WO2021179782A1

WO2021179782A1 - Method, device and apparatus for improving execution efficiency of database appliance, and medium

Info

Publication number: WO2021179782A1
Application number: PCT/CN2021/070568
Authority: WO
Inventors: 张远斌
Original assignee: 苏州浪潮智能科技有限公司
Priority date: 2020-03-13
Filing date: 2021-01-07
Publication date: 2021-09-16
Also published as: CN111400346A

Abstract

A method, device and apparatus for improving the execution efficiency of a database appliance, and a medium. The method comprises the following steps: screening out the maximum value and minimum value of stored data in each storage unit in a storage node, and storing the maximum value and the minimum value as interval end points (S301); in response to a user querying data, searching a memory of the storage node for a maximum value and minimum value interval of a corresponding storage unit where the data is located (S302); in response to failing to find the corresponding intervals in the memory, further sequentially searching for the intervals in various storage units, and further querying the data in a storage unit corresponding to the found intervals (S303); and on the basis of the number of queries, storing, in the memory, information of the storage unit, which corresponds to the found intervals, and the maximum value and minimum value interval of the stored data in the storage unit (S304). Indexes are put in the memory, thereby saving on a hard disk storage space, and improving retrieval efficiency.

Description

Method, equipment, device and medium for improving execution efficiency of database integrated machine

This application requires that it be submitted to the State Intellectual Property Office of China on March 13, 2020. The application number is 202010174055.X, and the invention title is "A method, equipment, device and medium for improving the execution efficiency of a database integrated machine". Priority, the entire content of which is incorporated in this application by reference.

Technical field

The present invention relates to the computer field, and more specifically, to a method, equipment, device and medium for improving the execution efficiency of a database integrated machine.

Background technique

Currently, all-in-one database products are widely used in various fields. While the amount of business data is increasing rapidly, customers have higher demands for performance. The existing database all-in-one technology usually adopts the mode of separation of computing and storage, but this mode itself does not reduce the computing capacity of the computing nodes; and due to the limitation of the database software mechanism, simply increasing the number of computing nodes cannot achieve the overall performance Linear increase, so a workaround is needed to allow storage nodes to cooperate and assist computing nodes to complete calculations, which will fundamentally release the computing pressure of computing nodes, thereby achieving the effect of reducing costs.

There are two existing indexing methods. One is to store nodes without indexes and compute node B-tree indexes. As shown in Figure 1, the top level of the index is the root, which includes entries pointing to the next level in the index, and the next level is the branch block. , It points to the next-level block in the next level of the index. The bottom level is the leaf node, which contains index entries that point to the table row. The leaf block is bidirectionally associated, and the key value is scanned in ascending or descending order. Index; the second is the storage node has no index, and the node bitmap index is calculated. As shown in Figure 2, the bitmap index can also be organized in the form of B-tree, but the leaf node will store the bitmap of each key value, not the row ID (identification) list. Each bit in the bitmap corresponds to a possible row ID. If this bit is set, it means that the row with the corresponding row ID contains the key value.

The problems of the above two indexes: all known indexes are built on the computing nodes, and the computing pressure of the computing nodes is not shared; creating and maintaining indexes require time costs, and this cost increases as the amount of data increases; creating indexes And maintaining indexes requires space costs. Each index occupies the physical storage space of the database. The larger the amount of data, the larger the occupied space (the data table occupies the data space of the database); it will reduce the efficiency of adding, deleting, and modifying tables. Because the index needs to be dynamically maintained each time the index is added, deleted, and changed, the time becomes longer.

Summary of the invention

In view of this, the purpose of the embodiments of the present invention is to propose a method, equipment, device and medium for improving the execution efficiency of a database all-in-one machine, establish an invented intelligent index on a storage node, and assist the computing node SQL (Structured Query Language, structure) through the intelligent index Query language) processing, reduce the computing load of the computing node, and improve the overall performance of the all-in-one machine.

Based on the foregoing objectives, one aspect of the embodiments of the present invention provides a method for improving the execution efficiency of a database integrated machine, which includes the following steps:

Filter out the maximum value and minimum value of the stored data in each storage unit in the storage node, and store the maximum value and minimum value as the interval endpoints;

In response to a user's data query, search the memory of the storage node for the corresponding maximum and minimum interval of the storage unit where the data is located;

In response to not finding the corresponding interval in the memory, further searching for the interval in each storage unit in turn, and further querying the data in the storage unit corresponding to the found interval;

Based on the number of queries, the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data are stored in the memory.

In some embodiments, filtering out the maximum value and minimum value of the stored data in each storage unit in the storage node, and storing the maximum value and minimum value as interval endpoints includes:

Perform hash calculation on each data in each storage unit in the storage node to filter out the maximum and minimum values after hash calculation in each storage unit, and use the maximum and minimum values as The end points of the interval are stored.

In some embodiments, in response to a user's data query, searching in the memory of the storage node for the corresponding maximum and minimum interval of the storage unit where the data is located includes:

Perform a hash calculation on the data to be queried, and search for the corresponding maximum and minimum interval in the memory of the storage node for the hashed data.

In some embodiments, the method further includes:

In response to the data update of the storage unit in the storage node, the maximum and minimum values of the stored data of the storage unit are re-screened, and the stored maximum and minimum interval is updated according to the screening result.

In some embodiments, storing the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory includes:

The information of the storage unit and the maximum and minimum interval of the stored data and the correspondence relationship between the maximum and minimum interval and the information of the storage unit are stored in the memory in the form of a hash table.

In some embodiments, storing the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries includes:

In response to not finding the corresponding interval in the memory and the storage space in the memory reaches the upper threshold value, the interval search is further performed in the storage unit, and in response to the found corresponding storage unit in the storage node The number of queries recorded in the database is greater than the number of queries of the storage unit that has the least number of queries recorded in the database among the storage units stored in the memory, and the corresponding storage unit information found and its interval are compared The value replaces the storage unit with the least number of queries stored in the memory.

In some embodiments, the method is applicable to a K-DB database all-in-one machine.

Another aspect of the embodiments of the present invention provides a device for improving the execution efficiency of a database integrated machine, including:

The data calculation module is configured to filter out the maximum value and the minimum value of the stored data in each storage unit in the storage node, and store the maximum value and the minimum value as the interval endpoints;

A memory response module, configured to, in response to a user's data query, search for the corresponding maximum and minimum interval of the storage unit where the data is located in the memory of the storage node;

The storage unit response module is configured to, in response to failing to find the corresponding interval in the memory, to further search for the interval in each storage unit in turn, and to further inquire the storage unit corresponding to the found interval data;

The memory data update module is configured to save the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries.

At least one processor; and

A memory, the memory stores a program code that can be run by the processor, and the program code implements the method as described above when the program code is run by the processor.

Another aspect of the embodiments of the present invention provides a computer medium including program code executable by a processor, and the program code implements the above-mentioned method when being executed by the processor.

The present invention has the following beneficial technical effects: a method, equipment, device, and medium for improving the execution efficiency of a database integrated machine provided by the embodiments of the present invention comprehensively improve the processing of the OLAP (Online Analytical Processing) type business of the integrated integrated machine Efficiency: Reduce the CPU (central processing unit) load of the computing node and free up computing resources; put the index in the memory to save hard disk storage space and improve retrieval efficiency; while the overall performance is improved, the overall cost is reduced.

Description of the drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other embodiments can be obtained based on these drawings without creative work.

Figure 1 is a schematic diagram of a B-tree index in the prior art;

FIG. 2 is a schematic diagram of bitmap index in the prior art;

3 is a flowchart of a method for improving the execution efficiency of a database integrated machine according to the present invention;

4 is a schematic diagram of the intelligent storage index established according to the method of the present invention in the structure of a database integrated machine;

Figure 5 is a schematic diagram of the storage indexing technology of the method of the present invention;

6 is a schematic diagram of the hardware structure of a device for improving the execution efficiency of a database integrated machine according to the present invention;

Fig. 7 is a schematic diagram of a device for improving the execution efficiency of a database integrated machine according to the present invention.

Detailed ways

The embodiments of the present invention are described below. However, it should be understood that the disclosed embodiments are merely examples, and other embodiments may take various alternative forms. The drawings are not necessarily drawn to scale; some functions may be exaggerated or minimized to show details of specific components. Therefore, the specific structural and functional details disclosed herein should not be construed as restrictive, but merely serve as a representative basis for teaching those skilled in the art to use the present invention in various ways. As those of ordinary skill in the art will understand, various features shown and described with reference to any one drawing can be combined with features shown in one or more other drawings to produce embodiments that are not explicitly shown or described. . The combinations of features shown provide representative embodiments for typical applications. However, various combinations and modifications of features consistent with the teachings of the present invention may be desirable for certain specific applications or implementations.

In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following describes the embodiments of the present invention in detail in conjunction with specific embodiments and with reference to the accompanying drawings.

Based on the foregoing objectives, one aspect of the embodiments of the present invention proposes a method for improving the execution efficiency of a database integrated machine. As shown in FIG. 3, the method includes the following steps:

Step S301: Filter out the maximum value and the minimum value of the stored data in each storage unit in the storage node, and store the maximum value and the minimum value as the interval endpoints;

Step S302: In response to the user's data query, search for the corresponding maximum and minimum interval of the storage unit where the data is located in the memory of the storage node;

Step S303: In response to not finding the corresponding interval in the memory, further searching for intervals in each storage unit in turn, and further querying the data in the storage unit corresponding to the found interval;

Step S304: Save the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries.

In some embodiments, the storage software installs several local disks on a server, which is called a storage server. The storage servers are structurally independent. One of the capacity growth will not affect the other servers. Each storage server is regarded as a whole. This mutually independent horizontal storage structure enables large-capacity expansion of data and guarantees large data volume. As shown in Figure 4, the business data is stored in the integrated database machine using data blocks as a unit (ie storage unit). The intelligent database index according to the present invention is different from the traditional B-tree index. Data blocks are arranged, the peaks and valleys after the arrangement are taken out, and then the peaks and valleys are stored in the memory of the storage node. The subsequent SQL (Structured Query Language) request first judges the required data through the intelligent index in those data blocks Then, the relevant data block is transferred from the storage node to the computing node through the network for subsequent transaction requests and access. This method not only reduces the storage space, but also improves the query efficiency.

In some embodiments, as shown in FIG. 5, the peak and valley values are taken from each storage block in the database table and stored in the memory of the storage node, which are (4, 9), (1, 6), ( 3, 7), if a SQL query statement wants to find a value of C3 column equal to 2, the database will only scan in the second interval when doing row and column filtering, and any storage interval that cannot contain matching records will be skipped However, in most cases, this will drastically reduce the amount of I/O (input/output) that needs to be performed.

In some embodiments, filtering out the maximum value and minimum value of the stored data in each storage unit in the storage node, and storing the maximum value and minimum value as the interval endpoints includes: storing each of the storage nodes A hash calculation is performed on each data in the storage unit to filter out the maximum value and the minimum value after the hash calculation in each storage unit, and the maximum value and the minimum value are stored as interval endpoints.

In some embodiments, in response to a user's data query, searching in the memory of the storage node for the corresponding maximum and minimum interval of the storage unit where the data is located includes: performing the query on the data Hash calculation, and search for the corresponding maximum and minimum interval in the memory of the storage node for the data after the hash calculation.

In some embodiments, the method further includes: in response to a data update of the storage unit in the storage node, re-screening the maximum and minimum values of the data stored in the storage unit, and updating the stored data according to the screening result. The maximum and minimum interval.

In some embodiments, storing the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory includes: storing in the memory in the form of a hash table Correspondence between the information of the storage unit and the maximum and minimum interval of the stored data, and the correspondence between the maximum and minimum interval and the information of the storage unit.

In some embodiments, storing the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries includes: in response to not searching in the memory When the corresponding interval is reached and the storage space in the memory reaches the upper threshold, the interval search is further performed in the storage unit, and the number of queries recorded in the storage node database in response to the found corresponding storage unit is greater than the number of queries recorded in the storage node database. Among the storage units stored in the memory, the number of queries of the storage unit that has the least number of queries recorded in the database, and the corresponding information of the found storage unit and its interval value are substituted for all stored in the memory. The storage unit with the least number of queries.

In some embodiments, the method is applicable to K-DB database integrated machine (K-DB database is an enterprise-level database system developed by Inspur Company).

In an embodiment according to the present invention, the computing node starts the database instance to the Open state, executes the script to generate the system table, and at the same time generates the trigger A related to the storage index, and completes the application system database construction. The storage node installs the database, and starts the storage node instance to the nomount (started instance) state; modifies the storage node configuration file, turns on the intelligent index function, and the storage node B process automatically performs hash calculation for each database Extend storage unit. Each database storage unit corresponds to an intelligent index information on the disk space. This information maintains the peak and valley values of the columns in the tables involved in this area through the hash algorithm.

When a query statement that conforms to the smart index is initiated by the application, that is, when the user initiates a data query request, K-DB will build a smart index for the table involved in the query, that is, first go to the memory for query, and in the memory When the query is not found, query in each storage unit of the database, and store the queried storage unit information and the peak and valley values of its data in the memory of the storage node. Each grid disk of K-DB (grid disk) A hash table will be established in the memory, and each hash table will have an array of storage units corresponding to it, and the information of the storage units will be placed in the array.

Where technically feasible, the technical features listed above for different embodiments can be combined with each other, or changed, added, omitted, etc., to form additional embodiments within the scope of the present invention.

It can be seen from the above-mentioned embodiments that a method for improving the execution efficiency of a database all-in-one machine provided by the embodiment of the present invention comprehensively improves the processing efficiency of the OLAP (online analytical processing) type business of the overall all-in-one machine; reduces the CPU load of the computing node and frees up computing Resources; put the index in the memory, save hard disk storage space, improve retrieval efficiency; while improving the overall performance, reduce the overall cost.

Based on the foregoing objective, another aspect of the embodiments of the present invention proposes a device for improving the execution efficiency of a database integrated machine. FIG. 7 shows a schematic diagram of a device for improving the execution efficiency of a database integrated machine according to the present invention. As shown in FIG. 7, the device 700 includes:

The data calculation module 701 is configured to filter out the maximum value and the minimum value of the stored data in each storage unit in the storage node, and store the maximum value and the minimum value as the interval endpoints;

The memory response module 702 is configured to, in response to a user's data query, search for the corresponding maximum and minimum interval of the storage unit where the data is located in the memory of the storage node;

The storage unit response module 703 is configured to, in response to not finding the corresponding interval in the memory, further search for the interval in each storage unit in turn, and further query the storage unit corresponding to the found interval. The data;

The memory data update module 704 is configured to save the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries.

In another aspect of the embodiments of the present invention, a device for improving the execution efficiency of a database integrated machine is proposed, including:

At least one processor; and

A memory, the memory stores a program code that can be run by the processor, and the program code implements the method described in any of the foregoing embodiments when the program code is run by the processor.

As shown in FIG. 6, it is a schematic diagram of the hardware structure of an embodiment of an apparatus for improving the execution efficiency of a database integrated machine provided by the present invention.

As shown in FIG. 6, the device includes a processor 601 and a memory 602, and may also include: an input device 603 and an output device 604.

The processor 601, the memory 602, the input device 603, and the output device 604 may be connected by a bus or in other ways. In FIG. 6, the connection by a bus is taken as an example.

The memory 602, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, as implemented by the integrated database integrated machine in the embodiment of the present application. The efficient method corresponds to the program instructions/modules. The processor 601 executes various functional applications and data processing of the server by running non-volatile software programs, instructions, and modules stored in the memory 602, that is, implements the method for improving the execution efficiency of the integrated database machine in the foregoing method embodiment.

The memory 602 may include a storage program area and a storage data area. The storage program area may store an operating system and an application program required by at least one function; the storage data area may store data created according to a method for improving the execution efficiency of a database integrated machine, etc. . In addition, the memory 602 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 602 may optionally include a memory remotely provided with respect to the processor 601, and these remote memories may be connected to a local module through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

The input device 603 can receive inputted numeric or character information, and generate key signal input related to user settings and function control of the computer equipment that improves the execution efficiency of the database integrated machine. The output device 604 may include a display device such as a display screen.

The program instructions/modules corresponding to the one or more methods for improving the execution efficiency of the database integrated machine are stored in the memory 602, and when executed by the processor 601, the improved database integrated machine in any of the foregoing method embodiments is executed Methods of execution efficiency.

Any embodiment of the computer device that executes the method for improving the execution efficiency of the integrated database machine can achieve the same or similar effect as any of the foregoing method embodiments corresponding to it.

Finally, it should be noted that a person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing relevant hardware through a computer program, and the program can be stored in a computer readable storage medium. When the program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, the storage medium can be a magnetic disk, an optical disc, a read-only memory (ROM) or a random access memory (RAM), etc.

In addition, typically, the devices, devices, etc. disclosed in the embodiments of the present invention may be various electronic terminal devices, such as mobile phones, personal digital assistants (PDA), tablet computers (PAD), smart TVs, etc., or large-scale terminals. Equipment, such as a server, etc., therefore, the protection scope disclosed in the embodiments of the present invention should not be limited to a specific type of equipment or equipment. The client disclosed in the embodiments of the present invention may be applied to any of the above-mentioned electronic terminal devices in the form of electronic hardware, computer software, or a combination of the two.

In addition, the method disclosed according to the embodiment of the present invention may also be implemented as a computer program executed by a CPU, and the computer program may be stored in a computer-readable storage medium. When the computer program is executed by the CPU, it executes the above-mentioned functions defined in the method disclosed in the embodiment of the present invention.

In addition, the above method steps and system units can also be implemented by a controller and a computer-readable storage medium for storing a computer program that enables the controller to implement the above steps or unit functions.

In addition, it should be understood that the computer-readable storage medium (eg, memory) described herein may be volatile memory or nonvolatile memory, or may include both volatile memory and nonvolatile memory. By way of example and not limitation, non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory Memory. Volatile memory can include random access memory (RAM), which can act as external cache memory. As an example and not limitation, RAM can be obtained in many forms, such as synchronous RAM (DRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchronous link DRAM (SLDRAM) and direct Rambus RAM (DRRAM). The storage devices of the disclosed aspects are intended to include, but are not limited to, these and other suitable types of memory.

Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. In order to clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and functions have been described in general terms. Whether this function is implemented as software or as hardware depends on the specific application and the design constraints imposed on the entire system. Those skilled in the art can implement the described functions in various ways for each specific application, but such implementation decisions should not be construed as causing a departure from the scope of the disclosure of the embodiments of the present invention.

The various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure herein can be implemented or executed using the following components designed to perform the functions described herein: general-purpose processors, digital signal processors (DSP), and dedicated Integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in combination with a DSP, and/or any other such configuration.

The steps of the method or algorithm described in combination with the disclosure herein may be directly included in hardware, a software module executed by a processor, or a combination of the two. The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM (Compact Disc Read-Only Memory, read-only optical drive), or in the field Any other known storage media. An exemplary storage medium is coupled to the processor such that the processor can read information from or write information to the storage medium. In an alternative, the storage medium may be integrated with the processor. The processor and the storage medium may reside in the ASIC. The ASIC can reside in the user terminal. In an alternative, the processor and the storage medium may reside as discrete components in the user terminal.

In one or more exemplary designs, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions can be stored as one or more instructions or codes on a computer-readable medium or transmitted through the computer-readable medium. Computer-readable media include computer storage media and communication media, including any media that facilitates the transfer of a computer program from one location to another location. A storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer. By way of example and not limitation, the computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage devices, magnetic disk storage devices or other magnetic storage devices, or may be used to carry or store instructions in the form of Or any other medium that can be accessed by a general-purpose or special-purpose computer or general-purpose or special-purpose processor. Also, any connection is properly termed a computer-readable medium. For example, if you use coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave to send software from a website, server, or other remote source, the above-mentioned coaxial cable Cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are all included in the definition of media. As used herein, magnetic disks and optical disks include compact disks (CDs), laser disks, optical disks, digital versatile disks (DVD), floppy disks, and Blu-ray disks. Disks usually reproduce data magnetically, while optical disks use lasers to optically reproduce data. . Combinations of the above content should also be included in the scope of computer-readable media.

It should be understood that as used herein, unless the context clearly supports exceptions, the singular form "a" is intended to also include the plural form. It should also be understood that "and/or" as used herein refers to any and all possible combinations including one or more items listed in association.

The serial numbers of the disclosed embodiments of the foregoing embodiments of the present invention are only for description, and do not represent the superiority or inferiority of the embodiments.

A person of ordinary skill in the art can understand that all or part of the steps in the above embodiments can be implemented by hardware, or by a program to instruct relevant hardware. The program can be stored in a computer-readable storage medium. The storage medium mentioned can be a read-only memory, a magnetic disk or an optical disk, etc.

The above-mentioned embodiments are possible examples of implementations, and are presented only for a clear understanding of the principle of the present invention. Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope of disclosure (including the claims) of the embodiments of the present invention is limited to these examples; under the idea of the embodiments of the present invention The above embodiments or the technical features in different embodiments can also be combined, and there are many other changes in different aspects of the embodiments of the present invention as described above, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.

Claims

A method for improving the execution efficiency of a database integrated machine is characterized in that it comprises the following steps:

Filter out the maximum value and minimum value of the stored data in each storage unit in the storage node, and store the maximum value and minimum value as the interval endpoints;

In response to a user's data query, search the memory of the storage node for the corresponding maximum and minimum interval of the storage unit where the data is located;

In response to not finding the corresponding interval in the memory, further searching for the interval in each storage unit in turn, and further querying the data in the storage unit corresponding to the found interval;

Based on the number of queries, the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data are stored in the memory.
The method according to claim 1, wherein the filtering out the maximum value and the minimum value of the stored data in each storage unit in the storage node, and storing the maximum value and the minimum value as the interval endpoints comprises:

Perform hash calculation on each data in each storage unit in the storage node to filter out the maximum and minimum values after hash calculation in each storage unit, and use the maximum and minimum values as The end points of the interval are stored.
The method according to claim 2, wherein, in response to a user's data query, searching the memory of the storage node for the corresponding maximum and minimum interval of the storage unit where the data is located comprises:

Perform a hash calculation on the data to be queried, and search for the corresponding maximum and minimum interval in the memory of the storage node for the hashed data.
The method according to claim 1, wherein the method further comprises:

In response to the data update of the storage unit in the storage node, re-screen the maximum and minimum values of the stored data of the storage unit, and update the stored maximum and minimum interval according to the screening result.
The method according to claim 1, wherein storing the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory comprises:

The information of the storage unit and the maximum and minimum interval of the stored data and the correspondence relationship between the maximum and minimum interval and the information of the storage unit are stored in the memory in the form of a hash table.
The method according to claim 1, wherein storing the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries comprises:

In response to not finding the corresponding interval in the memory and the storage space in the memory reaches the upper threshold value, the interval search is further performed in the storage unit, and in response to the found corresponding storage unit in the storage node The number of queries recorded in the database is greater than the number of queries of the storage unit that has the least number of queries recorded in the database among the storage units stored in the memory, and the corresponding storage unit information found and its interval are compared The value replaces the storage unit with the least number of queries stored in the memory.
The method according to claim 1, wherein the method is applicable to a K-DB database integrated machine.
A device for improving the execution efficiency of a database integrated machine, which is characterized in that it includes:

The data calculation module is configured to filter out the maximum value and the minimum value of the stored data in each storage unit in the storage node, and store the maximum value and the minimum value as the interval endpoints;

A memory response module, configured to, in response to a user's data query, search for the corresponding maximum and minimum interval of the storage unit where the data is located in the memory of the storage node;

The storage unit response module is configured to, in response to failing to find the corresponding interval in the memory, to further search for the interval in each storage unit in turn, and to further inquire the storage unit corresponding to the found interval data;

The memory data update module is configured to save the information of the storage unit corresponding to the found interval and the maximum and minimum interval of its stored data in the memory based on the number of queries.
A device for improving the execution efficiency of a database integrated machine, which is characterized in that it comprises:

At least one processor; and

A memory, the memory stores a program code that can be run by the processor, and the program code implements the method according to any one of claims 1-7 when the program code is run by the processor.
A computer medium, characterized by comprising a program code executable by a processor, the program code when being executed by the processor implements the method according to any one of claims 1-7.