CN110232073A - A kind of Data Management Analysis system and method - Google Patents
A kind of Data Management Analysis system and method Download PDFInfo
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- CN110232073A CN110232073A CN201910387206.7A CN201910387206A CN110232073A CN 110232073 A CN110232073 A CN 110232073A CN 201910387206 A CN201910387206 A CN 201910387206A CN 110232073 A CN110232073 A CN 110232073A
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- 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
- G06F16/2455—Query execution
- G06F16/24552—Database cache management
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- 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
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
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Abstract
The invention discloses a kind of Data Management Analysis system and methods, are related to data processing system technical field, for carrying out efficient processing and analysis to delay sensitive task and history static data batch mining task with a set of framework.The device includes: that data access unit, data buffer unit, data are united unit, storage unit, analytical unit in advance；Data access unit concurrently obtains real time data；The real time data that data buffer unit obtains data access unit caches；The data real time data that unit caches data buffer unit of uniting in advance carries out summarizing and analyzing for low time delay rank；Storage unit data the are united in advance real time data distributed storage after the summarizing and analyze of unit low time delay rank is history static data；Analytical unit is handled and is analyzed to the history static data after storage unit storage using distributed memory technology.The embodiment of the present invention is applied to Data Management Analysis.
Description
Technical field
The present invention relates to data processing system technical field more particularly to a kind of Data Management Analysis system and methods.
Background technique
With the fast development of Internet application, the data for needing to analyze processing are also more and more.These data are generally divided
For two classes, one kind is to need to handle real time data in real time and generate processing result " flow data "；Another kind of is desirable
The historical data of magnanimity is preserved in the cluster, and it is further statisticallyd analyze and " the big number of data mining
According to ".
In the prior art, the non real-time analysis system for the real-time analyzer of " flow data " processing and " big data " processing
System, according to different demands, general there are two types of build mode.
One is being designed to build respectively, each system is stored and is calculated to data respectively, when needs are to two classes
It is synchronous by the data between cluster when the Conjoint Analysis of data, data are subjected to convergence and carry out subsequent analysis.This side of building
Formula uses two sets of autonomous systems, therefore effective unified management and distribution can not be carried out to entire cluster resource, reduces entire
Cluster resource utilization rate increases the complexity in terms of system Construction, operation and maintenance, improves user cost；Meanwhile
When data class is various, when data volume is huge, generally require to ensure the synchronous consistency of data using complicated mechanism.To increase
The complexity for having added system to realize reduces the timeliness of data analysis, and data need to store more parts, waste cluster money
Source.
Another kind is the data processing technique using " mashed up " framework, can satisfy while handling two class data.Such skill
Art is generally using a set of storage cluster to meet the importing of real time data simultaneously and to the reading of historical data, or externally uses system
One interface provides service, is separated from each other on inside is realized.Wherein, real time data is met using a set of storage cluster simultaneously
The reading of importing and batch tasks to historical data largely effects on the efficiency in data analysis；Simultaneously as taken into account to batch
The processing of data is measured, therefore in the processing to real time data, is unable to satisfy the high real-time analysis very sensitive for time delay
Task.
Summary of the invention
The embodiment of the present invention provides a kind of Data Management Analysis system and method, for solving at data in the prior art
The problem that analysis system cluster resource utilization rate is low, structure is complicated and analysis efficiency is lower is managed, is realized with a set of framework to time delay
Sensitive task and history static data batch mining task carry out efficient processing and analysis.
In order to achieve the above objectives, the embodiment of the present invention adopts the following technical scheme that
In a first aspect, the embodiment provides a kind of Data Management Analysis system, which includes: data access
Unit, data buffer unit, data are united unit, storage unit, analytical unit in advance；
Data access unit, for concurrently obtaining real time data；
Data buffer unit, the real time data for obtaining to the data access unit cache；
Data are united unit in advance, and the real time data for caching to the data buffer unit carries out low time delay rank
Summarize and analyzes；
Storage unit is distributed for the real time data after the summarizing and analyze of unit low time delay rank that the data are united in advance
Formula is stored as history static data；
Analytical unit, for being carried out using distributed memory technology to the history static data after storage unit storage
Processing and analysis.
Second aspect, the embodiment provides a kind of Data Management Analysis methods, comprising:
Concurrently obtain real time data；
The real time data of acquisition is cached；
Summarizing and analyzing for low time delay rank is carried out to the real time data of caching；
It is history static data by the real time data distributed storage after the summarizing and analyze of low time delay rank；
The history static data after storage is handled and analyzed using distributed memory technology.
The third aspect, provides a kind of computer readable storage medium for storing one or more programs, it is one or
Multiple programs include instruction, and described instruction makes the computer execute the data as described in second aspect when executed by a computer
Handle analysis method.
Fourth aspect provides a kind of computer program product comprising instruction, when described instruction is run on computers
When, so that computer executes the Data Management Analysis method as described in second aspect.
5th aspect, provides a kind of data processing and analysis device, comprising: processor and memory, memory is for storing
Program, processor call the program of memory storage, to execute the Data Management Analysis method as described in second aspect.
The Data Management Analysis system and method that the embodiment of the present invention provides, concurrently obtains reality by data access unit
When data, data buffer unit caches the real time data of acquisition, and data unit of uniting in advance carries out the real time data of caching
Low time delay rank summarizes and analyzes, and realizes that the processing to delay sensitive task is analyzed, and storage unit is by the remittance of low time delay rank
Real time data distributed storage after summation analysis is history static data, and analytical unit is using distributed memory technology to storage
History static data afterwards carries out batch processing and analysis, realizes with a set of framework to delay sensitive task and history static data
Batch mining task carries out efficient processing and analysis.
Detailed description of the invention
Fig. 1 is a kind of configuration diagram of data system provided in an embodiment of the present invention；
Fig. 2 is a kind of structural schematic diagram of Data Management Analysis system provided in an embodiment of the present invention；
Fig. 3 is a kind of flow diagram of Data Management Analysis method provided in an embodiment of the present invention；
Fig. 4 is the structural schematic diagram of another Data Management Analysis system provided in an embodiment of the present invention.
Specific embodiment
A specific embodiment of the invention is described in further detail with reference to the accompanying drawing.
As shown in Figure 1, the present invention provides a kind of framework of data system.The data system includes: Data Management Analysis system
System 10, data source equipment 20.Wherein, data source equipment 20 can be sensor, the server, computer, individual on automobile
The terminals such as mobile device.
Wherein, Data Management Analysis system 10 is with data source equipment 20 by wirelessly or non-wirelessly connecting.Data processing point
Analysis system 10 can obtain the real time data in data source equipment 20, such as geographic position data, service according to actual needs
Journal file, the application data on computer, search record of personal mobile device of device etc., for executing data processing point
Analysis, and storage record and/or batch quantity analysis are carried out to these real time datas.
Fig. 2 shows the structural schematic diagrams of above-mentioned Data Management Analysis system 10.As shown in Fig. 2, the Data Management Analysis
System 10 includes that data access unit 11, data buffer unit 12, data are united unit 13, storage unit 14 and analytical unit in advance
15, Data Management Analysis system 10 uses distributed type assemblies framework, and all units can be by Data Management Analysis system 10
One or more have correlation function node form.It will appreciated by the skilled person that structure shown in Fig. 2 is only
For signal, the structure of data processing analysis system 10 is not caused to limit.For example, Data Management Analysis system 10 can also wrap
It includes the more perhaps less component than shown in Fig. 2 or has and different configurations illustrated in fig. 2.
Embodiment 1,
Fig. 3 is a kind of flow diagram of Data Management Analysis method provided in this embodiment, the Data Management Analysis side
Method is applied in data system as shown in Figure 1, and this method specifically includes:
S101, real time data is concurrently obtained.
Specifically, data access unit 11 concurrently obtains real time data.
For more efficient acquisition real time data, data access unit 11 uses distributed type assemblies framework, by more
A acquisition node concurrently obtains the real time data in data source equipment 20.It is opposite to pass due to using multiple acquisition nodes
The data acquiring mode of system can obtain more data in the same time, simultaneously because using distributed type assemblies framework, section
It is not interfere with each other between point, the stagnation of data acquisition caused by will not occurring because of acquisition node failure, the lag for causing processing to analyze.
Wherein, acquisition node can select different data acquiring modes according to the actual situation, in a kind of implementation, often
A acquisition node obtains different types of real time data respectively；In another implementation, each acquisition node obtains not respectively
With the real time data in data source equipment 20；In another implementation, each acquisition node is excellent according to processing analysis task
First degree acquires the real time data of different priorities.
Illustratively, akka frame can be used as running environment in data access unit, and akka has stronger vertical
The characteristics of extension, horizontal extension and high serious forgiveness, wherein akka-actors can create thousands of examples in a system,
It can simply be expanded in the machine of a cluster from a single node process, and when code does not have any modification
Long-range operation failure recovery and error handle cooperate distributed type assemblies framework to have when carrying out real-time data acquisition larger excellent
Gesture.
S102, the real time data of acquisition is cached.
Specifically, the real time data of 12 pairs of data buffer unit acquisitions caches.
When moment generating mass data, if transmitting-receiving process is not able to satisfy actual requirement, it may occur however that lose real time data
Abnormal conditions.It therefore, is the reliability for guaranteeing acquired real time data warehousing, in data access unit 11 and storage unit
Setting uses the data buffer unit 12 of distributed type assemblies framework between 14, undertakes appointing for data pipe by multiple buffer joints
Business, opposite individual node sending and receiving data, can receive and dispatch more data within the unit time, thus meet data access for
The Capability Requirement of back pressure avoids the abnormal conditions of loss of data.
S103, summarizing and analyzing for low time delay rank is carried out to the real time data of caching.
Specifically, data are united in advance, the real time data of 13 pairs of unit cachings carries out summarizing and analyzing for low time delay rank.
In the Data Management Analysis system 10 of the present embodiment, for the acquisition data of higher efficiency, data access unit
The task of 11 progress data acquisitions does not carry out processing analysis in real time to real time data.Therefore, in data buffer unit 12
Being added between accumulation layer 14 takes the data of distributed type assemblies framework to unite in advance unit 13, and when needing to handle analysis, ductility is sensitive
When task, the real time data of caching is summarized in real time by multiple pre- system nodes and analysis is handled.Illustratively, when low
That prolongs rank summarizes and analyzes the statistics that can be to real time data quantity, simple receptance function, polymerization and rolling index etc..
It S104, by the real time data distributed storage after the summarizing and analyze of low time delay rank is history static data.
Specifically, the real time data distributed storage after the summarizing and analyze of low time delay rank is history by storage unit 14
Static data.
As shown in Fig. 2, storage unit 14 includes severe writing module 141 and analysis module 142, two modules are using mutually only
Vertical storage architecture and different read/write load models guarantee that severe writing module 141 will not influence point when carrying out data storage
The speed of Data Management Analysis in module 142 is analysed, and is interconnected between module, so as to maximum according to own service feature
Change and utilizes hardware resource.
Wherein, severe writing module 141 carries out distributed storage to history static data using distributed type assemblies framework, with number
The performance for promoting global storage is matched according to buffer cell 12.Distributed storage uses more copy back mechanisms, and data are according to one
Fixed rule is stored on clustered node, and using the write-in of copy, and what multiple copies were read guarantees multiple data copies
Between consistency.It also has and can estimate and extension calculating, memory capacity and the performance of elasticity, and can pass through according to demand
Replication capacity is by the history static data synchronization of storage into analysis module 142.
Analysis module 142 and analytical unit 15 are located at same node, enable analytical unit 15 in analysis module 142
History static data realizes localized access, avoids the influence read and write repeatedly to 15 working efficiency of analytical unit, carries out higher
The batch processing and analysis of effect.Meanwhile analysis module 142 can wrap containing more data, such as with respect to severe writing module 141
Data are handled and are analyzed with the result etc. obtained.
S105, the history static data after storage is handled and is analyzed using distributed memory technology.
Specifically, analytical unit 15 is handled and is divided to the history static data after storage using distributed memory technology
Analysis.
In order to guarantee the efficiency excavated to history statistical data analysis, analytical unit 15 is located at same with analysis module 142
Node reduces the bottleneck limitation of the process and hardware device input/output transmitted in the cluster when data analysis, meanwhile, point
Analysis unit makes the batch mining analysis to history static data more efficient using distributed type assemblies framework.
Data Management Analysis system provided by the invention concurrently obtains real time data by data access unit, and data are slow
It rushes unit to cache the real time data of acquisition, data unit of uniting in advance carries out the real time data of caching the remittance of low time delay rank
Summation analysis, realizes and analyzes the processing of delay sensitive task, and storage unit is by the reality after the summarizing and analyze of low time delay rank
When data distribution formula be stored as history static data, analytical unit is using distributed memory technology to the history static number after storage
According to batch processing and analysis is carried out, realize with a set of framework to delay sensitive task and history static data batch mining task into
The efficient processing of row and analysis.
As shown in figure 4, optional, which can also include rm-cell 16, for pair
Unite in advance unit 13, storage unit 14 of data buffer unit 12, data carries out resource management and task schedule.
Rm-cell 16 is responsible for carrying out resource management and task schedule to entire Data Management Analysis system, can be with
Elastic management is done to the resource in cluster, provide effective resource isolation and is shared, and carries out resource in a manner of fine-grained
It manages to improve the utilization rate of entire cluster, the utilization rate and Data Management Analysis of Data Management Analysis system is improved with this
Efficiency.
The embodiment of the present invention provides a kind of computer readable storage medium for storing one or more programs, one
Or multiple programs include instruction, described instruction makes computer execute data processing as shown in Figure 3 when executed by a computer
Analysis method.
The embodiment of the present invention provides a kind of computer program product comprising instruction, when instruction is run on computers
When, so that computer executes Data Management Analysis method as shown in Figure 3.
The embodiment of the present invention provides a kind of data processing and analysis device, comprising: processor and memory, memory are used for
Program is stored, processor calls the program of memory storage, to execute Data Management Analysis method as shown in Figure 3.
By data processing and analysis device in an embodiment of the present invention, computer readable storage medium, computer program
Product can be applied to above-mentioned Data Management Analysis method, therefore, can be obtained technical effect see also the above method
Embodiment, details are not described herein for the embodiment of the present invention.
It should be noted that above-mentioned each unit can be the processor individually set up, also can integrate controller certain
It is realized in one processor, in addition it is also possible to be stored in the form of program code in the memory of controller, by controller
Some processor calls and executes the function of the above each unit.Processor described here can be a central processing unit
(Central Processing Unit, CPU) or specific integrated circuit (Application Specific
Integrated Circuit, ASIC), or be arranged to implement one or more integrated circuits of the embodiment of the present invention.
It should be understood that in various embodiments of the present invention, magnitude of the sequence numbers of the above procedures are not meant to execute suitable
Sequence it is successive, the execution of each process sequence should be determined by its function and internal logic, the implementation without coping with the embodiment of the present invention
Process constitutes any restriction.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided by the present invention, it should be understood that disclosed system, apparatus and method, it can be with
It realizes by another way.For example, apparatus embodiments described above are merely indicative, for example, the unit
It divides, only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units or components
It can be combined or can be integrated into another system, or some features can be ignored or not executed.Another point, it is shown or
The mutual coupling, direct-coupling or communication connection discussed can be through some interfaces, the indirect coupling of equipment or unit
It closes or communicates to connect, can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.
Claims (9)
1. a kind of Data Management Analysis system characterized by comprising data access unit, data buffer unit, data are united in advance
Unit, storage unit, analytical unit；
Data access unit, for concurrently obtaining real time data；
Data buffer unit, the real time data for obtaining to the data access unit cache；
Data are united unit in advance, and the real time data for caching to the data buffer unit carries out summarizing for low time delay rank
And analysis；
Storage unit is deposited for the real time data distribution after the summarizing and analyze of unit low time delay rank that the data are united in advance
Storage is history static data；
Analytical unit, for being handled using distributed memory technology the history static data after storage unit storage
And analysis.
2. Data Management Analysis system according to claim 1, which is characterized in that the storage unit includes that severe writes mould
Block and analysis module；
Told severe writing module, for storing the history static data, and by the history static data synchronization to described point
Analyse module；
The analysis module and the analytical unit are located at same node, quiet to the synchronous history for the analytical unit
State data carry out batch processing and analysis.
3. Data Management Analysis system according to claim 1, which is characterized in that the data access unit, data are slow
It rushes unit, data and unites unit, storage unit, analytical unit in advance using distributed type assemblies framework.
4. Data Management Analysis system according to claim 1, which is characterized in that further include:
Rm-cell, for the data buffer unit, data unite in advance unit, storage unit carry out resource management and appoint
Business scheduling.
5. a kind of Data Management Analysis method characterized by comprising
Concurrently obtain real time data；
The real time data of acquisition is cached；
Summarizing and analyzing for low time delay rank is carried out to the real time data of caching；
It is history static data by the real time data distributed storage after the summarizing and analyze of low time delay rank；
The history static data after storage is handled and analyzed using distributed memory technology.
6. Data Management Analysis method according to claim 5, which is characterized in that it is described by low time delay rank summarize and
The real time data distributed storage after analysis is history static data, comprising:
It is that history in severe writing module is quiet by the real time data distributed storage after the summarizing and analyze of low time delay rank
State data；
By the history static data synchronization to the analysis module for being located at same node with analytical unit.
7. a kind of computer readable storage medium for storing one or more programs, which is characterized in that one or more of journeys
Sequence includes instruction, and described instruction executes the computer as claim 5-6 is described in any item
Data Management Analysis method.
8. a kind of computer program product comprising instruction, which is characterized in that when described instruction is run on computers, so that
The computer executes such as the described in any item Data Management Analysis methods of claim 5-6.
9. a kind of data processing and analysis device characterized by comprising processor and memory, memory are used to store program,
Processor calls the program of memory storage, to execute such as the described in any item Data Management Analysis methods of claim 5-6.
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