CN107947978A - The method and device of a kind of associated data - Google Patents

The method and device of a kind of associated data Download PDF

Info

Publication number
CN107947978A
CN107947978A CN201711164688.7A CN201711164688A CN107947978A CN 107947978 A CN107947978 A CN 107947978A CN 201711164688 A CN201711164688 A CN 201711164688A CN 107947978 A CN107947978 A CN 107947978A
Authority
CN
China
Prior art keywords
data
daily record
record data
key values
master
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
CN201711164688.7A
Other languages
Chinese (zh)
Inventor
谢永恒
王雪松
火莽
火一莽
万月亮
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.)
Beijing Ruian Technology Co Ltd
Original Assignee
Beijing Ruian Technology 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 Beijing Ruian Technology Co Ltd filed Critical Beijing Ruian Technology Co Ltd
Priority to CN201711164688.7A priority Critical patent/CN107947978A/en
Publication of CN107947978A publication Critical patent/CN107947978A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/80—Information retrieval; Database structures therefor; File system structures therefor of semi-structured data, e.g. markup language structured data such as SGML, XML or HTML
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • 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
    • G06F9/52—Program synchronisation; Mutual exclusion, e.g. by means of semaphores
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
    • H04L41/0668—Management of faults, events, alarms or notifications using network fault recovery by dynamic selection of recovery network elements, e.g. replacement by the most appropriate element after failure

Abstract

The embodiment of the invention discloses the method and device of a kind of associated data, according to Policy Filtering daily record data to be associated from spout data；Association key values are generated according to associating policy；Redis clusters are inquired about according to key values, judge whether to return the result；If returning the result, parsing json strings, will be successfully associated field and write the daily record data to be associated, ensure the real-time of data, ensure correlation rule simplification, customizability, ensure that performance linear is expansible, ensure that stablizing for system is healthy and strong.

Description

The method and device of a kind of associated data
Technical field
The present embodiments relate to the technical field of computer information safe, more particularly to a kind of method of associated data with And device.
Background technology
With the arrival of the development of information technology, especially big data epoch, more and more industries need to carry out difference The data in source are associated fusion, excavate the maximum value of data.
Traditional data correlation method is roughly divided into two classes：
Using rear correlation technology, on hadoop (distributed file system) cluster by timed task to data complete or collected works into Row data correlation.This method can use global basis data, can carry out the business association of complexity, and association rate is high. But real time correlation cannot be carried out, it is impossible to ensure the real-time of data.
Using preceding correlation technology, the basic data after lattice are turned is stored in the memory chained list of single node system, chained list is looked into Ask and carry out business association processing, this method global can not use basic data, and association rate is low.And the realization of preceding correlation technology Write more using substrate, construction cycle length, development difficulty is big, and later stage O＆M cost is high.
In conclusion mass data real time correlation system needs：Real-time：Towards real-time stream；Rule comes into force in real time. Simplification:It is easy to develop and easy to maintain.It is expansible：Management individually can be write into line discipline by business personnel.It can determine System：It can support multiple associated services scenes.Reliability：The daily record data of flood tide and the basic data of flood tide just determine that system must Need there are enough stability and robustness.
The content of the invention
The purpose of the embodiment of the present invention is the method and device for proposing a kind of associated data, it is intended to solves traditional association Drawback present in method.
For this purpose, the embodiment of the present invention uses following technical scheme：
In a first aspect, a kind of method of associated data, the described method includes：
According to Policy Filtering daily record data to be associated from spout data；
Association key values are generated according to associating policy；
Redis clusters are inquired about according to key values, judge whether to return the result；
If returning the result, parsing json strings, will be successfully associated field and write the daily record data to be associated.
Alternatively, the field that will be successfully associated writes the daily record data to be associated, including：
According to the configuration field in standardization associating policy file, specific field is selected from daily record data and forms association Key values；
Matched basic data is associated out from the Redis clusters according to the association key values；
The basic data is inserted to the specific fields in the daily record data according to the standardization associating policy file；
Wherein, the standardization associating policy file describes the daily record data to be associated by expansible programming language and obtains Arrive, the expansible programming language includes：Protocol type, filter condition, association key values and/or backfill information.
Alternatively, the method further includes：
If not returning the result, association failure, returns and performs from spout data according to Policy Filtering daily record to be associated Data.
Alternatively, the method further includes：
The daily record data to be associated is stored in the form of string in the Redis clusters；
After the completion of jstorm cluster buildings, according to the degree of parallelism of the current each node blot of resource distribution.
Alternatively, the Redis clusters include：
Cluster and master-slave patterns；
The master-slave patterns include：Each node has one or more slave node；
After master node failures, corresponding slave nodes are replaced with new master.
Second aspect, a kind of device of associated data, described device include：
Screening module, for from spout data according to Policy Filtering daily record data to be associated；
Generation module, for generating association key values according to associating policy；
Judgment module, for inquiring about Redis clusters according to key values, judges whether to return the result；
Writing module, if for returning the result, parsing json strings, will be successfully associated field and write the day to be associated Will data.
Alternatively, said write module, is specifically used for：
According to the configuration field in standardization associating policy file, specific field is selected from daily record data and forms association Key values；
Matched basic data is associated out from the Redis clusters according to the association key values；
The basic data is inserted to the specific fields in the daily record data according to the standardization associating policy file；
Wherein, the standardization associating policy file describes the daily record data to be associated by expansible programming language and obtains Arrive, the expansible programming language includes：Protocol type, filter condition, association key values and/or backfill information.
Alternatively, described device further includes：
Module is returned to, if for not returning the result, association failure, returns and perform from spout data according to strategy Screen daily record data to be associated.
Alternatively, described device further includes：
Processing module, for storing the daily record data to be associated in the form of string in the Redis clusters； After the completion of jstorm cluster buildings, according to the degree of parallelism of the current each node blot of resource distribution.
Alternatively, the Redis clusters include：
Cluster and master-slave patterns；
The master-slave patterns include：Each node has one or more slave node；
After master node failures, corresponding slave nodes are replaced with new master.
The embodiment of the present invention has the beneficial effect that：It can support real time mass data stream association；Exploitation is simple, the construction cycle Short, O＆M cost is low；Number of concurrent linear expansion performance can be passed through according to cluster and mass data situation；Using ack mechanism and Affair mechanism ensures data accuracy, does not lose；During part of nodes failure, cluster possesses fault tolerant mechanism, automatic to distribute newly Worker, ensures that stablizing for cluster is healthy and strong；Basic data uses redis cluster modes, realizes shared global basis data, ensures Associate the global coherency of daily record data.
Brief description of the drawings
Fig. 1 is a kind of flow diagram of the method for associated data provided in an embodiment of the present invention；
Fig. 2 is a kind of high-level schematic functional block diagram of the device of associated data provided in an embodiment of the present invention.
Embodiment
The embodiment of the present invention is described in further detail with reference to the accompanying drawings and examples.It is understood that this Locate described specific embodiment to be used only for explaining the embodiment of the present invention, rather than the restriction to the embodiment of the present invention.In addition also It should be noted that for the ease of describing, part relevant with the embodiment of the present invention rather than entire infrastructure are illustrate only in attached drawing.
With reference to figure 1, Fig. 1 is a kind of flow diagram of the method for associated data provided in an embodiment of the present invention.Such as Fig. 1 institutes Show, the associated data includes：
Step 110, according to Policy Filtering daily record data to be associated from spout (jstorm intake assemblies) data；
Step 120, association key values are generated according to associating policy；
Step 130, a kind of Redis (key-value databases) cluster is inquired about according to key values, judges whether to return the result；
Step 140, if returning the result, parsing json (JavaScriptObject Notation, JS object marks Note) string, field will be successfully associated and write the daily record data to be associated.
Alternatively, the field that will be successfully associated writes the daily record data to be associated, including：
According to the configuration field in standardization associating policy file, specific field is selected from daily record data and forms association Key values；
Matched basic data is associated out from the Redis clusters according to the association key values；
The basic data is inserted to the specific fields in the daily record data according to the standardization associating policy file；
Wherein, the standardization associating policy file describes the daily record data to be associated by expansible programming language and obtains Arrive, the expansible programming language includes：Protocol type, filter condition, association key values and/or backfill information.
Exemplary, interconnected system is according to the field configured in standardization associating policy file, from massive logs data Select specific field and form association key, matched basic data, last foundation are then associated out from redis storehouses according to key values The basic data associated out is inserted the specific fields in daily record data by standardization associating policy file.
Strategy configuration, whole correlating method flow are described as follows according to more than：
First, the foundation of redis memory databases cluster, relating module can be according in BuildDBField labels In DataSet=" WA_BASIC_0021 " and Conditions labels<Condition Element=" " Value=" 124"/>Condition screens basic data, if the big agreement of basic data is WA_BASIC_0021 and data source is " 124 ", then the data meet associated storage condition.What relating module can be encoded with the B040022 in Expression labels It is worth for key, the value of B050004 is stored into the redis clusters of cluster patterns for value in DestElement labels.
Secondly, the association of daily record data, relating module can be according to the SubDataSet=" in QueryDBField labels In WA_SOURCE " and Conditions labels<Condition Element=" " Value=" 124 "/>Condition is to business Data are screened, if before the big protocol name of business datum nine be WA_SOURC and data source is " 124 ", the data Meet correlation inquiry condition.Relating module can remove cluster using the value that the B040022 in Expression labels is encoded as key Inquired about in the cluster of pattern.When there is the value of coding B050004 in the jason strings of return, then relating module can be by this The value of coding is backfilling into the field of business datum B050004.
So far, the basic data storage of relating module and business datum inquiry backfill are completed, and relevant action is completed.
Exemplary, standardization associating policy file standardizes expansible xml language description, by protocol type, filtering The parts such as condition, the keyword being associated, backfill information form.Following strategy is daily record data according to basic data certification word The associating policy of section backfill phone number.
Wherein,<BuildDbField>The content that label includes is to create the rule of redis databases：
Association type (Type)：Definition dynamically associates (String) or static association (IP).
Protocol type (Data_Set)：Define base data type.
Backfill field (<DestElement>Label)：Definition needs the field information backfilled.
Associate field (<Expression>Label)：Define the field information being associated.
Filter condition (<condition>Label)：Define basic data source, support and or logical expression.
Group type (SystemType):Define master slave mode (master-slave) and cluster mode (cluster).
Store the cycle (range)：Storage time of the data in redis clusters is defined, unit is day.
Wherein,<QueryDbField>The content that label includes is that inquiry redis basic databases are associated operation Rule：
Association type (Type)：Definition dynamically associates (String) or static association (IP).
Protocol type (SubDataSet)：Define daily record data type.
Associate field (<Expression>Label)：Define the field information being associated.
Filter condition (<condition>Label)：Define basic data source, support and or logical expression.
Group type (SystemType):Define master slave mode (master-slave) and cluster mode (cluster).
Alternatively, the method further includes：
If not returning the result, association failure, returns and performs from spout data according to Policy Filtering daily record to be associated Data.
Alternatively, the method further includes：
The daily record data to be associated is stored in the form of string in the Redis clusters；
After the completion of jstorm (streaming computing frame) cluster building, according to the current each node blot's of resource distribution Degree of parallelism.
Wherein, standardize associating policy file and provide default configuration according to standard by developer, business personnel can be independent Carry out service deployment.
Basic data is stored in redis clusters in the form of string, the string string lists of json forms up to clear and And field parsing is convenient.Wherein authentication infrastructure data storage is as follows：
1) authentication infrastructure data
With certification account (B040022) for key
The json being organized into calling number (B050004) goes here and there as value
Key=460030965343434
Value=
“H010014”:1476376208
“B050004”:”13561564747”
}。
When doing operation associated, if the certification account in certain user's internet log data exists in redis storehouses, with Its record as key, daily record data is inserted by the field value in the corresponding value of key.
Wherein, the Redis clusters include：
Cluster and master-slave patterns；
The master-slave patterns include：Each node has one or more slave node；
After master node failures, corresponding slave nodes are replaced with new master.
Exemplary, cluster the and master-slave patterns that the present invention is supported using redis3.0, use Cluster supports dynamic capacity-expanding, reduces bandwidth pressure.Master-slave patterns so that each node has one or more A slave nodes, after master node failures, corresponding slave nodes are promoted to new master come before replacing The function of master, improves the availability of system.
Exemplary, after the completion of jstorm cluster buildings, topology tasks need each according to current resource distribution The degree of parallelism of a bolt.Rational degree of parallelism configuration can be with rational management resource, faster more efficient processing mass data.Below It is configured to have in jstorm clusters configuration during 90 nodes, refer to as follows：
topology.workers:340
topology.acker.executors:0
spout.kafka.parallelism.hint:45
bolt.business.parallelism.hint:210
bolt.solrHBase.parallelism.hint:180
bolt.oracle.parallelism.hint:37
bolt.hdfs.parallelism.hint:92。
Closed in conclusion the mass data correlating method based on jstorm+redis technologies mainly there is provided a kind of solution The drawbacks of joining the universal model of business scenario, traditional association method can be solved.It is real-time that the present invention can make up rear correlating method The low deficiency of property, also can the problem of correlating method association rate is low more before foot, and development difficulty is big, and O＆M cost is high.The present invention can be with More efficient, more accurate, more stable association massive logs data.
The embodiment of the present invention has the beneficial effect that：It can support real time mass data stream association；Exploitation is simple, the construction cycle Short, O＆M cost is low；Number of concurrent linear expansion performance can be passed through according to cluster and mass data situation；Using ack mechanism and Affair mechanism ensures data accuracy, does not lose；During part of nodes failure, cluster possesses fault tolerant mechanism, automatic to distribute newly Worker, ensures that stablizing for cluster is healthy and strong；Basic data uses redis cluster modes, realizes shared global basis data, ensures Associate the global coherency of daily record data.
With reference to figure 2, Fig. 2 is a kind of high-level schematic functional block diagram of the device of associated data provided in an embodiment of the present invention.Such as Shown in Fig. 2, described device includes：
Screening module 210, for from spout data according to Policy Filtering daily record data to be associated；
Generation module 220, for generating association key values according to associating policy；
Judgment module 230, for inquiring about Redis clusters according to key values, judges whether to return the result；
Writing module 240, if for returning the result, parsing json strings, will be successfully associated described in field write-in and wait to close Join daily record data.
Alternatively, said write module 240, is specifically used for：
According to the configuration field in standardization associating policy file, specific field is selected from daily record data and forms association Key values；
Matched basic data is associated out from the Redis clusters according to the association key values；
The basic data is inserted to the specific fields in the daily record data according to the standardization associating policy file；
Wherein, the standardization associating policy file describes the daily record data to be associated by expansible programming language and obtains Arrive, the expansible programming language includes：Protocol type, filter condition, association key values and/or backfill information.
Alternatively, described device further includes：
Module is returned to, if for not returning the result, association failure, returns and perform from spout data according to strategy Screen daily record data to be associated.
Alternatively, described device further includes：
Processing module, for storing the daily record data to be associated in the form of string in the Redis clusters； After the completion of jstorm cluster buildings, according to the degree of parallelism of the current each node blot of resource distribution.
Alternatively, the Redis clusters include：
Cluster and master-slave patterns；
The master-slave patterns include：Each node has one or more slave node；
After master node failures, corresponding slave nodes are replaced with new master.
The embodiment of the present invention has the beneficial effect that：It can support real time mass data stream association；Exploitation is simple, the construction cycle Short, O＆M cost is low；Number of concurrent linear expansion performance can be passed through according to cluster and mass data situation；Using ack mechanism and Affair mechanism ensures data accuracy, does not lose；During part of nodes failure, cluster possesses fault tolerant mechanism, automatic to distribute newly Worker, ensures that stablizing for cluster is healthy and strong；Basic data uses redis cluster modes, realizes shared global basis data, ensures Associate the global coherency of daily record data.
Above in association with the technical principle of specific embodiment the invention has been described embodiment.These descriptions are intended merely to explain this The principle of inventive embodiments, and the limitation to protection domain of the embodiment of the present invention cannot be construed in any way.Based on herein Explanation, those skilled in the art, which would not require any inventive effort, can associate the other specific of the embodiment of the present invention Embodiment, these modes are fallen within the protection domain of the embodiment of the present invention.

Claims (10)

  1. A kind of 1. method of associated data, it is characterised in that the described method includes：
    According to Policy Filtering daily record data to be associated from spout data；
    Association key values are generated according to associating policy；
    Redis clusters are inquired about according to key values, judge whether to return the result；
    If returning the result, parsing json strings, will be successfully associated field and write the daily record data to be associated.
  2. 2. according to the method described in claim 1, it is characterized in that, the field that will be successfully associated writes the daily record to be associated Data, including：
    According to the configuration field in standardization associating policy file, specific field is selected from daily record data and forms association key values；
    Matched basic data is associated out from the Redis clusters according to the association key values；
    The basic data is inserted to the specific fields in the daily record data according to the standardization associating policy file；
    Wherein, the standardization associating policy file describes the daily record data to be associated by expansible programming language and obtains, The expansible programming language includes：Protocol type, filter condition, association key values and/or backfill information.
  3. 3. according to the method described in claim 1, it is characterized in that, the method further includes：
    If not returning the result, association failure, returns and performs from spout data according to Policy Filtering daily record number to be associated According to.
  4. 4. according to the method described in claims 1 to 3 any one, it is characterised in that the method further includes：
    The daily record data to be associated is stored in the form of string in the Redis clusters；
    After the completion of jstorm cluster buildings, according to the degree of parallelism of the current each node blot of resource distribution.
  5. 5. according to the method described in claims 1 to 3 any one, it is characterised in that the Redis clusters include：
    Cluster and master-slave patterns；
    The master-slave patterns include：Each node has one or more slave node；
    After master node failures, corresponding slave nodes are replaced with new master.
  6. 6. a kind of device of associated data, it is characterised in that described device includes：
    Screening module, for from spout data according to Policy Filtering daily record data to be associated；
    Generation module, for generating association key values according to associating policy；
    Judgment module, for inquiring about Redis clusters according to key values, judges whether to return the result；
    Writing module, if for returning the result, parsing json strings, will be successfully associated field and write the daily record number to be associated According to.
  7. 7. device according to claim 6, it is characterised in that said write module, is specifically used for：
    According to the configuration field in standardization associating policy file, specific field is selected from daily record data and forms association key values；
    Matched basic data is associated out from the Redis clusters according to the association key values；
    The basic data is inserted to the specific fields in the daily record data according to the standardization associating policy file；
    Wherein, the standardization associating policy file describes the daily record data to be associated by expansible programming language and obtains, The expansible programming language includes：Protocol type, filter condition, association key values and/or backfill information.
  8. 8. device according to claim 6, it is characterised in that described device further includes：
    Module is returned to, if for not returning the result, association failure, returns and perform from spout data according to Policy Filtering Daily record data to be associated.
  9. 9. according to the device described in claim 6 to 8 any one, it is characterised in that described device further includes：
    Processing module, for storing the daily record data to be associated in the form of string in the Redis clusters； After the completion of jstorm cluster buildings, according to the degree of parallelism of the current each node blot of resource distribution.
  10. 10. according to the device described in claim 6 to 8 any one, it is characterised in that the Redis clusters include：
    Cluster and master-slave patterns；
    The master-slave patterns include：Each node has one or more slave node；
    After master node failures, corresponding slave nodes are replaced with new master.
CN201711164688.7A 2017-11-21 2017-11-21 The method and device of a kind of associated data Pending CN107947978A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711164688.7A CN107947978A (en) 2017-11-21 2017-11-21 The method and device of a kind of associated data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711164688.7A CN107947978A (en) 2017-11-21 2017-11-21 The method and device of a kind of associated data

Publications (1)

Publication Number Publication Date
CN107947978A true CN107947978A (en) 2018-04-20

Family

ID=61929541

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711164688.7A Pending CN107947978A (en) 2017-11-21 2017-11-21 The method and device of a kind of associated data

Country Status (1)

Country Link
CN (1) CN107947978A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108959562A (en) * 2018-07-04 2018-12-07 北京京东尚科信息技术有限公司 Apply the magnanimity regular data processing method and system on block chain
CN113204531A (en) * 2021-05-08 2021-08-03 北京锐安科技有限公司 Data backfill method and device, electronic equipment and storage medium

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103942712A (en) * 2014-05-09 2014-07-23 北京联时空网络通信设备有限公司 Product similarity based e-commerce recommendation system and method thereof
CN106453512A (en) * 2016-09-05 2017-02-22 努比亚技术有限公司 Redis cluster information monitoring device and method
CN106599104A (en) * 2016-11-29 2017-04-26 北京锐安科技有限公司 Mass data association method based on redis cluster

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103942712A (en) * 2014-05-09 2014-07-23 北京联时空网络通信设备有限公司 Product similarity based e-commerce recommendation system and method thereof
CN106453512A (en) * 2016-09-05 2017-02-22 努比亚技术有限公司 Redis cluster information monitoring device and method
CN106599104A (en) * 2016-11-29 2017-04-26 北京锐安科技有限公司 Mass data association method based on redis cluster

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108959562A (en) * 2018-07-04 2018-12-07 北京京东尚科信息技术有限公司 Apply the magnanimity regular data processing method and system on block chain
CN113204531A (en) * 2021-05-08 2021-08-03 北京锐安科技有限公司 Data backfill method and device, electronic equipment and storage medium
WO2022236973A1 (en) * 2021-05-08 2022-11-17 北京锐安科技有限公司 Data backfilling method and apparatus, electronic device, and storage medium

Similar Documents

Publication Publication Date Title
Chen et al. Realtime data processing at facebook
US7844959B2 (en) Runtime optimization of distributed execution graph
US8201142B2 (en) Description language for structured graphs
Alvaro et al. Blazes: Coordination analysis for distributed programs
US9330161B2 (en) Creating global aggregated namespaces for storage management
US7953713B2 (en) System and method for representing and using tagged data in a management system
CN110471698A (en) The generation method and device, storage medium and computer equipment of API document
Oliveira et al. Delivering software with agility and quality in a cloud environment
CN107947978A (en) The method and device of a kind of associated data
CN104166546A (en) Implementation method and system used for data distribution service (DDS) application software and based on model driven architecture (MDA)
CN103699746A (en) CADDS5 piping three-dimensional design method and system based on database
Alvaro et al. Blazes: Coordination Analysis and Placement for Distributed Programs
Matic et al. Data access architecture in object oriented applications using design patterns
Meng et al. IT troubleshooting with drift analysis in the DevOps era
Marchese Conserving software-based artwork through software engineering
Turenne et al. A tool chain for generating the description files of highly available software
Urban et al. Decentralized data dependency analysis for concurrent process execution
Amer et al. Software Performance Evaluation: Graph grammar-based Transformation of UML design models into performance models
Vincy et al. Understanding hadoop framework through single-node cluster installation
Gamble et al. Specification of Fenix MPI Fault Tolerance library version 1.0.
Arnold Reliable, scalable tree-based overlay networks
Sakr et al. Large-scale stream processing systems
Hassine et al. Towards the generation of AMF configurations from use case maps based availability requirements
Whitmire Make Your Life Easier Down the Road
Alzahrani et al. Modeling fault tolerance tactics with reusable aspects

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

Application publication date: 20180420

RJ01 Rejection of invention patent application after publication