CN105760505A - Hive-based historical data analysis and archiving method - Google Patents
Hive-based historical data analysis and archiving method Download PDFInfo
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- CN105760505A CN105760505A CN201610098013.6A CN201610098013A CN105760505A CN 105760505 A CN105760505 A CN 105760505A CN 201610098013 A CN201610098013 A CN 201610098013A CN 105760505 A CN105760505 A CN 105760505A
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- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000007405 data analysis Methods 0.000 title claims abstract description 17
- 238000013499 data model Methods 0.000 claims abstract description 8
- 238000013506 data mapping Methods 0.000 claims abstract description 4
- 238000013507 mapping Methods 0.000 claims abstract description 4
- 239000007787 solid Substances 0.000 claims description 3
- 238000000547 structure data Methods 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 abstract description 4
- 238000013500 data storage Methods 0.000 abstract 1
- 238000000354 decomposition reaction Methods 0.000 abstract 1
- 230000010354 integration Effects 0.000 abstract 1
- 238000005192 partition Methods 0.000 abstract 1
- 230000008901 benefit Effects 0.000 description 4
- 238000009825 accumulation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003921 oil Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/283—Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/258—Data format conversion from or to a database
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/288—Entity relationship models
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- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a hive-based historical data analysis and archiving method, which comprises the steps of constructing a relational data model and a cloud data model, setting a storage mode of metadata, a storage mode of entity data and a mapping step of a data mapping layer in a relational database, analyzing a large data volume, performing association decomposition and integration on a large data volume file stored by a hbase, optimizing an analysis result, storing and archiving according to different dimensions, and providing an operation interface. According to the method, the key/value format data file is converted into the structured data format through the data storage model, the result data is subjected to partition archiving and storage through multi-table analysis and association, and the problems of hbase data rapid analysis, hbase data archiving, non-professional operation and the like are solved.
Description
Technical field
The present invention relates to the storage of big data, analysis technical field, be specifically related to a kind of historical data analysis based on hive and archiving method.
Background technology
Big data, while bringing huge technological challenge, also bring huge technological innovation and business opportunities.Constantly the big packet of accumulation is containing the deep knowledge much not possessed when small data quantity and value, it will be that industry/enterprise brings huge commercial value that big data analysis excavates, realize the value-added service of various high added value, promote economic benefit and the social benefit of industry/enterprise further.Owing to big data imply huge deep value, U.S. government thinks that big data are " following young oils ", and following scientific and technological and economic development will be brought profound influence.Therefore, in future, country has the scale of data and the ability of maintenance data will become the important component part of overall national strength, occupying, control and using and also will become contention focus new between country and between enterprise data.
Summary of the invention
The technical problem to be solved in the present invention is: the present invention provides a kind of historical data analysis based on hive and archiving method, the model stored by data is by the data file of key/value form, it is converted into structurized data form, and by multilist analyzing and associating, result data is carried out subregion filing storage.
The technical solution adopted in the present invention is:
Historical data analysis and archiving method based on hive, described method is by building relational data model and cloud data model, the mapping step etc. of the memory module of metadata in relational database, the memory module of solid data and data mapping layer is set, big data quantity is analyzed, it is associated decomposing by the file of the hbase big data quantity stored and integrates, optimize and analyze result, achieve by different dimensions storage, and operation interface is provided, be easy to operation, solve hbase data are quickly analyzed, hbase archives data, the problem such as layman's operation.
The data analysis system deploying step that described method relates to is as follows:
The first step, disposes service and the Hbase distributed storage nodes such as hbase, hive relevant for Hadoop;
Second step, mounting structure data base;
3rd step, disposes data analysis system.
Described method concrete operation step is as follows:
Step 1:hive is outside maps hbase data;
Step 2: create hive and achieve table, and create the division;
Step 3: the hbase data that outside maps are analyzed, are stored in interim table;
Step 4: verify interim table content;
Step 5: after being verified, is inserted with interim table content in the archive table of subregion;
Step 6: be operated by interface, carries out data summarization and inquiry.
Hive is based on a Tool for Data Warehouse of Hadoop, it is possible to structurized data file is mapped as a database table, and provides complete sql query function, it is possible to sql statement is converted to MapReduce task and runs.Its advantage is that learning cost is low, it is possible to quickly realize simple MapReduce statistics by class SQL statement, it is not necessary to develops special MapReduce application, is very suitable for the statistical analysis of data warehouse.
The invention have the benefit that
The model that the present invention is stored by data is by the data file of key/value form, it is converted into structurized data form, and by multilist analyzing and associating, result data is carried out subregion filing storage, solve hbase data are quickly analyzed, hbase archives data, the problem such as layman's operation.
Accompanying drawing explanation
Fig. 1 is the flowage structure figure of the present invention.
Detailed description of the invention
Below in conjunction with Figure of description, by detailed description of the invention, the present invention is further described:
Embodiment 1:
Historical data analysis and archiving method based on hive, described method is by building relational data model and cloud data model, the mapping step etc. of the memory module of metadata in relational database, the memory module of solid data and data mapping layer is set, big data quantity is analyzed, it is associated decomposing by the file of the hbase big data quantity stored and integrates, optimize and analyze result, achieve by different dimensions storage, and operation interface is provided, be easy to operation, solve hbase data are quickly analyzed, hbase archives data, the problem such as layman's operation.
Embodiment 2:
On the basis of embodiment 1, the data analysis system deploying step that method described in the present embodiment relates to is as follows:
The first step, disposes service and the Hbase distributed storage nodes such as hbase, hive relevant for Hadoop;
Second step, mounting structure data base;
3rd step, disposes data analysis system.
Embodiment 2:
As it is shown in figure 1, on the basis of embodiment 1 or 2, described in the present embodiment, method concrete operation step is as follows:
Step 1:hive is outside maps hbase data;
Step 2: create hive and achieve table, and create the division;
Step 3: the hbase data that outside maps are analyzed, are stored in interim table;
Step 4: verify interim table content;
Step 5: after being verified, is inserted with interim table content in the archive table of subregion;
Step 6: be operated by interface, carries out data summarization and inquiry.
Embodiment of above is merely to illustrate the present invention; and it is not limitation of the present invention; those of ordinary skill about technical field; without departing from the spirit and scope of the present invention; can also make a variety of changes and modification; therefore all equivalent technical schemes fall within scope of the invention, and the scope of patent protection of the present invention should be defined by the claims.
Claims (3)
1. based on the historical data analysis of hive and archiving method, it is characterized in that: described method is by building relational data model and cloud data model, the mapping step of the memory module of metadata in relational database, the memory module of solid data and data mapping layer is set, big data quantity is analyzed, it is associated decomposing by the file of the hbase big data quantity stored and integrates, optimize and analyze result, achieve by different dimensions storage, and operation interface is provided.
2. the historical data analysis based on hive according to claim 1 and archiving method, it is characterised in that the data analysis system deploying step that described method relates to is as follows:
The first step, disposes hbase, hive service relevant for Hadoop and Hbase distributed storage node;
Second step, mounting structure data base;
3rd step, disposes data analysis system.
3. the historical data analysis based on hive according to claim 1 and 2 and archiving method, it is characterised in that described method concrete operation step is as follows:
Step 1:hive is outside maps hbase data;
Step 2: create hive and achieve table, and create the division;
Step 3: the hbase data that outside maps are analyzed, are stored in interim table;
Step 4: verify interim table content;
Step 5: after being verified, is inserted with interim table content in the archive table of subregion;
Step 6: be operated by interface, carries out data summarization and inquiry.
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106227862A (en) * | 2016-07-29 | 2016-12-14 | 浪潮软件集团有限公司 | E-commerce data integration method based on distribution |
CN106250465A (en) * | 2016-07-29 | 2016-12-21 | 沈阳华创风能有限公司 | A kind of method and device improving database filing efficiency |
CN106844496A (en) * | 2016-12-26 | 2017-06-13 | 山东中创软件商用中间件股份有限公司 | Data transmission scheduling method, device and server based on ESB |
CN106909645A (en) * | 2017-02-21 | 2017-06-30 | 中国科学院电子学研究所 | A kind of space-time data organization of unity method of expansible definition |
CN108268565A (en) * | 2017-01-04 | 2018-07-10 | 北京京东尚科信息技术有限公司 | Method and system based on data warehouse processing user browsing behavior data |
CN108470045A (en) * | 2018-03-06 | 2018-08-31 | 平安科技(深圳)有限公司 | The method and storage medium that electronic device, data chain type are filed |
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CN102521246A (en) * | 2011-11-11 | 2012-06-27 | 国网信息通信有限公司 | Cloud data warehouse system |
CN103678665A (en) * | 2013-12-24 | 2014-03-26 | 焦点科技股份有限公司 | Heterogeneous large data integration method and system based on data warehouses |
US20140156638A1 (en) * | 2012-11-30 | 2014-06-05 | Orbis Technologies, Inc. | Ontology harmonization and mediation systems and methods |
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CN102521246A (en) * | 2011-11-11 | 2012-06-27 | 国网信息通信有限公司 | Cloud data warehouse system |
US20140156638A1 (en) * | 2012-11-30 | 2014-06-05 | Orbis Technologies, Inc. | Ontology harmonization and mediation systems and methods |
CN103678665A (en) * | 2013-12-24 | 2014-03-26 | 焦点科技股份有限公司 | Heterogeneous large data integration method and system based on data warehouses |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106227862A (en) * | 2016-07-29 | 2016-12-14 | 浪潮软件集团有限公司 | E-commerce data integration method based on distribution |
CN106250465A (en) * | 2016-07-29 | 2016-12-21 | 沈阳华创风能有限公司 | A kind of method and device improving database filing efficiency |
CN106844496A (en) * | 2016-12-26 | 2017-06-13 | 山东中创软件商用中间件股份有限公司 | Data transmission scheduling method, device and server based on ESB |
CN106844496B (en) * | 2016-12-26 | 2020-04-10 | 山东中创软件商用中间件股份有限公司 | Data transmission scheduling method and device based on enterprise service bus and server |
CN108268565A (en) * | 2017-01-04 | 2018-07-10 | 北京京东尚科信息技术有限公司 | Method and system based on data warehouse processing user browsing behavior data |
CN106909645A (en) * | 2017-02-21 | 2017-06-30 | 中国科学院电子学研究所 | A kind of space-time data organization of unity method of expansible definition |
CN106909645B (en) * | 2017-02-21 | 2019-03-26 | 中国科学院电子学研究所 | A kind of space-time data organization of unity method of expansible definition |
CN108470045A (en) * | 2018-03-06 | 2018-08-31 | 平安科技(深圳)有限公司 | The method and storage medium that electronic device, data chain type are filed |
CN108470045B (en) * | 2018-03-06 | 2020-02-18 | 平安科技(深圳)有限公司 | Electronic device, data chain archiving method and storage medium |
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