CN111414387B - Method and equipment for querying streaming data based on full-memory calculation - Google Patents
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- CN111414387B CN111414387B CN202010189737.8A CN202010189737A CN111414387B CN 111414387 B CN111414387 B CN 111414387B CN 202010189737 A CN202010189737 A CN 202010189737A CN 111414387 B CN111414387 B CN 111414387B
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Abstract
The invention discloses a method and a device for inquiring streaming data based on full memory calculation, wherein the method comprises the following steps: the method comprises the steps of receiving a data query request sent by a user, determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is a stream adaptation process and a stream connection process, the event window is a window for receiving and accumulating the stream data in the stream connection process, and then returning the query result to the user.
Description
Technical Field
The present application relates to the field of real-time stream data processing, and more particularly, to a method and an apparatus for querying stream data based on full memory computation.
Background
The stream data is a group of sequential, large-volume, rapid and continuous arriving data sequences, and generally, the stream data can be regarded as a dynamic data set which grows infinitely along with the time duration and is applied to the fields of network monitoring, sensor networks, aerospace, meteorological measurement and control, financial services and the like.
In the prior art, data processing is mainly divided into two modes of batch processing and micro-batch processing.
The batch processing technology based on the disk is mainly used for processing historical data, namely managing and operating "static" data, and mainly operates a large-capacity, bounded and persistent-storage static data set, and the processing mode has the following defects when oriented to stream data: firstly, the processed data is bounded, that is, the processed data is limited in amount and limited to a limited data set, and is not suitable for operation by unbounded stream data; secondly, batch processing depends heavily on persistent storage, each task needs to execute reading and writing operations for many times, frequently interacts with a disk, is limited by a certain time node or data scale during data processing, and returns a calculation result after the calculation process is completed, so that the query performance is low, the response speed is slow, the processing performance always has large delay, and the delay is continuously increased along with the continuous increase of the data amount.
In order to improve the processing efficiency of the streaming data, the continuous streaming data is processed by simulating streaming processing in a micro-batch processing mode. Despite the significant reduction in latency, the bounded nature of the amount of data processed remains unsolved, making it difficult to meet real-time (or near real-time) processing and analysis requirements for streaming data, especially where the amount of data is large and continues to increase, the latency becomes increasingly significant.
Therefore, in the prior art, when stream data is queried, only bounded data can be queried, the response speed is low, and the processing efficiency is low.
Disclosure of Invention
Aiming at the problems of limited data query, low response speed and low processing efficiency in the process of querying stream data in the prior art, the invention provides a method for querying stream data based on full-memory computation, which is applied to a memory system comprising a plurality of memory databases connected in parallel, and comprises the following steps:
receiving a data query request sent by a user;
determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process;
and returning the query result to the user.
Preferably, before receiving a data query request issued by a user, the method further comprises:
obtaining a notification including the amount of streaming data based on a listening streaming data event, the streaming data event being triggered when the streaming data enters the memory system;
establishing the stream processing progress matched with the number according to the notification;
writing the stream data into a preset named pipeline according to a preset format based on the stream adaptation process, wherein the stream adaptation process corresponds to the named pipeline one by one;
receiving and accumulating the stream data in the named pipe based on the event window, wherein the event window is established synchronously with the stream processing progress.
Preferably, after returning the query result to the user, the method further includes:
and deleting or storing the data in the query result.
Preferably, the preset format is comma separated value CSV format, and the named pipe is Linux named pipe.
Preferably, the event window is closed when there is no streaming data entering the memory system.
Correspondingly, the invention also provides a device for querying streaming data based on full-memory computing, which is applied to a memory system comprising a plurality of memory databases connected in parallel, and comprises:
the receiving module is used for receiving a data query request sent by a user;
a determining module, configured to determine a query result from an event window of a stream processing process of stream data according to the data query request, where the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process;
and the return module is used for returning the query result to the user.
Preferably, the method further comprises the following steps:
an obtaining module configured to obtain a notification including the number of the stream data based on a stream data monitoring event, where the stream data event is triggered when the stream data enters the memory system;
the writing module is used for writing the stream data into a preset named pipeline according to a preset format based on the stream adaptation process, and the stream adaptation process corresponds to the named pipeline one by one;
and the accumulation module is used for receiving and accumulating the stream data in the named pipeline based on the event window, and the event window is established synchronously with the stream processing process.
Preferably, the data processing module is further included for:
and deleting or storing the data in the query result.
Preferably, the preset format is a comma separated value CSV format, and the named pipe is a Linux named pipe.
Preferably, the system further comprises a closing module for:
and closing the event window when the streaming data entering the memory system does not exist.
The invention discloses a method and a device for inquiring streaming data based on full memory calculation, wherein the method comprises the following steps: the method comprises the steps of receiving a data query request sent by a user, determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is a stream adaptation process and a stream connection process, the event window is a window for receiving and accumulating the stream data in the stream connection process, and then returning the query result to the user.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart illustrating a method for querying streaming data based on full-memory computation according to an embodiment of the present application;
fig. 2 is a schematic flowchart illustrating a method for querying streaming data based on full-memory computation according to another embodiment of the present application;
fig. 3 is a schematic flowchart illustrating a method for querying streaming data based on full-memory computation according to yet another embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a method for querying streaming data based on full-memory computation according to another embodiment of the present application;
fig. 5 is a schematic structural diagram illustrating a device for querying streaming data based on full-memory computation according to an embodiment of the present application;
FIG. 6 is a schematic diagram illustrating a prior art disk-based batch processing technique proposed by an embodiment of the present application;
fig. 7 is a schematic process diagram illustrating a method for querying streaming data based on full-memory computation according to an embodiment of the present application;
fig. 8 shows a schematic process diagram of the stream adaptation process delivering the stream data in the embodiment of the present application.
Detailed Description
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.
With the development of various industries in modern society, the information of stream data of various industries is more and more huge, and the processing of a set of data sequence which is sequentially, massively, rapidly and continuously arrived, such as stream data, is more and more important.
The inventor finds in research that processing of stream data in various industries is processing of historical data, data processed by a disk-based batch processing technology in the prior art is bounded and is limited to a limited data set, the disk-based batch processing technology depends heavily on persistent storage, each task needs to perform multiple read and write operations, the data processing is limited by a certain time node or data size, the result is returned after the calculation process is completed, the query performance is low, the response speed is slow, the processing performance is delayed greatly, and the delay is more obvious as the data amount is increased.
Specifically, as shown in fig. 6, in the batch processing technology based on a disk in the prior art, a received data stream is stored in the disk first, when an application sends an inquiry signal to a memory system, the memory system needs to load data from the disk first, and then the memory system performs calculation and returns a result to the application.
However, in the prior art, the micro batch processing method processes the continuous data stream by simulating stream processing, and also cannot solve the problem of the boundedness of the processed data, so that the real-time (or near real-time) processing and analyzing requirements of the stream data are difficult to meet.
Therefore, the inventor proposes a method for querying streaming data based on full memory computation, which can improve the above problems.
In order to further illustrate the technical idea of the present invention, embodiments of the present application will be specifically described below with reference to the accompanying drawings and specific application scenarios so as to explain the technical solution of the present invention.
Full memory, i.e., data, is not only computed in memory, but is also stored in memory. And (4) full-memory calculation, namely, data needs to be completely loaded into a memory for calculation, and the database based on the full-memory calculation is a full-memory database.
Referring to fig. 1, an embodiment of the present application provides a method for querying streaming data based on full-memory computation, which is applied to a memory system including a plurality of memory databases connected in parallel, where the method includes:
step S101: and receiving a data query request sent by a user.
It can be understood that, when inquiring streaming data, it is necessary to receive a data inquiry request from a user through a terminal device.
It should be noted that the memory system proposed in the present application is a memory system including a plurality of full memory databases connected in parallel, and the system further stores at least one full memory database instance operated by the plurality of memory databases in parallel, the terminal device may be different terminal devices such as a mobile phone and a personal computer, and the protection range of the present application is not affected by different devices applied by a user or different ways of sending a data query request.
Step S102: determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process.
In order to quickly query real-time stream data, an event window and its corresponding configuration, i.e. a stream processing process, are created for real-time query computation, and a stream adaptation process and a stream connection process in the stream processing process are created synchronously, wherein the event window receives and accumulates stream data and provides a query, and the size of the event window generally depends on the size of a stream data event.
Specifically, an event window is arranged in a stream processing process of the stream data, when the memory system provided by the application receives the stream data, the stream data is received and accumulated through the event window so as to facilitate subsequent query operation, after the memory system receives a data query request from a user in the above steps, the data query request is sent to the event window for access query, that is, the event window is used for receiving, accumulating and processing the stream data, and meanwhile, when the user sends the query request, the data accumulated in the event window is used for completing access query of the stream and returning a query result.
Step S103: and returning the query result to the user.
Specifically, as shown in fig. 7, after the user sends a data query request to the memory system provided in the present application, the user returns a query result to the user after completing the access query of the stream through the event window.
The method for inquiring the streaming data based on the full-memory calculation receives a data inquiry request sent by a user, determines an inquiry result from an event window of a streaming processing process of streaming data according to the data inquiry request, wherein the streaming processing process is a stream adaptation process and a stream connection process, the event window is a window for receiving and accumulating the streaming data in the stream connection process, and then returns the inquiry result to the user.
Referring to fig. 2, another embodiment of the present application provides a method for querying a data stream based on full memory computation, which is applied to a memory system including a plurality of memory databases connected in parallel, where the method includes:
step S201: obtaining a notification including the amount of streaming data based on a snoop streaming data event, the data event being triggered when the streaming data enters a memory system.
Specifically, the memory system provided by the present application may set a stream data event listener at a stream data receiving end, and once stream data enters, the stream data event listener may determine the amount of the stream data, and may send a determination result to the full memory database instance in the memory system of the present application in a form of notification, where the stream data event is triggered when the stream data enters the memory system of the present application.
Step S202: and establishing a stream processing process matched with the number according to the notification, wherein the stream processing process specifically comprises a stream adaptation process and a stream connection process.
Specifically, the full-memory stream database instance in the memory system receives a notification sent by a stream data event listener, determines the amount of stream data according to the notification, and then creates one or more stream data adapters and stream data connectors, i.e., a stream adaptation process and a stream connection process, according to the amount, where the stream adaptation process and the stream connection process are the stream processing process in the present application.
Step S203: and writing the stream data into a preset named pipeline according to a preset format based on the stream adaptation process, wherein the stream adaptation process corresponds to the named pipeline one by one.
Specifically, the stream adaptation process converts the stream data in the original format into the stream data in the preset format, and writes the converted stream data into a preset named pipeline, where the preset format may be a comma separated value CSV format, and the named pipeline may be a Linux pipeline.
Specifically, as shown in fig. 8, the stream adaptation process converts stream data from an original format into a data stream in a preset format, writes the stream data converted into the preset format into a preset naming pipeline, so as to perform data transmission, then connects the transmitted stream data with a stream connection process corresponding to the stream adaptation process, and the stream connection process processes the stream data after format conversion using an event window, and accumulates the stream data after format conversion in the event window, and once a user sends a query request, the data accumulated in the event window is used to complete an access query on the stream, where it is to be noted that the stream adaptation process is implemented by a stream adapter, and the stream connection process is implemented by a stream connector.
The stream adaptation processes are in one-to-one correspondence with the named pipes, and each stream adaptation process corresponds to one named pipe.
It should be noted that the preset format and the preset pipeline are not limited to the CSV format and the Linux pipeline of comma separated values, and the different formats and pipelines may be preset according to actual needs in a specific application scenario, and any changes that may be considered by those skilled in the art should be included in the scope of protection of the present application.
Step S204: receiving and accumulating the stream data in the named pipe based on an event window, wherein the event window is established synchronously with the stream processing progress.
Specifically, the stream join process receives and accumulates stream data delivered through the named pipe using an event window, and completes data query on the stream through data accumulated in the event window to obtain a data query result, and the event window is synchronously created when a stream process, that is, a stream adaptation process and a stream join process, are configured.
Step S205: and receiving a data query request sent by a user.
Step S206: and determining a query result from the event window according to the data query request.
Step S207: and returning the query result to the user.
The method for inquiring the streaming data based on the full-memory calculation receives a data inquiry request sent by a user, determines an inquiry result from an event window of a streaming processing process of streaming data according to the data inquiry request, wherein the streaming processing process is a stream adaptation process and a stream connection process, the event window is a window for receiving and accumulating the streaming data in the stream connection process, and then returns the inquiry result to the user.
Referring to fig. 3, another embodiment of the present invention provides a method for querying streaming data based on full-memory computation, which is applied to a memory system including a plurality of memory databases connected in parallel, and the method includes:
step S301: and receiving a data query request sent by a user.
Step S302: determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process.
Step S303: and returning the query result to the user.
Step S304: and deleting or storing the data in the query result.
Specifically, after the current data query request is completed and the query result is returned, the query result may be deleted or stored according to actual needs, and the event window continues to accumulate the stream data and waits for the next query.
The method for inquiring the streaming data based on the full-memory calculation receives a data inquiry request sent by a user, determines an inquiry result from an event window of a streaming processing process of streaming data according to the data inquiry request, wherein the streaming processing process is a stream adaptation process and a stream connection process, the event window is a window for receiving and accumulating the streaming data in the stream connection process, and then returns the inquiry result to the user.
Referring to fig. 4, a method for querying streaming data based on full-memory computation according to another embodiment of the present application is applied to a memory system including a plurality of memory databases connected in parallel, and the method includes:
step S401: and receiving a data query request sent by a user.
Step S402: determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process.
Step S403: and returning the query result to the user.
Step S404: and closing the event window when the streaming data entering the memory system does not exist.
Specifically, in order to save system resources, when there is no data query request and no stream data enters the memory system, the memory system closes the event window.
The method for inquiring the streaming data based on the full-memory calculation receives a data inquiry request sent by a user, determines an inquiry result from an event window of a streaming processing process of streaming data according to the data inquiry request, wherein the streaming processing process is a stream adaptation process and a stream connection process, the event window is a window for receiving and accumulating the streaming data in the stream connection process, and then returns the inquiry result to the user.
In order to achieve the above technical object, an embodiment of the present application further provides an apparatus for querying streaming data based on full-memory computation, which is applied to a memory system including a plurality of memory databases connected in parallel, and as shown in fig. 8, the apparatus includes:
the receiving module 501 is configured to receive a data query request sent by a user.
A determining module 502, configured to determine a query result from an event window of a stream processing process of stream data according to the data query request, where the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process.
A returning module 503, configured to return the query result to the user.
In a specific application scenario, the method further includes:
an obtaining module to obtain a notification including the amount of the streaming data based on a listening streaming data event, the streaming data event being triggered when the streaming data enters the memory system.
And the writing module is used for writing the stream data into a preset named pipeline according to a preset format based on the stream adaptation process, and the stream adaptation process corresponds to the named pipeline one by one.
And the accumulation module is used for receiving and accumulating the stream data in the named pipeline based on the event window, and the event window is established synchronously with the stream processing process.
In a specific application scenario, the system further comprises a data processing module, configured to:
and deleting or storing the data in the query result.
In a specific application scenario, the method further includes:
the preset format is a comma separated value CSV format, and the named pipeline is a Linux named pipeline.
In a specific application scenario, the system further comprises a closing module, configured to:
and closing the event window when the streaming data entering the memory system does not exist.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present invention.
Those skilled in the art will appreciate that the modules in the apparatus may be distributed in the apparatus according to the description of the implementation scenario, or may be located in one or more apparatuses different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not necessarily depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A method for querying streaming data based on full-memory computing is applied to a memory system comprising a plurality of memory databases connected in parallel, and is characterized in that the method comprises the following steps:
receiving a data query request sent by a user;
before receiving a data query request sent by a user, the method further comprises the following steps:
obtaining a notification including the amount of streaming data based on a listening streaming data event, the streaming data event being triggered when the streaming data enters the memory system;
establishing a stream processing process matched with the number according to the notification;
determining a query result from an event window of a stream processing process of stream data according to the data query request, wherein the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process;
and returning the query result to the user.
2. The method of claim 1, wherein the stream data is written in a preset format into a preset named pipe based on the stream adaptation process, and the stream adaptation process corresponds to the named pipe one to one;
receiving and accumulating the stream data in the named pipe based on the event window, wherein the event window is established synchronously with the stream processing progress.
3. The method of claim 1, after returning the query results to the user, further comprising:
and deleting or storing the data in the query result.
4. The method of claim 2, wherein the predetermined format is a comma separated values CSV format and the named pipe is a Linux named pipe.
5. The method of claim 1, further comprising closing the event window when there is no streaming data entering the memory system.
6. An apparatus for querying streaming data based on full-memory computation, applied to a memory system including a plurality of memory databases connected in parallel, the apparatus comprising:
the receiving module is used for receiving a data query request sent by a user;
a determining module, configured to determine a query result from an event window of a stream processing process of stream data according to the data query request, where the stream processing process is specifically a stream adaptation process and a stream connection process, and the event window is a window for receiving and accumulating the stream data in the stream connection process;
the return module is used for returning the query result to the user;
wherein the apparatus further comprises:
an obtaining module to obtain a notification including the amount of the streaming data based on a listening streaming data event, the streaming data event being triggered when the streaming data enters the memory system.
7. The apparatus of claim 6, further comprising:
the writing module is used for writing the stream data into a preset named pipeline according to a preset format based on the stream adaptation process, and the stream adaptation process corresponds to the named pipeline one by one;
and the accumulation module is used for receiving and accumulating the stream data in the named pipeline based on the event window, and the event window is established synchronously with the stream processing process.
8. The device of claim 6, further comprising a data processing module to:
and deleting or storing the data in the query result.
9. The apparatus of claim 7,
the preset format is a comma separated value CSV format, and the named pipeline is a Linux named pipeline.
10. The device of claim 6, further comprising a shutdown module to:
and closing the event window when the streaming data entering the memory system does not exist.
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| US8122006B2 (en) * | 2007-05-29 | 2012-02-21 | Oracle International Corporation | Event processing query language including retain clause |
| US8180801B2 (en) * | 2009-07-16 | 2012-05-15 | Sap Ag | Unified window support for event stream data management |
| JP5396184B2 (en) * | 2009-07-31 | 2014-01-22 | 株式会社日立製作所 | Computer system and stream data distribution processing method using a plurality of computers |
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| US11132778B2 (en) * | 2017-03-29 | 2021-09-28 | Nec Corporation | Image analysis apparatus, image analysis method, and recording medium |
| CN109213778B (en) * | 2017-07-07 | 2023-07-18 | 北方工业大学 | Stream data sliding window gathering query method |
| CN109614413B (en) * | 2018-12-12 | 2023-03-24 | 上海金融期货信息技术有限公司 | Memory flow type computing platform system |
| CN111400351A (en) * | 2020-03-18 | 2020-07-10 | 威讯柏睿数据科技(北京)有限公司 | Method and device for inquiring streaming data based on distributed parallel architecture |
| CN111414386B (en) * | 2020-03-18 | 2021-06-18 | 威讯柏睿数据科技(北京)有限公司 | Method and device for inquiring flow data based on distributed architecture |
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