CN107480229B - Distributed computer database system for object retrieval and retrieval method thereof - Google Patents
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Abstract
The invention discloses a distributed computer database system for object retrieval and a retrieval method thereof, relating to a computer database system. The system comprises: the task server, the extraction server, the arbitration server and the plurality of regional servers are matched for use, so that the server is subjected to regional micro-management, the processing load of the task server and the arbitration server is reduced, the server is prevented from being congested, the efficiency of file extraction is improved, the number of files extracted corresponding to each keyword is calculated, the number of corresponding key words extracted in each region is calculated according to the number of the files extracted corresponding to each keyword, fair extraction in each region is realized, unnecessary retrieval is reduced, and the efficiency of file extraction can be improved.
Description
Technical Field
The present invention relates to computer database systems, and more particularly, to a distributed computer database system for object retrieval and a retrieval method thereof.
Background
The distributed database is composed of a group of data distributed on different computers in a computer network, each node in the network under the condition can realize an independent processing function, and can operate global application under the action of a network communication subsystem.
However, with the rapid increase of user usage in the computer network operation process, higher requirements are put forward on the capacity and network operation performance of the computer network, and due to the limitation of the existing computer network resource conditions, the load of the server is increased more and more, thereby causing the congestion of the server.
Disclosure of Invention
The embodiment of the invention provides a distributed computer database system for object retrieval and a retrieval method thereof, which are used for solving the problem of server congestion caused by large load of a server in the prior art.
The embodiment of the invention provides a distributed computer database system for object retrieval, which comprises: the system comprises a task server, an extraction server, an arbitration server and a plurality of regional servers, wherein each regional server is correspondingly connected with a plurality of computers;
the number of files which are stored in each computer in the area correspondingly according to each preset keyword and the number of files which are stored in the area correspondingly according to each preset keyword are stored in each area server;
the task server is used for receiving a retrieval instruction, analyzing a plurality of keywords from the retrieval instruction and sending a statistical instruction to each regional server; the statistical instruction is used for counting the number of files correspondingly stored by each keyword in a plurality of keywords for each regional server; the system comprises a server, a server management server and a plurality of keywords, wherein the server management server is used for sending an arbitration instruction to the arbitration server, and the arbitration instruction is used for indicating the arbitration server to count the number of files correspondingly stored by each keyword; the method comprises the steps of inquiring the maximum storage capacity which can be currently stored by an extraction server, wherein the maximum storage capacity is the maximum number of files which can be currently stored; the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for sending the maximum storage capacity which can be currently stored by an extraction server to a mediation server;
when the regional server receives the statistical instruction, comparing each keyword in the plurality of keywords with a plurality of preset keywords, and when the preset keywords same as the keywords exist in the plurality of preset keywords, sending the number of files correspondingly stored in the regional area by the preset keywords to an arbitration server;
the arbitration server is used for calculating the number of the files extracted corresponding to each keyword and the number of the files extracted corresponding to each keyword in each regional server;
and the regional server is used for calculating the number of the files extracted by each keyword in each computer, sending the number of the files extracted by each keyword correspondingly to each computer, extracting the number of the files corresponding to each keyword, and transmitting the files to the extraction server.
The embodiment of the invention provides a retrieval method of a distributed computer database system for object retrieval, which comprises the following steps:
s1, storing the number of files correspondingly stored by each preset keyword in each computer in the area and the number of files correspondingly stored by each preset keyword which can be retrieved by the area server in each area server;
s2, when the task server receives a retrieval instruction, analyzing a plurality of keywords from the retrieval instruction, and sending a statistical instruction to each regional server; the statistical instruction is used for indicating each regional server to count the number of files which are correspondingly stored in the region by each keyword in the plurality of keywords;
s3, when the region server receives the statistical instruction, comparing each keyword in the keywords with a plurality of preset keywords, and when the preset keywords same as the keywords exist in the preset keywords, sending the number of files correspondingly stored in the preset keywords in the region to an arbitration server;
s4, the task server inquires the maximum storage capacity which can be currently stored by the extraction server, and sends an arbitration instruction and the maximum storage capacity which can be currently stored by the extraction server to the arbitration server; the arbitration instruction is used for indicating an arbitration server to count the number of files correspondingly stored by each keyword; the maximum storage capacity is the maximum number of files which can be stored currently;
s5, the arbitration server counts the total number of the files stored corresponding to each keyword, and calculates the number of the files extracted corresponding to each keyword and the number of the files extracted corresponding to each keyword in each regional server;
s6, when receiving the number of the files extracted corresponding to each keyword, the regional server calculates the number of the files extracted corresponding to each keyword in each computer, and sends the number of the files extracted corresponding to each keyword to each computer;
s7, the computer extracts the corresponding keywords and the corresponding number of files and sends the files to the extraction server.
Preferably, the step of calculating, by the mediation server, the number of the extracted files corresponding to each keyword includes:
and the arbitration server calculates the number of the files extracted corresponding to each keyword according to the sum of the total number of the files stored corresponding to the keywords in all the areas, the total number of the files stored corresponding to each keyword in all the areas and the maximum storage capacity which can be currently stored by the extraction server.
Preferably, the step of calculating the number of the files extracted by each keyword in each regional server by the mediation server includes:
and the arbitration server calculates the number of the files correspondingly extracted by the keywords in each regional server according to the number of the files correspondingly extracted by the keywords, the number of the files correspondingly stored in the region by the keywords and the total number of the files correspondingly stored by the keywords.
Preferably, the calculating, by the region server, the number of the files extracted by each keyword in each computer includes:
and the regional server calculates the number of the files correspondingly extracted by the keywords in each computer according to the number of the files correspondingly extracted by the keywords in each regional server, the number of the files correspondingly stored by the keywords in the region, and the number of the files correspondingly extracted by the keywords in each computer according to the number of the files correspondingly stored by the keywords in the computer.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, through regional micro-management, the processing load of the task server and the arbitration server is reduced, the congestion of the server is avoided, the file extraction efficiency is improved, the number of the files extracted corresponding to each keyword can be calculated according to the sum of the maximum storage capacity of the current extraction server, the total number of the files stored corresponding to the keywords in all the regions and the total number of the files stored corresponding to each keyword in all the regions, and further, the number of the files extracted corresponding to the keywords in each region can be calculated according to the number of the files extracted corresponding to each keyword, so that fair extraction of each region is realized, namely, more files are extracted in each region, less files are extracted, unnecessary retrieval is reduced, and the file extraction efficiency can also be improved.
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FIG. 1 is a schematic structural diagram of a distributed computer database system for object retrieval according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a retrieval method of a distributed computer database system for object retrieval according to an embodiment of the present invention.
Description of the drawings:
1. a task server; 2. extracting a server; 3. a mediation server; 4. and a regional server.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 is a schematic structural diagram of a distributed computer database system for object retrieval according to an embodiment of the present invention; as shown in fig. 1, the distributed computer database system for object retrieval includes: the system comprises a task server 1, an extraction server 2, a mediation server 3 and a plurality of area servers 4, wherein each area server is correspondingly connected with a plurality of computers.
The number of files stored in each computer in the area corresponding to each preset keyword and the number of files stored in each preset keyword in the area corresponding to each preset keyword are stored in each area server 4;
the task server 1 is used for receiving a retrieval instruction, analyzing a plurality of keywords from the retrieval instruction, and sending a statistical instruction to each regional server; the statistical instruction is used for counting the number of files correspondingly stored by each keyword in a plurality of keywords for each regional server; the system is used for sending an arbitration instruction to the arbitration server 3, wherein the arbitration instruction is used for indicating the arbitration server to count the number of files correspondingly stored by each keyword; the method comprises the steps of inquiring the maximum storage capacity which can be currently stored by an extraction server, wherein the maximum storage capacity is the maximum number of files which can be currently stored; for sending the maximum storage capacity that the extraction server 2 is currently able to store to the mediation server.
When the regional server 4 receives the statistical instruction, each keyword in the keywords is compared with a plurality of preset keywords, and when the preset keywords which are the same as the keywords exist in the preset keywords, the number of files which are stored in the regional area corresponding to the preset keywords is sent to the arbitration server.
And the arbitration server 3 is used for calculating the number of the files extracted corresponding to each keyword and the number of the files extracted corresponding to each keyword in each regional server.
And the regional server 4 is used for calculating the number of the files extracted by each keyword in each computer, sending the number of the files extracted by each keyword to each computer, extracting the number of the files corresponding to each keyword, and transmitting the files to the extraction server.
Fig. 2 is a flowchart illustrating a retrieval method of a distributed computer database system for object retrieval according to an embodiment of the present invention. As shown in fig. 2, the method includes:
and S1, storing the number of files correspondingly stored by each preset keyword in each computer in the area and the number of files correspondingly stored by each preset keyword which can be retrieved by the area server in each area server.
In order to reduce congestion of the server, the method is divided into management modes in areas, namely, one server in a certain area manages all computers in the area, namely, the area server is a server for managing all computers in the area.
For example, the present invention includes three zones M1, M2, and M3, that is, three zone servers, i.e., zone server 1, zone server 2, and zone server 3, and the computers managed by zone server 1 are M1-PC1, M1-PC2, and M1-PC 3; the computers managed by the regional server 2 are M2-PC1 and M2-PC 2; the computers managed by the zone server 3 are M3-PC1, M1-PC2, and M1-PC1 are computers under the M1 zone
For clearer understanding, the number of files stored in each preset keyword in each computer in the area correspondingly is stored in each area server, and the number of files stored in each preset keyword correspondingly and can be retrieved by the area server, a table is established, wherein the table comprises the table 1, the table 2 and the table 3, the number of files stored in each preset keyword in each computer in the area correspondingly and can be retrieved by the area server is stored in the area server 1, the area server 2 and the area server 3 correspondingly, and the number of files stored in each preset keyword correspondingly and can be retrieved by the area server.
Table 1 shows the number of files stored in each preset keyword in each computer in the region M1 and the number of files stored in each preset keyword in the region
Wherein, K11_ Num1 is the number of files stored in the M1 in-region PC1 stored in the region server 1 corresponding to the preset keyword K11, and K11_ Num2 is the number of files stored in the M1 in-region PC2 stored in the region server 1 corresponding to the preset keyword K11; k12_ Num1 is the number of files stored in the M1 region in the PC1 corresponding to the preset keyword K12 stored in the region server 1, and K11_ Num is the number of files stored in the M1 region in the region server 1 corresponding to the preset keyword K11, that is, K11_ Num ═ K11_ Num1+ K11_ Num2+ K11_ Num 3.
Table 2 shows the number of files stored in each preset keyword in each computer in the region M2 and the number of files stored in each preset keyword in the region
Wherein, K21_ Num1 is the number of files stored in the M2 in-region PC1 stored in the region server 2 corresponding to the preset keyword K21, and K21_ Num2 is the number of files stored in the M2 in-region PC2 stored in the region server 2 corresponding to the preset keyword K21; k22_ Num1 is the number of files stored in the M2 region in the PC1 corresponding to the preset keyword K22 stored in the region server 2, and K21_ Num is the number of files stored in the M2 region in the region server 2 corresponding to the preset keyword K21, that is, K21_ Num ═ K21_ Num1+ K21_ Num 2.
Table 3 shows the number of files stored in each preset keyword in each computer in the region M3 and the number of files stored in each preset keyword in the region
Wherein, K31_ Num1 is the number of files stored in the M3 in-region PC1 in the region server 3 corresponding to the preset keyword K31, and K31_ Num2 is the number of files stored in the M3 in-region PC2 in the region server 3 corresponding to the preset keyword K31; k32_ Num1 is the number of files stored in the M3 region in the PC1 corresponding to the preset keyword K32 stored in the region server 3, and K31_ Num is the number of files stored in the M3 region in the region server 3 corresponding to the preset keyword K31, that is, K31_ Num ═ K31_ Num1+ K31_ Num 2.
It should be noted that tables 1, 2 and 3 are only examples of the present invention and are not intended to limit the present invention.
S2, when the task server receives a retrieval instruction, analyzing a plurality of keywords from the retrieval instruction, and sending a statistical instruction to each regional server; the statistical instruction is used for indicating each regional server to count the number of files correspondingly stored in the region by each keyword in the plurality of keywords.
For example, the task server parses a plurality of keywords from the retrieval instruction, wherein the keywords are key1, key2 and key3 …;
and S3, when the region server receives the statistical instruction, comparing each keyword in the plurality of keywords with a plurality of preset keywords, and when the preset keywords same as the keywords exist in the plurality of preset keywords, sending the number of files correspondingly stored in the preset keywords in the region to an arbitration server.
For example, when the region server 1 receives the statistical instruction, it compares key1 with K11, K12, K13 and K14 in turn, and sends the number of files K11_ Num stored in the M1 region stored in the region server 1 as the preset keyword K11 to the mediation server when key1 is the same as K11.
And S4, the task server inquires the maximum storage capacity which can be currently stored by the extraction server, and sends an arbitration instruction and the maximum storage capacity which can be currently stored by the extraction server to the arbitration server.
The arbitration instruction is used for indicating an arbitration server to count the number of files correspondingly stored by each keyword; the maximum storage capacity is the maximum number of files which can be stored currently;
s5, the arbitration server counts the total number of the files stored corresponding to each keyword, and calculates the number of the files extracted corresponding to each keyword and the number of the files extracted corresponding to each keyword in each regional server.
Table 4 shows the total number of the files stored corresponding to each keyword counted by the mediation server
| | Area server | 1 | |
|
Total number of |
| key1 | key1_M1_Num | key1_M2_Num | key1_M3_Num | key1_Num | |
| key2 | key2_M1_Num | key2_M2_Num | key2_M3_Num | key2_Num |
Wherein, key1_ M1_ Num is the number of files stored in the region server 1 corresponding to the keyword key1, key1_ M2_ Num is the number of files stored in the region server 2 corresponding to the keyword key1, key1_ M3_ Num is the number of files stored in the region server 3 corresponding to the keyword key1, key2_ M2_ Num is the number of files stored in the region server 2 corresponding to the keyword key2, key2_ M2_ Num is the number of files stored in the region server 2 corresponding to the keyword key2, key2_ M3_ Num is the number of files stored in the region server 3 corresponding to the keyword 2, key1_ Num is the total number of the keywords of the files stored in all the regions corresponding to the keyword key 375, and key2_ M is the total number of the files stored in all the regions corresponding to the keyword 2.
And calculating the number of the files extracted corresponding to each keyword according to the sum of the number of the files stored corresponding to each keyword, the sum of the number of the files stored corresponding to each keyword in all the keywords and the maximum storage capacity which can be currently stored by the extraction server.
For example,
the key1_ Max is the number of files extracted by the key1, and the Max _ Num is the maximum storage capacity which can be currently stored by the extraction server.
Wherein, key2_ Max is the number of the files extracted corresponding to key 2.
Optionally, when calculating the number of the files extracted by each keyword in each regional server, the arbitration server calculates the number of the files extracted by each keyword in each regional server according to the number of the files extracted by each keyword in correspondence, the number of the files stored by each keyword in the region, and the total number of the files stored by each keyword in correspondence.
For example,
the key1_ M1_ Max is the number of the files corresponding to the keyword key1 in the M1 area, the key2_ M1_ Max is the number of the files corresponding to the keyword key2 in the M1 area, and the key1_ M2_ Max is the number of the files corresponding to the keyword key1 in the M2 area.
S6, when the region server receives the number of the files extracted corresponding to each keyword, the number of the files extracted corresponding to each keyword in each computer is calculated, and the number of the files extracted corresponding to each keyword is sent to each computer.
When the regional server calculates the number of the files extracted by each keyword in each computer, the regional server calculates the number of the files extracted by each keyword in each computer according to the number of the files extracted by each keyword in each regional server, the number of the files stored by each keyword in the region, and the number of the files extracted by each keyword in each computer according to the number of the files stored by each keyword in each computer.
For example, key1 ═ K11,
the number of files correspondingly extracted by the keyword key1 in the computer PC1 can be calculated.
S7, the computer extracts the corresponding keywords and the corresponding number of files and sends the files to the extraction server.
The embodiment of the invention reduces the processing load of the task server and the arbitration server and improves the efficiency of extracting the files by micro-management in areas, and can calculate the number of the files extracted corresponding to each keyword according to the sum of the maximum storage capacity of the current extraction server, the total number of the files stored corresponding to the keywords in all the areas and the total number of the files stored corresponding to each keyword in all the areas, and further calculate the number of the files extracted corresponding to the keywords in each area according to the number of the files extracted corresponding to each keyword, thereby realizing fair extraction in each area, namely extracting more files and less files corresponding to the keywords in each area, reducing unnecessary retrieval, and improving the efficiency of extracting the files.
The above disclosure is only a few specific embodiments of the present invention, and those skilled in the art can make various modifications and variations of the present invention without departing from the spirit and scope of the present invention, and it is intended that the present invention encompass these modifications and variations as well as others within the scope of the appended claims and their equivalents.
Claims (1)
1. A distributed computer database retrieval method for object retrieval, comprising: the system comprises a task server, an extraction server, an arbitration server and a plurality of regional servers, wherein each regional server is correspondingly connected with a plurality of computers;
the number of files which are stored in each computer in the area correspondingly according to each preset keyword and the number of files which are stored in the area correspondingly according to each preset keyword are stored in each area server;
the task server is used for receiving a retrieval instruction, analyzing a plurality of keywords from the retrieval instruction and sending a statistical instruction to each regional server; the statistical instruction is used for indicating each regional server to count the number of files correspondingly stored by each keyword in a plurality of keywords; the system comprises a server, a server management server and a plurality of keywords, wherein the server management server is used for sending an arbitration instruction to the arbitration server, and the arbitration instruction is used for indicating the arbitration server to count the number of files correspondingly stored by each keyword; the method comprises the steps of inquiring the maximum storage capacity which can be currently stored by an extraction server, wherein the maximum storage capacity is the maximum number of files which can be currently stored; the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for sending the maximum storage capacity which can be currently stored by an extraction server to a mediation server;
when the regional server receives the statistical instruction, comparing each keyword in the plurality of keywords with a plurality of preset keywords, and when the preset keywords same as the keywords exist in the plurality of preset keywords, sending the number of files correspondingly stored in the regional area by the preset keywords to an arbitration server;
the arbitration server is used for calculating the number of the files extracted corresponding to each keyword and the number of the files extracted corresponding to each keyword in each regional server;
the regional server is used for calculating the number of the files extracted by each keyword in each computer and sending the number of the files extracted by each keyword to each computer;
the computer is used for extracting the corresponding keywords and the files with the corresponding quantity and sending the files to the extraction server;
the method comprises the following steps:
s1, storing the number of files which are stored correspondingly by each preset keyword in each computer in the area and the number of files which can be retrieved by the area server and are stored correspondingly by each preset keyword in each area server;
s2, when the task server receives a retrieval instruction, analyzing a plurality of keywords from the retrieval instruction, and sending a statistical instruction to each regional server; the statistical instruction is used for indicating each regional server to count the number of files which are correspondingly stored in the region by each keyword in the plurality of keywords;
s3, when the region server receives the statistical instruction, comparing each keyword in the keywords with a plurality of preset keywords, and when the preset keywords same as the keywords exist in the preset keywords, sending the number of files correspondingly stored in the preset keywords in the region to an arbitration server;
s4, inquiring the maximum storage capacity which can be currently stored by the extraction server through the task server, and sending an arbitration instruction and the maximum storage capacity which can be currently stored by the extraction server to the arbitration server; the arbitration instruction is used for indicating an arbitration server to count the number of files correspondingly stored by each keyword; the maximum storage capacity is the maximum number of files which can be stored currently;
s5, counting the total number of the files stored corresponding to each keyword through the arbitration server, and calculating the number of the files extracted corresponding to each keyword and the number of the files extracted corresponding to each keyword in each regional server;
s6, when the regional server receives the number of the files extracted corresponding to each keyword, calculating the number of the files extracted corresponding to each keyword in each computer, and sending the number of the files extracted corresponding to each keyword to each computer;
s7, extracting corresponding keywords and files with corresponding quantity through a computer, and sending the files to an extraction server;
the arbitration server calculates the number of the files extracted by each keyword correspondingly, and the method comprises the following steps:
the arbitration server calculates the number of the files extracted corresponding to each keyword according to the sum of the total number of the files stored corresponding to the keywords in all the areas, the total number of the files stored corresponding to each keyword in all the areas and the maximum storage capacity which can be currently stored by the extraction server;
the method for calculating the number of the files correspondingly extracted from each regional server by the mediation server comprises the following steps:
the arbitration server calculates the number of the files extracted by the keywords in each regional server according to the number of the files extracted by the keywords correspondingly, the number of the files stored by the keywords correspondingly in the region and the total number of the files stored by the keywords correspondingly;
the region server calculates the number of the files correspondingly extracted from each keyword in each computer, and the method comprises the following steps:
and the regional server calculates the number of the files correspondingly extracted by the keywords in each computer according to the number of the files correspondingly extracted by the keywords in each regional server, the number of the files correspondingly stored by the keywords in the region, and the number of the files correspondingly extracted by the keywords in each computer according to the number of the files correspondingly stored by the keywords in the computer.
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