WO2021179722A1 - Procédé et système d'analyse d'énoncé sql, et dispositif informatique et support de stockage - Google Patents

Procédé et système d'analyse d'énoncé sql, et dispositif informatique et support de stockage Download PDF

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Publication number
WO2021179722A1
WO2021179722A1 PCT/CN2020/135735 CN2020135735W WO2021179722A1 WO 2021179722 A1 WO2021179722 A1 WO 2021179722A1 CN 2020135735 W CN2020135735 W CN 2020135735W WO 2021179722 A1 WO2021179722 A1 WO 2021179722A1
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layer
sql
field
directed acyclic
acyclic graph
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PCT/CN2020/135735
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English (en)
Chinese (zh)
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陈玉
张茜
凌海挺
杜均
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平安科技（深圳）有限公司
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Publication of WO2021179722A1 publication Critical patent/WO2021179722A1/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
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/242—Query formulation
    • G06F16/2433—Query languages
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformation of program code
    • G06F8/41—Compilation
    • G06F8/42—Syntactic analysis
    • G06F8/425—Lexical analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformation of program code
    • G06F8/41—Compilation
    • G06F8/42—Syntactic analysis
    • G06F8/427—Parsing

Definitions

  • This application relates to the field of data processing technology, in particular to SQL statement parsing methods, systems, computer equipment and storage media.
  • data needs to be managed, maintained and used through data governance.
  • data blood relationship is analyzed through the SQL statements used in the data processing process to analyze the source and destination of the data. Govern other tasks to provide an important data foundation.
  • the SQL statements used in data blood relationship analysis can be divided into original SQL statements and SQL statements converted by the database system.
  • This method uses the original SQL statement for analysis.
  • the original SQL basically has no dependence on the database software, which reduces the complexity of the data blood relationship analysis system.
  • the inventor realizes that the data dictionary can provide auxiliary data for implicit references, making the analysis results of blood data more comprehensive and detailed. However, it may cause unnecessary data information leakage.
  • the data dictionary enlarges the range of metadata that can be accessed during the SQL parsing process, which poses a certain security risk.
  • this method does not use the data dictionary, try to fully resolve the implicit references between the fields appearing in the SQL statement, and generate the data blood relationship.
  • this application provides a SQL statement parsing method, system, computer equipment, and storage medium, by which SQL statement parsing method can avoid interaction with database software, without having to access additional metadata, and try to protect user metadata Security.
  • the present application provides a method for parsing SQL statements based on the blood relationship of data, and the method for parsing SQL statements includes:
  • Step 1 Obtain a directed acyclic graph, which is obtained by combing SQL statements;
  • Step 2 Traverse the layers of the directed acyclic graph with SQL sub-query to obtain the layer where the substitution symbol appears, and the layer where the substitution symbol first appears during the traversal is the current layer;
  • Step 3 Obtain the field corresponding to the substitute character in the current layer according to the field of the previous layer in the current layer;
  • Step 4 Continue to obtain the remaining layers where the substitute symbols appear, and perform the substitution of the substitute symbols, until all the substitute symbols in the directed acyclic graph are resolved.
  • the present application also provides a SQL statement analysis system based on the blood relationship of the data, and the SQL statement analysis system includes:
  • the data set module is used to obtain a directed acyclic graph, which is obtained by combing SQL statements
  • the traversal module is used to traverse the layers of the directed acyclic graph with SQL sub-queries, and obtain the layer where the substitution symbol appears, and the layer where the substitution symbol first appears during the traversal is the current layer;
  • the substitution module is used to obtain the field corresponding to the substitute symbol in the current layer according to the field of the previous layer of the current layer; The substitution of substitute characters until all substitute characters in the directed acyclic graph are resolved.
  • the present application also provides a computer device, including a memory and a processor.
  • the memory stores computer-readable instructions.
  • the processor executes the following steps:
  • Step 1 Obtain a directed acyclic graph, which is obtained by combing SQL statements;
  • Step 2 Traverse the layers of the directed acyclic graph with SQL sub-query to obtain the layer where the substitution symbol appears, and the layer where the substitution symbol first appears during the traversal is the current layer;
  • Step 3 Obtain the field corresponding to the substitute character in the current layer according to the field of the previous layer in the current layer;
  • Step 4 Continue to obtain the remaining layers where the substitute symbols appear, and perform the substitution of the substitute symbols, until all the substitute symbols in the directed acyclic graph are resolved.
  • this application also provides a storage medium storing a program file capable of implementing the following steps, the steps including:
  • Step 1 Obtain a directed acyclic graph, which is obtained by combing SQL statements;
  • Step 2 Traverse the layers of the directed acyclic graph with SQL sub-query to obtain the layer where the substitution symbol appears, and the layer where the substitution symbol first appears during the traversal is the current layer;
  • Step 3 Obtain the field corresponding to the substitute character in the current layer according to the field of the previous layer in the current layer;
  • Step 4 Continue to obtain the remaining layers where the substitute symbols appear, and perform the substitution of the substitute symbols, until all the substitute symbols in the directed acyclic graph are resolved.
  • the above application provides a SQL statement analysis method, system, computer device and storage medium, wherein the SQL statement analysis method obtains a directed acyclic graph, and the directed acyclic graph is obtained by combing SQL statements; To an acyclic graph layer with SQL sub-query, get the layer where the substitution symbol appears, and take the layer where the substitution symbol appears first during the traversal as the current layer; according to the field of the previous layer of the current layer, get the current layer The field corresponding to the substitution symbol; continue to obtain the remaining layers where the substitution symbol appears, and replace it until all the substitution symbols in the directed acyclic graph are resolved.
  • the SQL statement analysis method used in the SQL-based data blood relationship analysis software tool or system does not need to interact with the database software and does not need to access additional metadata to achieve data blood relationship analysis; in addition, in data security
  • this SQL statement parsing method can achieve high cohesion and low coupling data blood relationship analysis function, which can reduce external dependence, and does not need to obtain other metadata that does not appear in the data blood relationship, so it can be guaranteed as much as possible
  • the security of user metadata will not expose metadata information that does not appear in the relevant SQL due to the analysis of the blood relationship of the data.
  • this application also involves blockchain technology.
  • Figure 1 is an implementation environment diagram of a SQL statement parsing method provided in an embodiment
  • Figure 2 is a block diagram of the internal structure of a computer device in an embodiment
  • Figure 3 is a flowchart of a method for parsing SQL statements in an embodiment
  • Figure 4 is a flow chart for generating a directed acyclic graph in an embodiment
  • Figure 5 is a flowchart of SQL code cleaning in an embodiment
  • Fig. 6 is a schematic diagram of a SQL nested query structure in an embodiment
  • Fig. 7 is a schematic diagram of a directed acyclic graph generated according to Fig. 6;
  • Figure 8 is a schematic diagram of a directed acyclic graph in an embodiment
  • Example 9 is a schematic diagram of the directed acyclic graph of Example 1 in an embodiment
  • Figure 10 is a schematic diagram of the directed acyclic graph of Example 2 in an embodiment
  • Example 11 is a schematic diagram of the directed acyclic graph of Example 3 in an embodiment
  • Figure 12 is a schematic diagram of a SQL statement parsing system in an embodiment
  • Figure 13 is a schematic diagram of a data set module in an embodiment
  • Figure 14 is a schematic diagram of a cleaning module in an embodiment
  • 15 is a schematic diagram of the structure of a computer device in an embodiment
  • FIG. 16 is a schematic diagram of the structure of a storage medium in an embodiment.
  • FIG. 1 is an implementation environment diagram of an SQL statement parsing method based on data blood relationship provided in an embodiment. As shown in FIG. 1, the implementation environment includes a computer device 110 and a display device 120.
  • the computer device 110 may be a computer device used by the user, such as a computer, and the computer device 110 is equipped with a SQL statement parsing system based on the blood relationship of the data.
  • the user can perform analysis on the computer device 110 according to the SQL statement analysis method based on the blood relationship of the data, and display the analysis result on the display device 120.
  • the combination of the computer device 110 and the display device 120 can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited to this.
  • Figure 2 is a schematic diagram of the internal structure of a computer device in an embodiment.
  • the computer device includes a processor, a non-volatile storage medium, a memory, and a network interface connected through a system bus.
  • the non-volatile storage medium of the computer device stores an operating system, a database, and computer-readable instructions.
  • the database may store control information sequences.
  • the processor can realize a A SQL statement parsing method based on the blood relationship of the data.
  • the processor of the computer equipment is used to provide calculation and control capabilities, and supports the operation of the entire computer equipment.
  • a computer readable instruction may be stored in the memory of the computer device, and when the computer readable instruction is executed by the processor, the processor may execute a SQL statement parsing method based on the blood relationship of the data.
  • the network interface of the computer device is used to connect and communicate with the terminal.
  • a method for parsing SQL statements based on data blood relationship is proposed.
  • This application can also be applied to data warehouse scenarios, thereby promoting the purpose of building big data.
  • the SQL statement parsing method can be applied to the aforementioned computer device 110 and display device 120, and specifically can include the following steps:
  • Step 31 Obtain a directed acyclic graph, which is obtained by combing SQL statements.
  • a complex SQL may be composed of multiple sub-SQL (query statements).
  • the most basic and atomic SQL may be composed of basic elements such as SQL keywords, fields, tables, functions, etc., in order to record the basics of SQL as completely as possible. Elements and the relationship between them, resulting in a field-level mapping relationship.
  • a directed acyclic graph can be obtained, specifically, including:
  • the S311 includes:
  • the script file may be a script such as perl.
  • S312 Perform lexical analysis on the regularized SQL statement to produce an abstract syntax tree, and generate a directed acyclic graph according to the abstract syntax tree.
  • FIG. 6 illustrate how to form a directed acyclic graph through SQL statements, that is, the SQL nested query structure can be converted into the following tree structure.
  • FIG. 6 is assumed for the SQL query S, S is the field that contains the C ij (i, j ⁇ N), comprising a source table T i (i ⁇ N); where S represents a C i0 query
  • the i-th field of the result, C ij , (i ⁇ N,j ⁇ N*) represents the j-th field referenced by the i-th field of the S query result;
  • T i represents the i-th source table that appears in S;
  • S i with different subscripts is used to indicate.
  • the SQL query in the above figure is S 0
  • the source tables of S 0 are S 1 and S 2
  • S 1 comes from T 1 and S 2 comes from T 2
  • T 1 and T 2 represent table aliases
  • S 0 includes fields C 00 and C 10
  • S 1 includes fields C 01 and C 02
  • S 2 includes fields C 11 .
  • C 00 represents 0 field S 0 query results
  • C 10 refers to the first field S 0 query results
  • C 01 represents 0 field S 1 search results referenced by the first field
  • C 02 represents the second field referenced by the 0th field of the S 1 query result
  • C 11 represents the first field referenced by the first field of the S 2 query result
  • T 1 represents the first field that appears in S 1 Source table
  • T 2 represents the second source table appearing in S 2 ; when the source table in S 0 is a sub-query, there are two sub-queries S 1 and S 2.
  • the SQL nested query structure in Figure 6 is transformed into a tree structure with three layers, that is, the generated directed acyclic graph has three layers, and the generated directed acyclic graph is shown in Figure 7. Show.
  • the SQL statement parsing method is mainly used when there is "*" (full field substitution symbol) in a complex SQL statement.
  • the two-way inference is carried out based on the field names used in the upper and lower tables and subqueries, and the "*" "Convert to a real field reference.
  • the SQL statement parsing method has two situations where the field represented by "*" cannot be inferred, and the details are as follows:
  • the SQL statement parsing method can also be said to have three main cases that can be inferred.
  • the first case is that there are table aliases, which can be inferred based on the mapping relationship;
  • the second case is that the source tables or subqueries are between The set relationship can be inferred based on the mapping relationship;
  • the third case is when the column listed in the query in the SQL statement does not specify the alias of the table, and at the same time, there are multiple source tables or subqueries, and the source tables or subqueries are between Association relationship, and only one subquery field uses "*" at the same time, it can be inferred from the correlation between the upper and lower levels and the same level.
  • Step 32 Traverse the layers of the directed acyclic graph with the SQL subquery to obtain the layer where the substitution symbol appears, and the layer where the substitution symbol first appears during the traversal is the current layer.
  • the layers of the directed acyclic graph with SQL subqueries can be traversed from top to bottom or the layers of the directed acyclic graph with SQL subqueries can be traversed from bottom to top.
  • the directed acyclic graph has five layers, where the second and third layers have substitution symbols. If the directed acyclic graph is traversed from top to bottom, the second layer is the current layer. Traverse the directed acyclic graph from bottom to top, and the third layer is the current layer.
  • Step 33 Obtain the field corresponding to the substitute character in the current layer according to the field of the previous layer in the current layer.
  • the previous layer of the current layer is the field layer
  • the field layer can map the corresponding field to the subquery of the current layer according to the subquery alias, and use the fields of the field layer to Replace the substitute character of the current layer.
  • the current layer is the first layer to be traversed, then continue to look for the layer without the substitution symbol, and the first layer without the substitution symbol is the field layer, and the previous layer of the field layer
  • the layer is an alternative layer, to infer the field corresponding to the alternative symbol in the alternative layer according to the field layer.
  • field mapping can be performed between the sub-queries at the same level to obtain the field corresponding to the substitute character.
  • the final layer must not be a subquery but a table, and there will be no fields or "*".
  • the final layer may not be considered in the inference process. Refer to Figure 8 for details.
  • Step 34 continue to obtain the remaining layers where the substitute symbols appear, and perform the substitution of the substitute symbols, until all the substitute symbols in the directed acyclic graph are resolved.
  • step 32 and step 33 if there are alternative symbols in other layers, field inference can be performed through the mapping relationship between the upper and lower layers until all alternative symbols are resolved.
  • Figure 8 is a tree structure.
  • the non-"*" field appears in the L 0 layer (that is, the top layer), L m of the query statement.
  • L n layer ie the bottom layer
  • the field represented by "*" is inferred to the upper and lower layers, and the result of data blood relationship is generated.
  • L n+1 is the final layer that does not contain sub-queries.
  • the corresponding field can be mapped to the lower-level sub-query according to the sub-query alias.
  • the lower-level sub-query contains "*”
  • the field C ij is added to the field list of the lower-level sub-query, and the above steps are performed recursively downward.
  • Example 1 For example:
  • the top level is set to level 0, which means that table0 data query is generated.
  • Table0 contains three fields, namely col3, col4, and col5; according to the expression T 1 .col1+ T at level 0 2.
  • col2 as col3 It can be seen that the data of col3 comes from T 1 .col1 and T 2 .col2; the data of col4 comes from S 1 .col4, the data of col5 comes from S 1 .col5; the next layer (layer 1) consists of 2 sheets
  • the two tables are table1 alias T 1 and table2 alias T 2 , and the subquery alias S 1 ; the field queried by the S 1 subquery in the first level is "*", and it is searched in the 0th level
  • the field reference aliased as S 1 has S 1 .col4 and S 2 in the 0th level.
  • col5 refers to the field in the S 1 subquery, so use col4 and col5 to replace the "*" in the S 1 subquery, S 1 is replaced by select col4,col5 ...; the next layer of T 3 (the second layer) is the subquery S 2 , the field queried in the subquery S 2 is "*", so look for the reference field in the upper layer ; Because the source table of S 1 only has sub-query S 2 , all the fields appearing in S 1 should come from sub-query S 2 , so the "*" in S 2 should be replaced with the field appearing in T 3 , S 2 After replacement, select col4, col5 from table3.
  • Example 2 For example:
  • the above SQL statement is converted into a tree structure (directed acyclic graph) shown in FIG. 10, according to the SQL statement, inferred table0 the '*' S 1 according to the representative of col4 col4.
  • Example 3 please refer to Example 3, for example:
  • the corresponding summary information is obtained based on the analysis result of the SQL statement analysis method based on the blood relationship of the data.
  • the summary information is obtained by hashing the analysis result of the SQL statement analysis method based on the data blood relationship, such as Use sha256s algorithm processing to get.
  • Uploading summary information to the blockchain can ensure its security and fairness and transparency to users.
  • the user can download the summary information from the blockchain to verify whether the analysis result of the SQL statement analysis method based on the blood relationship of the data has been tampered with.
  • the blockchain referred to in this example is a new application mode of computer technology such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm.
  • Blockchain essentially a decentralized database, is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information for verification. The validity of the information (anti-counterfeiting) and the generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer
  • This application provides a SQL statement parsing method based on data blood relationship, by obtaining a directed acyclic graph, which is obtained by combing SQL statements; traversing a directed acyclic graph with layers of SQL sub-queries, Get the layer where the substitute character appears, and take the layer where the substitute character appears first during the traversal as the current layer; obtain the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer; continue to obtain the remaining appearances Replace the layer of substitute symbols and perform replacement until all the substitute symbols in the directed acyclic graph are resolved.
  • the SQL statement analysis method used in the SQL-based data blood relationship analysis software tool or system does not need to interact with the database software or access additional metadata to achieve data blood relationship analysis; in addition, in data security
  • this SQL statement parsing method can achieve high-cohesion, low-coupling data kinship analysis function, which can reduce external dependence, and at the same time, it does not need to obtain other metadata that does not appear in the data kinship, so it can be guaranteed as much as possible
  • the security of user metadata will not expose metadata information that does not appear in the relevant SQL due to the analysis of the blood relationship of the data.
  • this application also involves blockchain technology.
  • the present application also provides a SQL statement parsing system based on data blood relationship.
  • the SQL statement parsing system can be integrated into the above-mentioned computer device 110, and specifically can include a data set module 20, a traversal module 30, and an alternative Module 40.
  • the data set module 20 is configured to obtain a directed acyclic graph, which is obtained by combing SQL statements;
  • the traversal module 30 is used to traverse the layers of the directed acyclic graph with SQL sub-queries, and obtain the layer where the substitution symbol appears, and the layer where the substitution symbol appears first during the traversal is the current layer;
  • the substitution module 40 is configured to obtain the field corresponding to the substitute symbol in the current layer according to the field of the previous layer of the current layer; the substitution module continues to obtain the remaining layers marked by the traversal module where the substitute symbol appears , And replace the substitute characters until all the substitute characters in the directed acyclic graph are resolved.
  • the data set module 20 includes a cleaning module 21 and a generating module 22.
  • the cleaning module 21 extracts regularized SQL statements from script files containing SQL codes to complete the cleaning of the SQL statements;
  • the generating module 22 is used to perform lexical analysis on the regularized SQL statements to produce abstract grammars Trees, and can generate directed acyclic graphs based on abstract syntax trees.
  • the cleaning module 21 includes a searching module 211 and a rule module 212.
  • the search module 211 is used to obtain a script file containing SQL code and search for the flag bit of the SQL code;
  • the rule module 212 is used to use the flag bit to filter irrelevant content in the script file, and retain the regularized SQL code Statement.
  • the traversal module 30 further implements: traversing the layers of the directed acyclic graph with SQL subquery from top to bottom or traversing the layers of the directed acyclic graph with SQL subquery from bottom to top.
  • the replacement module 40 further implements: if the previous layer of the current layer is a field layer, the field layer can map the corresponding field to the subquery of the current layer according to the subquery alias, And use the field of the field level to replace the current level of substitution.
  • the substitution module 40 further implements: if the current layer is the first layer to be traversed, continue to search for the layer without the substitution symbol, and take the first layer without the substitution symbol as the field layer, and The previous layer of the field layer is the substitution layer, so that the field corresponding to the substitution symbol in the substitution layer can be inferred from the field layer.
  • the computing system further includes a display module (not shown) for displaying calculation results.
  • the display module may be a display of a desktop computer or a display device of other computer equipment.
  • FIG. 15 is a schematic structural diagram of a device according to an embodiment of the application.
  • the device 200 includes a processor 201 and a memory 202 coupled to the processor 201.
  • the memory 202 stores program instructions for implementing the SQL statement parsing method based on data blood relationship described in any of the above embodiments.
  • the processor 201 is configured to execute program instructions stored in the memory 202.
  • the processor 201 may also be referred to as a CPU (Central Processing Unit, central processing unit).
  • the processor 201 may be an integrated circuit chip with signal processing capability.
  • the processor 201 may also be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component .
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • FIG. 16 is a schematic structural diagram of a storage medium according to an embodiment of the application.
  • the storage medium of this embodiment of the present application stores a program file 301 that can implement all the above methods, where the program file 301 may be stored in the above storage medium in the form of a software product, and the computer-readable storage medium may be a non-volatile , It can also be volatile, which includes several instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or all of the methods described in the various embodiments of this application. Part of the steps.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes.
  • terminal devices such as computers, servers, mobile phones, and tablets.

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Abstract

La présente invention concerne un procédé et un appareil d'analyse d'énoncé SQL, un dispositif informatique et un support de stockage. Le procédé d'analyse d'énoncé SQL comprend les étapes consistant à : acquérir un graphe acyclique orienté, le graphe acyclique orienté étant obtenu par passage au peigne fin d'un énoncé SQL (S31) ; traversée des couches, qui ont une sous-requête SQL, du graphe acyclique orienté pour acquérir une couche où apparaît un symbole de substitution, et amenée de la couche où un symbole de substitution apparaît d'abord pendant la traversée en tant que couche courante (S32) ; selon un champ de la couche précédente de la couche courante, acquisition d'un champ correspondant au symbole de substitution dans la couche courante (S33) ; et poursuite de l'acquisition des couches restantes où apparaît un symbole de substitution, et remplacement des symboles de substitution jusqu'à ce que l'analyse de tous les symboles de substitution dans le graphe acyclique orienté soit achevée (S34). Par conséquent, à l'aide d'un procédé d'analyse d'énoncé SQL dans un outil ou système logiciel d'analyse de lignée de données à base de SQL, ni l'interaction avec un logiciel de base de données ni l'accès à des métadonnées supplémentaires ne sont nécessaires, de telle sorte que la sécurité des métadonnées d'utilisateur peut être sauvegardée autant que possible, et que l'exposition, due à l'analyse de lignée de données, d'informations de métadonnées qui n'apparaissent pas dans un SQL associé ne se produise pas.
PCT/CN2020/135735 2020-10-21 2020-12-11 Procédé et système d'analyse d'énoncé sql, et dispositif informatique et support de stockage WO2021179722A1 (fr)

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CN116303370B (zh) * 2023-05-17 2023-08-15 建信金融科技有限责任公司 一种脚本血缘解析方法、装置、存储介质、设备及产品

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103186541A (zh) * 2011-12-27 2013-07-03 阿里巴巴集团控股有限公司 一种映射关系生成方法及装置
US20190026358A1 (en) * 2016-03-28 2019-01-24 Alibaba Group Holding Limited Big data-based method and device for calculating relationship between development objects
CN109325078A (zh) * 2018-09-18 2019-02-12 拉扎斯网络科技（上海）有限公司 基于结构数据的数据血缘确定方法及装置
CN111125758A (zh) * 2019-12-19 2020-05-08 北京安华金和科技有限公司 一种基于全语法树解析的动态脱敏方法
CN111538743A (zh) * 2020-04-22 2020-08-14 电子科技大学 基于sql的数据血缘关系分析方法以及系统

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130091266A1 (en) * 2011-10-05 2013-04-11 Ajit Bhave System for organizing and fast searching of massive amounts of data
CN109033109B (zh) * 2017-06-09 2020-11-27 杭州海康威视数字技术股份有限公司 数据处理方法及系统
CN109582660B (zh) * 2018-12-06 2021-08-10 深圳前海微众银行股份有限公司 数据血缘分析方法、装置、设备、系统及可读存储介质

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103186541A (zh) * 2011-12-27 2013-07-03 阿里巴巴集团控股有限公司 一种映射关系生成方法及装置
US20190026358A1 (en) * 2016-03-28 2019-01-24 Alibaba Group Holding Limited Big data-based method and device for calculating relationship between development objects
CN109325078A (zh) * 2018-09-18 2019-02-12 拉扎斯网络科技（上海）有限公司 基于结构数据的数据血缘确定方法及装置
CN111125758A (zh) * 2019-12-19 2020-05-08 北京安华金和科技有限公司 一种基于全语法树解析的动态脱敏方法
CN111538743A (zh) * 2020-04-22 2020-08-14 电子科技大学 基于sql的数据血缘关系分析方法以及系统

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113868253A (zh) * 2021-09-28 2021-12-31 中通服创立信息科技有限责任公司 一种数据关系捕获及大数据关系树构建方法
CN113868253B (zh) * 2021-09-28 2024-04-23 中通服创立信息科技有限责任公司 一种数据关系捕获及大数据关系树构建方法
CN114911785A (zh) * 2022-05-16 2022-08-16 北京航空航天大学 一种数据血缘管理方法、装置及电子设备
CN115237936A (zh) * 2022-09-14 2022-10-25 北京海致星图科技有限公司 检测sql语句中字段的方法、装置、存储介质和设备
CN115237936B (zh) * 2022-09-14 2024-04-05 北京海致星图科技有限公司 检测sql语句中字段的方法、装置、存储介质和设备
CN115544065A (zh) * 2022-11-28 2022-12-30 北京数语科技有限公司 一种数据血缘发现方法、系统、设备及存储介质
CN115544065B (zh) * 2022-11-28 2023-02-28 北京数语科技有限公司 一种数据血缘发现方法、系统、设备及存储介质
CN115563150A (zh) * 2022-12-02 2023-01-03 浙江大华技术股份有限公司 Hive SQL与执行引擎DAG的映射方法、设备及存储介质
CN116541887B (zh) * 2023-07-07 2023-09-15 云启智慧科技有限公司 一种大数据平台数据安全保护方法

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