CN108334565A - A kind of data mixing storage organization, data store query method, terminal and medium - Google Patents
A kind of data mixing storage organization, data store query method, terminal and medium Download PDFInfo
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- CN108334565A CN108334565A CN201810036069.8A CN201810036069A CN108334565A CN 108334565 A CN108334565 A CN 108334565A CN 201810036069 A CN201810036069 A CN 201810036069A CN 108334565 A CN108334565 A CN 108334565A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- 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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
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Abstract
The invention belongs to database technical fields, and in particular to a kind of data mixing storage organization, data store query method, terminal and medium, including N number of stored copies, N number of stored copies include N1A line stored copies and N2A column stored copies；N=N1+N2；N1=N × (1 ω)；N2=N × ω；ω ∈ [0,1]；Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.The present invention is not necessarily to do the access compromise of OLTP and OLAP, and two kinds of storage organizations of line and column are organically combined together, respective advantage is given full play to；Copy is taken full advantage of, utilization rate and the flexibility of copy are improved.
Description
Technical field
The invention belongs to database technical fields, and in particular to a kind of data mixing storage organization, data store query side
Method, terminal and medium.
Background technology
Database, is widely used in various application programs, and SQL (structured query language) is that execution inquiry is most common
Language.Conventional RD BMS (Relational DBMS) does data with behavior unit and stores (as shown in Figure 1), column storage
Database does data storage (as shown in Figure 2) to arrange for unit.Line storage is suitable for OLTP (Transaction Processing) system, and
Column storage is suitable for OLAP (on-line analytical processing) system.Each has respective advantage and disadvantage, but can not unify：Line
The suitable random additions and deletions of storage, which change, looks into, but is not suitable for large-scale scanning；Column storage is very suitable for scanning on a large scale, but not
Change suitable for random additions and deletions and looks into.Traditional Enterprise IT System needs two sets of different systems:OLTP processing business；OLAP handles report
Business intelligence.Business datum, which needs to move by ETL, carries out analyzing processing in OLAP system.Data-moving and redundancy are larger.
With the rise of HTAP systems, to storage system, more stringent requirements are proposed, i.e., the same storage system is supported
The large-scale data of high speed scans, and can efficiently carry out random read-write, thus the storage scheme to improve to some extent occurs.Example
Storage scheme is mixed as Kudu, Kudu provide a ranks, is a kind of compromise of design, column is more partial in this design
Storage, the design of this compromise causes it to prove to possess good scan characteristic in test result, but random read-write performance is then
It is poor.Such as PAX, PAX are equally a kind of compromises of design, column performance and line performance can not be with pure column systems
System and line system are compared.
Big data epoch new technology continuously emerges.Using Apache Hadoop as representative, numerous NoSQL schemes are also continuous
It emerges in large numbers.These novel systems all use large-scale distributed structure to improve the processing capacity of system.That thus brings asks
Topic is exactly that the high availability of data is on the hazard, because hardware fault rate can significantly increase with the increase of number of nodes, in order to
Ensure that the reliability of data, all these systems all use more copies, i.e., all data are owned by N number of copy, are stored in
On different machine nodes.But this N number of copy all uses identical memory module, does not make full use of copy, reduces
The utilization rate of copy and flexibility.
Invention content
For the defects in the prior art, the present invention provides a kind of data mixing storage organization, data store query sides
Method, terminal and medium, the present invention are not necessarily to do the access compromise of OLTP and OLAP, organically by two kinds of storage organizations of line and column
It is combined together, gives full play to respective advantage；Copy is taken full advantage of, utilization rate and the flexibility of copy are improved.
In a first aspect, the present invention provides a kind of data mixing storage organization, including N number of stored copies, N number of storage
Copy includes N1A line stored copies and N2A column stored copies；
N=N1+N2；
N1=N × (1- ω)；
N2=N × ω；
ω ∈ [0,1]；
Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.
Second aspect, the present invention provides a kind of data store query methods, include the following steps：
S1 is biased to parameter according to the system of setting, creates the tables of data with data mixing storage organization；
S2 obtains write request data, line stored copies and column that write request data are written in tables of data is stored secondary
This；
S3 obtains read request data, judges the data type of read request data, the data type include OLTP data and
OLAP data；If OLTP data, then the line stored copies in tables of data are accessed by line storage engines, if OLAP numbers
According to, then pass through column storage engines access tables of data in column stored copies.
Preferably, the tables of data includes N number of stored copies, and N number of stored copies include N1A line storage is secondary
Sheet and N2A column stored copies；
N=N1+N2；
N1=N × (1- ω)；
N2=N × ω；
ω ∈ [0,1]；
Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.
Preferably, the S2 is specially：
SQL compilers in database obtain write request data；
The SQL compilers obtain the line stored copies and row in tables of data according to the metadata being stored in system
The locations of copies information of formula stored copies；
According to the locations of copies information, SQL actuators are write write request data by storage engines using burse mode
Enter the line stored copies and column stored copies in tables of data.
Preferably, judge that the data type of read request data is specially in S3：
The threshold value row A of difference OLTP data and OLAP data boundary is set0；
The SQL compilers are analyzed by the histogram of tables of data and obtain the line number A of read request data influence1；
If A1 is less than A0, the read request data is OLTP data, if A1 is more than A0, the read request data is
OLAP data.
The third aspect, the present invention provides a kind of terminal, including processor and the memory that is connected to the processor,
In, the memory is for storing computer program, and the computer program includes program instruction, and the processor is configured to use
In calling described program instruction, the method described in above-mentioned second aspect is executed.
Fourth aspect, the present invention provides a kind of computer readable storage medium, the computer storage media is stored with
Computer program, the computer program include program instruction, and described program instruction makes the processing when being executed by a processor
Device executes the method described in above-mentioned second aspect.
Beneficial effects of the present invention are：Access without being OLTP and OLAP is compromised, by two kinds of storage knots of line and column
Structure is organically combined together, and gives full play to respective advantage；Take full advantage of copy, improve copy utilization rate and flexibly
Property.
Description of the drawings
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described.In all the appended drawings, similar element
Or part is generally identified by similar reference numeral.In attached drawing, each element or part might not be drawn according to actual ratio.
Fig. 1 is the storage organization figure for doing data storage in the present embodiment with behavior unit；
Fig. 2 be in the present embodiment with row be unit do data storage storage organization figure；
Fig. 3 is the flow chart of data store query method in the present embodiment.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
It should be appreciated that ought use in this specification and in the appended claims, term " comprising " and "comprising" instruction
Described feature, entirety, step, operation, the presence of element and/or component, but one or more of the other feature, whole is not precluded
Body, step, operation, element, component and/or its presence or addition gathered.
It is also understood that the term used in this description of the invention is merely for the sake of the mesh for describing specific embodiment
And be not intended to limit the present invention.As description of the invention and it is used in the attached claims, unless on
Other situations are hereafter clearly indicated, otherwise " one " of singulative, "one" and "the" are intended to include plural form.
It will be further appreciated that the term "and/or" used in description of the invention and the appended claims is
Refer to any combinations and all possible combinations of one or more of associated item listed, and includes these combinations.
Embodiment one：
Embodiment one provides a kind of data mixing storage organization, including N number of stored copies, N number of stored copies packet
Include N1A line stored copies and N2A column stored copies；
N=N1+N2；
N1=N × (1- ω)；
N2=N × ω；
ω ∈ [0,1]；
Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.The value of ω is by user according to the business of oneself enterprise
Depending on conditions of demand, if business majority is partial to OLAP, ω is turned up, and column stored copies are with regard to more in such copy, pole
It could be provided as 1 in the case of end, then all copies are all column stored copies, are suitable for pure OLAP system.If business is more
Number is partial to OLTP, then ω is turned down, and line stored copies are with regard to more in such copy, if being set as 0, all copies are all
Line stored copies are suitble to deposit OLTP systems.The data mixing storage organization of the present embodiment, by two kinds of storage knots of line and column
Structure is organically combined together, and gives full play to respective advantage.
Embodiment two：
Embodiment two provides a kind of data store query method, as shown in figure 3, including the following steps：
S1 is biased to parameter according to the system of setting, creates the tables of data with data mixing storage organization；
The tables of data with data mixing storage organization includes N number of stored copies, and N number of stored copies include
N1A line stored copies and N2A column stored copies；
N=N1+N2；
N1=N × (1- ω)；
N2=N × ω；
ω ∈ [0,1]；
Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.
The value of ω by user depending on the business demand situation of oneself enterprise, for the system based on OLTP business, ω<
0.5；For the system based on OLAP business, ω>0.5.
S2 obtains write request data, line stored copies and column that write request data are written in tables of data is stored secondary
This；
This step is specially：
SQL compilers in database obtain write request data；
According to the metadata being stored in system, (metadata is stored in system metadata table to the SQL compilers
In), obtain the locations of copies information of the line stored copies and column stored copies in tables of data；
According to the locations of copies information, SQL actuators are write write request data by storage engines using burse mode
Enter the line stored copies and column stored copies in tables of data.If any 2 two copies of copy 1 and copy, copy 1 is called to store
Write request data are stored in copy 1 by the function of writing of engine, call the function of writing of 2 storage engines of copy that write request data are stored in pair
This 2.
Each storage engines return to ACK after success to SQL actuators.SQL actuators are asked in the ACK for receiving all copies
Determination is written successfully after asking, and otherwise reports an error, and executes undo operations.
S3 obtains read request data, judges the data type of read request data, the data type include OLTP data and
OLAP data；If OLTP data, then the line stored copies in tables of data are accessed by line storage engines, if OLAP numbers
According to, then pass through column storage engines access tables of data in column stored copies.
Wherein, judge that the data type of read request data is specially in S3：
The threshold value row A of difference OLTP data and OLAP data boundary is set0；
The SQL compilers (SQL optimizers) obtain the row of read request data influence by the histogram of tables of data, analysis
Number A1；
Histogram describes distribution situation of the data inside a table, in total how many row, the row of different numberical ranges
The information such as number distribution.It therefore, can be in conjunction in histogram according to its filter condition when the analysis of SQL optimizers gives SQL statement
Distributed data, and estimate and substantially need to access how many row data.For example given SQL conditions are to access table T1, WHERE condition to be
c1>10.Optimizer is known that T1 tables one share 1,000,000 row data by histogram, and eligible c1>10 line number is 50
Wan Hang, therefore the line number accessed needed for given SQL query can be calculated.
In the present embodiment, if A1 is less than A0, the read request data is OLTP data, if A1 is more than A0, the reading
Request data is OLAP data.Threshold value row A is such as set0For 10000 rows, show that the line number that read request data influences is when analyzing
9800 rows, then read request data is OLTP data, then the line stored copies in tables of data are accessed by line storage engines；When
Analysis show that the line number that read request data influences is 11000 rows, then accessing the column in tables of data by column storage engines deposits
Store up copy.
Citing：There is different business in client, for Table A, needs to execute a large amount of short inquiry, belong to OLTP industry
Business；For table B and C, needs to execute a large amount of scan operation, belong to OLAP business.
If total number of copies is 3, when creating Table A, it is 0.3 to specify w, then bottom establishes two line copies and a column
Copy.When running the inquiry about business A, two line copies can be made full use of to execute quick random access.
If total number of copies is 3, table B and C are being created, it is 0.7 to specify w, then establishes two column copies and a row respectively
Formula copy.When running the inquiry about table B and C, then two column copies can be utilized to carry out efficient large-scale scanning behaviour
Make.
In conclusion in a database, by having line storage and the data mixing of column storage to store simultaneously
Structure, the OLTP performances and OLAP performances that can have been obtained；And take full advantage of copy, improve copy utilization rate and flexibly
Property.
Embodiment three：The present invention provides a kind of terminal, including processor and the memory that is connected to the processor,
In, the memory is for storing computer program, and the computer program includes program instruction, and the processor is configured to use
In calling described program instruction, the method described in embodiment two is executed.
It should be appreciated that in the present embodiment, alleged processor can be central processing unit (Central Processing
Unit, CPU), which can also be other general processors, digital signal processor (Digital Signal
Processor, DSP), it is application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), existing
At programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete
Door or transistor logic, discrete hardware components etc..
The memory may include read-only memory and random access memory, and provide instruction and data to processor.
The a part of of memory can also include nonvolatile RAM.For example, memory can be with storage device type
Information.
Example IV：The present invention provides a kind of computer readable storage medium, the computer storage media is stored with
Computer program, the computer program include program instruction, and described program instruction makes the processing when being executed by a processor
Device executes the method described in embodiment two.
The computer readable storage medium can be the memory of terminal described in previous embodiment, such as the hard disk of terminal
Or memory.The computer readable storage medium can also be to match on the External memory equipment of the terminal, such as the terminal
Standby plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD)
Card, flash card (Flash Card) etc..Further, the computer readable storage medium can also both include the terminal
Memory also includes External memory equipment.The computer readable storage medium is for storing the computer program and described
Other programs needed for terminal and data.The computer readable storage medium can be also used for temporarily storing exported or
The data that person will export.
It is apparent to those skilled in the art that for convenience of description and succinctly, the end of foregoing description
The specific work process at end and medium, can refer to corresponding processes in the foregoing method embodiment, details are not described herein.
Technical scheme of the present invention substantially the part that contributes to existing technology or the technical solution in other words
It can completely or partially be expressed in the form of software products, which is stored in a storage medium,
It is used including some instructions so that a computer equipment (can be personal computer, server or the network equipment etc.) is held
Row all or part of the steps of the method according to each embodiment of the present invention.And storage medium above-mentioned includes：USB flash disk, mobile hard disk,
Read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic
The various media that can store program code such as dish or CD.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme should all cover in the claim of the present invention and the range of specification.
Claims (7)
1. a kind of data mixing storage organization, which is characterized in that including N number of stored copies, N number of stored copies include N1It is a
Line stored copies and N2A column stored copies；
N=N1+N2；
N1=N × (1- ω)；
N2=N × ω；
ω ∈ [0,1]；
Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.
2. a kind of data store query method is based on data mixing storage organization described in claim 1, which is characterized in that packet
Include following steps：
S1 is biased to parameter according to the system of setting, creates the tables of data with data mixing storage organization；
S2 obtains write request data, and write request data are written to line stored copies and column stored copies in tables of data；
S3 obtains read request data, judges that the data type of read request data, the data type include OLTP data and OLAP
Data；If OLTP data, then the line stored copies in tables of data are accessed by line storage engines, if OLAP data,
The column stored copies in tables of data are then accessed by column storage engines.
3. a kind of data store query method according to claim 2, which is characterized in that the tables of data includes N number of
Stored copies, N number of stored copies include N1A line stored copies and N2A column stored copies；
N=N1+N2；
N1=N × (1- ω)；
N2=N × ω；
ω ∈ [0,1]；
Wherein, N, N1、N2It is positive integer, ω is that system is biased to parameter.
4. a kind of data store query method according to claim 3, which is characterized in that the S2 is specially：
SQL compilers in database obtain write request data；
The SQL compilers according to the metadata being stored in system, deposit by the line stored copies and column that obtain in tables of data
Store up the locations of copies information of copy；
According to the locations of copies information, using burse mode number is written by storage engines in write request data by SQL actuators
According to the line stored copies and column stored copies in table.
5. a kind of data store query method according to claim 4, which is characterized in that judge read request data in S3
Data type is specially：
The threshold value row A of difference OLTP data and OLAP data boundary is set0；
The SQL compilers are analyzed by the histogram of tables of data and obtain the line number A of read request data influence1；
If A1 is less than A0, the read request data is OLTP data, if A1 is more than A0, the read request data is OLAP numbers
According to.
6. a kind of terminal, which is characterized in that including processor and the memory being connected to the processor, wherein the storage
Device is for storing computer program, and the computer program includes program instruction, and the processor is configured for described in calling
Program instruction executes such as claim 2-5 any one of them methods.
7. a kind of computer readable storage medium, which is characterized in that the computer storage media is stored with computer program, institute
It includes program instruction to state computer program, and described program instruction makes the processor execute as right is wanted when being executed by a processor
Seek 2-5 any one of them methods.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109635042A (en) * | 2018-12-07 | 2019-04-16 | 厦门铅笔头信息科技有限公司 | OLTP and the integrated auto metal halide lamp big data system of OLAP |
| CN110147372A (en) * | 2019-05-21 | 2019-08-20 | 电子科技大学 | A kind of distributed data base Intelligent Hybrid storage method towards HTAP |
| CN114356226A (en) * | 2021-12-17 | 2022-04-15 | 广州文远知行科技有限公司 | Sensor data storage method, device, equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440245A (en) * | 2013-07-15 | 2013-12-11 | 西北工业大学 | Line and column hybrid storage method of database system |
| CN105095294A (en) * | 2014-05-15 | 2015-11-25 | 中兴通讯股份有限公司 | Method and device for managing heterogeneous copy in distributed storage system |
-
2018
- 2018-01-15 CN CN201810036069.8A patent/CN108334565A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440245A (en) * | 2013-07-15 | 2013-12-11 | 西北工业大学 | Line and column hybrid storage method of database system |
| CN105095294A (en) * | 2014-05-15 | 2015-11-25 | 中兴通讯股份有限公司 | Method and device for managing heterogeneous copy in distributed storage system |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109635042A (en) * | 2018-12-07 | 2019-04-16 | 厦门铅笔头信息科技有限公司 | OLTP and the integrated auto metal halide lamp big data system of OLAP |
| CN109635042B (en) * | 2018-12-07 | 2022-06-14 | 厦门铅笔头信息科技有限公司 | OLTP and OLAP integrated automobile financial big data system |
| CN110147372A (en) * | 2019-05-21 | 2019-08-20 | 电子科技大学 | A kind of distributed data base Intelligent Hybrid storage method towards HTAP |
| CN110147372B (en) * | 2019-05-21 | 2022-12-23 | 电子科技大学 | HTAP-oriented distributed database intelligent hybrid storage method |
| CN114356226A (en) * | 2021-12-17 | 2022-04-15 | 广州文远知行科技有限公司 | Sensor data storage method, device, equipment and storage medium |
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