CN108804497A - A kind of big data analysis method based on daily record - Google Patents
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Abstract
The big data analysis method based on daily record that the invention discloses a kind of, the big data analysis method based on daily record is mainly applied by related Beats and carries out data acquisition in each server according to its configuration file, then collects the data by Beats application acquisitions by LogStash and the sequence generated by automatic indexing is deposited into ElasticSearch.ElasticSearch externally provides the query interface of succinct Restful styles.Elasticsearch, which is developed by java applet and realized using Lucene as its core, calls inquiry data, realize the function of all indexes and search, it can realize and be accurately positioned search log information and analyze related data, obtain the effect of accurately business datum.It is visually shown finally by Echart, to hide the complexity of Lucene itself, to allow index and search to become convenient intuitive.
Description
Technical field
The present invention relates to journal file technical fields, particularly relate to a kind of big data analysis method based on daily record.
Background technology
In recent years, since data are in the sustainable growth of internet arena, the processing that each company all suffers from mass data needs
It asks.Data analysis is mainly that the O&M decision of company provides support, is based primarily upon the daily record that each server generates to be analyzed,
Based on the data information that these daily records are provided accesses user, data traffic is in time dimension, product line dimension, domain name dimension
Etc. have specific quantized data, to be embodied as corporate server operation management, assignment of traffic, the offers reference such as estimate
Purpose.
Existing scheme major technique is that (elasticsearch, logstash&kibana, analysis can using ELK-Stack
Depending on changing platform) frame, the frame be by Elasticsearch (elasticity retrieval frame), IKAnalyzer (IK Chinese word segmentation machines),
Logstash (daily record storage), Beats (data acquisition applications).
As shown in Figure 1, be prior art ELK-Stack block schematic illustrations, including：
Beats is applied, and to acquire the daily record data generated by system and service, wherein Beats includes that file acquires again
Metricbeat (light-type index collection device) is applied using Filebeat (light-type log collector) and equipment detection, finally
It is collected by LogStash and stores ElasticSearch.
LogStash, to collector journal, interface service state and equipment operation condition and store arrive
ElasticSearch。
ElasticSearch to collect by the collected data of LogStash, and establishes index and provides retrieval behaviour
Make.
WebService (network service, a kind of technology of service orientation framework), to the data that Intranet is collected
It is stored in index database, and query interface is provided to outside.
Oracle (Oracle Database, oracle database, a relational database management system), returns Intranet
The data that collection gets up are stored in index database, and provide query interface to outside.
Service background：To store the intermediate data after analysis, and intranet and extranet is supported to penetrate function.
Data exhibiting, including Echarts CSS (one kind increase income visualization library) and HTML5 (the of hypertext markup language
Five material alteration versions), the result after analysis is graphically showed use by the WebService for providing a user
Family.
By taking monitoring of tools in the prior art as an example, the step of data processing, includes：
1. installing MetricBeat on needing the server monitored, and configure metricbeat.yml files, server
The step of operation includes：
The subsequent values of module are changed to system, as monitoring device system；
The index value to be monitored, such as CPU, Memory are configured under meticsets nodes；
The subsequent values of Period are set as to the time interval of monitoring.
2. changing LogStash configuration files, including step：
Newly-built Logstash_to_es.conf files；
The port 5044 of Beat is specified in the input for configuring LogStash, because monitoring of tools does not need filtration treatment,
Filter is not needed；
The output output for configuring LogStash, is output to ElasticSeach, specifies its IP and corresponding port, and refer to
Fixed its automatically generates the format of index name.
3. changing ElasticSearch configuration file elasticsearch.yml, including step：
Configure cluster name cluster.name and node name node.name；
The path (path.name, path.log) that specified data and daily record generate；
Specify the IP (network.host) and port (http.port) of itself；
It is specified to automatically generate index, the value of action.auto_create_index is set as true.
4.java programs obtain equipment state by HTTP；And it is shown by Echart instrument.
As shown in Figure 2, it is monitoring of tools Echart instrument display schematic diagrams under the prior art.
As can be seen from the above step, under the prior art after centralized management daily record, the statistics of daily record and retrieval become again
One cumbersome thing generally realizes retrieval and statistics using Linux commands such as grep, awk and wc, but for wanting
In the case of asking the requirements such as higher inquiry, sequence and statistics and huge data volume, deposited if still using conventional method
In the inaccurate problem of inefficient and finally obtained data.
Invention content
In view of this, it is an object of the invention to propose that a kind of big data analysis method realization based on daily record is accurately positioned
Search log information simultaneously analyzes related data, obtains the effect of accurately business datum.
Based on a kind of above-mentioned purpose big data analysis method based on daily record provided by the invention, which is characterized in that from top
It is respectively arranged with represent layer, control layer, service layer and basic data layer downwards；
The basic data layer provides data for whole system, interacts with data collection layer downwards, is carried for data collection layer
It is supported for basic data；The basic data layer includes：Database, ELK components, DAO, HTTP and caching；
The service layer：To provide service upwards for Control layers, DAO, ELK or caching query data are accessed downwards, and
The data got are handled；
The control layer：Request that responsible receiving front-end is sent out simultaneously calls service layer to obtain data, is finally fitted to corresponding
View return to front end；The front end includes displaying interface and user's interaction；
The presentation layer：Including blog search, monitoring of tools and visual display function.
As one embodiment, the database is relevant database, is used for the related data of storage system；
The ELK components are collecting correlation log data and device data；
The DAO provides interface, downward access relation type database for Service layers upwards；
The HTTP provides service to access ElasticSearch to upper layer Service layers；
The caching is ehcache (Cache Framework in the process of a pure Java) component, to provide hot topic for system
The buffer service of data.
As one embodiment, the basic data layer correlation Beats apply according to its configuration file each server into
Row data acquire, and then collect the data by Beats application acquisitions by LogStash and are generated by automatic indexing suitable
Sequence is deposited into ElasticSearch.
As one embodiment, the Elasticsearch is developed by java applet and Lucene is used to be used as its core
The heart calls inquiry data to realize, i.e., realizes the function of all indexes and search by Java and externally provide Restful styles
Query interface.
As one embodiment, the Elasticsearch has following functions：Distributed real-time files storage, i.e., often
A field is all indexed and can be searched；Distributed real-time analysis search engine is enough the service of extension process hundred or more
Device；Handle PB level structures or unstructured data.
As one embodiment, the query interfaces of the RESTful styles is hiding the complexity of Lucene itself.
As one embodiment, the service layer is responsible for interacting with the data collection layer in represent layer and ELK components,
The data that the service layer is collected by data collection layer match daily record by Grok regular expressions；The Grok
Regular expression is used for retrieving/replacing the text for meeting some pattern/rule, including：1, it is established under the path of response
Pattern files match corresponding content format with regular expression, are split to daily record；2, to according to the time and
Service name creates new index or is stored in old index.
As one embodiment, the represent layer is responsible for the data obtained from service layer to be showed in the form of more intuitive
User, display form include but not limited to line chart, block diagram, pie chart, table, map etc..
From the above it can be seen that a kind of big data analysis method based on daily record provided by the invention, mainly passes through
Related Beats is applied carries out data acquisition according to its configuration file in each server, is then collected by described by LogStash
The data of Beats application acquisitions are simultaneously deposited into ElasticSearch by the sequence of automatic indexing generation.ElasticSearch pairs
The outer query interface that succinct Restful styles are provided.Elasticsearch is developed by java applet and is made using Lucene
Inquiry data are called to realize for its core, that is, realizes the function of all indexes and search, can realize and be accurately positioned search day
Will information simultaneously analyzes related data, obtains the effect of accurately business datum.It is visually shown finally by Echart,
To hide the complexity of Lucene itself, to allow index and search to become convenient intuitive.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
Obtain other attached drawings according to these attached drawings.
Fig. 1 is prior art ELK-Stack block schematic illustrations；
Fig. 2 is monitoring of tools Echart instrument display schematic diagrams under the prior art；
Fig. 3 is total system logical architecture schematic diagram of the embodiment of the present invention.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in more detail.
Application journey to reach comprehensive monitoring application system services sequence, inexpensive service implementation is disposed, it is excellent to provide to the user
The efficient service system of matter, this programme is top-down to be respectively arranged with represent layer (View), control layer (Control), service layer
(Service), basic data layer.Wherein, the basic data layer includes：Data acquisition, data analysis, data storage, data
Caching.
As shown in figure 3, being total system logical architecture schematic diagram of the embodiment of the present invention.
Basic data layer is the data source of whole system, interacts with data collection layer downwards, is provided for data collection layer
Basic data supports.The basic data layer includes：(Data Access Object, data are visited by database, ELK components, DAO
Ask interface), HTTP (Hyper Text Transfer Protocol, hypertext transfer protocol) and caching.
The database is relevant database, is used for the related data of storage system；
The ELK components are collecting correlation log data and device data；
The DAO provides interface, downward access relation type database for Service layers upwards；
The HTTP provides service to access ElasticSearch to upper layer Service layers；
The caching is ehcache (Cache Framework in the process of a pure Java) component, to provide hot topic for system
The buffer service of data.
The service layer：Service is provided for Control layers upwards, accesses DAO, ELK or caching query data downwards, and right
The data got are handled.
The control layer：Request that responsible receiving front-end is sent out simultaneously calls service layer to obtain data, is finally fitted to corresponding
View return to front end.The front end includes displaying interface and user's interaction.
The presentation layer includes mainly blog search, monitoring of tools and visual display function.
The present invention is mainly applied by related Beats and carries out data acquisition in each server according to its configuration file, then
The data by Beats application acquisitions are collected by LogStash and the sequence generated by automatic indexing is deposited into
ElasticSearch.The inquiry that ElasticSearch externally provides Restful (a kind of software architecture, design style) style connects
Mouthful.Elasticsearch is by a kind of Java (programming language) program development and Lucene (full-text search engine) is used to be used as
Its core calls inquiry data to realize, that is, realizes the function of all indexes and search, visualized finally by Echart
Display.
The Elasticsearch also possesses following functions：Distributed real-time files storage, i.e., each field is by rope
Draw and can be searched；Distributed real-time analysis search engine can expand to up to a hundred servers；Handle PB level structures or
Unstructured data.Above-mentioned function, which can be realized, to be accurately positioned search log information and analyzes related data, and accurately industry is obtained
The effect for data of being engaged in.
The Lucene is the framework of the full-text search engine of an open source code, provide complete query engine and
Index engine.Simple RESTful API are to hide the complexity of Lucene itself, to allow index and search to become convenient
Intuitively.
Service layer is responsible for interacting with the data collection layer in represent layer and ELK components, and the service layer is adopted by data
The data that collection layer collects match daily record by Grok regular expressions.The Grok regular expressions are used for examining
Rope/replacement meets the text of some pattern/rule, including：1, pattern files are established under the path of response, with just
Then expression formula matches corresponding content format, is split to daily record；2, to be created newly according to time and service title
Index or be stored in old index.ElasticSearch stores related data according to index, and externally provides query interface.With
The prior art is compared, and the interactive mode of above-mentioned data collection layer is more efficient, and the result inquired is more accurate.
The represent layer by WEB page to the service of user's display systems and and service layer progress data interaction.Represent layer
Be responsible for the data obtained from service layer to show user in the form of more intuitive, display form include but not limited to line chart,
Block diagram, pie chart, table, map etc..
In conclusion a kind of big data analysis method based on daily record provided by the invention, is mainly answered by related Beats
Data acquisition is carried out in each server with according to its configuration file, is then collected by LogStash and is adopted by Beats applications
The data of collection are simultaneously deposited into ElasticSearch by the sequence of automatic indexing generation.ElasticSearch externally provides succinct
The query interface of Restful styles.Elasticsearch is developed by java applet and Lucene is used to be used as its core come real
Inquiry data are now called, that is, realize the function of all indexes and search, can be realized and be accurately positioned search log information and analyze
Related data obtains the effect of accurately business datum.It is visually shown finally by Echart, to hide Lucene
The complexity of itself, to allow index and search to become convenient intuitive.
Those of ordinary skills in the art should understand that：The discussion of any of the above embodiment is exemplary only, not
It is intended to imply that the scope of the present disclosure (including claim) is limited to these examples；Under the thinking of the present invention, above example
Or can also be combined between the technical characteristic in different embodiments, step can be realized with random order, and be existed such as
Many other variations of the different aspect of the upper present invention, for simplicity, they are not provided in details.Therefore, it is all
Within the spirit and principles in the present invention, any omission, modification, equivalent replacement, improvement for being made etc. should be included in the present invention's
Within protection domain.
Claims (8)
1. a kind of big data analysis method based on daily record, which is characterized in that top-down to be respectively arranged with represent layer, control
Layer, service layer and basic data layer；
The basic data layer provides data for whole system, is interacted with data collection layer downwards, and base is provided for data collection layer
Plinth data supporting；The basic data layer includes：Database, ELK components, DAO, HTTP and caching；
The service layer：To provide service upwards for Control layers, DAO, ELK or caching query data are accessed downwards, and to obtaining
The data got are handled；
The control layer：Request that responsible receiving front-end is sent out simultaneously calls service layer to obtain data, is finally fitted to and regards accordingly
Figure returns to front end；The front end includes displaying interface and user's interaction；
The presentation layer：Including blog search, monitoring of tools and visual display function.
2. the big data analysis method according to claim 1 based on daily record, which is characterized in that the database is relationship
Type database is used for the related data of storage system；
The ELK components are collecting correlation log data and device data；
The DAO provides interface, downward access relation type database for Service layers upwards；
The HTTP provides service to access ElasticSearch to upper layer Service layers；
The caching is ehcache (Cache Framework in the process of a pure Java) component, to provide hot data for system
Buffer service.
3. the big data analysis method according to claim 2 based on daily record, which is characterized in that the basic data layer phase
It closes Beats to apply according to its configuration file in the progress data acquisition of each server, then be collected by described by LogStash
The data of Beats application acquisitions are simultaneously deposited into ElasticSearch by the sequence of automatic indexing generation.
4. the big data analysis method according to claim 3 based on daily record, which is characterized in that described
Elasticsearch, which is developed by java applet and realized using Lucene as its core, calls inquiry data, that is, passes through
Java realizes the function of all indexes and search and externally provides the query interface of Restful styles.
5. the big data analysis method according to claim 3 based on daily record, which is characterized in that described
Elasticsearch has following functions：Distributed real-time files storage, i.e., each field are indexed and can be searched；Point
The real-time analysis search engine of cloth is enough the server of extension process hundred or more；Handle PB level structures or unstructured number
According to.
6. the big data analysis method according to claim 4 based on daily record, which is characterized in that the RESTful styles
Query interface to hide Lucene itself complexity.
7. the big data analysis method according to claim 1 based on daily record, which is characterized in that the service layer be responsible for
Data collection layer in represent layer and ELK components interacts, and the service layer is led to by the data that data collection layer collects
Grok regular expressions are crossed to match daily record；The Grok regular expressions are used for retrieving/replacing meeting some pattern/rule
Text then, including：1, pattern files are established under the path of response, are matched in corresponding with regular expression
Hold format, daily record is split；2, to create new index according to time and service title or be stored in old index.
8. the big data analysis method according to claim 1 based on daily record, which is characterized in that the represent layer is responsible for handle
The data obtained from service layer show user in the form of more intuitive, display form include but not limited to line chart, block diagram,
Pie chart, table, map etc..
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| PB01 | Publication | ||
| PB01 | Publication | ||
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| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 100070 Fengtai District, Feng Feng Road, No. 1, the era of fortune World Building, floor, layer 28, Beijing Applicant after: BEIJING GUODIANTONG NETWORK TECHNOLOGY Co.,Ltd. Applicant after: STATE GRID ZHEJIANG ELECTRIC POWER Co.,Ltd. Applicant after: STATE GRID INFORMATION & TELECOMMUNICATION GROUP Co.,Ltd. Applicant after: STATE GRID CORPORATION OF CHINA Address before: 100070 Fengtai District, Feng Feng Road, No. 1, the era of fortune World Building, floor, layer 28, Beijing Applicant before: BEIJING GUODIANTONG NETWORK TECHNOLOGY Co.,Ltd. Applicant before: STATE GRID ZHEJIANG ELECTRIC POWER Co.,Ltd. Applicant before: STATE GRID INFORMATION & TELECOMMUNICATION GROUP Co.,Ltd. Applicant before: State Grid Corporation of China |
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| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190719 Address after: 100085 Beijing city Haidian District Qinghe small Camp Road No. 15 Applicant after: BEIJING CHINA POWER INFORMATION TECHNOLOGY Co.,Ltd. Applicant after: STATE GRID ZHEJIANG ELECTRIC POWER Co.,Ltd. Applicant after: STATE GRID INFORMATION & TELECOMMUNICATION GROUP Co.,Ltd. Applicant after: STATE GRID CORPORATION OF CHINA Address before: 100070 Fengtai District, Feng Feng Road, No. 1, the era of fortune World Building, floor, layer 28, Beijing Applicant before: BEIJING GUODIANTONG NETWORK TECHNOLOGY Co.,Ltd. Applicant before: STATE GRID ZHEJIANG ELECTRIC POWER Co.,Ltd. Applicant before: STATE GRID INFORMATION & TELECOMMUNICATION GROUP Co.,Ltd. Applicant before: STATE GRID CORPORATION OF CHINA |
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| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181113 |