition server in the second system (located in the second computer room) to three first processing servers in the first system (located in the first computer room) are shown in the following table.
TABLE 2
The obtaining server may further process the obtained first processing result according to the obtained plurality of first processing results, to obtain an intermediate processing result, as shown in the following table.
TABLE 3
The mechanism for obtaining the intermediate processing result by dividing the Key value contained in the first processing result by the second processing server according to the dimension of the Key (i.e., the field identifying the service scene) may be referred to as a Shuffle mechanism. Of course, in this embodiment of the application, the Shuffle mechanism may also be completed by the first processing server in the first system, that is, the first system may process the first processing result through the first processing server included in the first system and the preset Shuffle mechanism, and send the processed first processing result to the second system, where it may be understood that after the first processing result is obtained by the first processing server, the first processing result may be converted into a form shown in table 3 through the preset Shuffle mechanism, and then the first processing result in this form is sent to the second system.
In this embodiment of the application, the Shuffle mechanism may also be completed by a second processing server included in the second system, after the obtaining server in the second system obtains each first processing result from the first system, the first processing result may be directly sent to the second processing server, and then the second processing server processes the obtained first processing result through the preset Shuffle mechanism to obtain an intermediate processing result, and performs Reduce processing on the intermediate processing result to finally obtain the second processing result. Of course, after the second processing server receives at least one first processing result sent by each acquisition server, the second processing server may also directly perform Reduce processing on the acquired first processing result to obtain a second processing result.
After the second processing server obtains at least one first processing result (the first processing result may also be a processed first processing result), the second processing server may perform Reduce processing on the obtained first processing result, and then obtain and output a corresponding second processing result.
Continuing with the above example, after the second processing server obtains the first processing result obtained by each obtaining server in the second system from the first system, the second processing server may perform Reduce processing on the obtained first processing result, and obtain a second processing result as shown in the following table.
TABLE 4
In table 4, in the second processing result obtained by the second processing server, the Value indicates the number of red packets sent by the user in the service scenario, and the second processing server may count the number of red packets sent by the user in each service scenario in real time and output the number of red packets sent by the user in each service scenario in this manner.
It should be noted that, in this embodiment of the application, the second system (located in the second machine room) may also randomly designate one or more servers to obtain each first processing result sent by each first system (located in each first machine room), and similarly, may also randomly designate at least one server to perform Reduce processing on each obtained first processing result, obtain a second processing result, and output the second processing result. In addition, the second system may select a plurality of servers from the plurality of servers included in the second system in a load balancing manner, and obtain each first processing result transmitted by each first system through the selected servers. Of course, it is also possible to select at least one server from the plurality of servers included in the second system in a load balancing manner, perform Reduce processing on each obtained first processing result through the selected server, obtain a second processing result, and output the second processing result.
According to the method, the data volume is greatly reduced compared with the acquired streaming data by the first system for processing the acquired streaming data to obtain the first processing result, so that the data transmission volume across the machine room can be greatly reduced, the time consumed during data transmission across the machine room is shortened, and the data processing efficiency is improved.
It should be noted that, in the embodiment of the present application, acquiring the first processing result sent by each first system and processing each acquired first processing result to obtain the second processing result may also be completed by one server in the second system. In other words, each first processing result sent by each first system may be sent to a designated server in the second system, and the designated server is responsible for aggregating each first processing result sent by each first system, and obtaining and outputting a corresponding second processing result according to each obtained first processing result.
In the prior art, in order to prevent a data processing process from being affected due to a shutdown or the like of a machine room (e.g., the machine room 5 in fig. 1) that collects streaming data, a standby machine room is usually established at present, and the standby machine room needs to synchronously collect data and processing results obtained by the machine room that collects data in real time, so that when the machine room that collects data is shutdown, the standby machine room can effectively and timely play a disaster tolerance role, and the data processing process is not affected by the shutdown of the machine room. However, the construction of a spare machine room consumes a lot of manpower and material resources, which greatly increases the operation and maintenance costs in the data processing process.
In this embodiment, the server in the second system (located in the second machine room) does not need to receive a large amount of streaming data, and only needs to obtain each first processing result with a smaller data amount obtained by each first system (located in each first machine room), so that a corresponding second processing result can be obtained according to the obtained first processing result. Therefore, the operation and maintenance personnel do not need to establish a standby machine room for the second machine room where the second system is located, but only need to set at least one standby server in the second system, and the standby server is used for acquiring the first processing results sent by each first system from the acquisition server in the second system when the second processing server in the second system fails, such as downtime, and then replacing the second processing server in the second system which fails, performing Reduce processing on the acquired first processing results, and acquiring and outputting corresponding second processing results. Wherein the number of standby servers is not greater than the number of second servers.
In the method, it can be seen that, compared with the prior art in which a standby machine room needs to be set, the cost of setting at least one standby server for the second processing server in the second system is greatly reduced, thereby reducing the cost consumption of the data processing process.
Similarly, in the embodiment of the present application, at least one standby server may be set in the second system for the obtaining server that obtains the first processing result, so as to ensure that when the obtaining server in the second system fails, the standby server may replace the obtaining server in the second system to obtain each first processing result sent by each first system.
Of course, the above-mentioned backup server (which may be a backup server of the acquisition server, or a backup server of the second processing server) may be disposed in the second system of the second computer room, or may be disposed in a system of another computer room.
It should be further noted that, in this embodiment of the application, the first system may not include a storage server, and the storing of the streaming data may be performed by a service server in the first system, that is, the service server in the first system may obtain the streaming data and store the obtained streaming data. The service server may store the obtained streaming data in a data queue included in the service server.
Correspondingly, the first processing server in the first system may obtain the streaming data stored by the service server from the service server, and perform Map processing on the obtained streaming data to obtain a first processing result.
In order to further explain the data processing method provided by the embodiment of the present application, the following will briefly explain the whole data processing process in a practical scenario of multiple first systems.
Fig. 5 is a schematic diagram illustrating that a plurality of first systems collect respective first processing results into one second system for processing according to the embodiment of the present application.
For each first system, the service server in the first system (located in the first computer room) may store the obtained streaming data in a storage server included in the first system, where the storage server may store the streaming data obtained by the service server in the form of a data queue. The first processing server in the first machine room may acquire streaming data from the data queue of the storage server, and then perform Map processing on the acquired streaming data to obtain a first processing result.
Each first system can obtain at least one first processing result through at least one first processing server contained in the first system, process the obtained first processing result through a preset shuffle mechanism, and send the processed first processing result to the same second system (located in a second machine room). The second system can acquire each first processing result sent by each first system through the acquisition server contained in the second system, and perform Reduce processing on each first processing result acquired by the acquisition server through the second processing server contained in the second system, so as to finally obtain and output a second processing result.
In the above embodiment, each first system may be a machine room capable of performing actual service processing, and the second system may be a machine room dedicated to collect the first processing results sent by each first system and obtain the second processing results. Of course, the machine room in which the second system is located may also be one machine room selected from the first machine rooms in which the first systems are located, in other words, the first system of each first machine room may have a capability of aggregating the first processing results generated by other first systems and obtaining the second processing result by combining the first processing results generated by the first system with the first processing results generated by the first system in addition to the capability of performing actual services.
In this embodiment of the application, after acquiring streaming data, a first system in a first machine room may perform Map processing on the streaming data, obtain a first processing result, and then send the first processing result obtained by the first system to a second system in a second machine room, so that the second system may obtain and output a second processing result according to the obtained first processing result sent by the first system. The first system processes the acquired streaming data to obtain a first processing result, and compared with the acquired streaming data, the data volume is greatly reduced, so that the data transmission volume across the machine room can be greatly reduced, the time consumed in data transmission across the machine room is shortened, and the data processing efficiency is improved.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, 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, 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.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, 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 apparatus 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 apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application 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.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of data processing, comprising:
a first system acquires and stores streaming data, wherein the first system is positioned in a first machine room;
map processing is carried out on the stored streaming data to obtain a first processing result, and the data volume of the first processing result is smaller than that of the streaming data;
sending the first processing result to a second system so that the second system obtains a second processing result according to the first processing result, wherein the second system is located in a second machine room;
the Map processing is performed on the stored streaming data to obtain a first processing result, and the method includes:
removing redundant fields in the streaming data by using a first processing server, reserving fields required for executing real-time operation, and obtaining a first processing result according to the required fields;
and the second processing result is a processing result obtained by the second system performing Reduce processing on the obtained first processing result.
2. The method of claim 1, the first system comprising: at least one business server, at least one storage server and at least one first processing server;
the first system acquires and stores streaming data, and specifically comprises:
the first system acquires the streaming data through the service server, and acquires and stores the streaming data from the service server through the storage server;
performing Map processing on the stored streaming data to obtain a first processing result, which specifically includes:
and performing Map processing on the streaming data stored by the storage server through the first processing server to obtain the first processing result.
3. The method according to claim 2, wherein sending the first processing result to a second system specifically comprises:
and processing the first processing result through the first processing server and a preset Shuffle mechanism, and sending the processed first processing result to a second system.
4. A method of data processing, comprising:
a second system obtains a first processing result obtained by at least one first system, wherein the second system is positioned in a second machine room;
reducing the obtained first processing result to obtain a second processing result;
the processing method includes that the first processing result is obtained by Map processing of stored streaming data by the first system, and the Map processing of the stored streaming data is performed to obtain the first processing result, and includes:
and removing redundant fields in the streaming data by using a first processing server, reserving fields required for executing real-time operation, and obtaining a first processing result according to the required fields.
5. The method of claim 4, wherein the second system comprises at least one acquisition server and at least one second processing server;
the second system obtaining a first processing result obtained by at least one first system specifically includes:
acquiring a first processing result obtained by at least one first system through at least one acquisition server included in the second system;
reduce processing is carried out to the first processing result who obtains, obtains the second processing result and outputs, specifically includes:
and performing Reduce processing on the first processing result acquired by the at least one acquisition server through the second processing server to obtain the second processing result.
6. The method according to claim 5, wherein the second system further comprises at least one backup server, and the at least one backup server is configured to perform Reduce processing on the first processing result obtained by the at least one obtaining server through the at least one backup server to obtain a second processing result when the at least one second processing server fails.
7. A system for data processing, comprising: the system comprises at least one business server, at least one storage server and at least one first processing server, wherein the system is positioned in a first machine room;
the service server acquires streaming data;
the storage server acquires the streaming data from the service server and stores the streaming data;
the first processing server performs Map processing on the streaming data stored by the storage server to obtain a first processing result;
the first processing server is specifically configured to:
removing redundant fields in the streaming data by using a first processing server, reserving fields required for executing real-time operation, and obtaining a first processing result according to the required fields;
and the second processing result is a processing result obtained by the second system performing Reduce processing on the obtained first processing result.
8. The system of claim 7, wherein the first processing server processes the first processing result through a preset Shuffle mechanism, and sends the processed first processing result to a second system, and the second system is located in a second computer room.
9. A system for data processing, comprising: the system comprises at least one acquisition server and at least one second processing server, wherein the system is positioned in a second machine room;
the acquisition server acquires a first processing result obtained by at least one first system;
the second processing server is used for carrying out Reduce processing on the first processing result obtained by the at least one obtaining server to obtain a second processing result;
the processing method includes that the first processing result is obtained by Map processing of stored streaming data by the first system, and the Map processing of the stored streaming data is performed to obtain the first processing result, and includes:
and removing redundant fields in the streaming data by using a first processing server, reserving fields required for executing real-time operation, and obtaining a first processing result according to the required fields.
10. The system of claim 9, further comprising: at least one backup server;
and the standby server performs Reduce processing on the first processing result acquired by the at least one acquisition server to obtain a second processing result when determining that the at least one second processing server fails.
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