Method and electronic device for obtaining hierarchical data structure and processing log entries

1. A method for processing a log entry, comprising:

receiving a request for processing a target log entry;

obtaining a hierarchical data structure by:

obtaining corresponding characteristic information comprised in each log entry of a set of log entries;

determining multiple log entry patterns based on the corresponding characteristic information, wherein pattern characteristic information of each log entry pattern corresponds to the characteristic information of a subset of log entries in the set of log entries; and

storing the set of log entries according to the hierarchical data structure so that each log entry is associated with at least one of multiple nodes of the hierarchical data structure, wherein the multiple nodes respectively correspond to the multiple log entry patterns, and are hierarchically organized based on respective corresponding log entry patterns, and wherein the request comprises a first request for analyzing a first node of the multiple nodes; and

processing the target log entry based on the hierarchical data structure, wherein processing comprises:

determining a first subset of target log entries associated with the first node;

determining, based on the first subset of target log entries and using a natural language processing model, a first pattern associated with the first subset of target log entries for responding to the first request by:

combining target log entries in the first subset of target log entries to obtain a first combined log text;

determining a first characteristic representation for the first combined log text with the natural language processing model; and

determining the first pattern by using the first characteristic representation as an input to a classifier module;

wherein the first pattern comprises key information in the first subset of target log entries, and wherein the natural language processing model comprises a pre-trained neural network; and

removing, based on the first pattern, redundant information recorded in the first subset of target log entries.

2. The method according to claim 1 , wherein in the hierarchical data structure, each log entry is at least associated with a top node, and the top node is located at a top level of the hierarchical data structure.

3. The method according to claim 2 , wherein each log entry is further associated with a branch node, the branch node is located at a level lower than the top level of the hierarchical data structure, and the branch node is associated with the top node.

4. The method according to claim 1 , further comprising:

in response to receiving a to-be-stored log entry, determining first characteristic information of the to-be-stored log entry;

determining at least one target node based on the first characteristic information, wherein the pattern characteristic information corresponding to the at least one target node matches the first characteristic information; and

storing the to-be-stored log entry as being associated with the at least one target node.

5. The method according to claim 4 , wherein determining the at least one target node comprises:

determining a branch node located at a bottom level of the hierarchical data structure based on the first characteristic information, wherein the pattern characteristic information related to the determined branch node matches the first characteristic information;

determining, based on the hierarchical data structure, a top node located at a top level of the hierarchical data structure and associated with the determined branch node; and

if the first characteristic information matches the pattern characteristic information related to the top node, determining the branch node and the top node as target nodes.

6. The method according to claim 5 , further comprising:

if the first characteristic information does not match the pattern characteristic information related to the top node, storing the to-be-stored log entry in a cache;

in response to the to-be-stored log entries in the cache reaching a predetermined number, clustering the predetermined number of the to-be-stored log entries to determine additional pattern characteristic information; and

creating an additional top node in the hierarchical data structure based on the additional pattern characteristic information, wherein the additional top node corresponds to an additional log entry pattern determined based on the additional pattern characteristic information; and

determining the branch node and the additional top node as target nodes.

7. The method according to claim 1 , wherein obtaining the characteristic information comprises:

identifying a format in which the set of log entries are recorded;

determining, based on the identified format, a predetermined rule for extracting the corresponding characteristic information; and

extracting the corresponding characteristic information based on the predetermined rule.

8. The method according to claim 1 , wherein the request comprises a query request at least related to a target log entry pattern, and processing the target log entry comprises:

determining, in the multiple nodes, at least one target node which matches the target log entry pattern; and

determining, from the set of log entries, a target log entry associated with the at least one target node, for responding to the query request.

9. The method according to claim 1 , wherein the request further comprises a second request for analyzing the first pattern and a second pattern associated with the first pattern, and processing the target log entry further comprises:

combining a second subset of target log entries associated with the second pattern to obtain a second combined log text;

determining a second characteristic representation for the second combined log text with the natural language processing model; and

determining a third pattern based on the first characteristic representation and the second characteristic representation, for responding to the second request, wherein pattern characteristic information of the third pattern identifies key information in content recorded by both the first subset of target log entries and the second subset of target log entries.

10. An electronic device, comprising:

a processor; and

a memory coupled to the processor and having instructions stored therein, wherein the instructions, when executed by the processor, cause the electronic device to execute actions, and the actions comprise:

receiving a request for processing a target log entry;

obtaining a hierarchical data structure at the electronic device, wherein obtaining comprises:

obtaining corresponding characteristic information comprised in each log entry of a set of log entries;

determining multiple log entry patterns based on the corresponding characteristic information, wherein pattern characteristic information of each log entry pattern corresponds to the characteristic information of a subset of log entries in the set of log entries; and

storing the set of log entries according to the hierarchical data structure so that each log entry is associated with at least one of multiple nodes of the hierarchical data structure, wherein the multiple nodes respectively correspond to the multiple log entry patterns, and are hierarchically organized based on respective corresponding log entry patterns, and wherein the request comprises a first request for analyzing a first node of the multiple nodes; and

processing the target log entry based on the hierarchical data structure, wherein processing comprises:

determining a first subset of target log entries associated with the first node;

determining, based on the first subset of target log entries and using a natural language processing model, a first pattern associated with the first subset of target log entries for responding to the first request by:

determining a first characteristic representation of the first subset of target log entries; and

determining the first pattern by using the first characteristic representation as an input to a classifier module;

wherein the first pattern comprises key information in the first subset of target log entries, and wherein the natural language processing model comprises a pre-trained neural network; and

removing, based on the first pattern, redundant information recorded in the first subset of target log entries.

11. The electronic device according to claim 10 , wherein the actions further comprise:

in response to receiving a to-be-stored log entry, determining first characteristic information of the to-be-stored log entry;

determining at least one target node based on the first characteristic information, wherein the pattern characteristic information corresponding to the at least one target node matches the first characteristic information; and

storing the to-be-stored log entry as being associated with the at least one target node.

12. The electronic device according to claim 11 , wherein determining the at least one target node comprises:

determining a branch node located at a bottom level of the hierarchical data structure based on the first characteristic information, wherein the pattern characteristic information related to the determined branch node matches the first characteristic information;

determining, based on the hierarchical data structure, a top node located at a top level of the hierarchical data structure and associated with the determined branch node; and

if the first characteristic information matches the pattern characteristic information related to the top node, determining the branch node and the top node as target nodes.

13. The electronic device according to claim 12 , wherein the actions further comprise:

if the first characteristic information does not match the pattern characteristic information related to the top node, storing the to-be-stored log entry in a cache;

in response to the to-be-stored log entries in the cache reaching a predetermined number, clustering the predetermined number of the to-be-stored log entries to determine additional pattern characteristic information; and

creating an additional top node in the hierarchical data structure based on the additional pattern characteristic information, wherein the additional top node corresponds to an additional log entry pattern determined based on the additional pattern characteristic information; and

determining the branch node and the additional top node as target nodes.

14. The electronic device according to claim 10 , wherein the request comprises a query request at least related to a target log entry pattern, and processing the target log entry comprises:

determining, in the multiple nodes, at least one target node which matches the target log entry pattern; and

determining, from the set of log entries, a target log entry associated with the at least one target node, for responding to the query request.

15. The electronic device according to claim 10 , wherein the request further comprises a second request for analyzing the first pattern and a second pattern associated with the first pattern, and processing the target log entry further comprises:

combining a second subset of target log entries associated with the second pattern to obtain a second combined log text;

determining a second characteristic representation for the second combined log text with the natural language processing model; and

determining a third pattern based on the first characteristic representation and the second characteristic representation, for responding to the second request, wherein pattern characteristic information of the third pattern identifies key information in content recorded by both the first subset of target log entries and the second subset of target log entries.

16. A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor, enables the computer processor to:

receive a request for processing a target log entry; and

obtain a hierarchical data structure by:

obtaining corresponding characteristic information comprised in each log entry of a set of log entries;

determining multiple log entry patterns based on the corresponding characteristic information, wherein pattern characteristic information of each log entry pattern corresponds to the characteristic information of a subset of log entries in the set of log entries; and

storing the set of log entries according to the hierarchical data structure so that each log entry is associated with at least one of multiple nodes of the hierarchical data structure, wherein the multiple nodes respectively correspond to the multiple log entry patterns, and are hierarchically organized based on respective corresponding log entry patterns, and wherein the request comprises a first request for analyzing a first node of the multiple nodes; and

processing the target log entry based on the hierarchical data structure, wherein processing comprises:

determining a first subset of target log entries associated with the first node;

determining, based on the first subset of target log entries and using a natural language processing model, a first pattern associated with the first subset of target log entries for responding to the first request by:

combining target log entries in the first subset of target log entries to obtain a first combined log text;

determining a first characteristic representation for the first combined log text with the natural language processing model; and

determining the first pattern by using the first characteristic representation as an input to a classifier module;

wherein the first pattern comprises key information in the first subset of target log entries, and wherein the natural language processing model comprises a pre-trained neural network; and

removing, based on the first pattern, redundant information recorded in the first subset of target log entries.