CN103064955A - Inquiry planning method and device - Google Patents
Inquiry planning method and device Download PDFInfo
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- CN103064955A CN103064955A CN2012105863060A CN201210586306A CN103064955A CN 103064955 A CN103064955 A CN 103064955A CN 2012105863060 A CN2012105863060 A CN 2012105863060A CN 201210586306 A CN201210586306 A CN 201210586306A CN 103064955 A CN103064955 A CN 103064955A
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Abstract
An embodiment of the invention provides an inquiry planning method and device. The inquiry planning method includes receiving an inquiry request message; determining at least one inquiry path according to operation objects of the inquiry request message, wherein each inquiry path includes at least one inquiry operating step; determining execution costs of each inquiry path according to each inquiry path; determining the inquiry path with minimum execution cost to be the optimal inquiry path; selecting memories for executing the inquiry operating steps according to operational capability of the current memories and set rules; and assigning the optimal inquiry path to an executer, and scheduling the inquiry operating steps of the optimal inquiry path to each memory to perform execution. By means of the inquiry planning method and device, the memories determined during optimal inquiry path planning can be used for executing steps of the optimal inquiry path so as to acquire inquiry results, and actual minimum execution costs of the inquiry results acquired by the optimal inquiry path can be guaranteed.
Description
Technical field
The embodiment of the invention relates to computer database technology, relates in particular to a kind of query planning method and device.
Background technology
When client sends query requests with the data in the Query Database to the master server of database, master server is by " query planning device " definite " Optimum Implementation Plan " for this query requests, " query planning device " is when determining " Optimum Implementation Plan ", usually first according to calculation cost, reading the factor such as dish speed determines to realize the execution in step of this query requests and the ordering relation between each operation steps, generate at least one " executive plan ", each " executive plan " consists of the search volume, then master server carries out respectively cost estimation to " executive plan " in this search volume, determine that according to the cost estimation result " executive plan " of Least-cost is as " Optimum Implementation Plan " for this query requests, the query executor of master server is sequentially carried out this " Optimum Implementation Plan " and is obtained Query Result, at last Query Result is fed back to the client that sends query requests by master server.
When the data in the database are distributed on the different memory devices, be that data are when being stored in the distributed memory system, in order to generate the Query Result for query requests, need a plurality of different memory devices to participate in, " Optimum Implementation Plan " that yet traditional query planning method is determined is in the situation that same storer order is carried out, can not be applicable to the distributed storage framework, obtain the scheme of Executing Cost minimum.
Summary of the invention
The embodiment of the invention provides a kind of query planning method and device, is intended to solve " Optimum Implementation Plan " that adopt existing query planning method to determine and inquires about and obtain Query Result, and the Executing Cost of in fact paying is minimum problem not necessarily.
First aspect, the embodiment of the invention provide a kind of query planning method, comprising:
Receive inquiry request message;
Determine at least one query path according to the operand of described inquiry request message, each query path comprises at least one query manipulation step;
For each described query path, determine the Executing Cost of each query path, wherein said Executing Cost comprises processor execution time, disk input and output time and network latency, and described network latency is that pending data are transmitted the time that consumes between storer;
The query path of determining the Executing Cost minimum is optimum query path;
Actuator is distributed in described optimum query path to be dispatched to each storer execution.
In conjunction with first aspect, in the possible implementation of the first of first aspect, before determining at least one query path according to the operand of described inquiry request message, also comprise:
According to the arithmetic capability of current each storer, according to the storer of setting rules selection execution query manipulation step.
Second aspect, the embodiment of the invention provide a kind of query planning device, comprising:
Receiver module is used for receiving inquiry request message;
The query planning module is used for determining at least one query path according to the operand of described inquiry request message that each query path comprises at least one query manipulation step; For each described query path, determine the Executing Cost of each query path, wherein said Executing Cost comprises processor execution time, disk input and output time and network latency, and described network latency is that pending data are transmitted the time that consumes between storer; The query path of determining the Executing Cost minimum is optimum query path;
Execution module is used for that actuator is distributed in described optimum query path and dispatches to each storer execution.
In conjunction with second aspect, in the possible implementation of the first of second aspect, also comprise:
The parallelization planning module was used for before the query planning module is determined at least one query path according to the operand of described inquiry request message, according to the arithmetic capability of current each storer, according to the storer of setting rules selection execution query manipulation step.
Query planning method and the device of the present embodiment, by receiving inquiry request message, determine at least one query path according to the operand of inquiry request message, each query path comprises at least one query manipulation step, for each described query path, determine the Executing Cost of each query path, wherein Executing Cost comprises the processor execution time, disk input and output time and network latency, the query path of determining the Executing Cost minimum is optimum query path, arithmetic capability according to current each storer, according to the storer of setting rules selection execution query manipulation step, wherein, the amount of memory of selecting is less than saturation point and greater than critical point, actuator is distributed in optimum query path to be dispatched to each storer execution, can realize that the storer of determining by according to optimum query path planning the time carries out the Query Result that each step of this optimum query path obtains, can guarantee to obtain the Executing Cost that in fact Query Result pay by this optimum query path minimum.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, the below will do one to the accompanying drawing of required use in embodiment or the description of the Prior Art and introduce simply, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the process flow diagram of query planning embodiment of the method one of the present invention;
Fig. 2 is that the nothing that the embodiment of the invention was suitable for is shared distributed data base networking structure schematic diagram;
Fig. 3 is the process flow diagram of query planning device embodiment one of the present invention.
Embodiment
For making the purpose, technical solutions and advantages of the present invention clearer, below in conjunction with the accompanying drawing among the present invention, the technical scheme among the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that obtains under the creative work prerequisite.
The query planning method of the present embodiment can adopt the query planning device to realize, this query planning device can realize by the mode of hardware or software, and the query planning device can be integrated in and realize the query planning method in the computing machine.
Fig. 1 is the process flow diagram of query planning embodiment of the method one of the present invention, the query planning method of the present embodiment can be used for carrying out the data query operation without sharing the networking of (Shared-nothing) distributed data base, Fig. 2 is that the nothing that the embodiment of the invention was suitable for is shared distributed data base networking structure schematic diagram, as shown in Figure 2, comprise without sharing the distributed data base networking: master server, standby server and some storeies, wherein, master server is control and the decision center that whole nothing is shared distributed data base system, provide service to client host, master server has been stored the data characteristics information such as data distributed intelligence in each storer, by the query requests of master server customer in response end main frame, standby server is the backup existence as master server.As shown in Figure 1, the query planning method of the present embodiment comprises:
101, receive inquiry request message.
Particularly, receive the inquiry request message that sends from any client host without the master server of sharing in the distributed data base, this inquiry request message can be Structured Query Language (SQL), the query manipulation that this Structured Query Language (SQL) request server is carried out in the present embodiment for example can for: request server arranges the names all students of C1, a C2 and C3 class from low to high according to mathematics achievement, and C1, a C2 and all students' of C3 class mathematics achievement can be distributed in dispersedly without sharing in a plurality of storeies of distributed data base.
102, determine at least one query path according to the operand of inquiry request message, each query path comprises at least one query manipulation step.
Particularly, the query planning device of master server is about to a C1 according to the operand of inquiry request message, all students of C2 and C3 class arrange the names from low to high according to mathematics achievement and determine at least one query path, this at least one query path is the query path that can access the result of this query requests, the query planning device of master server can generate at least one query path according to dynamic programming algorithm or genetic algorithm, each query path comprises at least one query manipulation step, for example the query planning device of master server is according to a query path A of dynamic programming algorithm generation, query path A comprises: the tabulation of operation 1-scanning achievement, namely according to the record of master server to the data memory location, know a C1, all students' of C2 and C3 class mathematics achievement data are in the memory location of each storer; Operation 2-heavily distributes data according to class's numbering, be about to each memory location that all students' of C1 class mathematics achievement data from scan arrives by Internet Transmission to target memory 1, each memory location that all students' of C2 class mathematics achievement data from scan is arrived by Internet Transmission to target memory 2, each memory location that all students' of C3 class mathematics achievement data from scan is arrived by Internet Transmission to target memory 3, this target memory 1, target memory 2 and target memory 3 can be that same storer also can be mutually different storer, can also be that wherein two storeies are identical different from another storer, the query planning device of master server for example can be according to the target memory 1 without the arithmetic capability of sharing all storeies in the distributed data base networking and this operation 2 of the definite execution of busy extent, target memory 2 and target memory 3; Operation 3-arranges the names the student of each class from low to high according to mathematics achievement, in target memory 1, target memory 2 and the target memory 3 of namely in aforesaid operations 2, determining respectively the mathematics achievement to all students of C1, C2 and C3 class sort.The query planning device of master server can also generate another query path B according to dynamic programming algorithm, and query path B comprises: the tabulation of operation 1-scanning achievement; Operation 2-arranges the names the student of C1, a C2 and C3 class from low to high according to mathematics achievement on local storage, namely according to the memory location that scans, in the storer at this achievement place achievement is sorted; Operation 3-heavily distributes data according to class's numbering, the student's of C1, a C2 in the local storage and C3 class mathematics achievement is transferred to respectively target memory 1, target memory 2 and target memory 3 by network, this target memory 1, target memory 2 and target memory 3 can be that same storer also can be mutually different storer, can also be that wherein two storeies are identical different from another storer; Operation 4-arranges the names the student of each class from low to high according to mathematics achievement on target memory 1, target memory 2 and target memory 3.Can both obtain the query requests result according to this query path A and query path B, the query planning device of master server can also generate other query path according to dynamic programming algorithm, does not enumerate one by one the operation that each query path comprises herein.
103, for each query path, determine the Executing Cost of each query path, wherein Executing Cost comprises processor execution time, disk input and output time and network latency, and network latency is that pending data are transmitted the time that consumes between storer.
Particularly, calculate master server and storer and carry out the needed Executing Cost of each query path, each that calculates namely that master server and storer carry out that each query path comprises operates needed processor execution time, disk input and output time and network latency.
for example: calculate respectively query path A, the query planning device of query path B and master server is according to the Executing Cost of other query path of dynamic programming algorithm generation, the Executing Cost of query path A is: the needed processor of executable operations 1 carry out time of scanning list of results and executable operations 2 by student's mathematics achievement from the local storage at achievement place by Internet Transmission to the network latency of the required cost of target memory and executable operations 3 needed on target memory to student performance needed processor sum computing time that sorts, the Executing Cost of query path B is: the processor that the time that the needed processor of executable operations 1 is carried out the scanning list of results and required of executable operations 2 are located in memory to student performance sort that needed processor computing time and executable operations 3 produce by the student's of identical class mathematics achievement from the local storage at achievement place by network latency and the target memory executable operations 4 needed processor computing time sums of Internet Transmission to the required cost of target memory.
104, the query path of determining the Executing Cost minimum is optimum query path.
Particularly, the Executing Cost value of each query path of determining in more above-mentioned 103, as optimum query path, for example the Executing Cost value of query path A is minimum with the query path of Executing Cost value minimum, and then query path A is optimum query path.
105, optimum query path being distributed to actuator dispatches to each storer execution.
Particularly, the query planning device of master server is distributed to optimum query path the actuator of master server, actuator participates in the storer of each operation of this optimum query path according to the query path scheduling, obtain operating result, for example: the target memory that the operation 2 of optimum query path A is carried out in the participation of determining is storer 1 and storer 2, all students' of C1 and C2 class mathematics achievement is transferred to storer 1, all students' of C3 class mathematics achievement is transferred to storer 2, then the actuator of master server scheduling storer 1 and storer 2 executable operations 2.Redo 3, carry out the achievement ordering.
Storer 1 and storer 2 feed back to master server with execution result.
The query planning method of the present embodiment, considered net cost by increase, namely considered the transmission cost between different memory of appearance in each operation of data, can be applicable to the distributed storage framework, guarantee to obtain the Executing Cost minimum that in fact Query Result is paid by this optimum query path.
On the basis of above-described embodiment, further, the query planning device of master server can also be according to the arithmetic capability of current each storer, according to the storer of setting rules selection execution query manipulation step before determining at least one query path according to the operand of inquiry request message.
Particularly, when selecting to carry out the storer of query manipulation step, for example: when before determining at least one query path according to the operand of inquiry request message, select carrying out the storer of operation 2 of query path A, the query planning device of master server can be according to the degree that is busy with one's work of current each storer, and the storer of the selecting factors right quantity such as free memory space size is carried out the operation 2 of query path A, the right quantity of this storer can be less than saturation point and greater than critical point, and the saturation point of amount of memory and critical point can dynamically be determined according to the current busy state of storer.For example, if 3 storeies participate in the executable operations 2 required costs of paying and participate in executable operations 2 needed costs less than 4 storeies, can think that so 4 is saturation points of the amount of memory of executable operations 2, if 2 storeies participate in the executable operations 2 required costs of paying and participate in executable operations 2 needed costs greater than 3 storeies, can think that so 2 is critical points of the amount of memory of executable operations 2.
One of ordinary skill in the art will appreciate that: all or part of step that realizes said method embodiment can be finished by the relevant hardware of programmed instruction, aforesaid program can be stored in the computer read/write memory medium, this program is carried out the step that comprises said method embodiment when carrying out; And aforesaid storage medium comprises: the various media that can be program code stored such as ROM, RAM, magnetic disc or CD.
Fig. 3 is the process flow diagram of query planning device embodiment one of the present invention, as shown in Figure 3, the query planning device 300 of the present embodiment comprises: receiver module 301, query planning module 302 and execution module 303, and wherein, receiver module 301 can be used for receiving inquiry request message; Query planning module 302 can be for determining at least one query path according to the operand of described inquiry request message, and each query path comprises at least one query manipulation step; For each described query path, determine the Executing Cost of each query path, wherein said Executing Cost comprises processor execution time, disk input and output time and network latency, and described network latency is that pending data are transmitted the time that consumes between storer; The query path of determining the Executing Cost minimum is optimum query path; Execution module 303 can be used for that actuator is distributed in described optimum query path to be dispatched to each storer execution.
The query planning device 300 of the present embodiment can be used for carrying out the query planning method of query planning embodiment of the method one, and concrete manner of execution can with reference to query planning embodiment of the method one, repeat no more herein.
The query planning device of the present embodiment, receive inquiry request message by receiver module, the query planning module is determined at least one query path according to the operand of inquiry request message, each query path comprises at least one query manipulation step, for each described query path, determine the Executing Cost of each query path, wherein Executing Cost comprises the processor execution time, disk input and output time and network latency, the query path of determining the Executing Cost minimum is optimum query path, execution module is distributed to actuator with optimum query path and is dispatched to each storer execution, can realize obtaining the Executing Cost minimum that in fact Query Result is paid according to the optimum query path that the query planning module is determined.
Further, on the basis of above-described embodiment, query planning device 300 can also comprise: the parallelization planning module, wherein, the parallelization planning module can be used for before the query planning module is determined at least one query path according to the operand of described inquiry request message, according to the arithmetic capability of current each storer, according to the storer of setting rules selection execution query manipulation step.
It should be noted that at last: above each embodiment is not intended to limit only in order to technical scheme of the present invention to be described; Although with reference to aforementioned each embodiment the present invention is had been described in detail, those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment puts down in writing, and perhaps some or all of technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the scope of various embodiments of the present invention technical scheme.
Claims (4)
1. a query planning method is characterized in that, comprising:
Receive inquiry request message;
Determine at least one query path according to the operand of described inquiry request message, each query path comprises at least one query manipulation step;
For each described query path, determine the Executing Cost of each query path, wherein said Executing Cost comprises processor execution time, disk input and output time and network latency, and described network latency is that pending data are transmitted the time that consumes between storer;
The query path of determining the Executing Cost minimum is optimum query path;
Actuator is distributed in described optimum query path to be dispatched to each storer execution.
2. query planning method according to claim 1 is characterized in that, before determining at least one query path according to the operand of described inquiry request message, also comprises:
According to the arithmetic capability of current each storer, according to the storer of setting rules selection execution query manipulation step.
3. a query planning device is characterized in that, comprising:
Receiver module is used for receiving inquiry request message;
The query planning module is used for determining at least one query path according to the operand of described inquiry request message that each query path comprises at least one query manipulation step; For each described query path, determine the Executing Cost of each query path, wherein said Executing Cost comprises processor execution time, disk input and output time and network latency, and described network latency is that pending data are transmitted the time that consumes between storer; The query path of determining the Executing Cost minimum is optimum query path;
Execution module is used for that actuator is distributed in described optimum query path and dispatches to each storer execution.
4. device according to claim 3 is characterized in that, also comprises:
The parallelization planning module was used for before the query planning module is determined at least one query path according to the operand of described inquiry request message, according to the arithmetic capability of current each storer, according to the storer of setting rules selection execution query manipulation step.
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| CN108874954A (en) * | 2018-06-04 | 2018-11-23 | 深圳市华傲数据技术有限公司 | A kind of optimization method of data base querying, medium and equipment |
| CN110955726A (en) * | 2019-11-26 | 2020-04-03 | 中思博安科技（北京）有限公司 | Method and device for determining distributed cost, storage medium and electronic equipment |
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Application publication date: 20130424 |