WO2021179722A1

WO2021179722A1 - Sql statement parsing method and system, and computer device and storage medium

Info

Publication number: WO2021179722A1
Application number: PCT/CN2020/135735
Authority: WO
Inventors: 陈玉; 张茜; 凌海挺; 杜均
Original assignee: 平安科技（深圳）有限公司
Priority date: 2020-10-21
Filing date: 2020-12-11
Publication date: 2021-09-16
Also published as: CN112256721B; CN112256721A

Abstract

Disclosed are an SQL statement parsing method and system, and a computer device and a storage medium. The SQL statement parsing method comprises: acquiring a directed acyclic graph, wherein the directed acyclic graph is obtained by combing an SQL statement (S31); traversing layers, which have an SQL sub-query, of the directed acyclic graph to acquire a layer where a substitute symbol appears, and taking the layer where a substitute symbol first appears during traversal as the current layer (S32); according to a field of the previous layer of the current layer, acquiring a field corresponding to the substitute symbol in the current layer (S33); and continuing to acquire the remaining layers where a substitute symbol appears, and replacing the substitute symbols until the parsing of all the substitute symbols in the directed acyclic graph is completed (S34). Therefore, by using an SQL statement parsing method in an SQL-based data lineage analysis software tool or system, neither interaction with database software nor accessing additional metadata is necessary, such that the security of user metadata can be safeguarded as much as possible, and exposure, due to data lineage parsing, of metadata information that does not appear in a related SQL does not occur.

Description

SQL statement parsing method, system, computer equipment and storage medium

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on October 21, 2020, the application number is 202011134553.8, and the application name is "SQL statement parsing method, system, computer equipment and storage medium", the entire content of which is incorporated by reference Incorporated in this application.

To

Technical field

This application relates to the field of data processing technology, in particular to SQL statement parsing methods, systems, computer equipment and storage media.

Background technique

As an important asset of an enterprise, data needs to be managed, maintained and used through data governance. As an important part of 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. Compared with the SQL statement converted by the database software, 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. In scenarios where data security is more sensitive, the data dictionary enlarges the range of metadata that can be accessed during the SQL parsing process, which poses a certain security risk.

Therefore, 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.

technical problem

Based on this, 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.

Technical solutions

In order to achieve the above-mentioned purpose, 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.

In order to achieve the above objective, the present application also provides a computer device, including a memory and a processor. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor Perform the following steps:

In order to achieve the above objective, this application also provides a storage medium storing a program file capable of implementing the following steps, the steps including:

Beneficial effect

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. Therefore, 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 In demanding scenarios, 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. At the same time, this application also involves blockchain technology.

Description of the drawings

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;

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;

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.

Embodiments of the present invention

In order to make the purpose, technical solutions, and advantages of this application clearer and clearer, the following further describes the application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not used to limit the present application.

It can be understood that the terms "first", "second", etc. used in this application can be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element.

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. When calculating, 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.

It should be noted that 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. As shown in Figure 2, the computer device includes a processor, a non-volatile storage medium, a memory, and a network interface connected through a system bus. Wherein, 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. When the computer-readable instructions are executed by the processor, 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. Those skilled in the art can understand that the structure shown in FIG. 2 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may Including more or fewer parts than shown in the figure, or combining some parts, or having a different arrangement of parts.

As shown in FIG. 3, in one embodiment, 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.

Specifically, 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. Further, please refer to Figures 4 and 5, by extracting SQL statements from scripts containing SQL code, and by combing SQL statements, a directed acyclic graph can be obtained, specifically, including:

S311. Extract regularized SQL statements from the script file containing the SQL code, and complete the cleaning of the SQL statements;

Further, the S311 includes:

S3111, obtain the script file containing the SQL code, and look for the flag bit of the SQL code;

Preferably, the script file may be a script such as perl.

S3112. Use the flag bit to filter irrelevant content in the script file, and retain the regularized SQL code statements.

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.

According to the SQL statement parsing method, please refer to FIG. 6 to 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.

Specifically, referring to FIG. 6, 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; When the source table in S is a subquery, S _i with different subscripts is used to indicate.

According to Figure 6, the SQL query in the above figure is S ₀ , and the source tables of _{S 0} _{are S 1} and S ₂ , that is, 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 , and S ₂ includes fields C ₁₁ . Further, 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.

According to the above description, it can be seen that 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.

What needs to be explained here is that 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. However, the SQL statement parsing method has two situations where the field represented by "*" cannot be inferred, and the details are as follows:

In the first case, when all query fields in the SQL statement are replaced by "*", inference cannot be made.

For example, taking Fig. 8 as an example, if S ₀ is "*", if S ₁ , S ₂ and S ₃ are all "*", no inference can be made.

In the second case, when the columns listed in the query in the SQL statement do not specify the alias of the table, at the same time, there are multiple source tables or sub-queries, and the source tables or sub-queries are related, and at least two sub-queries are in the same time If the fields are all represented by "*", the field represented by "*" cannot be accurately inferred.

For example, take Figure 8 as an example. If S ₀ is "a+b+c", if S ₁ is "*", S ₂ is "*", and S ₃ shows c, then S ₁ and S ₂ cannot be inferred. of.

In the same way, 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.

Specifically, due to the directed acyclic graph itself, 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.

More specifically, suppose that 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.

Specifically, in one of the embodiments, the previous layer of the current layer is the field layer, and 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.

Specifically, in one of the embodiments, if 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.

Further, if there are multiple sub-queries at the same level, and if the sub-queries at the same level have a set operation relationship, field mapping can be performed between the sub-queries at the same level to obtain the field corresponding to the substitute character.

It should be noted that, according to the SQL grammar rules, 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.

Specifically, according to 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.

According to the above four steps, please continue to refer to Figure 8, which is a tree structure. In this SQL statement parsing method, it can be solved that the non-"*" field appears in the L ₀ layer (that is, the top layer), L _{m of the query statement.} When the layer (ie middle layer) and L _n layer (ie the bottom layer) are used, 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.

Among them, when the non-"*" field C _ij appears in L ₀ , the corresponding field can be mapped to the lower-level sub-query according to the sub-query alias. When the lower-level sub-query contains "*", use the field C _ij instead; _{When the field C ij} is not included in the lower-level sub-query, the field C _{ij is} added to the field list of the lower-level sub-query, and the above steps are performed recursively downward.

Specifically, please refer to Example 1, for example:

insert into table0

select

t1.col1+t2.col2 as col3,s1.col4,s1.col5

from table1 t1

join table2 t2

on t1.id = t2.id

join (select * from (

select *

from table3 t3) s2

) S1

on t2.id = t3.id;

Please refer to Figure 9. The above SQL statement is transformed into a tree structure (directed acyclic graph) as shown in Figure 9. The solid line in Figure 9 represents the dependency relationship of the fields, and the dashed line represents the inferred relationship between the fields. According to the above The SQL statement is explained as follows:

Specifically, the top level is set to level 0, which means that table0 data query is generated. In this query, 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.

Among them, when _{the field of the middle layer L m} is not "*", if the "*" in the previous query has a table alias (such as T ₃ .*), you can infer whether the field listed in the middle layer is based on the table alias It is the field that the upper layer "*" should represent; if the upper layer "*" has no table alias identification, confirm whether the current query is the only source table of the upper query, if it is the only source table, the field that appears in the current query is the upper Fields that should be represented by "*" at one level; if it is not the only source table, all fields listed in all source tables (subqueries) are the fields that should be represented by "*" at the previous level.

Specifically, please refer to Example 2, for example:

insert into table0

SELECT

*

from(

select col1+col2+col3 as col4 from (

select col1,col2,col3 from table1 t1

)s2

) s1;

Please refer to FIG. 10, 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.

Specifically, from SQL, we can see that the field of table0 at level 0 is represented by'*'; the subquery S _{1 of level 1} contains a field col4, because the data source of the next level of table0 is only subquery S ₁ , then S ₁ All the fields in should appear in the query of the upper layer; use _{all the fields of the subquery S 1} of the first layer to replace the'*' in the upper layer, and the query of the 0th layer after the replacement should be select col4 from …….

Among them, when the relationship between multiple queries is _{in the form of S 0} , S ₁ , S ₂ , if the sub-queries at the same level are set (union\intersect\minus) operations, they can be performed between sub-queries at the same level Field mapping. Operational requirements set by the field names and field sequence are identical, the query can be reference mapping between fields in accordance with the non-child "*" fields set of operations in the same level, can be inferred from the field S ₂ S ₃ should be included Fields, use the fields in S ₃ and S ₂ to infer the fields that should be included in table0.

Specifically, please refer to Example 3, for example:

insert into table0

select * from (

(Select * from table1 t1) s2

UNION

(Select col1,col2 from table2 t2) s3

)s1;

Please refer to Figure 11. In the SQL statement representing the set relationship of UNION, the above SQL statement is transformed into a tree structure (directed acyclic graph) as shown in Figure 11.

The above three examples are just examples. Further, in actual applications, it may be necessary to use the above method to combine multiple iterations according to the complexity of the SQL to fully enumerate the implicit field reference relationship.

In an optional implementation manner, it is also possible to upload the analysis result of the SQL statement analysis method based on the blood relationship of the data to the blockchain.

Specifically, 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. Specifically, 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. Therefore, 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 In demanding scenarios, 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. At the same time, this application also involves blockchain technology.

As shown in FIG. 12, 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.

In one embodiment, referring to FIG. 13, the data set module 20 includes a cleaning module 21 and a generating module 22. Wherein, 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.

In one embodiment, please refer to FIG. 14, the cleaning module 21 includes a searching module 211 and a rule module 212. Wherein, 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.

In one embodiment, 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.

In one embodiment, 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.

In one embodiment, 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.

In one embodiment, 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.

Please refer to FIG. 15, which is a schematic structural diagram of a device according to an embodiment of the application. As shown in FIG. 15, 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.

Refer to FIG. 16, which 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. , Or terminal devices such as computers, servers, mobile phones, and tablets.

It should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements not only includes those elements, It also includes other elements not explicitly listed, or elements inherent to the process, device, article, or method. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, device, article, or method that includes the element.

The serial numbers of the foregoing embodiments of the present application are for description only, and do not represent the superiority or inferiority of the embodiments. Through the description of the above implementation manners, those skilled in the art can clearly understand that the above-mentioned embodiment method can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is better.的实施方式。 Based on this understanding, the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disk, optical disk), including a number of instructions to make a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) execute the method described in each embodiment of the present application.

Claims

1. A SQL statement parsing method based on data blood relationship, wherein the SQL statement parsing method includes:

2. The SQL statement parsing method according to claim 1, wherein the directed acyclic graph is obtained by combing SQL statements, comprising:

Extract regularized SQL statements from script files containing SQL codes to complete the cleaning of SQL statements;

Perform lexical analysis on regularized SQL statements to generate an abstract syntax tree, and generate a directed acyclic graph according to the abstract syntax tree.

3. The SQL statement parsing method according to claim 2, wherein said extracting and obtaining regularized SQL statements from a script file containing SQL codes to complete the cleaning of SQL statements comprises:

Obtain the script file containing the SQL code, and look for the flag bit of the SQL code;

Use the flag bit to filter the irrelevant content in the script file, and retain the regularized SQL code statements.

4. The SQL statement parsing method according to claim 1, wherein the traversing the directed acyclic graph with SQL sub-query layers includes: traversing the directed acyclic graph with SQL sub-queries from top to bottom Layers or layers with SQL subqueries traversed from bottom to top in a directed acyclic graph.

5. The SQL statement parsing method according to claim 1, wherein said obtaining the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer comprises: the previous layer of the current layer It is the field layer, and 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 layer to replace the substitute character of the current layer.

6. The SQL statement parsing method according to claim 1, wherein said obtaining the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer comprises: if the current layer is the first layer to be traversed , Then continue to look for the layer without the substitution symbol, the first layer without the substitution symbol is the field layer, and the layer before the field layer is the substitution layer, so as to infer the substitution symbol corresponding to the substitution layer according to the field layer Field.

7. The SQL statement parsing method of claim 1, wherein after all the substitution symbols in the directed acyclic graph are resolved, the parsing result is uploaded to the blockchain, so that the block The chain encrypts and stores the analysis result.

8. A SQL statement parsing system based on data blood relationship, wherein the SQL statement parsing system includes:

The data set module is used to obtain a directed acyclic graph, which is obtained by combing SQL statements;

9. A computer device comprising a memory and a processor, and computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by the processor, the processor is caused to perform the following steps:

10. The computer device according to claim 9, wherein the directed acyclic graph is obtained by combing SQL statements, comprising:

11. The computer device according to claim 10, wherein said extracting and obtaining regularized SQL statements from a script file containing SQL codes to complete the cleaning of SQL statements comprises:

12. The computer device of claim 9, wherein the traversal of the directed acyclic graph layer with SQL subquery comprises: traversing the directed acyclic graph layer with SQL subquery from top to bottom or Traverse the layers of the directed acyclic graph with SQL subqueries from bottom to top.

13. The computer device according to claim 9, wherein the obtaining the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer comprises: the previous layer of the current layer is a field 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 layer to replace the substitute character of the current layer.

14. The computer device according to claim 9, wherein the obtaining the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer comprises: if the current layer is the first layer to be traversed, then Continue to look for the layer without the substitution symbol, the first layer without the substitution symbol is the field layer, and the layer before the field layer is the substitution layer, so as to infer the field corresponding to the substitution symbol in the substitution layer according to the field layer .

15. A storage medium, wherein a program file capable of implementing the following steps is stored, the steps including:

16. The storage medium of claim 15, wherein the directed acyclic graph is obtained by combing SQL statements, comprising:

17. The storage medium of claim 16, wherein said extracting and obtaining regularized SQL statements from a script file containing SQL codes to complete the cleaning of SQL statements comprises:

18. The storage medium of claim 15, wherein the traversal of the directed acyclic graph layer with SQL subquery comprises: traversing the directed acyclic graph layer with SQL subquery from top to bottom or Traverse the layers of the directed acyclic graph with SQL subqueries from bottom to top.

19. The storage medium of claim 15, wherein the obtaining the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer comprises: the previous layer of the current layer is a field 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 layer to replace the substitute character of the current layer.

20. The storage medium of claim 15, wherein the obtaining the field corresponding to the substitute character in the current layer according to the field of the previous layer of the current layer comprises: if the current layer is the first layer to be traversed, then Continue to look for the layer without the substitution symbol, the first layer without the substitution symbol is the field layer, and the layer before the field layer is the substitution layer, so as to infer the field corresponding to the substitution symbol in the substitution layer according to the field layer .