CN111523000A - Method, device, equipment and storage medium for importing data - Google Patents

Abstract

The present application discloses a method, apparatus, device and storage medium for importing data, and relates to the field of knowledge graphs. The specific implementation scheme is: obtaining at least one target node and a directed edge between at least one target node; obtaining the original identification information and internal identification information of at least one target node; determining the target import sequence of each directed edge; The original identification information of the two connected target nodes and the target import sequence are sequentially imported into the internal identification information of at least one target node. The method performs data import according to the target import sequence, which improves the efficiency of data import.

Description

Method, apparatus, device and storage medium for importing data

technical field

The embodiments of the present application relate to the field of computer technologies, and further relate to the field of knowledge graphs, and in particular, to a method, apparatus, device, and storage medium for importing data.

Background technique

Graph databases support databases that store and query data in a graph-like data structure. In a graph database, all data is usually stored in the form of nodes and edges.

Data import performance is an important performance indicator for evaluating graph databases. When the amount of data reaches a certain level, the limitation of system resources such as memory and disk will affect the data import performance, which in turn will affect the query performance of the graph database.

SUMMARY OF THE INVENTION

A method, apparatus, device, and storage medium for importing data are provided.

According to a first aspect, a method for importing data is provided, the method comprising: acquiring at least one target node and a directed edge between the at least one target node; acquiring original identification information and internal identification information of the at least one target node ; Determine the target import sequence of each directed edge; and sequentially import the internal identification information of at least one target node according to the original identification information of the two target nodes connected by the directed edge and the target import sequence.

According to a second aspect, there is provided an apparatus for importing data, the apparatus comprising: a first obtaining unit configured to obtain at least one target node and a directed edge between the at least one target node; a second obtaining unit, is configured to obtain the original identification information and internal identification information of at least one target node; the determination unit is configured to determine the target import order of each directed edge; the import unit is configured to be configured according to the two target nodes connected by the directed edge. The original identification information and the target import sequence are sequentially imported into the internal identification information of at least one target node.

According to a third aspect, an electronic device is provided, the electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor. The at least one processor executes to enable the at least one processor to perform the method as described in the first aspect.

According to a fourth aspect, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method as described in the first aspect.

The technology according to the present application solves the problem that the existing data import method occupies a large amount of disk, resulting in low import efficiency, realizes data import according to the target import sequence, and improves the efficiency of data import.

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 application, nor is it intended to limit the scope of the application. Other features of the present application will become readily understood from the following description.

Description of drawings

The accompanying drawings are used for better understanding of the present solution, and do not constitute a limitation to the present application. in:

FIG. 1 is an exemplary system architecture diagram to which an embodiment of the present application may be applied;

Figure 2 is a flowchart of one embodiment of a method for importing data according to the present application;

3 is a schematic diagram of a directed edge between at least one target node and at least one target node in the embodiment shown in FIG. 2;

4 is a schematic diagram of an application scenario of the method for importing data according to the present application;

Figure 5 is a flowchart of yet another embodiment of a method for importing data according to the present application;

6 is a schematic structural diagram of an embodiment of an apparatus for importing data according to the present application;

FIG. 7 is a schematic structural diagram of an electronic device suitable for implementing the embodiments of the present application.

Detailed ways

Exemplary embodiments of the present application are described below with reference to the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.

FIG. 1 shows an exemplary architecture 100 to which the method for importing data or the apparatus for importing data of the present application may be applied.

As shown in FIG. 1 , the system architecture 100 may include a server 101 , a network 102 , a source database server 103 and a target database server 104 . The network 102 is a medium used to provide a communication link between the server 101 and the source database server 103 and the target database server 104 . The network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The source database server 103 may deploy the source database, which may be a database server that provides data support to the server 101 . The source database can be a storage device, which can store at least one target node and a directed edge between at least one target node, the target node can represent the target entity, and the directed edge can represent the association relationship between the target entities. The server 101 can obtain at least one target node and a directed edge between the at least one target node from the source database server 103 through the network 102 .

The server 101 may sequentially import the internal identification information of at least one target node according to the original identification information of the two target nodes connected by the directed edge.

The target database server 104 may deploy the target database. The server 101 may store the internal identification information of the two target nodes connected by the directed edge and the directed edge in the target database through the network 102 . The target database can be a graph database, and the server 101 can also generate a knowledge graph according to the data stored in the graph database.

It should be noted that the method for importing data provided by the embodiments of the present application is generally executed by the server 101 , and correspondingly, the apparatus for importing data is generally set in the server 101 .

It should be understood that the numbers of servers, networks, source database servers, and target database servers in FIG. 1 are merely illustrative. There can be any number of servers, networks, source database servers, and target database servers, depending on the implementation needs.

With continued reference to FIG. 2, a flow 200 of one embodiment of a method for importing data according to the present application is shown. The method for importing data includes the following steps:

Step 201: Obtain at least one target node and a directed edge between at least one target node.

In this embodiment, the execution body of the above-mentioned method for importing data (for example, the server 101 shown in FIG. 1 ) may obtain a directed edge between at least one target node and the above-mentioned at least one target node from a graph database. Here, target nodes can be used to represent target entities, such as people, animals, objects, places, etc., and directed edges can be used to represent associations between target entities. It can be understood that the target node and the directed edges between the target nodes may be the target graph database to be imported in the source database (for example, the source database deployed by the source database server 103 shown in FIG. 1 ) (for example, as shown in FIG. 1 ). data in the target database deployed by the target database server 104).

Step 202: Acquire original identification information and internal identification information of at least one target node.

In this embodiment, the above-mentioned execution body may acquire the original identification information and internal identification information of at least one target node from the identification mapping relationship of at least one target node. Here, the original identification information may be the identification information of the target entity corresponding to the target node when it is stored in the source database. The internal identification information may be the identification information of the target entity when it is stored in the target database. The internal identification information may be fixed-length identification information for the convenience of subsequent inquiries, such as digital identifications 1, 2, 3, and 4. The internal identification may be pre-generated by the execution body, or may be generated by other electronic devices according to the original identification information of each target node. The internal identification information of each target node may have a certain relationship, for example, each internal identification information may form an increasing sequence.

Step 203: Determine the target import sequence of each directed edge.

In this embodiment, the above-mentioned execution body may determine the import sequence of each directed edge in various ways. For example, randomize each directed edge to determine the target import order of each directed edge. When importing data, the above-mentioned execution body needs to read the data to be imported into the memory first, and then write the data into the target database from the memory. It is understandable that when the memory capacity is limited and multiple directed edges need to be imported, different import orders may bring different memory read costs. Therefore, in this embodiment, the target import sequence needs to be determined.

In some optional implementation manners of this implementation, the above step 203 can be specifically implemented by the following steps: determining the number of directed edges connected to each target node; Directed edges connected by target nodes, determine at least one target node and the import order of directed edges.

In this optional implementation manner, the above-mentioned execution body may first determine the number of directed edges connected to each target node, and then, according to the number of directed edges connected to each target node, perform the task for each target node in descending order. Arrangement is performed, and then according to the arrangement order of each target node, the directed edges connected to each target node are sequentially arranged, and the import sequence of each directed edge is determined.

FIG. 3 is a schematic diagram of a directed edge between at least one target node and at least one target node in the embodiment shown in FIG. 2 . In Figure 3, the target nodes can be T1, T2, T3, T4, the directed edge L1 connects the target nodes T1, T2, the directed edge L2 connects the target nodes T1, T4, and the directed edge L3 connects the target nodes T1, T3, The directed edge L4 connects the target nodes T3 and T4, then the number of directed edges connected to the target node T1 is 3 (directed edges L1, L2, L3), and the number of directed edges connected to the target node T2 is The number is 1 (directed edge L1), the number of directed edges connected to the target node T3 is 2 (directed edges L3, L4), and the number of directed edges connected to the target node T4 is 2 ( directed edges L2, L4), then the order of each target node is T1, T3, T4, T2, or T1, T4, T3, T2, and the import order of each directed edge is L1, L2, L3, L4, or L2, L1, L3, L4, or L3, L1, L2, L4, etc.

The target import sequence determined by this implementation method can preferentially import target nodes with more associations when importing data, and does not need to read memory frequently when importing these target nodes, thereby improving the efficiency of data importing.

Step 204: Import the internal identification information of at least one target node in sequence according to the original identification information of the two target nodes connected by the directed edge and the target import sequence.

In this embodiment, the above-mentioned execution body may determine the corresponding directed edges according to the original identification information of the two target nodes connected by the directed edges, and then sequentially load the directed edges according to the finally determined target import sequence. The original identification information of the two connected target nodes is replaced with the internal identification information.

In some optional implementations of the present implementation, the above method may further include the following steps not shown in FIG. 2 : according to the entity types of the two target nodes connected by each directional edge, for the at least one target node and each Directed edges are stored.

In this optional implementation manner, the above-mentioned execution body may first determine the entity type of at least one target node, and then store the directed edge according to the entity types of the two target nodes connected by the directed edge. For example, the entity type of the target node T1 connected by the directed edge L1 is human, the entity type of the target node T2 is book, the entity type of the target node T1 connected by the directed edge L2 is human, and the entity type of the target node T3 is animal, then the above execution The main body can first load the original identification information and internal identification information of the target node T1 and the original identification information and internal identification information of T2 into the memory, and import the directed edge L1. The original identification information and internal identification information of the node T3 are loaded into the memory, and the directed edge L2 is imported.

In some existing data import methods, the mapping relationship between the identifiers of all nodes to be imported needs to be stored in the memory of the execution body. When the number of nodes to be imported is large, it is easy to cause insufficient memory, and external storage is required. The read performance of external storage is much lower than that of memory, which causes the execution subject to spend more time reading nodes. There are also some existing data import methods, which save each node to be imported and the edges between each node in the disk, and perform mixed sorting according to the identifier. As a result, the execution body relies heavily on the read and write performance of the disk and the sorting performance of the main memory. When the number of nodes to be imported is large, the import efficiency will also be reduced.

Through this implementation, each target node and directed edges are stored by type. When importing data, it is only necessary to load the identity mapping relationship of the two target nodes corresponding to the two types of entity types into the memory. After the import is completed, the identity mapping relationship corresponding to the new entity type is loaded into the memory. Therefore, it is not necessary to load the identification mapping relationship of all target nodes into the memory, so that the data import can be completed under the condition of limited memory and no external storage.

Continuing to refer to FIG. 4 , FIG. 4 is a schematic diagram of an application scenario of the method for importing data according to the present application. In the application scenario of FIG. 4 , the above-mentioned execution body 401 can obtain at least one target node (T1, T2, T3, T4) and at least one directed edge (L1, L2, L3) between the target nodes sent by the source database server 402 , L4), and the mapping relationship between the original identification information (T1, T2, T3, T4) of the target node and the internal identification information (1, 2, 3, 4) (T1 corresponds to 1, T2 corresponds to 2, T3 corresponds to 3 , T4 corresponds to 4). 403 represents two target nodes connected by each directed edge. The above-mentioned execution body 401 determines the target import sequence 404 of each directed edge, and then sequentially imports the internal identification information of at least one target node according to the target import sequence 404 . 405 is the import result of the data.

The method for importing data provided by the above-mentioned embodiments of the present disclosure includes acquiring at least one target node, a directed edge between at least one target node, and the original identification information and internal identification information of at least one target node, and then determining each target node. The target import sequence of the directed edge, and finally, according to the original identification information of the two target nodes connected by the directed edge and the target import sequence, the internal identification information of at least one target node is sequentially imported. The method performs data import according to the target import sequence, which improves the efficiency of data import.

Continuing to refer to FIG. 5, a flow 500 of yet another embodiment of a method for importing data according to the present application is shown. The method for importing data includes the following steps:

Step 501: Obtain at least one target node and a directed edge between at least one target node.

Step 502: Acquire original identification information and internal identification information of at least one target node.

The above steps 501 and 502 are respectively consistent with the steps 201 and 202 in the foregoing embodiments. The above descriptions of the steps 201 and 202 are also applicable to the steps 501 and 502, and are not repeated here.

Step 503: Perform full sorting on each directed edge to determine the candidate import sequence.

In this embodiment, the above-mentioned execution body may perform full sorting on directed edges to determine the import sequence of candidates. For example, if the directed edges are L1, L2, L3, the candidate import order can be L1, L2, L3, L1, L3, L2, L2, L1, L3, L2, L3, L3, L3, L1, L2, L3, L2, L1.

Step 504: Determine the memory read cost corresponding to each candidate import sequence.

In this embodiment, the above-mentioned execution body may determine the memory read cost corresponding to each candidate import sequence. Here, the memory read cost can refer to the time value of occupying memory, or the amount of memory used.

In some optional implementation manners of this implementation, the memory read cost corresponding to each candidate import sequence may also be determined by the following steps: take the two target nodes connected by each directed edge as the node corresponding to the directed edge Set; for each candidate import order, determine the memory read cost corresponding to each candidate import order according to the difference set of the node sets corresponding to two adjacent directed edges in the candidate import order.

In this optional implementation manner, the above-mentioned execution body may take the two target nodes connected by each directed edge as the node set corresponding to the directed edge, and then determine the corresponding nodes corresponding to two adjacent directed edges in the candidate import sequence. The difference set of the node set, and then based on the difference set of the node sets corresponding to two adjacent directed edges, the memory read cost corresponding to the candidate import order is determined.

For example, the candidate import sequence is L1, L2, L3, L4, the node set corresponding to the directed edge L1 is (T1, T2), the node set corresponding to the directed edge L1 is (T2, T3), and the node set corresponding to the directed edge L1 is (T2, T3). The difference set of the node sets corresponding to the adjacent directed edge L2 is (T1, T3). The above execution body can preset the calculation formula of the memory read cost corresponding to the import order of each directed edge:

Among them, n represents the number of node sets corresponding to the directed edge, W represents the memory read cost, and W1 represents the memory read cost corresponding to the first directed edge in the candidate import sequence (usually 2M, M represents a target node corresponding to The average memory read cost of ), E _i represents the node set corresponding to the directed edge i, and |E _i+1 -E _i | represents the absolute value of the number of target nodes in the difference set.

In this implementation manner, the memory read cost corresponding to each candidate import sequence can be quickly determined based on the above-mentioned calculation formula of the memory read cost.

Step 505: Determine the target import sequence from the candidate import sequences according to the memory read cost.

In this embodiment, after determining the memory read cost corresponding to each candidate import order, the execution body can determine the target import order. For example, the above-mentioned execution body may use the candidate import order with the lowest memory read cost as the target import order. Alternatively, the execution body may use the candidate import order whose memory read cost is less than the preset threshold as the target import order.

Step 506: Import the internal identification information of at least one target node in sequence according to the original identification information of the two target nodes connected by the directed edge and the target import sequence.

The foregoing step 506 is respectively consistent with the step 204 in the foregoing embodiment, and the above description of the step 204 is also applicable to the step 506, and details are not repeated here.

The flowchart 500 of the method for importing data in this embodiment illustrates another method for determining the target import order of each directed edge. By determining the corresponding memory read cost of each candidate import order, select the memory read The candidate import sequence with the lowest price is replaced as the target import sequence, which improves the efficiency of data import.

Referring further to FIG. 6 , as an implementation of the methods shown in the above figures, the present application provides an embodiment of an apparatus for importing data. The apparatus embodiment corresponds to the method embodiment shown in FIG. 2 . Can be applied to various electronic devices.

As shown in FIG. 6 , the apparatus 600 for importing data provided in this embodiment includes a first acquiring unit 601 , a second acquiring unit 602 , a determining unit 603 , and an importing unit 604 . Wherein, the first obtaining unit 601 is configured to obtain at least one target node and a directed edge between at least one target node; the second obtaining unit 602 is configured to obtain the original identification information and internal identification information of at least one target node Determining unit 603 is configured to determine the target import sequence of each directed edge; Import unit 604 is configured to import at least one target node successively according to the original identification information of the two target nodes connected by directed edges and the target import sequence internal identification information.

In this embodiment, in the apparatus 600 for importing data: the specific processing of the first acquiring unit 601, the second acquiring unit 602, the determining unit 603 and the importing unit 604 and the technical effects brought by them can be referred to FIG. 2 respectively. Corresponding descriptions of step 201, step 202, step 203, and step 204 in the embodiment are not repeated here.

In some optional implementations of this embodiment, the second obtaining unit 602 is further configured to determine the target import sequence of each directed edge through the following modules: a first determining module, configured to determine the target nodes connected to each target node. The number of directed edges; the second determining module is configured to determine the import sequence of each directed edge according to the number of directed edges connected to each target node and the directed edges connected to each target node.

In some optional implementations of this embodiment, the second obtaining unit 602 is further configured to determine the target import sequence of each directional edge through the following modules: a third determining module, configured to perform a full operation on each directional edge. Sorting, to determine the candidate import order; the fourth determination module, configured to determine the memory read cost corresponding to each candidate import order; the fifth determination module, configured to determine from the candidate import order according to the memory read cost Target import order.

In some optional implementations of this embodiment, the fourth determining module is further configured to: take the two target nodes connected by each directed edge as the node set corresponding to the directed edge; for each candidate import sequence , according to the difference set of the node sets corresponding to two adjacent directed edges in the candidate import sequence, determine the memory read cost corresponding to each candidate import sequence.

In some optional implementations of this embodiment, the apparatus further includes: a storage unit (not shown in the figure), configured to store at least one target node according to the entity types of the two target nodes connected by each directed edge And each directed edge is stored.

In the apparatus provided by the above-mentioned embodiments of the present application, the first obtaining unit 601 obtains at least one target node and a directed edge between the at least one target node, and then the second obtaining unit 602 obtains the original identification information of the at least one target node and the For the internal identification information, the determining unit 603 determines the target import sequence of each directed edge, and the import unit 604 sequentially imports the internal identification information of at least one target node according to the original identification information and target import sequence of the two target nodes connected by the directed edge. The device can perform data importing according to the target importing sequence, which improves the efficiency of data importing.

According to the embodiments of the present application, the present application further provides an electronic device and a readable storage medium.

As shown in FIG. 7 , it is a block diagram of an electronic device for a method for importing data according to an embodiment of the present application. 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, 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 application described and/or claimed herein.

As shown in FIG. 7 , the electronic device includes: one or more processors 701 , a memory 702 , and interfaces for connecting various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or otherwise as desired. The processor may process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used with multiple memories and multiple memories, if desired. Likewise, multiple electronic devices may be connected, each providing some of the necessary operations (eg, as a server array, a group of blade servers, or a multiprocessor system). A processor 701 is taken as an example in FIG. 7 .

The memory 702 is the non-transitory computer-readable storage medium provided by the present application. Wherein, the memory stores instructions executable by at least one processor, so that the at least one processor executes the method for importing data provided by the present application. The non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to perform the method for importing data provided by the present application.

As a non-transitory computer-readable storage medium, the memory 702 can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions/modules ( For example, the first acquiring unit 601, the second acquiring unit 602, the determining unit 603, and the importing unit 604 shown in FIG. 6). The processor 701 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions and modules stored in the memory 702, that is, implementing the method for importing data in the above method embodiments.

The memory 702 may include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required for at least one function; the stored data area may store data created according to the use of the electronic device for importing the data Wait. Additionally, memory 702 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 702 may optionally include memory located remotely from processor 701 that may be connected via a network to an electronic device for importing data. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

The electronic device for the method of importing data may further include: an input device 703 and an output device 704 . The processor 701 , the memory 702 , the input device 703 and the output device 704 may be connected by a bus or in other ways, and the connection by a bus is taken as an example in FIG. 7 .

The input device 703 can receive input numerical or character information, and generate key signal input related to user settings and function control of the electronic device for importing data, such as touch screen, keypad, mouse, trackpad, touchpad, pointing stick , one or more mouse buttons, trackballs, joysticks and other input devices. Output devices 704 may include display devices, auxiliary lighting devices (eg, LEDs), haptic feedback devices (eg, vibration motors), and the like. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display, and a plasma display. In some implementations, the display device may be a touch screen.

Various implementations of the systems and techniques described herein can be implemented in digital electronic circuitry, integrated circuit systems, application specific ASICs (application specific integrated circuits), 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.

These computational programs (also referred to as programs, software, software applications, or codes) include machine instructions for programmable processors, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages calculation program. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or apparatus for providing machine instructions and/or data to a programmable processor ( For example, magnetic disks, optical disks, memories, programmable logic devices (PLDs), including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.

To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having a display device (eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user ); and a keyboard and pointing device (eg, a mouse or trackball) through which a user can provide input to the computer. 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's 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), and the Internet.

A computer 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.

According to the technical solutions of the embodiments of the present application, the efficiency of data import can be improved.

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 application can be performed in parallel, sequentially or in different orders, and as long as the desired results of the technical solutions disclosed in the present application 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 application. 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 principles of this application shall be included within the protection scope of this application.

Claims (12)

1. A method for importing data, comprising: obtaining at least one target node and a directed edge between the at least one target node; Obtain the original identification information and internal identification information of the at least one target node; determining the target import order of each of the directed edges; According to the original identification information of the two target nodes connected by the directed edge and the target import sequence, the internal identification information of the at least one target node is sequentially imported. 2. The method according to claim 1, wherein the determining the target import order of each of the directed edges comprises: Determine the number of directed edges connected to each target node; The import sequence of each directed edge is determined according to the number of directed edges connected to each target node and the directed edges connected to each target node. 3. The method according to claim 1, wherein the determining the target import order of each of the directed edges comprises: Perform full sorting on each of the directed edges to determine the candidate import sequence; determining the memory read cost corresponding to each of the candidate import sequences; The target import order is determined from the candidate import orders according to the memory read cost. 4. The method according to claim 3, wherein the determining the memory read cost corresponding to each of the candidate import sequences comprises: Taking the two target nodes connected by each directed edge as the node set corresponding to the directed edge; For each candidate import sequence, the memory read cost corresponding to each candidate import sequence is determined according to the difference set of node sets corresponding to two adjacent directed edges in the candidate import sequence. 5. The method of claim 1, wherein the method further comprises: The at least one target node and each of the directed edges are stored according to the entity types of the two target nodes connected by each of the directed edges. 6. An apparatus for importing data, comprising: a first obtaining unit, configured to obtain at least one target node and a directed edge between the at least one target node; a second acquiring unit, configured to acquire original identification information and internal identification information of the at least one target node; a determination unit configured to determine the target import order of each of the directed edges; The import unit is configured to sequentially import the internal identification information of the at least one target node according to the original identification information of the two target nodes connected by the directed edge and the target import sequence. 7. The apparatus according to claim 6, wherein the second obtaining unit is further configured to determine the target import order of each of the directed edges by the following modules: a first determining module, configured to determine the number of directed edges connected to each target node; The second determining module is configured to determine the import sequence of each directed edge according to the number of directed edges connected to each target node and the directed edges connected to each target node. 8. The apparatus according to claim 6, wherein the second obtaining unit is further configured to determine the target import order of each of the directed edges by the following modules: The third determining module is configured to fully sort each of the directed edges, and determine the candidate import sequence; a fourth determining module, configured to determine a memory read cost corresponding to each of the candidate import sequences; A fifth determining module is configured to determine the target import order from the candidate import orders according to the memory read cost. 9. The apparatus of claim 8, wherein the fourth determination module is further configured to: Taking the two target nodes connected by each directed edge as the node set corresponding to the directed edge; For each candidate import sequence, the memory read cost corresponding to each candidate import sequence is determined according to the difference set of node sets corresponding to two adjacent directed edges in the candidate import sequence. 10. The apparatus of claim 6, wherein the apparatus further comprises: The storage unit is configured to store the at least one target node and each of the directed edges according to the entity types of the two target nodes connected by each of the directed edges. 11. An electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the execution of any of claims 1-5 Methods. 12. A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to perform the method of any one of claims 1-5.

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