CN114238377A - Method for realizing percentile _ cont analysis function in OpenGauss - Google Patents
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Abstract
The invention belongs to the technical field of relational database management and operating systems, and particularly relates to a method for realizing a percentile _ cont analysis function in OpenGauss and application thereof. The invention firstly provides a method for realizing the percent _ cont analysis function in the stage of executing the query plan in the OpenGauss database, so that the OpenGauss database can support the running of the percent _ cont analysis function, thereby overcoming the defect that the OpenGauss database does not support the percent _ cont analysis function, providing powerful technical support for the application of the percent _ cont analysis function in the OpenGauss database management system, contributing to better playing the database performance and obviously improving the working efficiency of the database.
Description
Technical Field
The invention belongs to the technical field of relational database management and operating systems, and particularly relates to a method for realizing a percentile _ cont analysis function in OpenGauss and application thereof.
Background
OpenGauss is an open-source relational database management system, the kernel of which is derived from PostgreSQL, and the system is used as an open-source free database platform and aims to encourage community contribution and cooperation. In a typical relational database management system such as OpenGauss, a query is processed, usually in the following three phases:
(1) the lexical and syntactic analysis mainly converts the input text (SQL) of a user into an internal data structure generally called as a syntactic parse tree, verifies the correctness of the grammar and finally obtains the syntactic parse tree expressing the SQL.
(2) And query optimization, namely performing optimization based on rules and physical cost on the syntax parse tree obtained in the previous stage to generate an optimal query plan.
(3) Executing the query plan, executing the query plan generated in the previous stage (generally adopting an iterator mode), obtaining a query result and returning the query result to the user.
In the process of analyzing data for a database, a series of analysis functions are often used, and percentile _ cont is a common and very valuable analysis function. percentile _ cont is an inverse distribution function that assumes a continuous distribution model, has a percentage value and a sorted grouping, and returns an interpolated value within a given percentage value range for the sorted grouping concerned.
The percentile _ cont function input is two parameters: the first is floating point type, the parameter is a decimal between 0 and 1, called percentile; the second is an indeterminate one-dimensional array, which is an ordered array, with ascending and descending order specified by SQL, and the elements in the array being numeric data, such as integer or floating point.
For the following examples:
SELECT color,percentile_cont(0.5)WITHIN GROUP(ORDER BY value)over(partition by color)FROM(VALUES('red',1),('red',3),('blue',2),('blue',4))v(color,value)；
is for a 4-line record containing two fields (color and value): ('red', 1), ('red', 3), ('blue', 2), ('blue', 4) are grouped in the color field, which results in two groups: the first group is ('red', 1), ('red', 3); the second group is ('blue', 2), ('blue', 4), and then the value fields of each group are sorted to obtain the interpolated value with a rank of 0.5 in percentile.
The final output result is:
however, in the existing OpenGauss database, the running of the percentile _ cont analysis function is not realized, so that the application of the percentile _ cont analysis function in the OpenGauss database management system is limited, the performance of the database is influenced, and the working efficiency is reduced.
Disclosure of Invention
In order to overcome the defect that the OpenGauss database does not support the percentile _ cont analysis function at present, the invention provides a solution. The invention provides a method for realizing a percentile _ cont analysis function in OpenGauss for the first time.
The method comprises the following steps:
a semantic analysis stage: converting the object statement into an internal representation of the function;
(II) query plan execution stage: when executing the window aggregation function, grouping data according to a specified grouping rule, sequencing the data in each group, recording each row in each group, calling a transient function of the window aggregation function, and processing input data by the transient function according to business needs; after the transient function completes the processing process of all the data in each group, the terminal function of the window aggregation function is called continuously for each data in each group, the terminal function processes the data according to the processing result of the transient function, the calculation process is executed, the final calculation result is obtained, and then the calculation result is returned and output.
Further, the step (one) of the method comprises the following treatment processes:
(1) searching a function in a system table according to the function name and the parameter type;
(2) processing the parameter type, and converting the parameter type of the input actual parameter according to the function definition in the system table; the parameter type conversion refers to converting the parameters of the numerical type into wider types according to the function definition in the system table, for example, the parameter requirement in the function definition is a 32-bit integer, but the actually input parameter is a 16-bit integer, so that the parameter is converted into a 32-bit integer;
(3) checking the over statement and the within statement, checking whether the field in the over statement is a subset of the sequencing field of the whole query statement, if so, finishing the check, otherwise, indicating that the sequencing field conflicts exist, and reporting the error by the checking program to exit;
(4) generating an internal representation of the window aggregation function, and filling internal information, wherein the internal information comprises a parameter type, a return value type, a system ID of the function and the like.
Further, the step (two) of the method of the present invention, wherein the transient function processes the input data according to the service requirement, comprises the following processing procedures:
(1) creating an execution environment, when calling data in a packet for the first time, firstly creating the execution environment, acquiring a first parameter percentile of the percentile _ cont, setting a stored data counter to be 0, and creating a sorted data structure for storing each data in a second parameter; the execution environment created in the step can be transferred to the terminal function at the later stage, and the terminal function completes the calculation process and the result output in the execution environment;
(2) storing the input data in the packet into a sorting data structure of the execution environment, and incrementing a stored data counter by 1.
Further, the information recorded in the sorted data structure in the above method includes a data type, an alignment manner, a sorting manner, and a usable memory size of data in each packet.
Further, the step (ii) of the method of the present invention, wherein the processing of the data by the termination function according to the processing result of the transient function includes the following processing steps:
(1) in the execution environment of the transient function, judging whether the processing process of the group is finished or not, if the processing process of the group is finished completely, directly returning a result from a field of a cache, and if the processing process of the group is not finished, entering the following steps;
(2) acquiring percentile and the number of stored data array _ length, sorting the number _ array stored in the array according to data, and executing the following calculation process to calculate a final result:
A. if array _ length is 0, returning to 0;
B. if the array _ length is greater than 0, taking the value of the first point first _ pos as floor (percentage _ length-1), that is, the result of rounding down the first point first _ pos, and taking the value of the second point second _ pos as ceiling (array _ length-1), that is, the result of rounding up the second point second _ pos; at this time, if the value of first _ pos is equal to the value of second _ pos, the value of first _ pos data in the number _ array is directly returned; if the value of first _ pos is not equal to the value of second _ pos, the value of first point data number _ array [ first _ pos ] is taken as first _ val, the value of second point data number _ array [ second _ pos ] is taken as transmitted _ val, then the difference proportion probability of the two is calculated, the calculation formula is percentage (array _ length-1) -first _ pos, and finally the difference is made by using the first _ val transmitted _ val probability: first _ val + (section _ val-first _ val), and obtaining a final calculation result;
(3) setting the state of the execution environment as the current packet after processing, receiving the next packet to be processed, and storing the calculation result obtained in the previous step into a field corresponding to the execution environment;
(4) and returning the final calculation result.
In addition, the invention also relates to the application of the method for realizing the percentile _ cont analysis function in the OpenGauss in OpenGauss database management or operating systems.
In summary, the invention provides a method for implementing a percentile _ cont analysis function in an OpenGauss database query planning execution stage for the first time, and the method enables the OpenGauss database to support the running of the percentile _ cont analysis function, thereby providing a powerful technical support for the application of the percentile _ cont analysis function in an OpenGauss database management system, contributing to better exerting the database performance and remarkably improving the working efficiency of the database.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention are briefly described below, it is obvious that the following drawings are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the embodiments described are merely illustrative of some, but not all, of the present invention and that the invention may be embodied or carried out in various other specific forms, and that various modifications and changes in the details of the specification may be made without departing from the spirit of the invention.
Also, it should be understood that the scope of the invention is not limited to the particular embodiments described below; it is also to be understood that the terminology used in the examples is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention.
Example 1: a method for implementing a percentile _ cont analysis function in OpenGauss.
The method comprises the following steps (see fig. 1):
a semantic analysis stage: converting the object statement into the internal representation of the function, specifically comprising the following processing procedures:
(1) searching a function in a system table according to the function name and the parameter type;
(2) processing the parameter type, and converting the parameter type of the input actual parameter according to the function definition in the system table; the parameter type conversion refers to converting the parameters of the numerical type into wider types according to the function definition in the system table, for example, the parameter requirement in the function definition is a 32-bit integer, but the actually input parameter is a 16-bit integer, so that the parameter is converted into a 32-bit integer;
(3) checking the over statement and the within statement, checking whether the field in the over statement is a subset of the sequencing field of the whole query statement, if so, finishing the check, otherwise, indicating that the sequencing field conflicts exist, and reporting the error by the checking program to exit;
(4) generating an internal representation of the window aggregation function, and filling internal information, wherein the internal information comprises a parameter type, a return value type, a system ID of the function and the like.
(II) query plan execution stage: when executing the window aggregation function, grouping data according to a specified grouping rule, sequencing the data in each group, recording each row in each group, calling a transient function of the window aggregation function, and processing input data by the transient function according to business needs; after the transient function completes the processing process of all the data in each packet, the terminal function of the window aggregation function is continuously called for each data in each packet, the terminal function processes the data according to the processing result of the transient function, executes the calculation process and obtains the final calculation result, and then returns and outputs the calculation result, which specifically comprises the following processing processes:
(1) transient function processing
(a) Creating an execution environment, when data in a group is called for the first time, firstly creating the execution environment, acquiring a first parameter percentile of the percentile _ cont, setting a stored data counter to be 0, and creating a sorted data structure for storing each data in a second parameter, wherein information recorded in the data structure comprises the data type, alignment mode, sorting mode, usable memory size and the like of the data in each group; the execution environment created in the step can be transferred to the terminal function at the later stage, and the terminal function completes the calculation process and the result output in the execution environment;
(b) storing the input data in the packet into a sorting data structure of the execution environment, and incrementing a stored data counter by 1.
(2) Terminating function processing
(a) In the execution environment of the transient function, judging whether the processing process of the group is finished or not, if the processing process of the group is finished completely, directly returning a result from a field of a cache, and if the processing process of the group is not finished, entering the following steps;
(b) acquiring percentile and the number of stored data array _ length, sorting the number _ array stored in the array according to data, and executing the following calculation process to calculate a final result:
if array _ length is 0, returning to 0;
if the array _ length is greater than 0, taking the value of the first point first _ pos as floor (percentage _ length-1), that is, the result of rounding down the first point first _ pos, and taking the value of the second point second _ pos as ceiling (array _ length-1), that is, the result of rounding up the second point second _ pos; at this time, if the value of first _ pos is equal to the value of second _ pos, the value of first _ pos data in the number _ array is directly returned; if the value of first _ pos is not equal to the value of second _ pos, the value of first point data number _ array [ first _ pos ] is taken as first _ val, the value of second point data number _ array [ second _ pos ] is taken as transmitted _ val, then the difference proportion probability of the two is calculated, the calculation formula is percentage (array _ length-1) -first _ pos, and finally the difference is made by using the first _ val transmitted _ val probability: first _ val + (section _ val-first _ val), and obtaining a final calculation result;
(c) setting the state of the execution environment as the current packet after processing, receiving the next packet to be processed, and storing the calculation result obtained in the previous step into a field corresponding to the execution environment;
(d) and returning the final calculation result.
Example 2: example 1 application of the method in the specific case.
SELECT color,percentile_cont(0.5)WITHIN GROUP(ORDER BY value)over(partition by color)FROM(VALUES('red',1),('red',3),('blue',2),('blue',4))v(color,value)；
The above-mentioned SQL requires sorting the value fields after grouping them according to the values of the color fields, and then taking the value of the data at the 0.5 position within the data of each group. Here, the data is divided into two groups: the first group is a grouping with color red (data in the group is 1 and 3); the second group is a grouping with color blue (data in group 2 and 4).
When the differential value of 0.5 position within each packet is obtained, the following transient function and terminating function are called for each packet.
The transient function is executed as follows:
(1) if the data in the packet is called for the first time, firstly creating an execution environment, acquiring a first parameter of the percentile _ cont, namely 0.5, storing the first parameter as the percentile, setting a stored data counter to be 0, and creating a sorted data structure for storing each data in a second parameter, wherein the sorted data structure can record that the data type of the data in each packet is int32, the alignment mode of the current int32, the ascending sort mode, the size of a usable memory and the like; the execution environment created in the step can be transferred to the terminal function at the later stage, and the terminal function completes the calculation process and the result output in the execution environment;
(2) and acquiring each sequenced data in the packet from the lower node, storing the data into a sequencing data structure of the execution environment, and incrementing a stored data counter by 1.
The termination function is performed as follows:
(1) and if the processing process of the group is finished, directly returning the processing result of the group, otherwise, entering the next step.
(2) And when the current array _ length is 2, sorting the stored data in the group according to the alignment mode and the ascending sorting mode of int 32. For the color red group, the data rank is 13, the value of first _ pos is 0, the value of second _ pos is 1, and the probability is 0.5, so the calculation formula is 1+ (3-1) × 0.5 ═ 2, and the final result is 2. Similarly, for a packet with color blue, the end result is 3. And after the data of the packet is processed, caching the processing result and returning the result.
The embodiments of the present invention are described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, replacement, or the like that comes within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (6)
1. A method for implementing a percentile _ cont analysis function in OpenGauss, the method comprising the steps of:
a semantic analysis stage: converting the object statement into an internal representation of the function;
(II) query plan execution stage: when executing the window aggregation function, grouping data according to a specified grouping rule, sequencing the data in each group, recording each row in each group, calling a transient function of the window aggregation function, and processing input data by the transient function according to business needs; after the transient function completes the processing process of all the data in each group, the terminal function of the window aggregation function is called continuously for each data in each group, the terminal function processes the data according to the processing result of the transient function, the calculation process is executed, the final calculation result is obtained, and then the calculation result is returned and output.
2. The method according to claim 1, wherein the step (one) includes the following steps:
(1) searching a function in a system table according to the function name and the parameter type;
(2) processing the parameter type, and converting the parameter type of the input actual parameter according to the function definition in the system table;
(3) checking the over statement and the within statement, checking whether the field in the over statement is a subset of the sequencing field of the whole query statement, if so, finishing the check, otherwise, indicating that the sequencing field conflicts exist, and reporting the error by the checking program to exit;
(4) an internal representation of the window aggregation function is generated, and the internal information is filled.
3. The method according to claim 1, wherein the step (two) of processing the input data by the transient function according to the service requirement includes the following processing procedures:
(1) creating an execution environment, when calling data in a packet for the first time, firstly creating the execution environment, acquiring a first parameter percentile of the percentile _ cont, setting a stored data counter to be 0, and creating a sorted data structure for storing each data in a second parameter; the execution environment created in the step can be transferred to the terminal function at the later stage, and the terminal function completes the calculation process and the result output in the execution environment;
(2) storing the input data in the packet into a sorting data structure of the execution environment, and incrementing a stored data counter by 1.
4. The method of claim 3, wherein the information recorded in the ordered data structure includes a data type, an alignment manner, an ordering manner of data in each packet, and a usable memory size.
5. The method according to claim 1, wherein the processing of the data by the terminating function according to the processing result of the transient function in step (ii) includes the following processing procedures:
(1) in the execution environment of the transient function, judging whether the processing process of the group is finished or not, if the processing process of the group is finished completely, directly returning a result from a field of a cache, and if the processing process of the group is not finished, entering the following steps;
(2) acquiring percentile and the number of stored data array _ length, sorting the number _ array stored in the array according to data, and executing the following calculation process to calculate a final result:
A. if array _ length is 0, returning to 0;
B. if the array _ length is greater than 0, taking the value of the first point first _ pos as floor (percentage _ length-1), that is, the result of rounding down the first point first _ pos, and taking the value of the second point second _ pos as ceiling (array _ length-1), that is, the result of rounding up the second point second _ pos; at this time, if the value of first _ pos is equal to the value of second _ pos, the value of first _ pos data in the number _ array is directly returned; if the value of first _ pos is not equal to the value of second _ pos, the value of first point data number _ array [ first _ pos ] is taken as first _ val, the value of second point data number _ array [ second _ pos ] is taken as transmitted _ val, then the difference proportion probability of the two is calculated, the calculation formula is percentage (array _ length-1) -first _ pos, and finally the difference is made by using the first _ val transmitted _ val probability: first _ val + (section _ val-first _ val), and obtaining a final calculation result;
(3) setting the state of the execution environment as the current packet after processing, receiving the next packet to be processed, and storing the calculation result obtained in the previous step into a field corresponding to the execution environment;
(4) and returning the final calculation result.
6. Use of the method of any of claims 1-5 in OpenGauss to implement a percentile _ cont analysis function in an OpenGauss database management or operating system.
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