CN114218265A

CN114218265A - Processing method and device of offline model, storage medium and processor

Info

Publication number: CN114218265A
Application number: CN202111329172.XA
Authority: CN
Inventors: 陈壮豪
Original assignee: Alibaba Singapore Holdings Pte Ltd
Current assignee: Alibaba Innovation Co
Priority date: 2021-11-10
Filing date: 2021-11-10
Publication date: 2022-03-22

Abstract

The invention discloses a processing method, a device, a storage medium and a processor of an offline model, wherein the method comprises the following steps: determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; and executing calculation by adopting the updated off-line model. The invention solves the technical problem of resource waste when the offline model is adopted for calculation due to the existence of the calculation node irrelevant to the target output node in the offline model of the relevant technology.

Description

Processing method and device of offline model, storage medium and processor

Technical Field

The invention relates to the technical field of information processing, in particular to a processing method and device of an offline model, a storage medium and a processor.

Background

In an offline big data modeling platform, the platform provides the arrangement capacity of a business model graph for a user, the model graph is a Directed Acyclic Graph (DAG) consisting of a plurality of SQL (structured query language) nodes or script nodes, and the platform can perform scheduling execution according to the model graph (DAG) arranged by the user, wherein each node corresponds to one offline computing task. Because the model is a combination of a series of computation logics built by a user according to services, each model has at least one target output node, and after the user selects a plurality of target output nodes, part of computation nodes irrelevant to the target output nodes often exist in the model, and the computation of the part of nodes causes waste of resources.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the invention provides a processing method, a processing device, a storage medium and a processor of an offline model, which are used for at least solving the technical problem of resource waste when computing is carried out by adopting the offline model due to the fact that computing nodes irrelevant to target output nodes exist in the offline model of the related technology.

According to an aspect of the embodiments of the present invention, there is provided an offline model processing method, including: determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; and executing calculation by adopting the updated off-line model.

Further, the method further comprises: if the target output nodes are a plurality of nodes, respectively searching the father node of each target output node and the father node of each target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a plurality of inquiry sub-results; and taking the plurality of query sub-results as the query result.

Further, deleting nodes in the offline model except for the nodes included in the query result, and obtaining an updated offline model includes: deleting nodes except the nodes included in the inquiry sub-results in the offline model respectively to obtain a plurality of sub-models; and combining the plurality of sub models to obtain an updated off-line model.

Further, after deleting the nodes in the offline model except the nodes included in the query result to obtain an updated offline model, the method further includes: starting from a root node of the updated offline model, judging whether a current node in the updated offline model is an SQL node or not, wherein the SQL node represents a calculation rule described by an SQL script; if the current node is an SQL node, starting merging, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list; merging the nodes in the final merged list, constructing a single-node field for the merged nodes, and taking the merged nodes for constructing the single-node field as the merged nodes in the updated offline model; if the traversed node is not the SQL node, constructing a field of a single node for the non-SQL node, and taking the non-SQL node of the field of the single node as an original node in the updated offline model; and obtaining an optimized off-line model according to the fusion node and the original node.

Further, when the nodes in the final merge list are merged, the method further includes: stopping merging the current nodes in the final merging list when the current nodes meet any preset rule, wherein the preset rule at least comprises the following steps: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

Further, before obtaining the optimized offline model according to the fusion node and the original node, the method further includes: judging whether the nodes in the updated offline model are traversed or not; and if the nodes in the updated offline model are traversed, determining that the updated offline model is optimized, and executing the step of obtaining the optimized offline model according to the fusion nodes and the original nodes.

Further, performing calculations using the updated offline model includes: and executing calculation by adopting the optimized off-line model.

According to another aspect of the embodiments of the present invention, there is also provided an apparatus for processing an offline model, including: a first determining unit, configured to determine a target output node selected by a user in an offline model, where the offline model is composed of a plurality of nodes based on offline computation, and the nodes represent a computation rule; the first searching unit is used for searching the father node of the target output node in the offline model in a one-by-one traversal mode until the found node is a root node to obtain a query result, wherein the query result comprises at least one queried node; the first processing unit is used for deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; and the calculating unit is used for executing calculation by adopting the updated offline model.

According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute any one of the processing methods of the offline model described above.

According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes a processing method of any one of the above offline models.

In the embodiment of the invention, a mode of deleting nodes irrelevant to target output nodes in an offline model is adopted, specifically, the target output nodes selected by a user are determined in the offline model, wherein the offline model consists of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; the updated offline model is adopted to execute the calculation, so that the technical effect of avoiding resource waste when the updated offline model is adopted for calculation is achieved, and the technical problem that the resource waste exists when the offline model is adopted for calculation due to the fact that the calculation nodes irrelevant to the target output node exist in the offline model of the related technology is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

fig. 1 is a block diagram of a hardware configuration of a computer terminal according to an embodiment of the present invention;

FIG. 2 is a flow chart of a method for processing an offline model according to an embodiment of the present invention;

FIG. 3 is a first schematic diagram of an offline model according to a first embodiment of the present invention;

FIG. 4 is a second schematic diagram of the offline model according to the first embodiment of the present invention;

FIG. 5 is a third schematic diagram of an offline model according to an embodiment of the present invention;

FIG. 6 is a fourth schematic diagram of the offline model according to the first embodiment of the present invention;

FIG. 7 is a fifth schematic diagram of an offline model according to an embodiment of the present invention;

FIG. 8 is a sixth schematic diagram of an offline model provided according to an embodiment of the present invention;

FIG. 9 is a seventh schematic diagram of an offline model according to an embodiment of the present invention;

FIG. 10 is an eighth schematic diagram of an offline model provided in accordance with an embodiment of the present invention;

FIG. 11 is a diagram nine of an offline model provided according to an embodiment of the present invention;

FIG. 12 is a schematic diagram of an alternative method for processing an offline model according to an embodiment of the present invention;

FIG. 13 is a schematic diagram of an apparatus for processing an offline model according to a second embodiment of the present invention;

fig. 14 is a block diagram of an alternative computer terminal according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

First, some terms or terms appearing in the description of the embodiments of the present application are applicable to the following explanations:

and (3) off-line calculation: off-line calculations are calculations performed on the premise that all input data is known before the calculation begins and no changes are made to the input data.

And (3) node: is a basic unit in the model, which represents a calculation rule, and the rule can be SQL script, SHELL script, PYTHON script, etc.

An offline node: an offline node is a node based on offline calculations.

Model: the model is a Directed Acyclic Graph (DAG) composed of a plurality of nodes, and is characterized in that: the result of the upstream node's output will be the input to the downstream node.

An off-line model: an offline model refers to a model made up of a series of offline nodes.

Example 1

In accordance with an embodiment of the present invention, there is provided an offline model processing method embodiment, it is noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.

The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Fig. 1 shows a hardware configuration block diagram of a computer terminal (or mobile device) for implementing a processing method of an offline model. As shown in fig. 1, the computer terminal 10 (or mobile device 10) may include one or more (shown as 102a, 102b, … …, 102 n) processors 102 (the processors 102 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device for communication functions. Besides, the method can also comprise the following steps: a display, an input/output interface (I/O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of the I/O interface), a network interface, a power source, and/or a camera. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the electronic device. For example, the computer terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

It should be noted that the one or more processors 102 and/or other data processing circuitry described above may be referred to generally herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part in software, hardware, firmware, or any combination thereof. Further, the data processing circuit may be a single stand-alone processing module, or incorporated in whole or in part into any of the other elements in the computer terminal 10 (or mobile device). As referred to in the embodiments of the application, the data processing circuit acts as a processor control (e.g. selection of a variable resistance termination path connected to the interface).

The memory 104 may be used to store software programs and modules of application software, such as program instructions/data storage devices corresponding to the offline model processing method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by executing the software programs and modules stored in the memory 104, that is, implementing the above-mentioned offline model processing method of the application program. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computer terminal 10 (or mobile device).

Under the above operating environment, the present application provides a processing method of the offline model as shown in fig. 2. Fig. 2 is a flowchart of a processing method of an offline model according to a first embodiment of the present invention.

And step S101, determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and each node represents a calculation rule.

For example, the offline model is shown in FIG. 3 with a target output node selected by the user in the dashed box.

Step S102, searching a father node of the target output node and a father node of the target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node.

Taking fig. 3 as an example, in fig. 3, the parent node of the target output node selected by the user and the parent node of the parent node are searched in the offline model in a one-by-one traversal manner until the searched node is the root node, and the searched node is the node shown in fig. 4.

And step S103, deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model.

Deleting the nodes in the offline model in fig. 3 except the nodes included in the query result to obtain an updated offline model, namely the model represented in fig. 4.

And step S104, calculating by adopting the updated off-line model.

Through the steps, the mode of deleting the nodes irrelevant to the target output nodes in the offline model is adopted, the technical effect of avoiding resource waste when the updated offline model is adopted for calculation is achieved, and the technical problem that the resource waste exists when the offline model is adopted for calculation due to the fact that the calculation nodes irrelevant to the target output nodes exist in the offline model of the related technology is solved.

Optionally, in the processing method of the offline model provided in the embodiment of the present application, the method further includes: if the target output nodes are a plurality of nodes, respectively searching the father node of each target output node and the father node of each target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a plurality of inquiry sub-results; and taking the plurality of query sub-results as the query result.

As shown in fig. 5, nodes in two dashed boxes in the offline model represent target output nodes selected by the user, the parent node of each target output node and the parent node of each target output node are respectively searched in a one-by-one traversal manner, and a plurality of query sub-results, such as a first query sub-result (first query _ SQL, FILTER, DATA _ SOURCE), and a second query sub-result (FILTER, JOIN, second query _ SQL, FILTER, DATA _ SOURCE, FILTER), are obtained until the searched nodes are root nodes.

For another example, as shown in fig. 6, two target output nodes selected by the user respectively search the parent node of each target output node and the parent node of each target output node in a one-by-one traversal manner until the searched nodes are root nodes, and obtain a plurality of query sub-results, for example, a first query sub-result (container _ SQL, FILTER, DATA _ SOURCE) and a second query sub-result (FILTER, DATA _ SOURCE).

Under the condition that the target output node selected by the user is a plurality of nodes, a plurality of inquiry sub-results can be accurately obtained through the scheme.

Optionally, in the method for processing an offline model provided in the embodiment of the present application, deleting nodes in the offline model except for the node included in the query result, and obtaining an updated offline model includes: deleting nodes except the nodes included in the inquiry sub-results in the offline model respectively to obtain a plurality of sub-models; and combining the plurality of sub models to obtain an updated off-line model.

For example, deleting the nodes except the query sub-result one (CUSTOM _ SQL, FILTER, DATA _ SOURCE) in FIG. 5 results in the sub-model shown in FIG. 7. Deleting the nodes except the query sub-result two (FILTER, JOIN, store _ SQL, FILTER, DATA _ SOURCE, FILTER) in fig. 5 to obtain the sub-model shown in fig. 8. And combining the sub-model shown in fig. 7 with the sub-model shown in fig. 8 to obtain an updated off-line model.

For example, the nodes except the first query sub-result (CUSTOM _ SQL, FILTER, DATA _ SOURCE) in fig. 6 are deleted, resulting in sub-model one. Deleting the nodes except the second query sub-result (FILTER, DATA _ SOURCE) in the graph 6 to obtain a second sub-model. And combining the sub-model I and the sub-model II to obtain the model shown in the figure 9, and taking the model shown in the figure 9 as the updated offline model.

Optionally, in the method for processing an offline model provided in this embodiment of the present application, after deleting nodes in the offline model except for the node included in the query result to obtain an updated offline model, the method further includes: starting from a root node of the updated offline model, judging whether a current node in the updated offline model is an SQL node or not, wherein the SQL node represents a calculation rule described by an SQL script; if the current node is an SQL node, starting merging, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list; merging the nodes in the final merged list, constructing a single-node field for the merged nodes, and taking the merged nodes for constructing the single-node field as the merged nodes in the updated offline model; if the traversed node is not the SQL node, constructing a field of a single node for the non-SQL node, and taking the non-SQL node of the field of the single node as an original node in the updated offline model; and obtaining an optimized off-line model according to the fusion node and the original node. Optionally, performing a calculation using the updated offline model includes: and executing calculation by adopting the optimized off-line model.

Based on the idea of combining all SQL nodes in the offline model into one large node to reduce the resource occupation of the computer by the execution of a plurality of single SQL tasks, in the above technical scheme, the SQL nodes in the updated offline model are combined, that is, the nodes in the offline model are partially combined to optimize the nodes in the offline model, so as to obtain the optimized offline model, thereby further reducing the resource consumption when the offline model is used for computing.

Optionally, in the processing method of the offline model provided in the embodiment of the present application, when the nodes in the final merge list are merged, the method further includes: stopping merging the current nodes in the final merging list when the current nodes meet any preset rule, wherein the preset rule at least comprises the following steps: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

The rules in the preset rules are explained as follows: if the current node is the SQL node with the out-degree greater than 1, the result of the node may be multiplexed by a plurality of downstream nodes, and therefore merging of the current node is stopped. If the child nodes of the current node include nodes with the entry degree greater than 1, the child nodes of the current node are nodes with intersection, sum and difference operations, and the computation complexity is increased when merging is possible, so that merging of the current node is stopped. If the child nodes of the current node are non-SQL nodes, for example, data synchronization nodes, API nodes, SHELL script nodes, PYTHON script nodes, etc., merging of the current node is stopped. Because the merged node has no output result, if the current node is the output node of the non-leaf node, the output node can only be used as the last node in the field, and therefore merging of the current node is stopped. If the current node is a leaf node, the current node is required to output a result, and therefore merging of the current node is stopped.

For example, as shown in fig. 10, the updated offline model merges SQL nodes in fig. 10, and based on the preset rule, the nodes in the dashed line box in the model of fig. 10 may be merged to obtain the model in fig. 11, where the nodes in the rectangular dashed line box in fig. 11 represent merged nodes and are the result of merging multiple SQL nodes. The merging mode can be used for recombining a plurality of SQL into one SQL by analyzing the SQL, and carrying out SQL optimization by means of an SQL execution engine.

By the scheme, the rule for merging the nodes in the merging list is limited, the accuracy of merging the nodes is ensured, and the accuracy of the optimized offline model is ensured.

Optionally, in the processing method of the offline model provided in the embodiment of the present application, before obtaining the optimized offline model according to the fusion node and the original node, the method further includes: judging whether the nodes in the updated offline model are traversed or not; and if the nodes in the updated offline model are traversed, determining that the updated offline model is optimized, and executing the step of obtaining the optimized offline model according to the fusion nodes and the original nodes.

According to the scheme, before the optimized offline model is obtained, traversal of each node in the updated offline model is required to be completed, after traversal is completed, the nodes in the merging list can be adopted for local merging, the nodes which cannot be merged are reserved, and the fused nodes and the original nodes are obtained, so that the optimized offline model is obtained. And the SQL nodes and the non-SQL nodes in the model are distinguished by traversing all the nodes in the model, so that the accuracy of obtaining the optimized off-line model is ensured.

Optionally, as shown in fig. 12, traversing is started at a root node of the updated offline model, and whether the traversed current node is an SQL node is determined, if so, the current node is added to a merge list, the nodes in the updated offline model are locally merged according to a preset rule based on the nodes in the merge list, after the local merging is stopped, the nodes in the merge list are merged, and a STAGE (that is, a field of a single node) is constructed for a non-SQL node in the offline model or an SQL node in the merge list that does not meet the preset rule, and whether the updated offline model is optimized is determined, and if so, the optimized offline model is obtained.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.

Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

Example 2

According to an embodiment of the present invention, there is also provided an apparatus for implementing the processing method of the offline model, as shown in fig. 13, the apparatus includes: a first determining unit 1301, a first searching unit 1302, a first processing unit 1303 and a calculating unit 1304.

A first determining unit 1301, configured to determine a target output node selected by a user in an offline model, where the offline model is composed of a plurality of nodes based on offline computation, and the nodes represent a computation rule;

a first searching unit 1302, configured to search, in a one-by-one traversal manner, a parent node of the target output node and a parent node of the target output node in the offline model until the searched node is a root node, so as to obtain a query result, where the query result includes at least one queried node;

the first processing unit 1303 is configured to delete nodes in the offline model except for the node included in the query result, so as to obtain an updated offline model;

a calculating unit 1304, configured to perform calculation by using the updated offline model.

To sum up, in the processing apparatus of the offline model provided in the embodiment of the present application, a first determining unit 1301 determines a target output node selected by a user in the offline model, where the offline model is composed of a plurality of nodes based on offline computation, and the nodes represent a computation rule; the first searching unit 1302 searches the parent node of the target output node in the offline model in a one-by-one traversal manner, and obtains a query result until the found node is a root node, where the query result includes at least one queried node; the first processing unit 1303 deletes nodes in the offline model except for the node included in the query result to obtain an updated offline model; the calculation unit 1304 performs calculations using the updated offline model. The technical effect of avoiding resource waste when the updated offline model is adopted for calculation is achieved, and the technical problem that resource waste exists when the offline model is adopted for calculation due to the fact that the calculation nodes irrelevant to the target output nodes exist in the offline model of the related technology is solved.

Optionally, in the apparatus for processing an offline model provided in the embodiment of the present application, the apparatus further includes: a second searching unit, configured to search, in the offline model, a parent node of each target output node and a parent node of the parent node of each target output node in a one-by-one traversal manner if the target output node is a plurality of nodes, until the searched node is a root node, to obtain a plurality of query sub-results; a second determining unit, configured to use the plurality of query sub-results as the query result.

Optionally, in the processing apparatus of the offline model provided in the embodiment of the present application, the processing unit includes: the first processing module is used for deleting nodes except the nodes included in the inquiry sub-result in the offline model respectively to obtain a plurality of sub-models; and the merging module is used for merging the plurality of sub models to obtain an updated off-line model.

Optionally, in the apparatus for processing an offline model provided in the embodiment of the present application, the apparatus further includes: a first judging unit, configured to, after deleting nodes in the offline model except for the nodes included in the query result to obtain an updated offline model, starting from a root node of the updated offline model, judge whether a current node in the updated offline model is an SQL node, where the SQL node represents a calculation rule described by an SQL script; the traversal unit is used for starting merging if the current node is an SQL node, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list; a merging unit, configured to merge the nodes in the final merging list, construct a single-node field for the merged nodes, and use the merged nodes that construct the single-node field as the merged nodes in the updated offline model; the construction unit is used for constructing a field of a single node for a non-SQL node if the traversed node is not the SQL node, and taking the non-SQL node of the field of the single node as an original node in the updated offline model; and the third determining unit is used for obtaining the optimized off-line model according to the fusion node and the original node.

Optionally, in the apparatus for processing an offline model provided in the embodiment of the present application, the apparatus further includes: a second processing unit, configured to stop merging the current node in the final merge list when the current node meets any preset rule while merging the nodes in the final merge list, where the preset rule at least includes: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

Optionally, in the apparatus for processing an offline model provided in the embodiment of the present application, the apparatus further includes: a second judging unit, configured to judge whether nodes in the updated offline model have been traversed before obtaining the optimized offline model according to the fusion nodes and the original nodes; and a fourth determining unit, configured to determine that the updated offline model is optimized and complete if the nodes in the updated offline model have been traversed, and execute a step of obtaining an optimized offline model according to the fusion nodes and the original nodes.

Optionally, in the processing apparatus for an offline model provided in the embodiment of the present application, the calculating unit is further configured to perform calculation by using the optimized offline model.

It should be noted here that the first determining unit 1301, the first searching unit 1302, the first processing unit 1303 and the calculating unit 1304 correspond to steps S101 to S104 in embodiment 1, and the two modules are the same as the corresponding steps in the implementation example and application scenario, but are not limited to the disclosure in the first embodiment. It should be noted that the modules described above as part of the apparatus may be run in the computer terminal 10 provided in the first embodiment.

Example 3

The embodiment of the invention can provide a computer terminal which can be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced with a terminal device such as a mobile terminal.

Optionally, in this embodiment, the computer terminal may be located in at least one network device of a plurality of network devices of a computer network.

In this embodiment, the computer terminal may execute the program code of the following steps in the processing method of the offline model of the application program: determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; and executing calculation by adopting the updated off-line model.

The computer terminal can execute the program codes of the following steps in the processing method of the off-line model of the application program: the method further comprises the following steps: if the target output nodes are a plurality of nodes, respectively searching the father node of each target output node and the father node of each target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a plurality of inquiry sub-results; and taking the plurality of query sub-results as the query result.

The computer terminal can execute the program codes of the following steps in the processing method of the off-line model of the application program: deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model, wherein the step of deleting the nodes comprises the following steps: deleting nodes except the nodes included in the inquiry sub-results in the offline model respectively to obtain a plurality of sub-models; and combining the plurality of sub models to obtain an updated off-line model.

The computer terminal can execute the program codes of the following steps in the processing method of the off-line model of the application program: after deleting the nodes in the offline model except the nodes included in the query result to obtain an updated offline model, the method further includes: starting from a root node of the updated offline model, judging whether a current node in the updated offline model is an SQL node or not, wherein the SQL node represents a calculation rule described by an SQL script; if the current node is an SQL node, starting merging, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list; merging the nodes in the final merged list, constructing a single-node field for the merged nodes, and taking the merged nodes for constructing the single-node field as the merged nodes in the updated offline model; if the traversed node is not the SQL node, then the non-SQL node is processed

Constructing a field of a single node by the node, and taking a non-SQL node of the field of the single node as an original node in the updated offline model; and obtaining an optimized off-line model according to the fusion node and the original node.

The computer terminal can execute the program codes of the following steps in the processing method of the off-line model of the application program: when the nodes in the final merged list are merged, the method further comprises: stopping merging the current nodes in the final merging list when the current nodes meet any preset rule, wherein the preset rule at least comprises the following steps: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

The computer terminal can execute the program codes of the following steps in the processing method of the off-line model of the application program: before obtaining the optimized offline model according to the fusion node and the original node, the method further includes: judging whether the nodes in the updated offline model are traversed or not; and if the nodes in the updated offline model are traversed, determining that the updated offline model is optimized, and executing the step of obtaining the optimized offline model according to the fusion nodes and the original nodes.

The computer terminal can execute the program codes of the following steps in the processing method of the off-line model of the application program: performing a calculation using the updated offline model comprises: and executing calculation by adopting the optimized off-line model.

Alternatively, fig. 14 is a block diagram of a computer terminal according to an embodiment of the present invention. As shown in fig. 14, the computer terminal may include: one or more processors (only one shown in fig. 14), memory.

The memory may be configured to store software programs and modules, such as program instructions/modules corresponding to the offline model processing method and apparatus in the embodiments of the present invention, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, implements the offline model processing method described above. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory located remotely from the processor, and these remote memories may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The processor can call the information and application program stored in the memory through the transmission device to execute the following steps: determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; and executing calculation by adopting the updated off-line model.

Optionally, the processor may further execute the program code of the following steps: the method further comprises the following steps: if the target output nodes are a plurality of nodes, respectively searching the father node of each target output node and the father node of each target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a plurality of inquiry sub-results; and taking the plurality of query sub-results as the query result.

Optionally, the processor may further execute the program code of the following steps: deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model, wherein the step of deleting the nodes comprises the following steps: deleting nodes except the nodes included in the inquiry sub-results in the offline model respectively to obtain a plurality of sub-models; and combining the plurality of sub models to obtain an updated off-line model.

Optionally, the processor may further execute the program code of the following steps: after deleting the nodes in the offline model except the nodes included in the query result to obtain an updated offline model, the method further includes: starting from a root node of the updated offline model, judging whether a current node in the updated offline model is an SQL node or not, wherein the SQL node represents a calculation rule described by an SQL script; if the current node is an SQL node, starting merging, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list; merging the nodes in the final merged list, constructing a single-node field for the merged nodes, and taking the merged nodes for constructing the single-node field as the merged nodes in the updated offline model; if the traversed node is not the SQL node, constructing a field of a single node for the non-SQL node, and taking the non-SQL node of the field of the single node as an original node in the updated offline model; and obtaining an optimized off-line model according to the fusion node and the original node.

Optionally, the processor may further execute the program code of the following steps: when the nodes in the final merged list are merged, the method further comprises: stopping merging the current nodes in the final merging list when the current nodes meet any preset rule, wherein the preset rule at least comprises the following steps: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

Optionally, the processor may further execute the program code of the following steps: before obtaining the optimized offline model according to the fusion node and the original node, the method further includes: judging whether the nodes in the updated offline model are traversed or not; and if the nodes in the updated offline model are traversed, determining that the updated offline model is optimized, and executing the step of obtaining the optimized offline model according to the fusion nodes and the original nodes.

Optionally, the processor may further execute the program code of the following steps: performing a calculation using the updated offline model comprises: and executing calculation by adopting the optimized off-line model.

The embodiment of the invention provides a scheme of an offline model processing method. Determining a target output node selected by a user in an offline model by deleting nodes irrelevant to the target output node in the offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; the updated offline model is adopted to execute the calculation, so that the technical effect of avoiding resource waste when the updated offline model is adopted for calculation is achieved, and the technical problem that the resource waste exists when the offline model is adopted for calculation due to the fact that the calculation nodes irrelevant to the target output node exist in the offline model of the related technology is solved.

It can be understood by those skilled in the art that the structure shown in fig. 14 is only an illustration, and the computer terminal may also be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palmtop computer, a Mobile Internet Device (MID), a PAD, and the like. Fig. 14 is a diagram illustrating a structure of the electronic device. For example, the computer terminal 10 may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in FIG. 14, or have a different configuration than shown in FIG. 14.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

Example 4

The embodiment of the invention also provides a storage medium. Optionally, in this embodiment, the storage medium may be configured to store a program code executed by the offline model processing method provided in the first embodiment.

Optionally, in this embodiment, the storage medium may be located in any one of computer terminals in a computer terminal group in a computer network, or in any one of mobile terminals in a mobile terminal group.

Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule; searching a father node of a target output node and a father node of the target output node in the offline model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a query result, wherein the query result comprises at least one queried node; deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model; and executing calculation by adopting the updated off-line model.

The storage medium is further configured to store program code for performing the steps of: the method further comprises the following steps: if the target output nodes are a plurality of nodes, respectively searching the father node of each target output node and the father node of each target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a plurality of inquiry sub-results; and taking the plurality of query sub-results as the query result.

The storage medium is further configured to store program code for performing the steps of: deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model, wherein the step of deleting the nodes comprises the following steps: deleting nodes except the nodes included in the inquiry sub-results in the offline model respectively to obtain a plurality of sub-models; and combining the plurality of sub models to obtain an updated off-line model.

The storage medium is further configured to store program code for performing the steps of: after deleting the nodes in the offline model except the nodes included in the query result to obtain an updated offline model, the method further includes: starting from a root node of the updated offline model, judging whether a current node in the updated offline model is an SQL node or not, wherein the SQL node represents a calculation rule described by an SQL script; if the current node is an SQL node, starting merging, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list; merging the nodes in the final merged list, constructing a single-node field for the merged nodes, and taking the merged nodes for constructing the single-node field as the merged nodes in the updated offline model; if the traversed node is not the SQL node, constructing a field of a single node for the non-SQL node, and taking the non-SQL node of the field of the single node as an original node in the updated offline model; and obtaining an optimized off-line model according to the fusion node and the original node.

The storage medium is further configured to store program code for performing the steps of: when the nodes in the final merged list are merged, the method further comprises: stopping merging the current nodes in the final merging list when the current nodes meet any preset rule, wherein the preset rule at least comprises the following steps: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

The storage medium is further configured to store program code for performing the steps of: before obtaining the optimized offline model according to the fusion node and the original node, the method further includes: judging whether the nodes in the updated offline model are traversed or not; and if the nodes in the updated offline model are traversed, determining that the updated offline model is optimized, and executing the step of obtaining the optimized offline model according to the fusion nodes and the original nodes.

The storage medium is further configured to store program code for performing the steps of: performing a calculation using the updated offline model comprises: and executing calculation by adopting the optimized off-line model.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims

1. A method for processing an offline model, comprising:

determining a target output node selected by a user in an offline model, wherein the offline model is composed of a plurality of nodes based on offline calculation, and the nodes represent a calculation rule;

searching a father node of the target output node in the offline model in a one-by-one traversal mode, wherein the father node of the target output node is obtained until the searched node is a root node, and a query result is obtained, wherein the query result comprises at least one queried node;

deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model;

and executing calculation by adopting the updated offline model.

2. The method of claim 1, further comprising:

if the target output nodes are a plurality of nodes, respectively searching the father node of each target output node and the father node of each target output node in the off-line model in a one-by-one traversal mode until the searched nodes are root nodes, and obtaining a plurality of inquiry sub-results;

and taking the plurality of query sub-results as the query result.

3. The method of claim 2, wherein deleting nodes in the offline model except for the nodes included in the query result to obtain an updated offline model comprises:

deleting nodes except the nodes included in the inquiry sub-results in the offline model respectively to obtain a plurality of sub-models;

and combining the plurality of sub models to obtain an updated off-line model.

4. The method according to claim 1, wherein after deleting nodes in the offline model except for the nodes included in the query result to obtain an updated offline model, the method further comprises:

starting from a root node of the updated offline model, judging whether a current node in the updated offline model is an SQL node or not, wherein the SQL node represents a calculation rule described by an SQL script;

if the current node is an SQL node, starting merging, adding the current node into a merging list, traversing child nodes of the current node, judging whether the child nodes are the SQL nodes or not until the traversed nodes are root nodes, and obtaining a final merging list;

merging the nodes in the final merged list, constructing a single-node field for the merged nodes, and taking the merged nodes for constructing the single-node field as the merged nodes in the updated offline model;

if the traversed node is not the SQL node, constructing a field of a single node for the non-SQL node, and taking the non-SQL node of the field of the single node as an original node in the updated offline model;

and obtaining an optimized off-line model according to the fusion node and the original node.

5. The method of claim 4, wherein when merging nodes in the final merged list, the method further comprises:

stopping merging the current nodes in the final merging list when the current nodes meet any preset rule, wherein the preset rule at least comprises the following steps: the current node is an SQL node with the out-degree greater than 1, the child nodes of the current node comprise nodes with the in-degree greater than 1, the child nodes of the current node are non-SQL nodes, the current node is an output node of a non-leaf node, and the current node is a leaf node.

6. The method of claim 4, wherein before deriving the optimized offline model from the fused node and the original node, the method further comprises:

judging whether the nodes in the updated offline model are traversed or not;

and if the nodes in the updated offline model are traversed, determining that the updated offline model is optimized, and executing the step of obtaining the optimized offline model according to the fusion nodes and the original nodes.

7. The method of claim 4, wherein performing a calculation using the updated offline model comprises: and executing calculation by adopting the optimized off-line model.

8. An apparatus for processing an offline model, comprising:

a first determining unit, configured to determine a target output node selected by a user in an offline model, where the offline model is composed of a plurality of nodes based on offline computation, and the nodes represent a computation rule;

the first searching unit is used for searching the father node of the target output node in the offline model in a one-by-one traversal mode until the found node is a root node to obtain a query result, wherein the query result comprises at least one queried node;

the first processing unit is used for deleting nodes in the offline model except the nodes included in the query result to obtain an updated offline model;

and the calculating unit is used for executing calculation by adopting the updated offline model.

9. A computer-readable storage medium, characterized in that the storage medium comprises a stored program, wherein when the program runs, the apparatus on which the storage medium is located is controlled to execute the processing method of the offline model according to any one of claims 1 to 7.

10. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the processing method of the offline model according to any one of claims 1 to 7 when running.