CN110232073A - A kind of Data Management Analysis system and method - Google Patents

A kind of Data Management Analysis system and method Download PDF

Info

Publication number
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
Authority
CN
China
Prior art keywords
data
unit
real time
storage
analysis
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201910387206.7A
Other languages
Chinese (zh)
Inventor
吴洋
张涛
高洁
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China United Network Communications Group Co Ltd
Original Assignee
China United Network Communications Group Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China United Network Communications Group Co Ltd filed Critical China United Network Communications Group Co Ltd
Priority to CN201910387206.7A priority Critical patent/CN110232073A/en
Publication of CN110232073A publication Critical patent/CN110232073A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • G06F16/2455Query execution
    • G06F16/24552Database cache management
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • G06F16/2458Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2471Distributed queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/48Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806Task transfer initiation or dispatching
    • G06F9/4843Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Probability & Statistics with Applications (AREA)
  • Mathematical Physics (AREA)
  • Fuzzy Systems (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

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

A kind of Data Management Analysis system and method
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.
CN201910387206.7A 2019-05-10 2019-05-10 A kind of Data Management Analysis system and method Pending CN110232073A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910387206.7A CN110232073A (en) 2019-05-10 2019-05-10 A kind of Data Management Analysis system and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910387206.7A CN110232073A (en) 2019-05-10 2019-05-10 A kind of Data Management Analysis system and method

Publications (1)

Publication Number Publication Date
CN110232073A true CN110232073A (en) 2019-09-13

Family

ID=67861278

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910387206.7A Pending CN110232073A (en) 2019-05-10 2019-05-10 A kind of Data Management Analysis system and method

Country Status (1)

Country Link
CN (1) CN110232073A (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111726256A (en) * 2020-06-29 2020-09-29 湖北亿咖通科技有限公司 Vehicle instruction issuing processing method and system and vehicle data processing method and system
CN112134929A (en) * 2020-08-28 2020-12-25 新华三技术有限公司 Session message analysis method, device and storage medium
CN112835711A (en) * 2021-01-27 2021-05-25 北京远盟普惠健康科技有限公司 Data processing method and system, computer equipment and computer storage medium
CN114785808A (en) * 2022-03-28 2022-07-22 深圳开源互联网安全技术有限公司 Data synchronization analysis method, device and equipment and readable storage medium

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050278350A1 (en) * 2004-05-27 2005-12-15 Oracle International Corporation Providing mappings between logical time values and real time values
CN102122301A (en) * 2011-03-09 2011-07-13 上海迅图数码科技有限公司 LBS (location-based service)-oriented real-time database system
CN104503894A (en) * 2014-12-31 2015-04-08 中国石油天然气股份有限公司 distributed server state real-time monitoring system and method
CN107070890A (en) * 2017-03-10 2017-08-18 北京市天元网络技术股份有限公司 Flow data processing device and communication network major clique system in a kind of communication network major clique system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050278350A1 (en) * 2004-05-27 2005-12-15 Oracle International Corporation Providing mappings between logical time values and real time values
CN102122301A (en) * 2011-03-09 2011-07-13 上海迅图数码科技有限公司 LBS (location-based service)-oriented real-time database system
CN104503894A (en) * 2014-12-31 2015-04-08 中国石油天然气股份有限公司 distributed server state real-time monitoring system and method
CN107070890A (en) * 2017-03-10 2017-08-18 北京市天元网络技术股份有限公司 Flow data processing device and communication network major clique system in a kind of communication network major clique system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
JIYAN WU: "Energy-Aware Concurrent Multipath Transfer for Real-Time Video Streaming Over Heterogeneous Wireless Networks", 《IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY》 *
罗乐: "内存计算技术研究综述", 《软件学报》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111726256A (en) * 2020-06-29 2020-09-29 湖北亿咖通科技有限公司 Vehicle instruction issuing processing method and system and vehicle data processing method and system
CN112134929A (en) * 2020-08-28 2020-12-25 新华三技术有限公司 Session message analysis method, device and storage medium
CN112134929B (en) * 2020-08-28 2022-05-27 新华三技术有限公司 Session message analysis method, device and storage medium
CN112835711A (en) * 2021-01-27 2021-05-25 北京远盟普惠健康科技有限公司 Data processing method and system, computer equipment and computer storage medium
CN114785808A (en) * 2022-03-28 2022-07-22 深圳开源互联网安全技术有限公司 Data synchronization analysis method, device and equipment and readable storage medium

Similar Documents

Publication Publication Date Title
CN110232073A (en) A kind of Data Management Analysis system and method
Isah et al. A survey of distributed data stream processing frameworks
Balsamo et al. A review on queueing network models with finite capacity queues for software architectures performance prediction
Fujimoto Parallel and distributed simulation systems
CN107092522B (en) Real-time data calculation method and device
US8745434B2 (en) Platform for continuous mobile-cloud services
US20220004480A1 (en) Log data collection method, log data collection device, storage medium, and log data collection system
CN109831478A (en) Rule-based and model distributed processing intelligent decision system and method in real time
CN104375882B (en) The multistage nested data being matched with high-performance computer structure drives method of calculation
CN107766147A (en) Distributed data analysis task scheduling system
Marie-Magdelaine et al. Proactive autoscaling for cloud-native applications using machine learning
CN109614227A (en) Task resource concocting method, device, electronic equipment and computer-readable medium
CN109088747A (en) The management method and device of resource in cloud computing system
CN112051771B (en) Multi-cloud data acquisition method and device, computer equipment and storage medium
CN107844406A (en) Method for detecting abnormality and system, service terminal, the memory of distributed system
CN116467061B (en) Task execution method and device, storage medium and electronic equipment
CN116302574B (en) Concurrent processing method based on MapReduce
CN110543462A (en) Microservice reliability prediction method, prediction device, electronic device, and storage medium
Luckow et al. Performance characterization and modeling of serverless and hpc streaming applications
CN115168042A (en) Management method and device of monitoring cluster, computer storage medium and electronic equipment
Pfandzelter et al. Towards a Benchmark for Fog Data Processing
CN110955602A (en) Distributed embedded software testing system based on resource sharing
Khan Hadoop performance modeling and job optimization for big data analytics
Avritzer et al. Automated generation of test cases using a performability model
Chaves et al. An IoT cloud and big data architecture for the maintenance of home appliances

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20190913