CN116775682A - Database query optimization method and device based on response time - Google Patents
Database query optimization method and device based on response time Download PDFInfo
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Abstract
The application provides a database query optimization method and device based on response time, which belong to the technical field of databases, and the method comprises the following steps: constructing a special query response library according to a preset database construction method; acquiring SQL query sentences and carrying out grammar analysis on the SQL query sentences; optimizing the parsed SQL query statement by adopting an RBO optimization algorithm; extracting features of the parsed SQL query sentences, querying a special query response library according to the extracted features, and determining response time; wherein the extracted features include: SQL feature type, SQL feature information and data volume; and optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm. The method and the device can automatically extract the characteristics of the SQL query statement, establish the relation between the characteristics and the response time, automatically store the relation into the special query response library, and provide accurate basis for the cost calculation of CBO, thereby improving the capability of database query optimization, reducing the cost and improving the query efficiency.
Description
Technical Field
The present application relates to the field of database technologies, and in particular, to a method, an apparatus, a device, and a storage medium for optimizing database query based on response time.
Background
With the increase of the size of the database, the execution cost of SQL is higher and higher, the execution is optimized, and the cost is reduced. Current database query optimization is commonly done Based on Rule-Based optimizers (RBO) or Cost-Based optimizers (CBO).
However, the above method still has the following disadvantages:
1. RBO is a series of rules manually formulated to select a query plan, cannot be optimized according to specific query and data statistics information, is troublesome to maintain, requires manual maintenance of a large number of optimization rules, and is difficult to maintain due to the fact that the rules become more and more complex over time;
2. CBO costs high in collecting statistics, and periodically collecting complete information requires scanning the full table, increasing the overhead of the database system.
3. The CBO cannot handle some special scenarios, for example, some plans include user-defined functions, the CBO cannot determine its specific computational complexity, and further tuning is required according to the plan generated by the CBO.
Disclosure of Invention
The application provides a database query optimization method, a device, equipment and a storage medium based on response time, which are used for establishing the relation between characteristics and response time through analyzing and extracting the characteristics of standard SQL grammar and automatically storing the relation into a special query response library, so as to provide accurate basis for calculating the cost of CBO, thereby improving the capability of database query optimization, reducing the cost and improving the query efficiency.
In a first aspect, an embodiment of the present application provides a method for optimizing a database query based on response time, the method including:
constructing a special query response library according to a preset database construction method;
acquiring SQL query sentences and carrying out grammar analysis on the SQL query sentences;
optimizing the parsed SQL query statement by adopting an RBO optimization algorithm;
extracting features of the parsed SQL query sentences, querying a special query response library according to the extracted features, and determining response time;
wherein the extracted features include: SQL feature type, SQL feature information and data volume;
and optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm.
Optionally, constructing the dedicated query response library according to a preset database construction method includes:
acquiring historical SQL query sentences and carrying out grammar analysis on the historical SQL query sentences;
optimizing the parsed SQL query statement by adopting an RBO optimization algorithm;
feature extraction is carried out on the parsed SQL query statement and the RBO optimized SQL query statement;
wherein the features include: SQL feature type, SQL feature information and data volume;
optimizing the SQL query statement after RBO optimization by adopting a CBO optimization algorithm;
executing the SQL query statement after CBO optimization to determine response time;
and constructing a special query response library according to the SQL feature type, the SQL feature information, the data quantity and the response time.
Optionally, obtaining the SQL query statement and parsing the SQL query statement includes:
and determining the SQL feature type according to the operator of the SQL query statement.
Optionally, optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm includes:
determining a first price calculation formula according to the CBO optimization algorithm and the scale, the line number cost, the calculation cost, the I/O cost and the network cost of the table and the index;
adding the response time as a time dimension into the first price calculation formula to obtain a second price calculation formula;
and calculating the query cost according to the second cost calculation formula, and optimizing the SQL query statement after RBO optimization according to the query cost.
Optionally, calculating the query cost according to the second cost calculation formula, and optimizing the SQL query statement after the RBO optimization according to the query cost, including:
the SQL query statement with the shortest response time is selected as the query statement.
Optionally, the response time-based database query optimization method further includes:
if the response time is not queried when the special query response library is queried, the query cost is calculated according to the first price calculation formula.
In a second aspect, an embodiment of the present application provides a response time-based database query optimization apparatus, including:
the construction module is used for constructing a special query response library according to a preset database construction method;
the acquisition module is used for acquiring the SQL query statement and carrying out grammar analysis on the SQL query statement;
the optimizing module is used for optimizing the parsed SQL query statement by adopting an RBO optimizing algorithm;
the determining module is used for extracting the characteristics of the parsed SQL query statement and querying the special query response library according to the extracted characteristics to determine response time;
wherein the extracted features include: SQL feature type, SQL feature information and data volume;
and the optimization module is also used for optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, where the memory stores a computer program, and the processor implements the method according to any implementation manner of the first aspect when executing the program.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method according to any of the implementations of the first aspect.
The application provides a database query optimization method, a device, equipment and a storage medium based on response time, which have the following beneficial effects:
1. the optimization method based on the response time does not need manual statistical information, and reduces the cost and complexity of manual maintenance.
2. The optimization method based on response time does not need to collect relevant statistical information by adopting periodic full-table scanning, and has high real-time performance; and can also directly and effectively optimize query for SQL which cannot analyze the complexity of execution.
It should be understood that the description in this summary is not intended to limit the critical or essential features of the embodiments of the application, nor is it intended to limit the scope of the application. Other features of the present application will become apparent from the description that follows.
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The above and other features, advantages and aspects of embodiments of the present application will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements.
FIG. 1 is a flow chart of a database query optimization method based on response time according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for constructing a specialized query response library according to an embodiment of the present application;
FIG. 3 is a flow chart of a database query optimization method based on response time according to another embodiment of the present application;
FIG. 4 is a schematic structural diagram of a database query optimization device based on response time according to an embodiment of the present application;
fig. 5 is a block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to enable a person skilled in the art to better understand the technical solutions in one or more embodiments of the present specification, the technical solutions in one or more embodiments of the present specification will be clearly and completely described below with reference to the drawings in one or more embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one or more embodiments of the present disclosure without inventive faculty, are intended to be within the scope of the present disclosure.
It should be noted that, the description of the embodiment of the present application is only for the purpose of more clearly describing the technical solution of the embodiment of the present application, and does not constitute a limitation on the technical solution provided by the embodiment of the present application.
FIG. 1 is a flow chart of a database query optimization method based on response time according to an embodiment of the present application. As shown in fig. 1, includes:
s101, constructing a special query response library according to a preset database construction method.
Alternatively, as shown in fig. 2: the construction of the special query response library according to the preset database construction method comprises the following steps:
s201, acquiring a historical SQL query statement and carrying out grammar analysis on the historical SQL query statement;
s202, optimizing the parsed SQL query statement by adopting an RBO optimization algorithm;
s203, extracting features of the parsed SQL query statement and the RBO optimized SQL query statement;
wherein the features include: SQL feature type, SQL feature information and data volume;
s204, optimizing the SQL query statement after RBO optimization by adopting a CBO optimization algorithm;
s205, determining response time by executing the SQL query statement after CBO optimization;
s206, constructing a special query response library according to the SQL feature type, the SQL feature information, the data quantity and the response time.
Specifically, in the historical SQL execution process, the features described in step S203 above are extracted, the response time of each feature is calculated, and the SQL feature type, the SQL feature information, the data amount, and the response time are stored in the dedicated query response library.
By way of example, in the parsing and optimizing stage, the SQL can extract different SQL features according to the characteristics of operators, the SQL features have universality, and by establishing the relationship between the SQL features and the response time of SQL feature execution of each stage, the relationship between historical SQL query sentences and response time can be established. For example, table 1 below shows:
TABLE 1
S102, acquiring the SQL query statement and carrying out grammar analysis on the SQL query statement.
Optionally, when the user inputs the SQL query statement to perform data query, the query statement input by the user is obtained, the SQL query statement is parsed, query content, execution steps, SQL operators used in the query statement and the like are analyzed, and different SQL features are divided according to the SQL operators.
Optionally, the operators of the SQL include: from operator, scan operator, filter operator, join operator, grouping operator, sort operator and projection operator, value operator, topN operator and Exchange operator.
S103, optimizing the parsed SQL query statement by adopting an RBO optimization algorithm.
Alternatively, the RBO optimization algorithm is passed through a manually formulated series of optimization rules, which are preset and fixed.
Alternatively, the optimization rules may include: the method comprises traditional column clipping, maximum and minimum elimination, projection elimination, predicate push-down and the like, and can also comprise complex push-down operations such as Join and the like; the RBO uses built-in rules as the basis for optimization, while the rules are hard coded in the code of KaiwuDB, the RBO selects one of many possible algebraic transformations of the target SQL as a logical plan based on the rules.
Optionally, the implementation of the RBO rule of the KaiwuDB includes: matching mode and replacement mode;
the matching mode comprises three parts, wherein the first part is the name of a rule and can be used as the identification of the rule when the Opt file is compiled, the second part is the rule scope, the rule scope has clear type division in the KaiwuDB, and the third part is the rule part and is the matching condition of the rule.
Illustratively, the match condition may be an equivalent expression, with the left child being not a variable and the right child being a variable.
S104, extracting features of the parsed SQL query sentences and querying a special query response library according to the extracted features to determine response time.
Wherein the extracted features include: SQL feature type, SQL feature information, and data volume.
Illustratively, the SQL query statement is analyzed, the extracted feature is a projection of the SQL feature type, the SQL feature information is a table name, and the special query response library is queried according to the extracted feature type and the feature information, so that the response time corresponding to the feature type is a.
S105, optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm.
Optionally, the CBO optimization algorithm is optimized based on periodically collected statistical information, collecting table and index size, line cost, computation cost, I/O cost, and network cost, and integrating these dimensions to initiate a query plan with minimal overall cost.
Specifically, in the CBO optimization stage, the extracted SQL features are read from the cache, and corresponding feature response time is queried from a special query response library; supplementing the response time as a time dimension into a cost calculation formula of the CBO to form a second cost calculation formula such as: computeCost (response time, first price calculation formula).
Illustratively, the second cost calculation formula takes the response time as a cost evaluation criterion preferentially, and if the corresponding response time of the SQL feature can be found in the special query response library, the response time is taken as a unique condition for cost comparison; in the cost comparison, selecting the query scheme with the shortest response time; if the corresponding response time of the SQL feature is not found in the special query response library, the previous first price calculation formula is used for price evaluation.
In a preferred embodiment, as shown in FIG. 3:
when a user performs SQL query, the SQL query statement of the user is parsed, and then optimized by adopting an RBO optimization algorithm, and the SQL features of the SQL query statement are extracted while the parsing and RBO optimization are performed.
The SQL features that can be extracted include: SQL feature type, SQL feature information, and data volume.
Further, CBO optimization is carried out on the query statement after RBO optimization, the SQL query statement is scheduled to be executed after CBO optimization is executed, and the response time of the SQL query statement is determined according to the execution result.
And recording each query of the user, recording the relations among the SQL feature type, the SQL feature information, the data quantity and the response time, and constructing a special query response library according to the relations.
After the special query response library is constructed, the user queries the special query response library according to SQL features obtained in the grammar analysis stage in the CBO optimization stage, finds the response time corresponding to the SQL features, and executes CBO optimization by combining the queried response time, so that the query efficiency can be further improved, and the problem that query cannot be optimized according to the original RBO optimization algorithm and the CBO optimization algorithm can be solved.
The embodiment of the application provides a database query optimization method based on response time, which comprises the following steps: constructing a special query response library according to a preset database construction method; acquiring SQL query sentences and carrying out grammar analysis on the SQL query sentences; optimizing the parsed SQL query statement by adopting an RBO optimization algorithm; extracting features of the parsed SQL query sentences, querying a special query response library according to the extracted features, and determining response time; wherein the extracted features include: SQL feature type, SQL feature information and data volume; and optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm. The method and the device can automatically extract the characteristics of the SQL query statement, establish the relation between the characteristics and the response time, automatically store the relation into the special query response library, and provide accurate basis for the cost calculation of CBO, thereby improving the capability of database query optimization, reducing the cost and improving the query efficiency.
The following describes in detail the apparatus provided by the embodiment of the present application, which can execute the database query optimization method based on response time.
Fig. 4 is a schematic structural diagram of a database query optimization device based on response time according to an embodiment of the present application; as shown in fig. 4, the optimizing means 40 includes:
a construction module 401, configured to construct a dedicated query response library according to a preset database construction method;
an obtaining module 402, configured to obtain an SQL query statement and parse the SQL query statement;
an optimizing module 403, configured to optimize the parsed SQL query statement by using an RBO optimizing algorithm;
a determining module 404, configured to perform feature extraction on the parsed SQL query statement and query the dedicated query response library according to the extracted feature, to determine a response time;
wherein the extracted features include: SQL feature type, SQL feature information and data volume;
the optimization module 403 is further configured to optimize the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm.
Optionally, the construction module 401 is further configured to obtain a historical SQL query statement and parse the historical SQL query statement; optimizing the parsed SQL query statement by adopting an RBO optimization algorithm; feature extraction is carried out on the parsed SQL query statement and the RBO optimized SQL query statement; wherein the features include: SQL feature type, SQL feature information and data volume; optimizing the SQL query statement after RBO optimization by adopting a CBO optimization algorithm; executing the SQL query statement after CBO optimization to determine response time; and constructing a special query response library according to the SQL feature type, the SQL feature information, the data quantity and the response time.
Optionally, the obtaining module 402 is further configured to determine the SQL feature type according to an operator of the SQL query statement.
Optionally, the optimizing module 403 is further configured to determine a first price computing formula according to the CBO optimization algorithm, the table and index size, the line number cost, the computing cost, the I/O cost, and the network cost; adding the response time as a time dimension into the first price calculation formula to obtain a second price calculation formula; and calculating the query cost according to the second cost calculation formula, and optimizing the SQL query statement after RBO optimization according to the query cost.
Optionally, the optimizing module 403 is further configured to select, as the query term, the SQL query term with the shortest response time.
Optionally, the optimizing module 403 is further configured to calculate the query cost according to the first price calculation formula if no response time is queried when querying the dedicated query response library.
The embodiment of the present application also provides a computer electronic device, fig. 5 shows a schematic diagram of a structure of an electronic device to which the embodiment of the present application can be applied, and as shown in fig. 5, the electronic device includes a central processing module (CPU) 501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the system operation are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output portion 507 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The drive 510 is also connected to the I/O interface 505 as needed. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as needed so that a computer program read therefrom is mounted into the storage section 508 as needed.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules or modules involved in the embodiments of the present application may be implemented in software or in hardware. The described modules or modules may also be provided in a processor, for example, as: a processor includes a building module 401, an obtaining module 402, an optimizing module 403, and a determining module 404, where the names of these modules do not in some cases constitute a limitation on the module itself, for example, the determining module 404 may also be described as "the determining module 404 for extracting features of the parsed SQL query statement and querying the dedicated query response library according to the extracted features, determines the response time".
As another aspect, the present application also provides a computer readable storage medium, which may be a computer readable storage medium included in a response time based database query optimizing apparatus as described in the above embodiments; or may be a computer-readable storage medium, alone, that is not incorporated into an electronic device. The computer readable storage medium stores one or more programs for use by one or more processors to perform a response time based database query optimization method described in the present application.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application referred to in the present application is not limited to the specific combinations of the technical features described above, but also covers other technical features formed by any combination of the technical features described above or their equivalents without departing from the inventive concept. Such as the above-mentioned features and the technical features disclosed in the present application (but not limited to) having similar functions are replaced with each other.
Claims (9)
1. A response time based database query optimization method, the method comprising:
constructing a special query response library according to a preset database construction method;
acquiring an SQL query statement and carrying out grammar analysis on the SQL query statement;
optimizing the parsed SQL query statement by adopting an RBO optimization algorithm;
extracting features of the parsed SQL query statement, querying the special query response library according to the extracted features, and determining response time;
wherein the extracted features include: SQL feature type, SQL feature information and data volume;
and optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm.
2. The response time-based database query optimization method of claim 1, wherein the constructing a dedicated query response library according to a preset database construction method comprises:
acquiring a historical SQL query statement and carrying out grammar analysis on the historical SQL query statement;
optimizing the parsed SQL query statement by adopting an RBO optimization algorithm;
feature extraction is carried out on the parsed SQL query statement and the RBO optimized SQL query statement;
wherein the features include: SQL feature type, SQL feature information and data volume;
optimizing the SQL query statement after RBO optimization by adopting a CBO optimization algorithm;
executing the SQL query statement after CBO optimization to determine response time;
and constructing the special query response library according to the SQL feature type, the SQL feature information, the data quantity and the response time.
3. The response time based database query optimization method of claim 1, wherein the retrieving and parsing the SQL query statement comprises:
and determining the SQL feature type according to the operator of the SQL query statement.
4. The response time based database query optimization method of claim 1, wherein optimizing the RBO-optimized SQL query statement according to the response time and CBO optimization algorithm comprises:
determining a first price computing formula according to the CBO optimization algorithm and the scale, the line cost, the computing cost, the I/O cost and the network cost of the table and the index;
adding the response time as a time dimension to the first price calculation formula to obtain a second price calculation formula;
and calculating the query cost according to the second cost calculation formula, and optimizing the SQL query statement after RBO optimization according to the query cost.
5. The response time based database query optimization method of claim 4, wherein the calculating the query cost according to the second cost calculation formula and optimizing the RBO-optimized SQL query statement according to the query cost comprises:
the SQL query statement with the shortest response time is selected as the query statement.
6. The response time based database query optimization method of claim 4, further comprising:
if the response time is not queried when the special query response library is queried, the query cost is calculated according to the first price calculation formula.
7. A response time based database query optimization apparatus, the apparatus comprising:
the construction module is used for constructing a special query response library according to a preset database construction method;
the acquisition module is used for acquiring the SQL query statement and carrying out grammar analysis on the SQL query statement;
the optimizing module is used for optimizing the parsed SQL query statement by adopting an RBO optimizing algorithm;
the determining module is used for extracting the characteristics of the parsed SQL query statement and querying the special query response library according to the extracted characteristics to determine response time;
wherein the extracted features include: SQL feature type, SQL feature information and data volume;
and the optimization module is also used for optimizing the SQL query statement after RBO optimization according to the response time and the CBO optimization algorithm.
8. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, the processor implementing the method according to any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, characterized in that a computer program is stored, which computer program, when being executed by a processor, implements the method according to any of claims 1 to 6.
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