WO2016169237A1 - Procédé et dispositif de traitement de données - Google Patents

Procédé et dispositif de traitement de données Download PDF

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Publication number
WO2016169237A1
WO2016169237A1 PCT/CN2015/092759 CN2015092759W WO2016169237A1 WO 2016169237 A1 WO2016169237 A1 WO 2016169237A1 CN 2015092759 W CN2015092759 W CN 2015092759W WO 2016169237 A1 WO2016169237 A1 WO 2016169237A1
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WIPO (PCT)
Prior art keywords
data
split
import
processing
module
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PCT/CN2015/092759
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English (en)
Chinese (zh)
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韩烨
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中兴通讯股份有限公司
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Publication of WO2016169237A1 publication Critical patent/WO2016169237A1/fr

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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
    • 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
    • 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

Definitions

  • the present invention relates to the field of communications, and in particular to a data processing method and apparatus.
  • Database technology is the core of various information systems such as management information systems, office automation systems, and decision support systems. Part of it is an important technical means for scientific research and decision management.
  • the present invention provides a data processing method and apparatus to solve at least the problem of low data import efficiency existing in the related art.
  • a data processing method includes: receiving a data import instruction for instructing data to be imported into a database; and splitting the data according to the data import instruction; The data chunks are imported into different storage spaces in the database.
  • the splitting the data according to the data importing instruction comprises: determining, according to the data importing instruction, a table structure of the table and data distribution information of the data on the table; according to the table structure And the data distribution information and the descriptor information of the data carried in the data importing instruction identify each data row field in the data; and perform the data according to each data row field in the identified data.
  • Split processing comprises: determining, according to the data importing instruction, a table structure of the table and data distribution information of the data on the table; according to the table structure And the data distribution information and the descriptor information of the data carried in the data importing instruction identify each data row field in the data; and perform the data according to each data row field in the identified data.
  • performing the splitting process on the data according to the data importing instruction includes: determining whether the data satisfies a splitting rule; and if the determining result is yes, performing the splitting process on the data; If the result is no, the data is subjected to correction processing; and the corrected data is subjected to split processing.
  • importing the split data into the different storage spaces in the database includes: downloading the split processed data; and importing the downloaded split data into the storage In the different storage spaces in the database.
  • the method further includes: deleting the downloaded data after the split processing.
  • the method further includes: summarizing the import result after the split processed data is imported; and feeding back the import result.
  • a data processing apparatus comprising: a receiving module configured to receive a data import instruction for instructing data to be imported into a database; and a processing module configured to: according to the data import instruction The data is split and processed; the import module is configured to import the split processed data into different storage spaces in the database.
  • the processing module includes: a determining unit, configured to determine a table structure of the table according to the data importing instruction and data distribution information of the data on the table; and an identifying unit configured to be according to the table structure And the data distribution information and the descriptor information of the data carried in the data importing instruction identify each data row field in the data; the first processing unit is configured to each data according to the identified data The row field splits the data.
  • the processing module includes: a determining unit, configured to determine whether the data satisfies a splitting rule; and a second processing unit configured to: when the determining result of the determining unit is yes, the data is Performing a splitting process; the correcting unit is configured to perform a correction process on the data when the determination result of the determination unit is negative; and the third processing unit is configured to perform a split process on the data after the correction process.
  • the importing module includes: a downloading unit configured to download the split processed data; and an importing unit configured to import the downloaded split processed data into blocks into different storages in the database In space.
  • the device further includes: a deleting module, configured to delete the downloaded split processed data.
  • a deleting module configured to delete the downloaded split processed data.
  • the device further includes: a summary module, configured to summarize the import result after the split processing is performed, and the feedback module is configured to feed back the import result.
  • a summary module configured to summarize the import result after the split processing is performed
  • the feedback module is configured to feed back the import result.
  • a data import instruction for instructing data to be imported into a database is received; the data is split according to the data import instruction; and the split data block is imported into the database.
  • the problem of low data import efficiency existing in the related art is solved, and the effect of improving data import efficiency is achieved.
  • FIG. 1 is a flow chart of a data processing method according to an embodiment of the present invention.
  • FIG. 2 is a block diagram showing the structure of a data processing apparatus according to an embodiment of the present invention.
  • FIG. 3 is a first structural block diagram of a processing module 24 in a data processing apparatus according to an embodiment of the present invention.
  • FIG. 4 is a block diagram showing a second structure of the processing module 24 in the data processing apparatus according to an embodiment of the present invention.
  • FIG. 5 is a structural block diagram of an import module 26 in a data processing apparatus according to an embodiment of the present invention.
  • FIG. 6 is a block diagram of a first preferred structure of a data processing apparatus according to an embodiment of the present invention.
  • FIG. 7 is a block diagram showing a second preferred structure of a data processing apparatus according to an embodiment of the present invention.
  • FIG. 8 is a block diagram showing the structure of an import system according to an embodiment of the present invention.
  • FIG. 9 is a flow chart of data import processing in accordance with an embodiment of the present invention.
  • FIG. 1 is a flowchart of a data processing method according to an embodiment of the present invention. As shown in FIG. 1, the process includes the following steps:
  • Step S102 receiving a data import instruction for instructing to import data into the database
  • Step S104 performing splitting processing on the data according to the data importing instruction
  • step S106 the split data block is imported into different storage spaces in the database.
  • the above-mentioned database can be called a distributed database system, in which the database system is free from the dependence of large equipment by constructing a high-availability and high-expansion cluster by using ordinary inexpensive equipment.
  • a good distributed database architecture can be easily accessed for high availability and can scale out.
  • the import and export function of large data volume is a key technology in distributed databases.
  • the data may be split according to the table used for splitting, wherein the data is imported according to the data import instruction.
  • Performing the splitting process includes: determining, according to the data importing instruction, a table structure of the table and data distribution information of the data on the table; and identifying data according to the table structure, the data distribution information, and the descriptor information of the data carried in the data importing instruction.
  • Each data row field; the data is split according to each data row field in the identified data.
  • the legality of the data import instruction may be first determined, and then the table structure information and the distribution policy information of the imported destination library table are obtained, and then the data file is read, according to the table structure information and the distribution strategy.
  • Splitting the imported data file into multiple underlying databases ie, the above-mentioned storage space) storing a plurality of corresponding small files and transmitting them to the underlying database of each destination
  • the cluster management module issues instructions to each of the underlying databases to perform import of the corresponding files.
  • the splitting the data according to the data importing instruction includes: determining whether the data satisfies the splitting rule; and if the determining result is yes, splitting the data; If not, the above data is corrected; the corrected data is split.
  • there may be multiple correction methods which may be performed by an administrator, that is, artificially; or, by means of a module that performs split processing, other modules may be acquired without manual intervention.
  • Correction is performed according to some correction rules; of course, it can be corrected by manual and corresponding modules, and so on.
  • This method can be used to know in time whether the data that needs to be imported into the database can be split, thereby further improving the splitting efficiency.
  • the error line data can be extracted to ensure the correctness of the imported data.
  • the split processed data when the split data block is imported into a different storage space in the database, the split processed data may be downloaded first; and the downloaded split processed data is downloaded. The partitions are imported into different storage spaces in the database.
  • the method further includes: Delete the downloaded split processed data. Thereby achieving the purpose of clearing the garbage data file and reducing the memory occupation. This allows the database to store more data.
  • the import result may also be fed back.
  • the method further includes: performing import processing on the split processed data. After the import result; feedback the above import results. This allows the user to clearly determine the import result.
  • the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware, but in many cases, the former is A better implementation.
  • the technical solution of the present invention which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a cell phone, a computer, a server, or a network device, etc.) to perform the methods of various embodiments of the present invention.
  • a data processing device is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described again.
  • the term “module” may implement a combination of software and/or hardware of a predetermined function.
  • the apparatus described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware, is also possible and contemplated.
  • FIG. 2 is a block diagram showing the structure of a data processing apparatus according to an embodiment of the present invention. As shown in FIG. 2, the apparatus includes a receiving module 22, a processing module 24, and an importing module 26. The apparatus will be described below.
  • the receiving module 22 is configured to receive a data import instruction for instructing to import data into the database; the processing module 24, The receiving module 22 is configured to split the data according to the data importing instruction; the importing module 26 is connected to the processing module 24, and is configured to import the split processed data into different storages in the database. In space.
  • FIG. 3 is a first structural block diagram of a processing module 24 in a data processing apparatus according to an embodiment of the present invention.
  • the processing module 24 includes a determining unit 32, an identifying module 34, and a first processing unit 36. The device will be described.
  • the determining unit 32 is configured to determine the table structure of the table and the data distribution information of the data on the table according to the data importing instruction; the identifying unit 34 is connected to the determining unit 32, and is set according to the table structure, the data distribution information, and the data importing instruction.
  • the descriptor information of the carried data identifies each data line field in the data; the first processing unit 36, coupled to the above-described identification unit 34, is arranged to split the data according to each of the data row fields in the identified data.
  • FIG. 4 is a second structural block diagram of a processing module 24 in a data processing apparatus according to an embodiment of the present invention.
  • the processing module 24 includes a determining unit 42, a second processing unit 44, a correcting unit 46, and a third Processing unit 48, the processing module 24 will be described below.
  • the determining unit 42 is configured to determine whether the data satisfies the splitting rule; the second processing unit 44 is connected to the determining unit, and is configured to perform splitting processing on the data if the determining result of the determining unit 42 is YES; The correcting unit 46 is connected to the determining unit 42 and configured to perform correction processing on the data when the determination result of the determining unit 42 is negative. The third processing unit 48 is connected to the correcting unit 46 and is set to correct the data. The processed data is split.
  • the import module 26 includes a download unit 52 and an import unit 54, which will be described below.
  • the download unit 52 is configured to download the split processed data
  • the import unit 54 is connected to the download unit 52, and is configured to import the downloaded split processed data into different storage spaces in the database.
  • FIG. 6 is a block diagram of a first preferred structure of a data processing apparatus according to an embodiment of the present invention. As shown in FIG. 6, the apparatus includes a deletion module 62 in addition to all the modules shown in FIG. Be explained.
  • the deletion module 62 is connected to the above-described import module 26 and is set to delete the downloaded split processed data.
  • FIG. 7 is a second preferred structural block diagram of a data processing apparatus according to an embodiment of the present invention. As shown in FIG. 7, the apparatus includes a summary module 72 and a feedback module 74, in addition to all the modules shown in FIG. The device will be described.
  • the summary module 72 is connected to the import module 26, and is provided to summarize the import result after the split processing data is imported.
  • the feedback module 74 is connected to the summary module 72 and is provided to feed back the import result.
  • the existing solutions in the related art are all performed on a traditional single database, and the efficiency of the table is not required, and the system architecture is not required.
  • the solution in the embodiment of the present invention is based on a distributed database system, and satisfies the characteristics of the atomicity/consistency/isolation/durability (ACID) of the database, and can be executed concurrently.
  • ACID atomicity/consistency/isolation/durability
  • the data import client module 82 is included.
  • the module may be located between an external system and a data import server module, or may be located in an external system.
  • the module is not shown in FIG. 8), the data import server module 84 (corresponding to the download server 84 in FIG. 8, the same as the receiving module 22, the processing module 24, and the import module 26), and the metadata center module 86 ( Corresponding to the metadata server 84 in FIG. 8 , the cluster management center module 88 (corresponding to the cluster manager 88 in FIG. 8 , the same as the summary module 72 and the feedback module 74 described above), and the database proxy module 810 (the same as the above deletion) Module 62) and database module 812, each module will be described below.
  • the data import client module 82 (LoadClient) is mainly for the user, and the user initiates an import and export command through the module.
  • the data import server module 84 (LoadServer) is configured to accept the import and export commands sent by the client, split and merge the data files according to the data distribution policy, and interact with other modules to coordinate the entire import and export process.
  • the metadata center module 86 is arranged to store and manage all metadata information for the entire distributed database system.
  • the cluster management center module 88 is mainly responsible for monitoring, managing, and maintaining various database clusters (DBClusters).
  • the database agent module 810 is a database node management monitoring module. It is responsible for real-time monitoring of the running status of the DB nodes under its jurisdiction, and periodically collects running statistics.
  • Database module 812 is the underlying module that holds all data.
  • the data import and export server module 84 queries the metadata center module 86 for the metadata information of the table according to the cluster ID, the database name, and the table name, and is used to obtain the table structure definition and the data distribution information;
  • the data import server module 84 uses the obtained information (plus the data file descriptor information) to identify each data row field in the data file (datafilename), and performs data file splitting;
  • the data import server module 84 requests the cluster management center module 88 to notify each database agent module 810 to download the split file of the managed DBGroup;
  • the data import server module 84 requests the cluster management center module 88 to notify the respective database agent module 810 to execute the real load data file LOAD DATA INFILE command after each database agent module 810 downloads successfully;
  • the data import and export server module 84 requests the cluster management center 88 to notify each database agent module 810 to delete the garbage data file (the garbage data file here may be the downloaded data after being loaded);
  • the data import server module 84 summarizes the results and notifies the data import and export client module 82.
  • FIG. 9 is a flowchart of data import processing according to an embodiment of the present invention. As shown in FIG. 9, the flow includes the following steps:
  • Step S902 the data import client module 82 sends an import data request to the data import server module 84.
  • Step S904 the data import server module 84 sends a query database metadata request to the metadata center module 86 according to the cluster ID, the database name, and the table name, and the request is used to query the metadata information of the table;
  • Step S906 the metadata center module 86 returns a table structure definition and data distribution information, including various field types and lengths of the table, and distribution keys and which DBGroups are distributed;
  • step S908 the data import server module 84 uses the information returned by the metadata center module 88 (in addition, the data file descriptor information) to identify each data row field in the data file (datafilename) for data file splitting. If the data is wrong during the splitting process, if the type does not meet the definition of the table, the error data is selected and placed in the error file;
  • Step S910 the data import server module 84 requests the cluster management center module 88 to notify each database agent module 810 to download the split file of the managed DBGroup;
  • Step S912 the cluster management center module 88 notifies each database proxy module 810 to download the split file of the managed DBGroup;
  • each database proxy module 810 notifies the ftp service connection data import server module 84 to download the corresponding split file, and each database proxy module 810 successfully downloads the corresponding split file and returns to the cluster management center module 88. response;
  • Step S916 the cluster management center module 88 summarizes the download result
  • Step S918 after receiving the successful response of all the database proxy modules 810, the cluster management center module 88 returns a successful response to the data import server module 84.
  • Step S920 after the data import server module 84 downloads successfully, the cluster management center module 88 is requested to notify each database agent module 810 to execute a real LOAD DATA INFILE command;
  • Step S922 the cluster management center module 88 notifies the database proxy module 810 to execute the real LOAD DATA INFILE command;
  • each database proxy module 810 connects to the managed database module to execute a real LOAD DATA INFILE command; after each database proxy module 810 executes the real LOAD DATA INFILE command successfully, it returns a successful response to the cluster management center module 88;
  • Step S926 after receiving the successful response of all the database proxy modules 810, the cluster management center module 88 returns a successful response to the data import server module 84; after the LOAD DATA INFILE command is successfully executed, the data import server module 84 requests the cluster management center module again. 88 to notify each database agent module to delete the garbage data file; the data import server module 84 summarizes the results and notifies the data import client module 82.
  • the solution in the above embodiment is based on a distributed database system, and can import all data types supported by the Mysql database, and of course, can support other types of numbers.
  • Applying the solution in the embodiment of the present invention to the distributed database system can increase the concurrency of 2 to 3 times, balance the load, ensure the correctness of importing and exporting data, and the system is robust.
  • each of the above modules may be implemented by software or hardware.
  • the foregoing may be implemented by, but not limited to, the foregoing modules are all located in the same processor; or, the modules are located in multiple In the processor.
  • Embodiments of the present invention also provide a storage medium.
  • the foregoing storage medium may be configured to store program code for performing the following steps:
  • the foregoing storage medium may include, but is not limited to, a USB flash drive, a Read-Only Memory (ROM), and a Random Access Memory (RAM).
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • modules or steps of the present invention described above can be implemented by a general-purpose computing device that can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device such that they may be stored in the storage device by the computing device and, in some cases, may be different from the order herein.
  • the steps shown or described are performed, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps thereof are fabricated as a single integrated circuit module.
  • the invention is not limited to any specific combination of hardware and software.
  • the data processing method and apparatus provided by the embodiments of the present invention have the following beneficial effects: the problem of low data import efficiency existing in the related art is solved, and the effect of improving data import efficiency is achieved.

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Abstract

L'invention concerne un procédé et un dispositif de traitement de données. Le procédé comprend les étapes consistant à : recevoir une instruction d'importation de données destinée à donner une consigne d'importation de données dans une base de données; diviser les données selon l'instruction d'importation de données; et importer les données divisées dans différents espaces de stockage dans la base de données en blocs. La présente invention aborde le problème existant dans l'état de la technique apparentée du faible rendement d'importation de données, améliorant ainsi le rendement d'importation de données.
PCT/CN2015/092759 2015-04-23 2015-10-23 Procédé et dispositif de traitement de données WO2016169237A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019205415A1 (fr) * 2018-04-22 2019-10-31 平安科技（深圳）有限公司 Procédé et appareil de gestion d'importation de données, terminal mobile et support d'informations

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108153852A (zh) * 2017-12-22 2018-06-12 中国平安人寿保险股份有限公司 一种数据处理方法、装置、终端设备及存储介质
CN108256087B (zh) * 2018-01-22 2020-12-04 北京腾云天下科技有限公司 一种基于位图结构的数据导入、查询及处理方法
CN110110024B (zh) * 2019-04-29 2021-12-17 东南大学 一种大容量vct文件导入空间数据库方法
CN110795764A (zh) * 2019-11-01 2020-02-14 中国银行股份有限公司 一种数据脱敏方法及系统
CN110990405B (zh) * 2019-11-28 2024-04-12 中国银行股份有限公司 一种数据装载方法、装置、服务器及存储介质
CN113722277A (zh) * 2020-05-25 2021-11-30 中兴通讯股份有限公司 一种数据导入方法、装置、服务平台及存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050055351A1 (en) * 2003-09-05 2005-03-10 Oracle International Corporation Apparatus and methods for transferring database objects into and out of database systems
CN102750368A (zh) * 2012-06-18 2012-10-24 天津神舟通用数据技术有限公司 一种数据库集群数据高速导入方法
CN102906751A (zh) * 2012-07-25 2013-01-30 华为技术有限公司 一种数据存储、数据查询的方法及装置
CN103077183A (zh) * 2012-12-14 2013-05-01 北京普泽天玑数据技术有限公司 一种分布式顺序表的数据导入方法及其系统
CN103473334A (zh) * 2013-09-18 2013-12-25 浙江中控技术股份有限公司 数据存储、查询方法及系统

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8078825B2 (en) * 2009-03-11 2011-12-13 Oracle America, Inc. Composite hash and list partitioning of database tables

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050055351A1 (en) * 2003-09-05 2005-03-10 Oracle International Corporation Apparatus and methods for transferring database objects into and out of database systems
CN102750368A (zh) * 2012-06-18 2012-10-24 天津神舟通用数据技术有限公司 一种数据库集群数据高速导入方法
CN102906751A (zh) * 2012-07-25 2013-01-30 华为技术有限公司 一种数据存储、数据查询的方法及装置
CN103077183A (zh) * 2012-12-14 2013-05-01 北京普泽天玑数据技术有限公司 一种分布式顺序表的数据导入方法及其系统
CN103473334A (zh) * 2013-09-18 2013-12-25 浙江中控技术股份有限公司 数据存储、查询方法及系统

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019205415A1 (fr) * 2018-04-22 2019-10-31 平安科技（深圳）有限公司 Procédé et appareil de gestion d'importation de données, terminal mobile et support d'informations

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