CN114595198A - Breakdown analysis method and device, electronic equipment and storage medium - Google Patents
Breakdown analysis method and device, electronic equipment and storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/16—File or folder operations, e.g. details of user interfaces specifically adapted to file systems
- G06F16/164—File meta data generation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/0766—Error or fault reporting or storing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/079—Root cause analysis, i.e. error or fault diagnosis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/14—Details of searching files based on file metadata
- G06F16/148—File search processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/17—Details of further file system functions
- G06F16/172—Caching, prefetching or hoarding of files
Abstract
The application provides a crash analysis method, a crash analysis device, an electronic device and a storage medium. The method comprises the following steps: receiving a crash file; analyzing the crash file to obtain stack frame data information of the crash file, wherein each stack frame data information comprises at least one stack frame; taking each stack frame in at least one stack frame as a target stack frame respectively; analyzing the attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of the database according to the attribute information, and acquiring symbol data corresponding to the target stack frame from the target storage space; and integrating and outputting the obtained symbol data corresponding to at least one stack frame. The collapse analysis mode can effectively improve the analysis efficiency and reduce the collapse analysis time, and the reading pressure is effectively reduced due to the fact that the reading amount in the analysis process is greatly reduced.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a crash analysis method and apparatus, an electronic device, and a storage medium.
Background
After an application of some terminals (for example, a PC terminal) is crashed, a client installed on the terminal uploads a crash file to a server, and the server is used to perform crash analysis. In the crash analysis process of the server, the symbol table file is required to be used for searching and analyzing.
In the prior art, the size of the symbol table file is large, and a large symbol table file is needed to be used in the analysis process of the crash file, so that the crash analysis can be completed by adopting a large number of reading processes due to the large size of the symbol table file, and the efficiency of the whole analysis is reduced.
Disclosure of Invention
In view of the above, an object of the present application is to provide a crash analysis method, apparatus, electronic device and storage medium to solve or partially solve the above technical problems.
In view of the above, a first aspect of the present application provides a crash resolution method, including:
receiving a crash file;
analyzing the crash file to obtain stack frame data information of the crash file, wherein each stack frame data information comprises at least one stack frame;
taking each stack frame in the at least one stack frame as a target stack frame respectively;
analyzing attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of a database according to the attribute information, and acquiring symbol data corresponding to the target stack frame from the target storage space;
and integrating and outputting the obtained symbol data corresponding to the at least one stack frame.
In some embodiments, prior to said receiving the crash file, the method further comprises:
receiving a symbol table file for crash analysis;
analyzing the symbol table file to obtain a plurality of symbol data;
and the symbol data are divided into at least one group, and the at least one group of symbol data are forwarded to at least one storage space of the database through an intermediate repeater for storage, wherein one group of symbol data corresponds to one storage space.
In some embodiments, the parsing the symbol table file to obtain a plurality of symbol data includes:
storing the symbol table file in a temporary memory;
determining an analysis task for analyzing the symbol table file, and generating a corresponding first message queue according to the analysis task;
and sending the first message queue to a resolver, and resolving the symbol table file in the temporary storage by using the resolver to obtain a plurality of symbol data.
In some embodiments, the sub-packaging the plurality of symbol data into at least one group, and forwarding the at least one group of symbol data to at least one storage space of the database through an intermediate forwarder for storage comprises:
in response to determining that the symbol table file parsing is completed, the intermediate forwarder generates a second message queue and sends the second message queue to the parser;
the parser forwards the parsed symbol data to the database through an intermediate forwarder;
and split charging is carried out on the basis of the address information of the plurality of symbol data by utilizing the database according to the address information of each group of preset number to obtain at least one group of symbol data, and the at least one group of symbol data is stored in at least one storage space of the database.
In some embodiments, before performing the split using the database based on the address information of the plurality of symbol data, according to each group of a predetermined number of address information, the method further includes:
determining the mapping relation of each symbol data, recording the mapping relation of each symbol data into at least one mapping map, and storing the at least one mapping map in the database.
In some embodiments, the map comprises at least one of:
a range map representing a functional range relationship;
an address map representing the address relationship;
an inclusion map representing the functional relationship of inclusion.
In some embodiments, after the forwarding at least one group of symbol data to at least one storage space of the database through an intermediate forwarder for storage, the method further includes:
determining the number of symbol data in each storage space, and taking the storage space with the number of the symbol data smaller than a first threshold value as a sparse storage space;
counting the number of the sparse storage spaces, and in response to determining that the number of the sparse storage spaces is greater than a second threshold value, performing merging processing on the sparse storage spaces and merging the sparse storage spaces into at least one dense storage space, wherein the storage number of the dense storage spaces is less than or equal to the predetermined number.
In some embodiments, the determining, according to the attribute information, a target storage space corresponding to the attribute information from at least one storage space of a database, and obtaining, from the target storage space, symbol data corresponding to the target stack frame includes:
sending the attribute information to the database through the intermediate forwarder;
and determining a target storage space corresponding to the attribute information from at least one storage space of the database, and acquiring the symbol data corresponding to the target stack frame from the target storage space through the intermediate repeater.
In some embodiments, the database comprises at least one of:
a relational database for storing source information of the symbol data;
a remote dictionary service database for caching the symbolic query instructions;
a base database comprising the at least one storage space.
In some embodiments, the parsing the attribute information of the target stack frame includes:
determining the name of the target stack frame according to the address information of the target stack frame;
acquiring target source information corresponding to the name of the target stack frame from the relational database through the intermediate forwarder;
caching the target source information as a symbol query instruction in the remote dictionary service database through the intermediate repeater;
determining the attribute information based on the address information of the target stack frame, the name of the target stack frame and the target source information.
In some embodiments, determining a target storage space corresponding to the attribute information from at least one storage space of the database, and obtaining, by the intermediate forwarder, symbol data corresponding to the target stack frame from the target storage space includes:
sending the attribute information to the basic database through the intermediate forwarder;
determining a target mapping relation according to at least one mapping chart corresponding to the attribute information by utilizing the basic database based on the attribute information;
and determining a corresponding target storage space from at least one storage space of the basic database according to the target mapping relation, and acquiring symbolic data corresponding to the target mapping relation from the target storage space.
In some embodiments, the respective symbol data in each storage space is stored in the form of key-value pairs, wherein a key-value pair comprises: a key formed by the attribute information, and a value formed by the symbol data.
Based on the same inventive concept, a second aspect of the present application provides a crash analysis apparatus, including:
the crash file receiving module is used for receiving a crash file;
the analysis module is used for analyzing the crash file to obtain stack frame data information of the crash file, wherein each stack frame data information comprises at least one stack frame;
a symbol obtaining module, configured to take each stack frame in the at least one stack frame as a target stack frame; analyzing attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of a database according to the attribute information, and acquiring symbol data corresponding to the target stack frame from the target storage space;
and the output module is used for integrating and outputting the obtained symbol data corresponding to the at least one stack frame.
Based on the same inventive concept, a third aspect of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the method of the first aspect.
Based on the same inventive concept, a fourth aspect of the present application proposes a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of the first aspect.
As can be seen from the above, the collapse analysis method, the collapse analysis device, the electronic device, and the storage medium provided in the present application, pre-allocate symbol data into each storage space of the database for storage, so that after receiving a collapse file, analyze the collapse file to obtain stack frame data information, search a corresponding target storage space from each storage space for each stack frame in the stack frame data information, analyze and match from the target storage space, and determine the symbol data corresponding to the stack frame, where the number of symbol data in each storage space is relatively small, so that the data reading amount is greatly reduced, and the analysis and matching time can be shortened; and finally, integrating one or more symbol data corresponding to the stack frame data information analysis matching to form an analysis result to be output, so as to judge the crash file according to the output analysis result and timely make a solution strategy for the crash situation. The collapse analysis mode can effectively improve the analysis efficiency and reduce the collapse analysis time, and the reading pressure is effectively reduced due to the fact that the reading amount in the analysis process is greatly reduced.
Drawings
In order to more clearly illustrate the technical solutions in the present application or the related art, the drawings needed to be used in the description of the embodiments or the related art will be briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1A is a schematic view of an application scenario according to an embodiment of the present application;
FIG. 1B is a diagram illustrating an exemplary architecture for crash resolution according to an embodiment of the present disclosure;
fig. 2A is a flowchart of a symbol table file storage process in the crash resolution method according to the embodiment of the present application;
FIG. 2B is a flowchart of a crash file parsing process in the crash parsing method according to the embodiment of the present application;
FIG. 3 is a block diagram of a crash resolution apparatus according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The principles and spirit of the present application will be described with reference to a number of exemplary embodiments. It should be understood that these embodiments are given solely for the purpose of enabling those skilled in the art to better understand and to practice the present application, and are not intended to limit the scope of the present application in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In the present application, it is to be understood that the number of any elements in the figures are intended to be illustrative rather than restrictive, and that any nomenclature is used for distinction only and not in any limiting sense.
The application provides a crash analysis scheme, symbol data are distributed into each storage space of a database in advance to be stored, after a crash file is received, the crash file is analyzed to obtain stack frame data information, each stack frame in the stack frame data information is searched for a corresponding target storage space from each storage space, then the target storage spaces are analyzed and matched, and the symbol data corresponding to the stack frame are determined; and finally, integrating one or more symbol data corresponding to the stack frame data information analysis matching to form an analysis result to be output, so as to judge the crash file according to the output analysis result and timely make a solution strategy for the crash situation.
The principles and spirit of the present application are explained in detail below with reference to several representative embodiments of the present application.
Fig. 1A is a schematic view of an application scenario of a crash resolution method according to an embodiment of the present application. The application scenario includes a terminal device 101, a server 102, and a data storage system 103. The terminal device 101, the server 102, and the data storage system 103 may be connected through a wired or wireless communication network. The terminal device 101 includes, but is not limited to, a Personal Computer (PC), a desktop Computer, a mobile phone, a mobile Computer, a tablet Computer, a media player, a smart wearable device, a Personal Digital Assistant (PDA), or other electronic devices capable of implementing the above functions. The server 102 and the data storage system 103 may be independent physical servers, may also be a server cluster or distributed system formed by a plurality of physical servers, and may also be cloud servers providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, and big data and artificial intelligence platforms.
The server 102 is configured to provide a crash resolution service to a user of the terminal apparatus 101, the terminal apparatus 101 is installed with a client communicating with the server 102, and when an application program of the terminal apparatus 101 crashes, a crash file may be sent to the server 102 through the client. The server 102 analyzes the crash file to obtain stack frame data information, searches a corresponding target storage space from each storage space for each stack frame in the stack frame data information, analyzes and matches from the target storage space, and determines symbol data corresponding to the stack frame; and finally, analyzing and matching the stack frame data information with one or more corresponding symbol data, and integrating to form an analysis result and output the analysis result. The analysis result may be displayed on a display interface of the server 102 for viewing by relevant personnel, so as to determine the cause of the crash and process the crash situation. The parsing result may also be fed back to the terminal device 101 or other electronic devices with a display function for viewing. The data storage system 103 provides data storage support for the work operation of the server 102, for example, temporarily storing a crash file, and storing a program for executing the crash analysis method.
An infrastructure for crash resolution is built in the server 102, and as shown in fig. 1B in particular, the infrastructure includes:
the system comprises a symbol table uploading module (fine _ symbol), which is connected with an adaptor way of a terminal device, wherein a packaging platform/RD of the terminal device can package a symbol table file into symbol.
And the temporary storage (tbs) is connected with the symbol table uploading module, and the symbol table uploading module uploads the symbol table file to the tbs for temporary storage.
And the symbol table uploading module generates a message queue (RocktMQ) and sends the message queue to the parser, and the parser parses the symbol table file stored in the temporary storage.
And the intermediate forwarder (pc _ date _ proxy) is connected with the resolver and is used for performing intermediate forwarding on some instructions or data.
And the relational database (MySQL) is connected with the intermediate transponder, and after the parser parses the symbol table file, the source file of the parsed symbol table can be stored in the relational database through the intermediate transponder.
And the remote dictionary service database (redis) is connected with the intermediate forwarder and is used for temporarily storing the required requests or data in MySQL.
And the basic database (ABase) is connected with the intermediate transponder and is used for subpackaging a plurality of symbol data obtained after the symbol table file is analyzed and subpackaging the symbol data into a plurality of buckets (storage spaces) for storage.
And the crash file analysis module (pc _ stack _ walk) is connected with the intermediate forwarder and used for analyzing the received crash file (RPC, Remote Procedure Call) and acquiring one or more symbol data corresponding to the crash file from a corresponding target storage space of the basic database by using the relational database through the intermediate forwarder according to an analysis result, and integrating and outputting the symbol data.
The crash resolution method according to an exemplary embodiment of the present application is described below with reference to the application scenarios shown in fig. 1A and 1B. It should be noted that the above application scenarios are only presented to facilitate understanding of the spirit and principles of the present application, and the embodiments of the present application are not limited in this respect. Rather, embodiments of the present application may be applied to any scenario where applicable.
The embodiment of the application provides a crash analysis method which is applied to a server.
In the crash analysis method of this embodiment, before performing crash analysis on a crash file, a symbol table file required by the crash analysis needs to be stored, as shown in fig. 2A, the storage process includes:
step 2a1, a symbol table file for crash resolution is received.
In specific implementation, a packaging platform on the terminal device (i.e., a client installed in the terminal device) packages the generated symbol table file, and after the packaging, a packaging file (e.g., symbol.
And step 2A2, analyzing the symbol table file to obtain a plurality of symbol data.
In specific implementation, the content of the symbol table file is large, and the symbol table file contains a large amount of symbol data, and the symbol data contained in the symbol table file needs to be analyzed and divided into a plurality of parts (buckets) for storage.
In some embodiments, the step 2a2 includes:
step 2a21, storing the symbol table file in a temporary memory.
In specific implementation, the symbol table uploading module uploads the symbol table file to a temporary storage (tbs) for temporary storage. And the subsequent calling analysis is convenient.
Step 2a22, determining an analysis task for analyzing the symbol table file, and generating a corresponding first message queue according to the analysis task.
In specific implementation, after the symbol table file is stored in the temporary memory, the symbol table uploading module generates a first message queue (rockmq) according to the parsing task, and sends the first message queue to the parser.
And step 2A23, sending the first message queue to a parser, and parsing the symbol table file in the temporary storage by using the parser to obtain a plurality of symbol data.
In specific implementation, after receiving the first message queue, the parser starts to retrieve the symbol table file from the temporary storage for parsing, and parses the huge symbol table file into a plurality of symbol data, and during the parsing process, the parser may also parse a mapping relationship corresponding to the symbol data and source information (e.g., a source of the symbol data) of each symbol data together, where the mapping relationship includes at least one of the following: functional scope, address relationships, and inclusive functional relationships, etc.
And step 2a3, splitting the plurality of symbol data into at least one group, and forwarding the at least one group of symbol data to at least one storage space of the database through an intermediate forwarder for storage, wherein one group of symbol data corresponds to one storage space.
Through the steps, the symbol data can be divided into a plurality of storage spaces (buckets) for storage, so that in the calling and searching process after the crash file is analyzed subsequently, the symbol data corresponding to the crash file only needs to be searched from one or more corresponding storage spaces, the whole symbol table file does not need to be called and searched, the searching time can be saved, and the efficiency of crash analysis is improved.
In some embodiments, step 2a3 specifically includes:
step 2a31, in response to determining that the symbol table file parsing is complete, the intermediate forwarder generates a second message queue and sends the second message queue to the parser.
In specific implementation, after the intermediate forwarder completes parsing the symbol table file, the intermediate forwarder can capture the message after the parsing is completed, so that the intermediate forwarder generates a second message queue (RockketMQ) and sends the second message queue (RockketMQ) to the parser, and the parser starts a sending process.
Step 2a32, the parser forwards the parsed symbol data to the database through an intermediate forwarder.
In specific implementation, after receiving the second message queue, the parser sends the parsed symbol data, source information, and mapping relationship to the intermediate forwarder for forwarding. The intermediate repeater has the function of intermediate route forwarding and can be matched with an appropriate database according to specific data information.
In some embodiments, the database comprises at least one of:
a relational database (MySQL) for storing source information of the symbolic data; a remote dictionary service database (redis) for caching symbolic query instructions; an underlying database (ABase) comprising said at least one memory space.
When the source information is sent to the intermediate forwarder by the resolver, the intermediate forwarder forwards the source information to the relational database; when the symbol data or the mapping relation is sent to the intermediate forwarder by the parser, the symbol data or the mapping relation is forwarded to the basic database.
Step 2a33, determining the mapping relation of each symbolic data, recording the mapping relation of each symbolic data into at least one mapping map, and storing the at least one mapping map in the database.
In specific implementation, the mapping relationship represents some characteristics of the symbolic data, including functional characteristics, attribute characteristics, and the like, and the symbolic data can be searched subsequently through the characteristics.
In some embodiments, the map comprises at least one of:
a range map (RangeMap) representing a functional range relationship; an address map (AddressMap) indicating an address relationship; a containment map (ContainedRangeMap) indicating a containment function relationship.
The procedure for recording the mapping relationships using the respective maps is as follows:
through the scheme, various mapping relations of the symbolic data can be stored in the form of the mapping map, so that the corresponding mapping relations can be determined according to the mapping maps during subsequent crash analysis, and then the corresponding symbolic data can be searched according to the mapping relations, wherein the symbolic data comprises information such as a method name, a line number of a code line and the like.
And step 2A34, performing split charging according to the address information of each group of preset number by using the address information of the database based on the plurality of symbol data to obtain at least one group of symbol data, and storing the at least one group of symbol data in at least one storage space of the database.
In some embodiments, the respective symbol data in each storage space is stored in the form of key-value pairs, wherein a key-value pair comprises: a key formed by attribute information of the symbol data, and a value formed by the symbol data.
The attribute information includes: and address information, name or source information, so that corresponding mapping relations can be searched in each mapping graph subsequently according to the attribute information of each stack frame in the crash information, and then symbolic data is called from corresponding storage space according to the mapping relations.
In some embodiments, the method further comprises:
and step 2A4, determining the number of symbol data in each storage space, and taking the storage space with the number of symbol data smaller than a first threshold value as a sparse storage space.
And step 2A5, counting the number of the sparse storage spaces, and in response to determining that the number of the sparse storage spaces is greater than a second threshold, performing merging processing on the sparse storage spaces and merging the sparse storage spaces into at least one dense storage space, wherein the storage number of the dense storage spaces is less than or equal to the predetermined number.
At present, a mac symbol table file is sometimes extremely sparse, a part of symbols often exist in a header, and a hole (for example, the size of the hole is 1G or a space above 1G) exists in the middle, so that a large number of buckets are generated, the storage redundancy is increased, the scale of a key (key) is increased from tens of thousands to millions or tens of millions, and a large amount of piles are generated when a symbol table file dump enters a database.
According to the sparse characteristic, a mode similar to a multi-level page table can be adopted to perform multi-level block partitioning (chunk), and for a sparse part (namely, a sparse storage space), a storage-intensive storage space (for example, a large chunk) is combined, so that the number of the chunks is greatly reduced, from millions of tens of millions of levels to tens of millions of levels, and the time for subsequent crash analysis can be reduced from an hour level to a minute level. The efficiency of breakdown analysis is greatly improved.
The crash resolution process, as shown in FIG. 2B, includes:
step 2B1, receive the crash file.
In specific implementation, if the terminal device is crashed, the client installed in the terminal device integrates the crashed situation into a crashed file and uploads the crashed file to the server. Wherein the crash file is a dump file that includes RPC requests. Specifically, a crash file parsing module (pc _ stack _ walk) on the server is used to receive the uploaded crash file.
And step 2B2, analyzing the crash file to obtain stack frame data information of the crash file, wherein each stack frame data information comprises at least one stack frame.
In specific implementation, the crash file analysis module is used for obtaining a context (i.e., at least one stack frame) of the crash file according to the crash file analysis, and determining a name (e.g., moudle) and an address (e.g., address) corresponding to each stack frame.
And step 2B3, taking each stack frame in the at least one stack frame as a target stack frame respectively.
In specific implementation, starting from the first stack frame obtained by analysis, the first stack frame is used as a target stack frame to perform query.
Step 2B4, analyzing the attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of a database according to the attribute information, and acquiring the symbolic data corresponding to the target stack frame from the target storage space.
During specific implementation, the crash file parsing module is used for parsing the first stack frame (namely, the target stack frame) and determining attribute information corresponding to the first stack frame. Because the attribute information and the symbol data in the database are stored in the form of key value pairs, after the attribute information of the first stack frame is analyzed, the method name, the line number of the code line and other symbol data corresponding to the first stack frame can be inquired according to the attribute information.
In some embodiments, step 2B4 specifically includes:
and step 2B41, determining the name of the target stack frame according to the address information of the target stack frame.
In specific implementation, the crash file parsing module is used for parsing the name (module) of the first stack frame (i.e., the target stack frame) according to the address of the first stack frame.
And step 2B42, acquiring, by the intermediate forwarder, target source information corresponding to the name of the target stack frame from the relational database.
In specific implementation, the crash file analysis module forwards the name of the target stack frame to the relational database through the intermediate forwarder, and searches for target source information (meta information) corresponding to the name from the relational database to obtain the size of the chunk _ size.
And step 2B43, caching the target source information as a symbol query instruction in the remote dictionary service database through the intermediate repeater.
During specific implementation, the intermediate forwarder is used as a transfer, and the target source information is cached in a remote dictionary service database (redis), so that the transfer is convenient.
Step 2B44, determining the attribute information based on the address information of the target stack frame, the name of the target stack frame and the target source information.
In specific implementation, according to the address, chunk _ size, and module of the target stack frame, an abase key (i.e., a key) of the chunk to which the address belongs may be obtained, where the abase key is module _ name + (address/chunk _ size)
And step 2B45, sending the attribute information to the database through the intermediate forwarder.
Step 2B46, determining a target storage space corresponding to the attribute information from at least one storage space of the database, and acquiring, by the intermediate forwarder, symbolic data corresponding to the target stack frame from the target storage space.
In some embodiments, step 2B46 specifically includes:
step 2B461, sending the attribute information to the basic database through the intermediate forwarder.
And step 2B462, determining a target mapping relation according to at least one mapping chart corresponding to the attribute information by utilizing the basic database based on the attribute information.
Step 2B463, determining a corresponding target storage space from at least one storage space of the basic database according to the target mapping relationship, and obtaining symbolic data corresponding to the target mapping relationship from the target storage space.
During specific implementation, the abase key determined according to the attribute information may be used to query data structures (RangeMap, AddressMap, conteinedrrangemap, which may store mapping relationships from memory addresses to method information and trace back stack frame modes) of several maps (i.e., maps) of chunk to which the address of the target stack frame belongs.
After the basic database obtains the map data structure, the target storage space where the target stack frame is located can be queried through the mapping relation, and the symbolic data (namely, the method name and the line number corresponding to the target stack frame) of the key (abase key) determined by the attribute information is queried from the target storage space. And the next stack frame can be found by including a map (ContainedRangeMap), the process of steps 2B41 through 2B46 above continues with the restoration of the symbolic data (e.g., method name and line number) of the next stack frame.
By the scheme, the symbolic data corresponding to each stack frame is sequentially obtained according to the obtained sequence of the stack frames, and the symbolic data is searched in a key value pair mode, so that the number searching efficiency can be rapidly improved.
And step 2B5, integrating and outputting the obtained symbol data corresponding to the at least one stack frame.
In specific implementation, the symbolic data corresponding to each stack frame is obtained through the above process, the symbolic data is sorted and integrated according to the sorting of the analyzed stack frames to obtain a final analysis result, and the analysis result is output to a display interface capable of displaying. The display interface may be directly arranged on the server, or may be another display interface connected with the server in a wired or wireless manner. Therefore, a user can know the content of the symbol data analyzed by the crash file through the display interface, and further quickly determine the cause of the crash.
Through the scheme of the embodiment, the symbol data are distributed into each storage space of the database in advance to be stored, after a crash file is received, the crash file is analyzed to obtain stack frame data information, each stack frame in the stack frame data information is searched for a corresponding target storage space from each storage space, then the target storage spaces are analyzed and matched, and the symbol data corresponding to the stack frame are determined; and finally, integrating one or more symbol data corresponding to the stack frame data information analysis matching to form an analysis result to be output, so as to judge the crash file according to the output analysis result and timely make a solution strategy for the crash situation.
The collapse analysis mode can effectively improve the analysis efficiency, reduce the collapse analysis time, and effectively reduce the reading pressure due to the fact that the reading amount in the analysis process is greatly reduced.
It should be noted that the method of the embodiment of the present application may be executed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiment, and the multiple devices interact with each other to complete the method.
It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Based on the same inventive concept, the application also provides a crash analysis device corresponding to the crash analysis method of any of the above embodiments.
Referring to fig. 3, the crash resolution apparatus includes:
a crash file receiving module 31 for receiving a crash file;
the analysis module 32 is configured to analyze the crash file to obtain stack frame data information of the crash file, where each stack frame data information includes at least one stack frame;
a symbol obtaining module 33, configured to use each stack frame in the at least one stack frame as a target stack frame; analyzing attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of a database according to the attribute information, and acquiring symbol data corresponding to the target stack frame from the target storage space;
and the output module 34 is configured to integrate and output the obtained symbol data corresponding to the at least one stack frame.
In some embodiments, the apparatus further comprises:
the symbol table receiving module is used for receiving the symbol table file analyzed by collapse;
the analysis module 32 is configured to analyze the symbol table file to obtain a plurality of symbol data;
the storage module is used for dividing the plurality of symbol data into at least one group, and forwarding the at least one group of symbol data to at least one storage space of the database through the intermediate forwarder for storage, wherein one group of symbol data corresponds to one storage space.
In some embodiments, parsing module 32 includes:
a temporary storage unit for storing the symbol table file in a temporary memory;
the first message generating unit is used for determining an analysis task for analyzing the symbol table file and generating a corresponding first message queue according to the analysis task;
and the analysis unit is used for sending the first message queue to an analyzer and analyzing the symbol table file in the temporary storage by using the analyzer to obtain a plurality of symbol data.
In some embodiments, the storage module comprises:
the second message generating unit is used for determining that the symbol table file is analyzed completely, and the intermediate forwarder generates a second message queue and sends the second message queue to the analyzer;
the forwarding unit is used for forwarding the analyzed symbol data to the database through an intermediate forwarder by using the analyzer;
and the storage unit is used for performing split charging according to the address information of each group of preset number by utilizing the database based on the address information of the plurality of symbol data to obtain at least one group of symbol data, and storing the at least one group of symbol data in at least one storage space of the database.
In some embodiments, the memory module further comprises:
and the mapping analysis unit is used for determining the mapping relation of each symbol data, recording the mapping relation of each symbol data into at least one mapping map, and storing the at least one mapping map in the database.
In some embodiments, the map comprises at least one of:
a range map representing a functional range relationship;
an address map representing an address relationship;
an inclusion map representing the inclusion functional relationship.
In some embodiments, the memory module further comprises: the sparse processing unit is specifically configured to:
determining the number of symbol data in each storage space, and taking the storage space with the number of the symbol data smaller than a first threshold value as a sparse storage space; counting the number of the sparse storage spaces, and in response to determining that the number of the sparse storage spaces is greater than a second threshold value, performing merging processing on the sparse storage spaces and merging the sparse storage spaces into at least one dense storage space, wherein the storage number of the dense storage spaces is less than or equal to the predetermined number.
In some embodiments, the symbol acquisition module 33 comprises:
the attribute forwarding unit is used for sending the attribute information to the database through the intermediate forwarder;
and the searching unit is used for determining a target storage space corresponding to the attribute information from at least one storage space of the database, and acquiring the symbol data corresponding to the target stack frame from the target storage space through the intermediate forwarder.
In some embodiments, the database comprises at least one of:
a relational database for storing source information of the symbol data;
a remote dictionary service database for caching the symbolic query instructions;
a base database comprising the at least one storage space.
In some embodiments, the symbol acquisition module 33 comprises: the attribute analysis unit is specifically configured to:
determining the name of the target stack frame according to the address information of the target stack frame; acquiring target source information corresponding to the name of the target stack frame from the relational database through the intermediate forwarder; caching the target source information as a symbol query instruction in the remote dictionary service database through the intermediate repeater; determining the attribute information based on the address information of the target stack frame, the name of the target stack frame and the target source information.
In some embodiments, the lookup unit is specifically configured to:
sending the attribute information to the basic database through the intermediate forwarder; determining a target mapping relation according to at least one mapping chart corresponding to the attribute information by utilizing the basic database based on the attribute information; and determining a corresponding target storage space from at least one storage space of the basic database according to the target mapping relation, and acquiring symbolic data corresponding to the target mapping relation from the target storage space.
In some embodiments, the respective symbol data in each storage space is stored in the form of key-value pairs, wherein a key-value pair comprises: a key formed by the attribute information, and a value formed by the symbol data.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations as the present application.
The apparatus of the foregoing embodiment is used to implement the corresponding method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the program, the method according to any of the above embodiments is implemented.
Fig. 4 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 410, a memory 420, an input/output interface 430, a communication interface 440, and a bus 450. Wherein processor 410, memory 420, input/output interface 430, and communication interface 440 are communicatively coupled to each other within the device via bus 450.
The processor 410 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present specification.
The Memory 420 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 420 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 420 and called to be executed by the processor 410.
The input/output interface 430 is used for connecting an input/output module to realize information input and output. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 440 is used for connecting a communication module (not shown in the figure) to realize communication interaction between the device and other devices. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
It should be noted that although the above-mentioned device only shows the processor 410, the memory 420, the input/output interface 430, the communication interface 440 and the bus 450, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
The electronic device of the foregoing embodiment is used to implement the corresponding crash resolution method in any one of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Based on the same inventive concept, corresponding to any of the above-described embodiment methods, the present application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method according to any of the above-described embodiments.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method according to any of the above embodiments, and have the beneficial effects of the corresponding method embodiment, and are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the context of the present application, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of brevity.
In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures for simplicity of illustration and discussion, and so as not to obscure the embodiments of the application. Furthermore, devices may be shown in block diagram form in order to avoid obscuring embodiments of the application, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the embodiments of the application are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the application, it should be apparent to one skilled in the art that the embodiments of the application can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present application has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
The present embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of the embodiments of the present application are intended to be included within the scope of the present application.
Claims (15)
1. A crash resolution method, comprising:
receiving a crash file;
analyzing the crash file to obtain stack frame data information of the crash file, wherein each stack frame data information comprises at least one stack frame;
taking each stack frame in the at least one stack frame as a target stack frame respectively;
analyzing attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of a database according to the attribute information, and acquiring symbol data corresponding to the target stack frame from the target storage space;
and integrating and outputting the obtained symbol data corresponding to the at least one stack frame.
2. The method of claim 1, wherein prior to the receiving the crash file, the method further comprises:
receiving a symbol table file for crash analysis;
analyzing the symbol table file to obtain a plurality of symbol data;
and the symbol data are divided into at least one group, and the at least one group of symbol data are forwarded to at least one storage space of the database through an intermediate repeater for storage, wherein one group of symbol data corresponds to one storage space.
3. The method of claim 2, wherein parsing the symbol table file to obtain a plurality of symbol data comprises:
storing the symbol table file in a temporary memory;
determining an analysis task for analyzing the symbol table file, and generating a corresponding first message queue according to the analysis task;
and sending the first message queue to a resolver, and resolving the symbol table file in the temporary storage by using the resolver to obtain a plurality of symbol data.
4. The method of claim 2, wherein the sub-packaging the plurality of symbol data into at least one group, and forwarding the at least one group of symbol data to the at least one storage space of the database through an intermediate repeater comprises:
in response to determining that the symbol table file parsing is complete, the intermediate forwarder generates a second message queue and sends the second message queue to the parser;
forwarding the analyzed symbol data to the database through an intermediate forwarder by using the analyzer;
and split charging is carried out on the basis of the address information of the plurality of symbol data by utilizing the database according to the address information of each group of preset number to obtain at least one group of symbol data, and the at least one group of symbol data is stored in at least one storage space of the database.
5. The method according to claim 4, before performing the split charging by each predetermined number of address information based on the address information of the plurality of symbol data using the database, further comprising:
determining the mapping relation of each symbol data, recording the mapping relation of each symbol data into at least one mapping map, and storing the at least one mapping map in the database.
6. The method of claim 5, wherein the map comprises at least one of:
a range map representing a functional range relationship;
an address map representing the address relationship;
an inclusion map representing the inclusion functional relationship.
7. The method according to any one of claims 4 to 6, further comprising, after forwarding at least one set of symbol data to at least one storage space of the database through an intermediate forwarder for storage, the step of:
determining the number of symbol data in each storage space, and taking the storage space with the number of the symbol data smaller than a first threshold value as a sparse storage space;
counting the number of the sparse storage spaces, and in response to determining that the number of the sparse storage spaces is greater than a second threshold value, performing merging processing on the sparse storage spaces and merging the sparse storage spaces into at least one dense storage space, wherein the storage number of the dense storage spaces is less than or equal to the predetermined number.
8. The method according to claim 2, wherein the determining, according to the attribute information, a target storage space corresponding to the attribute information from at least one storage space of a database, and obtaining the symbol data corresponding to the target stack frame from the target storage space, includes:
sending the attribute information to the database through the intermediate forwarder;
and determining a target storage space corresponding to the attribute information from at least one storage space of the database, and acquiring the symbol data corresponding to the target stack frame from the target storage space through the intermediate repeater.
9. The method of claim 8, wherein the database comprises at least one of:
a relational database for storing source information of the symbol data;
a remote dictionary service database for caching the symbolic query instructions;
a base database comprising the at least one storage space.
10. The method of claim 9, wherein the parsing the attribute information of the target stack frame comprises:
determining the name of the target stack frame according to the address information of the target stack frame;
acquiring target source information corresponding to the name of the target stack frame from the relational database through the intermediate forwarder;
caching the target source information as a symbol query instruction in the remote dictionary service database through the intermediate repeater;
determining the attribute information based on the address information of the target stack frame, the name of the target stack frame and the target source information.
11. The method according to claim 9, wherein determining a target storage space corresponding to the attribute information from at least one storage space of the database, and obtaining symbol data corresponding to the target stack frame from the target storage space through the intermediate forwarder comprises:
sending the attribute information to the basic database through the intermediate forwarder;
determining a target mapping relation according to at least one mapping chart corresponding to the attribute information by utilizing the basic database based on the attribute information;
and determining a corresponding target storage space from at least one storage space of the basic database according to the target mapping relation, and acquiring symbolic data corresponding to the target mapping relation from the target storage space.
12. The method of any one of claims 1 to 11, wherein the respective symbol data in each storage space is stored in the form of key-value pairs, wherein a key-value pair comprises: a key formed by the attribute information, and a value formed by the symbol data.
13. A crash resolution apparatus, comprising:
the crash file receiving module is used for receiving a crash file;
the analysis module is used for analyzing the crash file to obtain stack frame data information of the crash file, wherein each stack frame data information comprises at least one stack frame;
a symbol obtaining module, configured to take each stack frame in the at least one stack frame as a target stack frame; analyzing attribute information of the target stack frame, determining a target storage space corresponding to the attribute information from at least one storage space of a database according to the attribute information, and acquiring symbol data corresponding to the target stack frame from the target storage space;
and the output module is used for integrating and outputting the obtained symbol data corresponding to the at least one stack frame.
14. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 12 when executing the program.
15. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 12.
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