CN107766459B - Table dividing method and system - Google Patents
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Abstract
The invention relates to a table-dividing method and system, the method includes obtaining the ID number of the user; performing dimension splitting and random splitting according to the ID number to obtain a form ID number; the user data is stored in a table of table ID numbers. The invention can split the tables by adopting a mode of combining random splitting and dimension splitting, can greatly improve the usability of the database, can eliminate the data in the table to be uniformly distributed into other tables through a random algorithm when one table is unavailable, directly eliminates the random range of the random algorithm from a data source if the data source where a certain sub-table is positioned needs to be subjected to operations such as hardware upgrading and the like, and upgrades the database without stopping the machine, thereby not only completing the splitting of the table, but also greatly improving the usability of the database, ensuring the performance of the database and greatly reducing the loss caused by the shutdown upgrading.
Description
Technical Field
The invention relates to a table dividing method, in particular to a table dividing method and a table dividing system.
Background
With the continuous development of internet services, internet data is larger and larger, and a single database table cannot meet the development requirements of the services, so that data needs to be split, when the data of one table is too large to be processed, the data needs to be split into a plurality of tables, which is a method commonly adopted by internet companies at present. For example, the T _ PAY table has 10 billion data, the application processing is very slow, the data of the table needs to be split into 100 tables of T _ PAY _00, T _ PAY _01, … and T _ PAY _99, so that the data of each table is 1000W, and the program processing speed is greatly improved.
For the splitting of a database table, the existing splitting method is that an application system splits data according to a certain dimension, and it is common to take the last 2 bits of a user ID as a splitting dimension, for example, a user whose UID is XXXX00 falls into a T _ PAY _00 table, a user whose UID is XXXX89 falls into a T _ PAY _89 table. However, the table is split into a plurality of tables, a large table is split into a plurality of small tables, although the performance is improved, the number of tables is increased, and an association part exists between each table, and a problem of any table can cause the unavailability of services, and the availability of the whole system and the performance of the system are reduced.
Therefore, it is necessary to design a table splitting method, which can not only split the table, but also greatly improve the usability of the database, ensure the performance of the database, and greatly reduce the loss caused by shutdown upgrading.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a table dividing method and a system thereof.
In order to achieve the purpose, the invention adopts the following technical scheme: a method of partitioning a table, the method comprising:
acquiring an ID number of a user;
carrying out dimension splitting and random splitting according to the ID number to obtain the ID number of the table, wherein the steps are as follows
Acquiring the last two digits of the user ID number;
performing random operation according to the last two digits of the user ID number to obtain a random number;
combining the last two digits of the user ID number with a random number to form a new number;
acquiring two digits in the new digits to form a form ID number;
storing user data in the table of table ID numbers.
The further technical scheme is as follows: and combining the last two digits of the user ID number with the random number to form a new number, specifically combining the last two digits of the user ID number in front of the random number to form the new number.
The further technical scheme is as follows: and acquiring two digits in the new digits to form the table ID number, specifically acquiring the first digit and the last digit in the new digits to form the table ID number.
The further technical scheme is as follows: after the step of storing the user data in the table of the table ID number, the method further comprises the following specific steps:
sending a query or modification request;
acquiring a form ID according to the request;
and opening a corresponding table according to the table ID, and carrying out corresponding query or modification.
The invention also provides a table-dividing system, which comprises a user ID acquisition unit, a table ID acquisition unit and a storage unit;
the user ID obtaining unit is used for obtaining the ID number of the user;
the form ID acquisition unit is used for carrying out dimension splitting and random splitting according to the ID number to acquire the form ID number, and comprises a first acquisition module, a random number acquisition module, a new digital formation module and a second acquisition module,
the first acquisition module is used for acquiring the last two digits of the user ID number;
the random number acquisition module is used for carrying out random operation according to the last two digits of the user ID number to acquire a random number;
the new number forming module is used for combining the last two digits of the user ID number with a random number to form a new number;
the second acquisition module is used for acquiring two digits in the new digits to form a table ID number;
the storage unit is used for storing the user data in the table of the table ID number.
The further technical scheme is as follows: the system also comprises a request sending unit, a request acquiring unit and an opening unit;
the request sending unit is used for sending a query or modification request;
the request acquisition unit is used for acquiring a form ID according to the request;
and the opening unit is used for opening the corresponding table according to the table ID and carrying out corresponding query or modification.
Compared with the prior art, the invention has the beneficial effects that: the table splitting method provided by the invention can be used for splitting the tables in a random splitting and dimensionality splitting combined mode, the usability of the database can be greatly improved, when one table is unavailable, the table can be removed through a random algorithm, data in the table is uniformly distributed into other tables, if a data source where a certain table is located needs to be subjected to operations such as hardware upgrading and the like, the random range of the random algorithm is directly removed from the data source, the database upgrading is carried out without shutdown, the table splitting can be finished, the usability of the database is greatly improved, the performance of the database is ensured, and the loss caused by shutdown upgrading is greatly reduced.
The invention is further described below with reference to the accompanying drawings and specific embodiments.
Drawings
FIG. 1 is a flowchart of a table-splitting method according to an embodiment of the present invention;
fig. 2 is a flowchart of obtaining a table ID number according to an embodiment of the present invention;
fig. 3 is a block diagram of a table-splitting system according to an embodiment of the present invention;
fig. 4 is a block diagram of a table ID obtaining unit according to an embodiment of the present invention;
fig. 5 is a table splitting diagram according to an embodiment of the present invention.
Detailed Description
In order to more fully understand the technical content of the present invention, the technical solution of the present invention will be further described and illustrated with reference to the following specific embodiments, but not limited thereto.
As shown in the specific embodiments of fig. 1 to 5, the table splitting method provided in this embodiment can be applied to a table splitting process of a database, so that the table splitting can be completed, the availability of the database is greatly improved, the performance of the database is ensured, and the loss caused by shutdown upgrading is greatly reduced.
As shown in fig. 1, the present embodiment provides a table-dividing method, which includes:
s1, acquiring the ID number of the user;
s2, carrying out dimension splitting and random splitting according to the ID number to obtain a form ID number;
further, the step of obtaining the form ID number by performing dimension splitting and random splitting according to the ID number includes the following specific steps:
s21, acquiring the last two digits of the user ID number;
s22, performing random operation according to the last two digits of the user ID number to obtain a random number; s23, combining the last two digits of the user ID number with a random number to form a new number;
s24, acquiring two digits in the new digits to form a form ID number;
and S3, storing the user data in the table of the table ID number.
For the above step S1, obtaining the ID number of the user can make the data corresponding to the user have an identity, which is convenient for invoking the data and storing the data.
The step S21 is a basis for data splitting according to user dimensions.
For the above step S22, specifically to perform random splitting, a random algorithm dimension is added on the basis of the dimension of the previous splitting.
The above-mentioned steps S23 and S24 are performed by processing the random number and the dimension-divided number to form the ID number of the table. For the step S23, combining the last two digits of the user ID number with the random number to form a new number, specifically combining the last two digits of the user ID number before and the random number after to form a new number; for the above step S24, the step of obtaining two digits of the new digits to form the table ID number includes obtaining the first digit and the last digit of the new digits to form the table ID number.
The dimension splitting and the random number splitting are combined to obtain the form ID number, when one sub-library fails, the sub-library can be kicked off by a random number splitting algorithm (manually or automatically), the running water is uniformly distributed on other available sub-libraries, and in the worst case, only one sub-library is available and can also guarantee the availability ratio, so that the availability ratio of the database can be guaranteed to the maximum extent, and if a physical library is newly added, the table ID number can be easily added.
The ID of user 1 is Uid 1234567890, and the last 2-digit number 90 is taken; and performing random algorithm again to obtain 1, finally combining to obtain 901, taking the front and back 2 digits of 901, and using 91 as the ID number of the table, namely inserting the current payment information of the user 1 into the table T _ PAY _ 91. The ID of the user 1 is a user with a Uid of 1234567890, the last 2 digits 90 are taken, a random algorithm is performed again to obtain 2, finally, the combination is performed to obtain 902, the front and rear 2 digits of 902 are taken, and 92 is the ID number of the table, that is, the payment information of the user 1 is inserted into T _ PAY _ 92. That is, the data of the user with the Uid of 1234567890 may fall on T _ PAY _9X, which is obtained by the random algorithm. Similarly, the user data of the Uid 1234567891 may fall on T _ PAY _9X, where X is obtained by the random algorithm.
The deployment of the database is 10 logical data sources. The 10 tables of T _ PAY _00, T _ PAY _10 … T _ PAY _90 are in a group and are positioned on a DB _0 database; the 10 tables of T _ PAY _01, T _ PAY _11 … T _ PAY _91 are in a group and are positioned on a DB _1 database; and so on as shown in fig. 5.
From the perspective of a single user, the payment information will be evenly distributed on 10 logical data sources, that is, when the payment information of an individual user will be evenly hashed on DB _0 to DB _9, this is a logical data source (database). The 10 logical data sources are deployed on 10 independent physical machines, and when one data source (database) fails, the database can be kicked out by a database partitioning algorithm, so that the flow is uniformly distributed on other available databases. For example, if the data source DB _0 fails, the random algorithm is changed from the previous 0-9 range random access number to 1-9, 0 is removed, and all data are hashed in DB 1-DB 9; if DB1, DB2 fails, then the random algorithm will be random within the range of 0, 3, 4, 5, 6, 7, 8, 9, eliminating 1 and 2, the data will not fall into DB1, DB2, and will be randomly distributed in the other 8 sub-banks, if worst case, only DB9 is available, and the other 9 banks are down, then the random algorithm will return 9 each time, and all data will fall into DB 9. From the data hashing perspective, the best case is that the user data is hashed on 100 tables; in the worst case, the user data is hashed on 10 tables of a single data source. In the worst case, only one sub-database is available, the availability can be ensured, and the performance is improved by 10 times compared with that of a single table, so that the availability and the high performance of the database can be greatly ensured; conversely, if a bank has been restored, the random number for that bank is incremented, as long as modifications are made to the random algorithm.
In another embodiment, after the step of storing the user data in the table of the table ID number in the step of S3, the method further includes the following steps:
sending a query or modification request;
acquiring a form ID according to the request;
and opening a corresponding table according to the table ID, and carrying out corresponding query or modification.
According to the table splitting method, the tables are split in a mode of combining random splitting and dimension splitting, the usability of the database can be greatly improved, when one table is unavailable, the table can be removed through a random algorithm, data in the table are uniformly distributed into other tables, if a data source where a certain table is located needs to be subjected to operations such as hardware upgrading and the like, the random range of the random algorithm is directly removed from the data source, the database upgrading is carried out without stopping, the table splitting can be completed, the usability of the database is greatly improved, the performance of the database is guaranteed, and the loss caused by stopping upgrading is greatly reduced.
As shown in fig. 3, the present embodiment also provides a table-splitting system, which includes a user ID obtaining unit 1, a table ID obtaining unit 2, and a storage unit 3.
A user ID acquisition unit 1 for acquiring the ID number of the user. The data corresponding to the user can have the identity, and the data is convenient to call and store.
And the form ID acquisition unit 2 is used for carrying out dimension splitting and random splitting according to the ID number to acquire the form ID number.
Further, the table ID obtaining unit 2 includes a first obtaining module 21, a random number obtaining module 22, a new number forming module 23, and a second obtaining module 24, wherein,
a first obtaining module 21, configured to obtain the last two digits of the user ID number. Belonging to the basis of data splitting according to user dimensions.
And the random number acquisition module 22 is configured to perform random operation according to the last two digits of the user ID number to acquire a random number. Specifically, in order to perform random splitting, a random algorithm dimension is added on the basis of the previous splitting dimension.
A new number forming module 23, configured to combine the last two digits of the user ID number with a random number to form a new number.
And a second obtaining module 24, configured to obtain two digits of the new digits to form a table ID number.
And a storage unit 3 for storing user data in the table of the table ID numbers.
The new number forming module 23 and the second obtaining module 24 process the random number and the dimension-divided number to form the ID number of the table. For the new number forming module 23, combining is specifically performed according to the sequence that the last two digits of the user ID number are before and the random number is after to form a new number; for the second obtaining module 24, the first digit and the last digit in the new digits are obtained to form the table ID number.
Dimension split and random number split are combined together, form ID number is obtained, when one sub-bank fails, the sub-bank can be kicked off by the random number split algorithm, the flow is uniformly distributed on other available sub-banks, and in the worst case, only one sub-bank is available, and the availability ratio can be ensured, so that the availability ratio of the database can be greatly ensured, and if a physical bank is newly added, the addition can be easily carried out.
The ID of user 1 is Uid 1234567890, and the last 2-digit number 90 is taken; and performing random algorithm again to obtain 1, finally combining to obtain 901, taking the front and back 2 digits of 901, and using 91 as the ID number of the table, namely inserting the current payment information of the user 1 into the table T _ PAY _ 91. The ID of the user 2 is a user with a Uid of 1234567890, the last 2 digits of 90 are taken, a random algorithm is performed again to obtain 2, finally, 902 is obtained by combination, 2 digits before and after 902 are taken, 92 is an ID number of a table, that is, the payment information of the user 2 is inserted into T _ PAY _ 92. That is, the data of the user with the Uid of 1234567890 may fall on T _ PAY _9X, which is obtained by the random algorithm. Similarly, the user data of the Uid 1234567891 may fall on T _ PAY _9X, where X is obtained by the random algorithm.
The deployment of the database is 10 logical data sources. The 10 tables of T _ PAY _00, T _ PAY _10 … T _ PAY _90 are in a group and are positioned on a DB _0 database; the 10 tables of T _ PAY _01, T _ PAY _11 … T _ PAY _91 are in a group and are positioned on a DB _1 database; and so on as shown in fig. 5.
From the perspective of a single user, the payment information will be evenly distributed on 10 logical data sources, that is, when the payment information of an individual user will be evenly hashed on DB _0 to DB _9, this is a logical data source (database). The 10 logical data sources are deployed on 10 independent physical machines, and when one data source (database) fails, the database can be kicked out by a database partitioning algorithm, so that the flow is uniformly distributed on other available databases. For example, if the data source DB _0 fails, the random algorithm is changed from the previous 0-9 range random access number to 1-9, 0 is removed, and all data are hashed in DB 1-DB 9; if DB1, DB2 fails, then the random algorithm will be random within the range of 0, 3, 4, 5, 6, 7, 8, 9, eliminating 1 and 2, the data will not fall into DB1, DB2, and will be randomly distributed in the other 8 sub-banks, if worst case, only DB9 is available, and the other 9 banks are down, then the random algorithm will return 9 each time, and all data will fall into DB 9. From the data hashing perspective, the best case is that the user data is hashed on 100 tables; in the worst case, the user data is hashed on 10 tables of a single data source. In the worst case, only one sub-database is available, the availability can be ensured, and the performance is improved by 10 times compared with that of a single table, so that the availability and the high performance of the database can be greatly ensured; conversely, if a bank has been restored, the random number for that bank is incremented, as long as modifications are made to the random algorithm.
In another embodiment, the system further includes a request sending unit, a request obtaining unit, and an opening unit.
And the request sending unit is used for sending the query or modification request.
And the request acquisition unit is used for acquiring the form ID according to the request.
And the opening unit is used for opening the corresponding table according to the table ID and carrying out corresponding query or modification.
According to the table splitting system, the tables are split in a random splitting and dimensionality splitting combined mode, the usability of the database can be greatly improved, when one table is unavailable, data in the table can be uniformly distributed into other tables through random algorithm elimination, if a data source where a certain table is located needs to be subjected to operations such as hardware upgrading, the random range of the random algorithm is directly eliminated from the data source, the database upgrading is carried out without stopping, the table splitting can be completed, the usability of the database is greatly improved, the performance of the database is guaranteed, and the loss caused by stopping upgrading is greatly reduced.
The technical contents of the present invention are further illustrated by the examples only for the convenience of the reader, but the embodiments of the present invention are not limited thereto, and any technical extension or re-creation based on the present invention is protected by the present invention. The protection scope of the invention is subject to the claims.
Claims (6)
1. A method of partitioning a table, the method comprising:
acquiring an ID number of a user;
carrying out dimension splitting and random splitting according to the ID number to obtain the form ID number, wherein the step of carrying out dimension splitting and random splitting according to the ID number to obtain the form ID number comprises the following steps:
acquiring the last two digits of the user ID number;
performing random operation according to the last two digits of the user ID number to obtain a random number;
combining the last two digits of the user ID number with a random number to form a new number;
acquiring two digits in the new digits to form a form ID number; storing user data in the table of table ID numbers.
2. A method according to claim 1, characterized by the step of combining the last two digits of said user ID number with a random number to form a new digit, in particular combining in the order of the last two digits of the user ID number before and the random number after to form a new digit.
3. A method according to claim 2, characterized by the step of obtaining two digits of the new digits to form the table ID number, in particular obtaining the first digit and the last digit of the new digits to form the table ID number.
4. A method according to any one of claims 1 to 3, wherein the step of storing user data in said table of table ID numbers is followed by the specific steps of:
sending a query or modification request;
acquiring a form ID according to the request;
and opening a corresponding table according to the table ID, and carrying out corresponding query or modification.
5. A table-dividing system is characterized by comprising a user ID acquisition unit, a table ID acquisition unit and a storage unit;
the user ID obtaining unit is used for obtaining the ID number of the user;
the form ID acquisition unit is used for carrying out dimension splitting and random splitting according to the ID number to acquire the form ID number, and comprises a first acquisition module, a random number acquisition module, a new digital formation module and a second acquisition module,
the first acquisition module is used for acquiring the last two digits of the user ID number;
the random number acquisition module is used for carrying out random operation according to the last two digits of the user ID number to acquire a random number;
the new number forming module is used for combining the last two digits of the user ID number with a random number to form a new number;
the second acquisition module is used for acquiring two digits in the new digits to form a table ID number;
the storage unit is used for storing the user data in the table of the table ID number.
6. The system according to claim 5, further comprising a request sending unit, a request obtaining unit and an opening unit;
the request sending unit is used for sending a query or modification request;
the request acquisition unit is used for acquiring a form ID according to the request;
and the opening unit is used for opening the corresponding table according to the table ID and carrying out corresponding query or modification.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101566986A (en) * | 2008-04-21 | 2009-10-28 | 阿里巴巴集团控股有限公司 | Method and device for processing data in online business processing |
| CN102402586A (en) * | 2011-10-24 | 2012-04-04 | 深圳华强电子交易网络有限公司 | Distributed data storage method |
| CN102930062A (en) * | 2012-11-30 | 2013-02-13 | 南京富士通南大软件技术有限公司 | Rapid horizontal extending method for databases |
| CN103942209A (en) * | 2013-01-18 | 2014-07-23 | 阿里巴巴集团控股有限公司 | Data processing method |
| CN106202524A (en) * | 2016-07-22 | 2016-12-07 | 努比亚技术有限公司 | Data base and point meter apparatus and method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020073270A1 (en) * | 2000-12-07 | 2002-06-13 | Benson William E. | Headerless split sector format for optical disk drives |
-
2017
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101566986A (en) * | 2008-04-21 | 2009-10-28 | 阿里巴巴集团控股有限公司 | Method and device for processing data in online business processing |
| CN102402586A (en) * | 2011-10-24 | 2012-04-04 | 深圳华强电子交易网络有限公司 | Distributed data storage method |
| CN102930062A (en) * | 2012-11-30 | 2013-02-13 | 南京富士通南大软件技术有限公司 | Rapid horizontal extending method for databases |
| CN103942209A (en) * | 2013-01-18 | 2014-07-23 | 阿里巴巴集团控股有限公司 | Data processing method |
| CN106202524A (en) * | 2016-07-22 | 2016-12-07 | 努比亚技术有限公司 | Data base and point meter apparatus and method |
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