CN113127475A - Data processing method, system and device - Google Patents
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
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Abstract
The invention discloses a data processing method, a system and a device, and relates to the technical field of data processing. In the data processing method, after the storage server receives the query instruction of the database server, the target table is determined in the storage server based on the query instruction, the target data block is determined from the target table, and the target database is returned to the database server. Compared with the prior art, after the target table is determined in the storage server, all data blocks of the target table are returned to the database server, and the database server searches the target data from all data blocks of the target table, the data processing method not only reduces the transmission flow between the storage server and the database server, but also enables the database server to search the target data from fewer target data blocks instead of searching the target data from a large number of data blocks, and obviously reduces the workload of the database server in processing the data.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing method, system, and apparatus.
Background
In the data processing, processing of a query statement is included. Taking the Query statement as a Structured Query Language (SQL for short), as shown in fig. 1, the input/output processing flow of the conventional SQL database includes: the SQL database server receives an SQL query instruction initiated by a client, for example: SELECT FROM T1 WHERE B < 2; the SQL database server responds to the SQL query instruction and positions the physical position of the data file where the T1 table is located; based on the physical position, initiating an operation of reading all blocks of the T1 table to a storage position where a data file corresponding to the SQL query instruction is located; in response to the operation of reading all blocks of the T1 table, the underlying storage server reads all blocks of the T1 table and transmits all data blocks of the table to the SQL database server through a link with the SQL database server; the SQL database server reads the blocks into the memory and executes the SQL query instruction to screen rows and columns which meet the conditions to obtain a query result; and the SQL database server returns the query result set to the client.
From the above, the storage server at the bottom layer sends the data of the whole T1 table to the SQL database server, and what we need is only the data meeting the limited conditions, so that each time similar statements are executed, a large amount of input and output traffic is generated between the storage server at the bottom layer and the SQL database server, and meanwhile, the amount of data to be processed by the SQL database server is greatly increased, and a large amount of resources of the SQL database server are consumed.
Disclosure of Invention
The invention provides a data processing method, a system and a device, aiming at reducing the flow between a storage server and a database server and reducing the data processing amount in the database server.
In a first aspect, the present invention provides a data processing method, where a storage server includes at least one table, where the at least one table includes target tables, and each of the tables includes at least one data block, the method including:
receiving a query instruction of a database server, wherein the query instruction carries query conditions;
searching the target table in a storage server based on the query instruction, and determining a target data block from the target table;
and returning the target data block to a database server.
In the above-mentioned data processing method,
before the searching the target table in the storage server based on the query instruction, and determining the target data block from the target table, further comprising:
storing the at least one table on a disk, cutting the table into at least one data block, and storing each data block on each storage unit of the disk;
constructing an index for each of the data blocks, the index comprising: table names, column names and maximum and minimum values of pre-stored fields in each column; and storing the index of the data block in a memory.
In the above-mentioned data processing method,
in the step of searching the target table in a storage server based on the query instruction and determining a target data block from the target table, the method includes:
based on a preset rule, searching a target index meeting the query condition in the memory, wherein the query condition comprises a target table name, a target column name and a target numerical value;
and taking the data block corresponding to the target index as a target data block.
In the above-mentioned data processing method,
in the tables, the numerical values in the columns in each table have uniqueness.
In the above-mentioned data processing method,
the searching, based on the preset rule, the target index meeting the query condition in the memory includes:
the table name in the target index is the same as the target table name;
the column names in the target index are the same as the target column names;
the value interval of the maximum value and the minimum value in the target index covers the target value.
In a second aspect, the present invention provides a data processing method, including:
sending a query instruction to a storage server, wherein the query instruction carries query conditions;
and receiving a target data block returned by the storage server in a target table, wherein the target data block in the target table meets the query condition.
In the above-mentioned data processing method,
before the sending the query instruction to the storage server, the method further includes:
receiving a query request sent by a client, wherein the query request carries query conditions;
generating a query instruction based on the query request;
after the receiving the target data block returned by the storage server in the target table, the method further includes:
and acquiring target data based on the target data block, and returning the target data to the client.
In a third aspect, the present invention provides a data processing system comprising a memory and a processor;
the memory stores a table and an index for each data block in the table;
the processor, based on the received query instruction, looks up a target data block in the memory.
In a fourth aspect, the present invention provides an apparatus comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the method as claimed in any one of the above.
In a fifth aspect, the invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method as claimed in any one of the above.
In the data processing method, after the storage server receives the query instruction of the database server, the target table is determined in the storage server based on the query instruction, the target data block is determined from the target table, and the target database is returned to the database server. Compared with the prior art, after the target table is determined in the storage server, all data blocks of the target table are returned to the database server, and the database server searches the target data from all data blocks of the target table, the data processing method not only reduces the transmission flow between the storage server and the database server, but also enables the database server to search the target data from fewer target data blocks instead of searching the target data from a large number of data blocks, and obviously reduces the workload of the database server in processing the data.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a data processing method in the prior art;
FIG. 2 is a flowchart illustrating a data processing method according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating index construction according to a first embodiment of the present invention;
FIG. 4 is a flowchart of a data processing method according to a second embodiment of the present invention;
fig. 5 is a flowchart illustrating a data processing method according to a third embodiment 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 clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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.
Example one
The execution main body in the data processing method of the embodiment of the invention is a storage server, at least one table is stored in the storage server, the at least one table comprises a target table which can be inquired by an inquiry instruction, and each table comprises at least one data block, and can be two or even three or more data blocks. Specifically, a Table (Table) is a logical unit for managing data, and each Table corresponds to one or more data files on a storage medium (e.g., a magnetic disk). In a storage medium, the basic unit of composition of a data file is a data block (block), i.e. the data file comprises one or more data blocks; the data block comprises at least one data record, and one data record is data of one row in the data block; data recording refers to a contiguous segment of bytes on a storage medium. A data block is a unit of data that is transferred between a storage server and a data block server. FIG. 2 is a flow chart of data processing in an exemplary embodiment of the invention. In the embodiment of the present invention, the data processing flow includes the following steps.
And S020, receiving a query instruction of the database server, wherein the query instruction carries a query condition. I.e., the query instruction is generated based on a query request initiated by the client to the database server. The query condition may include only the target table name, the target table name and the target column name under the target table name, or the target table name, the target column name under the target table name, and the target numerical value under the target column name. Taking the example that the query request is SELECT FROM T1 WHERE B <2, the target table name in the query condition in the correspondingly generated query instruction is T1, the target column name under the target table name is B, and the target value under the target column name is B < 2. In addition, the query instruction in the data processing in the embodiment of the invention is an SQL statement.
And S040, determining the target table in the storage server and determining the target data block from the target table based on the query instruction. A target table, such as T1 or T2, is determined in the storage server based on the target table name of the query condition in the query instruction, and a target data block is determined from the target table based on the target list name under the target table name and the target value under the target list name. For example, column B in the T1 table is divided into two data blocks, WHERE data block a stores 0 and 1, and data block B stores 2 and 3, and the target data block corresponding to SELECT FROM T1 WHERE B <2 is data block a. In the T1 table, column B is divided into two data blocks, and the two data blocks can be stored in different storage units on the disk.
Step 060, returning the target data block to the database server. And the storage server returns the database A to the database server. In the prior art, for SELECT FROM T1 WHERE B <2, all blocks in T1, i.e. the data block a and the data block B, are returned by the storage server to the database server, and the database server searches the target data FROM the data block a and the data block B. In the embodiment of the invention, the database A is returned to the data block server by the storage server, so that the time for the storage server to scan a disk is reduced, the traffic transmitted between the storage server and the data block server is reduced, and the workload of the database server for searching the target data is reduced.
Before S020, the method may further include: s016 and S018.
And S016, storing the at least one table on a disk, cutting the table into at least one data block, and storing each data block on each storage unit of the disk. The table storage and the magnetic disk of the embodiment of the invention divide the table into a plurality of data blocks, correspondingly, the magnetic disk is also divided into a plurality of storage units, and each data block is stored in each storage unit. Of course, as a variation, two or more data blocks may be stored in one storage unit.
S018, constructing an index for each data block, wherein the index comprises: table names, column names and maximum and minimum values of pre-stored fields in each column; and storing the index of the data block in a memory. In order to search for the target data block conveniently, an index is constructed for each data block, and the index comprises a table name, a column name and the maximum value and the minimum value of pre-stored fields in each column. Referring to fig. 3, the second column in the left T1 is column B, and the index corresponding to the data block includes: 1/5, wherein T1 is the table name, B is the column name, 1 is the minimum value of the pre-stored fields in column B, and 5 is the maximum value of the pre-stored fields in column B; of course, the index corresponding to the data block further includes T1 a: and X/Y, wherein X is the minimum value of the prestored fields in the A column, and Y is the maximum value of the prestored fields in the A column. Similarly, the second column in the middle T1 is column B, and the index corresponding to the data block includes: 3/8, wherein T1 is the table name, B is the column name, 3 is the minimum value of the pre-stored fields in column B, and 8 is the maximum value of the pre-stored fields in column B; similarly, the first column in the right T2 table is column E, the third column is column G, and the index corresponding to the data block includes: T1E: a, j, and T1G: 4/9. Note that the table names in the index in fig. 3 are not shown.
Correspondingly, S040 includes S041 and S042.
And S041, based on a preset rule, searching a target index meeting the query condition in the memory, wherein the query condition comprises a target table name, a target column name and a target numerical value. And searching the target index meeting the query condition from the memory according to the requirement of the query condition so as to meet a preset rule. Based on a preset rule, finding the target index meeting the query condition in the memory, specifically comprising: the table name in the target index is the same as the target table name, the column name of the target index is the same as the target column name, and the value interval of the maximum value and the minimum value in the target index covers the target value. For example, if the target table name of the query is T1, the table name in the target index is T1, if the target column name of the query is C, the column name in the target index is C, and if the target value of the query is X, the value X is covered in the interval between the maximum value and the minimum value of the target index.
Of course, as a variation, based on a preset rule, the target index meeting the query condition may be found in the memory, or the column name of the target index may not be the same as the target column name. For example: and if the column name of the target index is in the front column of the target column name, the target column name of the query condition is C column, and the column name in the target index is B column.
And S042, taking the data block corresponding to the target index as a target data block.
In the embodiment of the invention, in order to find the target database more efficiently, in each table stored on the disk, the numerical value of each column has uniqueness, that is, the numerical value of each column does not have any repeated value. Or, only a small number of repeated values.
In addition, from a performance perspective, the better the ordering of data on the disk, the faster the average access time when used. In many scenarios where the data on the disk is well ordered, this will work well, and in typical order systems there are often many keys, such as associated dates (order date, shipping date, insertion date, return date, etc.) or sequentially generated numbers similar to order numbers.
Example two
An execution subject in the data processing method according to the embodiment of the present invention is a database server, and fig. 4 is a flowchart of data processing according to an exemplary embodiment of the present invention. In the embodiment of the present invention, the data processing flow includes the following steps.
S150, sending a query instruction to the storage server, wherein the query instruction carries query conditions.
S170, receiving the target data block in the target table returned by the storage server, wherein the target data block in the target table accords with the query condition.
The database server sends a query instruction to the storage server, and the storage server returns the target data block in the target table based on the query instruction. Compared with the prior art, the storage server returns all the blocks of the target table, and the embodiment of the invention only returns the target data block of the target table, thereby reducing the input flow of the database server and reducing the resource consumption of the database server.
Before S150, S110 and S130 are also included.
S110, receiving a query request sent by a client, wherein the query request carries query conditions. The query request sent by the client may be that the query request is SELECT FROM T1 WHERE B <2, or the query request is SELECT FROM T1 WHERE a ═ 102, and so on.
S130: and generating a query instruction based on the query request. And the database server generates a corresponding query instruction based on the query request to send to the storage server.
S190, obtaining target data based on the target data block and returning the target data to the client side is further included after S170. And the database server inquires and acquires target data aiming at the target data block and returns the target data to the client.
EXAMPLE III
The third embodiment of the present invention provides a specific data processing example. As mentioned in the first embodiment, the information of the maximum value and the minimum value of the field stored in each storage unit is stored in the index.
Table T1 contains two memory cells, memory cell 1 and memory cell 2. Column B max 5, min 1 in memory cell 1, column B max 8, min 3 in memory cell 2.
For example, a client initiates the operation of Select FROM T1 WHERE B <2, for which the storage server compares the limit conditions of the operation with the information of the maximum and minimum values stored in the index and makes a simple binary logic operation (bitmap: it is well known that all information of a computer is calculated by bit bits, the binary operation is very efficient in the computer, each bit can take a value of 0 or 1, the key logic decision in the present invention increases the running rate by efficient binary calculation), and the specific operation can refer to table 1.
TABLE 1
And screening out the storage units 1 meeting the where condition from the T1 table, excluding the storage units 2 not meeting the condition, and transmitting the data information in the storage units meeting the condition back to the database server, so that redundant storage scanning operation is avoided, input and output flow between the storage and the database server is reduced, and resource consumption of the database server is saved.
The whole data processing flow is shown in fig. 5. In fig. 5, a client is located at the upper end, a database server is located below the client, and a storage server is located below the database server. Inputting a query request Select FROM T1 WHERE B <2 at a client, and issuing an SQL statement query instruction to a storage server by a database server according to the query request; the storage server determines a storage unit which meets the condition by comparing the query condition (i.e. the where condition) with the maximum value and the minimum value information in the index; taking the database on the storage unit as a target data block and returning the target data block to the database server; the database server searches the target data and returns the target data to the client so as to obtain a query result set at the client.
Example four
The embodiment of the invention provides a data processing system, a device and a computer readable storage medium.
A data processing system includes a memory and a processor. The memory stores a table and an index for each data block in the table; the processor, based on the received query instruction, looks up a target data block in the memory.
The data processing system provided in the embodiment of the present application may further execute the method executed by the data processing system in fig. 2 or fig. 4, and implement the functions of the data processing system in the embodiment shown in fig. 2 or fig. 4, which are not described herein again.
An apparatus provided in an embodiment of the present invention includes: a memory, a processor and a computer program stored on said memory and executable on said processor, the computer program realizing the steps of the above data processing method when executed by said processor.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the data processing method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A data processing method, wherein a storage server comprises at least one table, wherein the at least one table comprises target tables, and wherein each table comprises at least one data block, the method comprising:
receiving a query instruction of a database server, wherein the query instruction carries query conditions;
searching the target table in a storage server based on the query instruction, and determining a target data block from the target table;
and returning the target data block to a database server.
2. The data processing method of claim 1,
before the searching the target table in the storage server based on the query instruction, and determining the target data block from the target table, further comprising:
storing the at least one table on a disk, cutting the table into at least one data block, and storing each data block on each storage unit of the disk;
constructing an index for each of the data blocks, the index comprising: table names, column names and maximum and minimum values of pre-stored fields in each column; and storing the index of the data block in a memory.
3. The data processing method of claim 2,
in the step of searching the target table in a storage server based on the query instruction and determining a target data block from the target table, the method includes:
based on a preset rule, searching a target index meeting the query condition in the memory, wherein the query condition comprises a target table name, a target column name and a target numerical value;
and taking the data block corresponding to the target index as a target data block.
4. A data processing method as claimed in claim 2 or 3, wherein the numerical values in each of the columns in each of the tables are unique.
5. The data processing method according to claim 3, wherein the finding, based on a preset rule, the target index meeting the query condition in the memory comprises:
the table name in the target index is the same as the target table name;
the column names in the target index are the same as the target column names;
the value interval of the maximum value and the minimum value in the target index covers the target value.
6. A data processing method, comprising:
sending a query instruction to a storage server, wherein the query instruction carries query conditions;
and receiving a target data block returned by the storage server in a target table, wherein the target data block in the target table meets the query condition.
7. The data processing method of claim 6, further comprising, before the sending the query instruction to the storage server:
receiving a query request sent by a client, wherein the query request carries query conditions;
generating a query instruction based on the query request;
after the receiving the target data block returned by the storage server in the target table, the method further includes:
and acquiring target data based on the target data block, and returning the target data to the client.
8. A data processing system comprising a memory and a processor;
the memory stores a table and an index for each data block in the table;
the processor, based on the received query instruction, looks up a target data block in the memory.
9. An apparatus, comprising: memory, processor and computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, carries out the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| WO2023237120A1 (en) * | 2022-06-10 | 2023-12-14 | 华为技术有限公司 | Data processing system and apparatus |
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| CN105677903A (en) * | 2016-02-05 | 2016-06-15 | 华为技术有限公司 | Data acquisition method and device as well as computer device |
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| CN102203773A (en) * | 2008-09-19 | 2011-09-28 | 甲骨文国际公司 | Hash join using collaborative parallel filtering in intelligent storage with offloaded bloom filters |
| CN105677903A (en) * | 2016-02-05 | 2016-06-15 | 华为技术有限公司 | Data acquisition method and device as well as computer device |
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