CN115203246A - A joint table query method, device, electronic device and storage medium - Google Patents

Abstract

The invention discloses a method, device, electronic device and storage medium for querying a linked table, comprising: constructing a mapping tree matching the driving table according to the mapping relationship between each index value and field value in the driving table; Each index value in the mapping tree corresponds to at least one field value; obtain the driven table corresponding to the driving table, traverse each field value in the driven table, and compare each field value in the driven table with the value of each field in the driven table. The field values in the mapping tree are compared; according to the comparison result, the target field value and the target index value are determined in the driven table, and the linked table query result is determined according to the target index value. The technical solutions of the embodiments of the present invention can reduce the number of times of traversal and comparison of data in the process of joint table query, and improve the efficiency of joint table query.

Description

A joint table query method, device, electronic device and storage medium

technical field

The present invention relates to the field of computer technology, and in particular, to a method, device, electronic device and storage medium for querying a linked table.

Background technique

With the development of computer technology, most business systems will involve the query of the joint table, and the execution efficiency of the query method of the joint table is very important for the response performance of the business system.

In the prior art, join table query methods mainly include Simple Nested-Loops Join (SNLJ) algorithm, Index Nested-Loops Join (INLJ) algorithm, and block-based nesting Loop join (Block Nested-Loops Join, BNLJ) algorithm. Because the SNLJ algorithm is too violent and the number of visits is too many, the SNLJ algorithm is not often used in the prior art. At present, the BNLJ algorithm and the INLJ algorithm are commonly used.

Among them, the BNLJ algorithm is mainly used in the case where the join field of the driven table does not have an index. For most business systems, there is usually an index when performing a join table query, so the INLJ algorithm is the most commonly used in business systems. Table query method. However, the INLJ algorithm is only good at dealing with join fields with a high repetition rate. For scenarios with a low repetition rate of join fields, the INLJ algorithm will degenerate into the BNLJ algorithm, resulting in lower query efficiency for join tables.

SUMMARY OF THE INVENTION

The invention provides a joint table query method, device, electronic equipment and storage medium, which can reduce the number of times of traversing and comparison of data in the joint table query process and improve the joint table query efficiency.

According to an aspect of the present invention, a method for querying a joint table is provided, comprising:

According to the mapping relationship between each index value and field value in the driving table, a mapping tree matching the driving table is constructed; each index value in the mapping tree corresponds to at least one field value;

Acquire the driven table corresponding to the driven table, traverse each field value in the driven table, and compare each field value in the driven table with the field value in the mapping tree;

According to the comparison result, a target field value and a target index value are determined in the driven table, and a linked table query result is determined according to the target index value.

Optionally, after building the mapping tree matching the drive table, the method further includes:

storing the mapping tree in a preset mapping buffer;

The comparison of each field value in the driven table with the field value in the mapping tree includes:

Compare each field value in the driven table with the field value in the mapping buffer area.

Optionally, according to the comparison result, determine the target field value and the target index value in the driven table, including:

Determine whether the driven table has the same field value as the mapping tree;

If so, take the field value as the target field value, and take the index value corresponding to the target field value in the driven table as the target index value.

Optionally, determining the query result of the join table according to the target index value, including:

Determine whether the target index value is consistent with the index value corresponding to the target field value on the mapping tree;

If so, obtain the associated data of the target index value in the driven table, and use the associated data as the query result of the linked table.

Optionally, the index value is a primary key value corresponding to each field value in the driver table.

According to another aspect of the present invention, a joint table query device is provided, the device comprising:

a mapping tree building module, configured to construct a mapping tree matching the driving table according to the mapping relationship between each index value and the field value in the driving table; each index value in the mapping tree corresponds to at least one field value;

The traversal module is used to obtain the driven table corresponding to the driven table, traverse each field value in the driven table, and compare each field value in the driven table with the field value in the mapping tree ;

The result determination module is configured to determine the target field value and the target index value in the driven table according to the comparison result, and determine the linked table query result according to the target index value.

Optionally, the mapping tree building module includes:

a mapping tree storage unit for storing the mapping tree in a preset mapping buffer area;

The traversal module includes:

The comparison unit is used for comparing each field value in the driven table with the field value in the mapping buffer area.

Optionally, the result determination module includes:

a field value judgment unit for judging whether the driven table has the same field value as the mapping tree;

The target field value determination unit is used for taking the field value as the target field value when the driven table has the same field value as the mapping tree, and taking the index value corresponding to the target field value in the driven table as the target field value target index value.

According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform any of the embodiments of the present invention. Link table query method.

According to another aspect of the present invention, a computer-readable storage medium is provided, where computer instructions are stored in the computer-readable storage medium, and the computer instructions are used to cause a processor to implement any of the embodiments of the present invention when executed. The join table query method.

According to the technical solution provided by the embodiment of the present invention, a mapping tree matching the driving table is constructed according to the mapping relationship between each index value and field value in the driving table, and the driven table corresponding to the driving table is obtained, and the corresponding driving table is obtained. Each field value in the driven table is traversed, and each field value in the driven table is compared with the field value in the mapping tree, and according to the comparison result, the target field value and the target field value are determined in the driven table. The technical means of determining the query result of the linked table according to the target index value can reduce the number of times of traversal and comparison of data in the process of the linked table query, and improve the efficiency of the linked table query.

It should be understood that the content described in this section is not intended to identify key or critical features of the embodiments of the invention, nor is it intended to limit the scope of the invention. Other features of the present invention will become readily understood from the following description.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 is a flowchart of a method for querying a linked table according to an embodiment of the present invention;

2 is a flowchart of another method for querying a linked table provided according to an embodiment of the present invention;

3 is a flowchart of another method for querying a linked table provided according to an embodiment of the present invention;

4 is a schematic structural diagram of a joint table query device provided according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an electronic device implementing the method for querying a linked table according to an embodiment of the present invention.

Detailed ways

In order to make those skilled in the art better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only Embodiments are part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having" and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

FIG. 1 is a flowchart of a method for querying a linked table according to Embodiment 1 of the present invention. This embodiment can be applied to the case of querying target data in multiple data tables associated with a business system, and the method can be queried by a linked table. The combined table query device can be implemented in the form of hardware and/or software, and the combined table query device can be configured in an electronic device (such as a terminal or a server) with a data processing function. As shown in Figure 1, the method includes:

Step 110: Build a mapping tree matching the driving table according to the mapping relationship between each index value and field value in the driving table; each index value in the mapping tree corresponds to at least one field value.

In this embodiment, the driving table is usually a data table with a small amount of data in the database, which may be a data table that is preferentially read during the execution of a Structured Query Language (SQL) statement. An index can be a data structure in a database that is specially used to help users query data quickly. Specifically, the index may be a directory of the data table. Before searching for data in the data table, the user may first search the index position in the directory, so as to quickly locate the query data.

In this step, the mapping relationship between each index value in the driver table and the corresponding field value can be obtained. Wherein, the field may be a join query field between the driving table and the driven table. The driven table is usually a data table with a large amount of data in the database, which may be a data table that is read later during the execution of the SQL statement.

After acquiring the mapping relationship between each index value and field value in the drive table, a mapping tree can be constructed according to the mapping relationship. Specifically, when the index value in the driver table has the unique constraint, each index value can correspond to one field value; when the index value does not have the unique constraint, each index value can correspond to multiple field values.

Step 120: Acquire a driven table corresponding to the driven table, traverse each field value in the driven table, and compare each field value in the driven table with the field value in the mapping tree.

Step 130: Determine a target field value and a target index value in the driven table according to the comparison result, and determine a linked table query result according to the target index value.

In this step, it can be judged whether the driven table has the same field value as the mapping tree, if so, the field value can be used as the target field value, and the index value corresponding to the target field value in the driven table can be used as The target index value is obtained, and the associated data of the target index value is obtained in the driven table, and the associated data is used as the query result of the linked table.

In the prior art, most of the business systems will involve query of linked tables. Taking the financial business system as an example, a large number of query fields may be involved in the joint table query process, such as the applicant's application information, credit information, and debt information. In this case, blindly adding query fields will affect the write performance of the database; deleting the old index, changing to a joint index, etc. will affect the existing business. Therefore, the existing BNLJ algorithm and INLJ algorithm can not meet the actual query requirements of join tables.

In this embodiment, by building a mapping tree between indexes and fields, the number of data traversals and comparisons can be reduced, and the query efficiency of join tables can be improved; The actual query requirements of the joint table, improve the applicability of the joint table query method.

According to the technical solution provided by the embodiment of the present invention, a mapping tree matching the driving table is constructed according to the mapping relationship between each index value and field value in the driving table, and the driven table corresponding to the driving table is obtained, and the corresponding driving table is obtained. Each field value in the driven table is traversed, and each field value in the driven table is compared with the field value in the mapping tree, and according to the comparison result, the target field value and the target field value are determined in the driven table. The technical means of determining the query result of the linked table according to the target index value can reduce the number of times of traversal and comparison of data in the process of the linked table query, and improve the efficiency of the linked table query.

FIG. 2 is a flowchart of a method for querying a joint table according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above-mentioned embodiment. As shown in Figure 2, the method includes:

Step 210: Build a mapping tree matching the driving table according to the mapping relationship between each index value and the field value in the driving table.

In one implementation of this embodiment, the index value is the primary key value ID corresponding to each field value in the drive table. Specifically, assuming that the field is "name", the mapping relationship between different IDs in the driver table and the "name" value can be obtained, and a mapping tree can be constructed according to the mapping relationship.

Step 220: Store the mapping tree in a preset mapping buffer.

In this step, the map tree may be stored in a map buffer (map_buffer) based on a buffer mechanism.

Step 230: Acquire a driven table corresponding to the driving table, and traverse each field value in the driven table.

Step 240: Compare each field value in the driven table with the field value in the mapping buffer area.

The advantage of this setting is that by storing the map tree in the map_buffer, the records in the driver table can be cached, reducing the number of traversals of the data in the driver table, and optimizing the join query method.

Step 250: Determine a target field value and a target index value in the driven table according to the comparison result, and determine a linked table query result according to the target index value.

According to the technical solution provided by the embodiments of the present invention, a mapping tree matching the driving table is constructed according to the mapping relationship between each index value and field value in the driving table, and the mapping tree is stored in a preset mapping buffer area. , obtain the driven table corresponding to the driven table, traverse each field value in the driven table, and compare each field value in the driven table with the field value in the mapping buffer area , according to the comparison result, determine the target field value and the target index value in the driven table, and determine the technical means of the query result of the linked table according to the target index value, which can reduce the number of times of traversing and comparison of data in the query process of the linked table The number of times to improve the query efficiency of the joint table.

FIG. 3 is a flowchart of a joint table query method provided in Embodiment 3 of the present invention, and this embodiment is a further refinement of the above-mentioned embodiment. As shown in Figure 3, the method includes:

Step 310: Build a mapping tree matching the driving table according to the mapping relationship between each index value and the field value in the driving table.

Step 320: Acquire a driven table corresponding to the driven table, traverse each field value in the driven table, and compare each field value in the driven table with the field value in the mapping tree.

Step 330: Determine whether the driven table has the same field value as the mapping tree, if yes, go to step 340, if not, go to step 370.

Step 340: Use the field value as the target field value, and use the index value corresponding to the target field value in the driven table as the target index value.

Step 350: Determine whether the target index value is consistent with the index value corresponding to the target field value on the mapping tree, if so, go to step 360, if not, go to step 370.

Step 360: Acquire the associated data of the target index value in the driven table, and use the associated data as the query result of the linked table.

Step 370: End the query process of the joint table.

In a specific implementation, it is assumed that in the specific business of join query, there are data table a (data volume of about 10 million) and data table b (data volume of about 100,000), ID is the clustered index of the data in the organization table, name is the join query field between data table a and data table b. Since the data volume of data table a is much larger than that of data table b, data table b can be used as a driving table, and data table a can be used as a driven table.

During the join query process, the driver table b can be traversed row by row, and a mapping tree can be constructed according to the mapping relationship between different IDs and name values in the driver table b, and then the mapping tree is stored in the map_buffer. The row traverses the driven table a, and judges whether each name value in the driven table a is consistent with the name value in the driving table b. If they are consistent, compare whether the ID of the name value in the driven table a is the same as the one in the mapping tree. The IDs are consistent. If they are consistent, the associated data corresponding to the ID is obtained in the driven table a, and the associated data is used as the result of the associated table.

In the prior art, taking the above data table as an example, when using the INLJ algorithm to perform a joint table query, it is necessary to traverse the driving table b first, read each row of data, and then traverse the driven table a in turn, and the number of traversals is 100,000 * 10 million. . When using the BNLJ algorithm for join table query, it is necessary to traverse the driving table b row by row, and store the data of each row in the join_buffer in blocks, and the data in the join_buffer is out of order, so when traversing the driven table a, each row The data needs to be compared 100,000 times, the total number of traversals is 10,000,000 times, and the number of comparisons is 10 million * 100,000 (ie, 100 million) times.

In this embodiment, compared with the prior art, by constructing a mapping tree, the number of traversal times can be 10,000,000, and the number of comparisons is less than 100 million times, thereby improving the query efficiency of join tables; Second, by double-comparing the field with the index, the accuracy of the query result of the join table can be improved.

According to the technical solution provided by the embodiment of the present invention, a mapping tree matching the driving table is constructed according to the mapping relationship between each index value and field value in the driving table, and the driven table corresponding to the driving table is obtained, and the corresponding driving table is obtained. Each field value in the driven table is traversed, and each field value in the driven table is compared with the field value in the mapping tree to determine whether the driven table has the same field value as the mapping tree, If so, take the field value as the target field value, and take the index value corresponding to the target field value in the driven table as the target index value, and judge whether the target index value is the index corresponding to the target field value on the mapping tree If the values are consistent, if so, obtain the associated data of the target index value in the driven table, and use the associated data as a technical means for the query result of the associated table, which can reduce the number of times of traversal and comparison of data in the process of querying the associated table. , to improve the query efficiency of the joint table.

FIG. 4 is a schematic structural diagram of a joint table query device according to Embodiment 4 of the present invention. As shown in FIG. 4 , the device includes: a mapping tree construction module 410 , a traversal module 420 and a result determination module 430 .

Wherein, the mapping tree construction module 410 is configured to construct a mapping tree matching the driving table according to the mapping relationship between each index value and field value in the driving table; each index value in the mapping tree corresponds to at least one field value;

The traversal module 420 is configured to obtain the driven table corresponding to the driven table, traverse each field value in the driven table, and compare each field value in the driven table with the field value in the mapping tree. Compare;

The result determination module 430 is configured to determine a target field value and a target index value in the driven table according to the comparison result, and determine a linked table query result according to the target index value.

According to the technical solution provided by the embodiment of the present invention, a mapping tree matching the driving table is constructed according to the mapping relationship between each index value and field value in the driving table, and the driven table corresponding to the driving table is obtained, and the corresponding driving table is obtained. Each field value in the driven table is traversed, and each field value in the driven table is compared with the field value in the mapping tree, and according to the comparison result, the target field value and the target field value are determined in the driven table. The technical means of determining the query result of the linked table according to the target index value can reduce the number of times of traversal and comparison of data in the process of the linked table query, and improve the efficiency of the linked table query.

Based on the above embodiment, the index value is the primary key value corresponding to each field value in the drive table.

The mapping tree building module 410 includes:

The mapping tree storage unit is used for storing the mapping tree in a preset mapping buffer area.

The traversal module 420 includes:

The comparison unit is used for comparing each field value in the driven table with the field value in the mapping buffer area.

The result determination module 430 includes:

a field value judgment unit for judging whether the driven table has the same field value as the mapping tree;

The target field value determination unit is used for taking the field value as the target field value when the driven table has the same field value as the mapping tree, and taking the index value corresponding to the target field value in the driven table as the target field value target index value;

an index value judgment unit for judging whether the target index value is consistent with the index value corresponding to the target field value on the mapping tree;

The associated data obtaining unit is configured to obtain the associated data of the target index value in the driven table, and use the associated data as the query result of the associated table.

The above-mentioned apparatus can execute the methods provided by all the foregoing embodiments of the present invention, and has corresponding functional modules and beneficial effects for executing the above-mentioned methods. For technical details not described in detail in the embodiments of the present invention, reference may be made to the methods provided by all the foregoing embodiments of the present invention.

FIG. 5 shows a schematic structural diagram of an electronic device 10 that can be used to implement embodiments of the present invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (eg, helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are by way of example only, and are not intended to limit implementations of the inventions described and/or claimed herein.

As shown in FIG. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a read only memory (ROM) 12, a random access memory (RAM) 13, etc., connected in communication with the at least one processor 11, wherein the memory stores There is a computer program executable by at least one processor, and the processor 11 can be executed according to a computer program stored in a read only memory (ROM) 12 or loaded from a storage unit 18 into a random access memory (RAM) 13. Various appropriate actions and processes are performed. In the RAM 13, various programs and data necessary for the operation of the electronic device 10 can also be stored. The processor 11 , the ROM 12 and the RAM 13 are connected to each other through a bus 14 . An input/output (I/O) interface 15 is also connected to the bus 14 .

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc. etc.; and a communication unit 19, such as a network card, modem, wireless communication transceiver, and the like. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.

The processor 11 may be various general and/or special purpose processing components having processing and computing capabilities. Some examples of processors 11 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various specialized artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the linked table query method.

In some embodiments, the linked table query method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18 . In some embodiments, part or all of the computer program may be loaded and/or installed on the electronic device 10 via the ROM 12 and/or the communication unit 19 . When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the linked table lookup method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the linked table lookup method by any other suitable means (eg, by means of firmware).

Various implementations of the systems and techniques described herein above may be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips system (SOC), load programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpretable on a programmable system including at least one programmable processor that The processor, which may be a special purpose or general-purpose programmable processor, may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device an output device.

Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/operations specified in the flowcharts and/or block diagrams to be carried out. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in connection with the instruction execution system, apparatus or device. Computer-readable storage media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), fiber optics, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having a display device (eg, a CRT (cathode ray tube) or an LCD (liquid crystal display)) for displaying information to the user monitor); and a keyboard and pointing device (eg, a mouse or trackball) through which a user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback); and can be in any form (including acoustic input, voice input, or tactile input) to receive input from the user.

The systems and techniques described herein may be implemented on a computing system that includes back-end components (eg, as a data server), or a computing system that includes middleware components (eg, an application server), or a computing system that includes front-end components (eg, a user computer having a graphical user interface or web browser through which a user may interact with implementations of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system may be interconnected by any form or medium of digital data communication (eg, a communication network). Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the Internet.

A computing system can include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or a cloud host. It is a host product in the cloud computing service system to solve the traditional physical host and VPS services, which are difficult to manage and weak in business scalability. defect.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, the steps described in the present invention can be performed in parallel, sequentially or in different orders, and as long as the desired results of the technical solutions of the present invention can be achieved, no limitation is imposed herein.

The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. A method for performing a link lookup, comprising:

constructing a mapping tree matched with a driving table according to the mapping relation between each index value and each field value in the driving table; each index value in the mapping tree corresponds to at least one field value;

acquiring a driven table corresponding to the driving table, traversing each field value in the driven table, and comparing each field value in the driven table with a field value in a mapping tree;

and according to the comparison result, determining a target field value and a target index value in the driven table, and determining an associative table query result according to the target index value.

2. The method of claim 1, after constructing the mapping tree matching the driving table, further comprising:

storing the mapping tree into a preset mapping cache region;

comparing each field value in the driven table with the field values in the mapping tree, including:

each field value in the driven table is compared with the field value in the mapping cache region.

3. The method of claim 1, wherein determining a target field value and a target index value in the driven table based on the comparison comprises:

judging whether the field value identical to the mapping tree exists in the driven table or not;

and if so, taking the field value as a target field value, and taking an index value corresponding to the target field value in the driven table as a target index value.

4. The method of claim 1, wherein determining a joint table query result from the target index value comprises:

judging whether the target index value is consistent with an index value corresponding to a target field value on a mapping tree or not;

and if so, acquiring the associated data of the target index value in the driven table, and taking the associated data as an associated table query result.

5. The method of claim 1, wherein the index value is a primary key value corresponding to each field value in a driving table.

6. A link lookup apparatus, comprising:

the mapping tree construction module is used for constructing a mapping tree matched with the driving table according to the mapping relation between each index value and the field value in the driving table; each index value in the mapping tree corresponds to at least one field value;

the traversal module is used for acquiring a driven table corresponding to the driving table, traversing each field value in the driven table, and comparing each field value in the driven table with a field value in a mapping tree;

and the result determining module is used for determining a target field value and a target index value in the driven table according to the comparison result, and determining an associated table query result according to the target index value.

7. The apparatus of claim 6, wherein the map tree construction module comprises:

the mapping tree storage unit is used for storing the mapping tree into a preset mapping cache region;

the traversal module comprises:

and the comparison unit is used for comparing each field value in the driven table with the field value in the mapping cache region.

8. The apparatus of claim 6, wherein the result determination module comprises:

a field value judging unit for judging whether a field value identical to a mapping tree exists in the driven table;

and the target field value determining unit is used for taking the field value as a target field value and taking an index value corresponding to the target field value in the driven table as a target index value when the field value identical to the mapping tree exists in the driven table.

9. An electronic device, characterized in that the electronic device comprises:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the associative table lookup method of any one of claims 1-5.

10. A computer-readable storage medium storing computer instructions for causing a processor to perform the associative table lookup method according to any one of claims 1 to 5 when executed.

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