WO2019161645A1 - Procédé d'extraction de données basé sur shell, terminal, dispositif et support de stockage - Google Patents

Procédé d'extraction de données basé sur shell, terminal, dispositif et support de stockage Download PDF

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Publication number
WO2019161645A1
WO2019161645A1 PCT/CN2018/101880 CN2018101880W WO2019161645A1 WO 2019161645 A1 WO2019161645 A1 WO 2019161645A1 CN 2018101880 W CN2018101880 W CN 2018101880W WO 2019161645 A1 WO2019161645 A1 WO 2019161645A1
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data
data information
data table
different types
target
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PCT/CN2018/101880
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English (en)
Chinese (zh)
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林林
戴建明
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平安科技（深圳）有限公司
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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
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution

Definitions

  • the present application relates to the field of computer technology, and in particular, to a Shell-based data table extraction method, terminal, device, and storage medium.
  • Shell is a free programming language for communicating between automated and interactive tasks without human intervention. Use it to create a script to provide input to a command or program. The shell can simulate the input of the standard input provided by the program according to the prompt of the program to implement interactive program execution.
  • the shell script In the existing shell script application, the shell script often involves more data tables. If you manually sort each shell script to get the data table in the shell script, the extraction process will be very time consuming, and The workload is very large; in addition, the statement of the data table in the shell script will change with the modification of the application version. It takes a lot of manpower to manually organize and update the information, and the compiled data table is also prone to appear. error.
  • the embodiment of the present application provides a Shell-based data table extraction method, terminal, device, and storage medium, which can simplify the finishing and updating process to the greatest extent, and can save a lot of human resources.
  • the embodiment of the present application provides a Shell-based data table extraction method, where the method includes:
  • the embodiment of the present application provides a shell-based data table extraction terminal, where the terminal includes:
  • a recognition unit for identifying a data table in the shell script
  • An extracting unit configured to extract a table name of the data table
  • a classification unit configured to classify the data table according to the extracted table name, where the data table includes a source table and a target table;
  • the obtaining unit is configured to obtain data information corresponding to different types of data tables, and output the obtained different types of data information into the same preset document.
  • the embodiment of the present application further provides a Shell-based data table extraction device, including:
  • a memory for storing a program implementing the data table extraction method
  • a processor for running a program for implementing the data table extraction method stored in the memory to perform the following operations:
  • the embodiment of the present application further provides a computer readable storage medium, where the one or more computer programs are stored, and the one or more computer programs may be one or more
  • the processor executes to implement the following steps:
  • the improved data table extraction method of the application of the present application does not require manual and cumbersome search for each script-related data table, greatly simplifies the collation and update process, and can save a lot of human resources.
  • FIG. 1 is a schematic flow chart of a Shell-based data table extraction method according to an embodiment of the present application
  • FIG. 2 is a schematic flowchart of a Shell-based data table extraction method according to an embodiment of the present application
  • FIG. 3 is a schematic flowchart of a method for extracting a data table based on a shell provided by an embodiment of the present application
  • FIG. 4 is a schematic flowchart of a Shell-based data table extraction method according to an embodiment of the present application.
  • FIG. 5 is a schematic flowchart of a method for extracting a data table based on a shell according to another embodiment of the present application.
  • FIG. 6 is a schematic block diagram of a shell-based data table extraction terminal according to an embodiment of the present application.
  • FIG. 7 is another schematic block diagram of a shell-based data table extracting terminal according to an embodiment of the present application.
  • FIG. 8 is another schematic block diagram of a shell-based data table extracting terminal according to an embodiment of the present application.
  • FIG. 9 is another schematic block diagram of a shell-based data table extraction terminal according to an embodiment of the present application.
  • FIG. 10 is another schematic block diagram of a shell-based data table extraction terminal according to an embodiment of the present application.
  • FIG. 11 is a schematic structural diagram of a Shell-based data table extraction device according to an embodiment of the present application.
  • FIG. 1 is a schematic flowchart of a method for extracting a data table based on a shell according to an embodiment of the present application.
  • the method can be run on terminals such as smart phones (such as Android phones, IOS phones, etc.), tablets, laptops, and smart devices.
  • the data dimension generation method described in the embodiment of the present application does not require manual cumbersome search for each script-related data table, greatly simplifies the collation and update process, and can save a lot of human resources.
  • 1 is a schematic flow chart of a Shell-based data table extraction method provided by an embodiment of the present application. The method includes steps S101 to S104.
  • the data table refers to a related data table that is called from a database through a SQL statement in a shell script; the database is connected in a shell script and the data table is called to obtain a database.
  • the data in the database can be obtained to achieve the purpose of monitoring certain information in the database, so as to further understand the performance of the device in real time.
  • Identifying the data table in the shell script can be implemented by identifying the keyword in the SQL statement.
  • the insert statement "insert into” can be identified to identify the data table following the insert statement;
  • the query can be identified by identifying the query *from", thereby identifying the data table following the query statement; also identifying the update statement "update” to identify the data table following the update statement; also identifying the delete statement "delete from” Delete the data table followed by the statement and so on.
  • the data table table name is stored in the temporary file, and the type of the data table includes a source table and a target table, where
  • the method for classifying the type of the data table according to the name of the data table may be: if the table name of the data table is an independent string, and there is a space or a new line before and after the independent string, and the from keyword is followed by the table name.
  • the type of the data table is a source table, if the data table table name is a separate string, and the independent string has spaces or newlines before and after the table name and the non-from keyword is followed by the table name, then the type of the data table
  • the target table optional, non-from keywords can be into, update and other SQL statement keywords.
  • the step S103 includes steps S201 to S202.
  • the character string refers to a string of characters corresponding to the table name of the data table. Since the table name of the data table may be composed of numbers, letters, and underscores, the string may also be a number, A character consisting of letters and underscores.
  • the data table is classified according to the character string, and the classification method is related to the SQL statement keyword in front of the data table table name, and the classification method may be: if the data table table name is an independent a string, and the independent string has spaces or newlines before and after the table name and the following keyword are followed by the from keyword, then the type of the data table is a source table, if the data table table name is an independent string, and the independent character There are spaces or newlines before and after the string and the non-from keyword is followed by the table name. Then the type of the data table is the target table.
  • the non-from keyword can be the SQL statement keyword such as into, update, and so on.
  • the data table is a Hadoop JOB association table
  • the Hadoop JOB association table is written by using a Hadoop statement and a SQL statement, and is saved in a corresponding database, and the Hadoop JOB association table is used.
  • the table name is written into the corresponding shell script.
  • the Hadoop JOB association table needs to be identified, the table name in the shell script is extracted first, that is, which JOB association tables are involved in the script, and the JOB associations are identified. Whether the type of the table belongs to the source table or the target table.
  • the source table refers to the table inside Hadoop and the table of the external relational database.
  • the string of the source table has spaces or newlines before and after the string, and the table name is followed by the from keyword;
  • the target table refers to Write mode is divided into insert target table and overlay target table, such as insert into tableA, this is the insert target table, insert overwrite tableB, this is the overlay target table,
  • the preset document can be the default database In the data table, for example, capture keywords and their related content from the script of the JOB association table, and record the captured content into a temporary file, which is done at the hdfs level of Hadoop, and then in the temporary file The result is loaded into the Hive table of the Hadoop.
  • the data in the Hive table is output to the specified preset Oracle database through the Sqoop method. Specifically, the data information is output to the pre-established data in the preset Oracle database. In the table.
  • the user can form a pre-established data table storing data information into an Oracle Pkg (Oracle packaging, Oracle packaging file). If the data table is needed for optimization, only the Oracle Pkg needs to be optimized.
  • the step S104 includes steps S301 to S303.
  • the source table is divided into an internal source table and an external source table.
  • the internal source table refers to a table inside Hadoop (for example, a Hive table of Hadoop), and the external source table refers to a table of an external relational database.
  • the data information includes table information, field information, and the like, where the table information may be a table name, a table type, or the like, and the field information may be a field name, a field type, or the like.
  • the preset document may be a pre-established data table in the preset Oracle database.
  • the acquired data information may be output to the pre-established data in the preset Oracle database.
  • the user can store the pre-established data table with data information and form an Oracle Pkg (Oracle packaging, Oracle package file). If you need to optimize the data table, you only need to optimize the Oracle Pkg to optimize. Preset the default data table created in the Oracle database.
  • the step S104 includes steps S401 to S403.
  • the target table is divided into an insertion target table and an overlay target table.
  • the insertion target table is, for example, the table tableA in the SQL statement "insert into table A", and the type of the target table is determined by the SQL statement keyword in front of the data table table name, such as into followed by insertion.
  • the target table, the coverage target table such as the table table B in the SQL statement "insert overwrite tableB”, the type of the target table is determined by the SQL statement keyword in front of the data table table name, such as overwrite followed by the overlay target table.
  • the data information includes table information, field information, and the like, where the table information may be a table name, a table type, or the like, and the field information may be a field name, a field type, or the like.
  • the preset document may be a pre-established data table in the preset Oracle database.
  • the acquired data information may be output to the pre-established data in the preset Oracle database.
  • the user can store the pre-established data table with data information and form an Oracle Pkg (Oracle packaging, Oracle package file). If you need to optimize the data table, you only need to optimize the Oracle Pkg to optimize. Preset the default data table created in the Oracle database.
  • the embodiment of the present application identifies the data table in the shell script, extracts the table name of the data table, and classifies the data table according to the extracted table name, where the data table includes the source table and the target.
  • the data information corresponding to different types of data tables is obtained, and the obtained different types of data information are output to the same preset document.
  • the improved data table extraction method of the application of the present application does not require manual and cumbersome search for each script-related data table, greatly simplifies the collation and update process, and can save a lot of human resources.
  • FIG. 5 is a schematic flowchart of a Shell-based data table extraction method according to an embodiment of the present application.
  • the method can be run on terminals such as smart phones (such as Android phones, IOS phones, etc.), tablets, laptops, and smart devices.
  • the method includes steps S501 to S506.
  • the shell script is traversed according to a preset keyword.
  • the rule for creating a short time is traversed by using a rule that traverses the data table first, and then traversing the rule that the data table is established for a long time, thereby implementing a data table for the shell script.
  • the traversal of the shell script from the creation time to the long creation time traversal rules can improve the efficiency of the shell script processing.
  • the position of the data table in the shell script is displayed by using the traversal result of the shell script, and the data table in the shell script is located by using the position information of the displayed data table.
  • the data table refers to a related data table that is called from a database through a SQL statement in a shell script; the database is connected in a shell script and the data table is called to obtain a database.
  • the data in the database can be obtained to achieve the purpose of monitoring certain information in the database, so as to further understand the performance of the device in real time.
  • Identifying the data table in the shell script can be implemented by identifying the keyword in the SQL statement.
  • the insert statement "insert into” can be identified to identify the data table following the insert statement;
  • the query can be identified by identifying the query *from", thereby identifying the data table following the query statement; also identifying the update statement "update” to identify the data table following the update statement; also identifying the delete statement "delete from” Delete the data table followed by the statement and so on.
  • the data table is classified according to the extracted table name, where the data table includes a source table and a target table.
  • the data table table name is stored in the temporary file, and the type of the data table includes a source table and a target table, where
  • the method for classifying the type of the data table according to the name of the data table may be: if the table name of the data table is an independent string, and there is a space or a new line before and after the independent string, and the from keyword is followed by the table name.
  • the type of the data table is a source table, if the data table table name is a separate string, and the independent string has spaces or newlines before and after the table name and the non-from keyword is followed by the table name, then the type of the data table
  • the target table optional, non-from keywords can be into, update and other SQL statement keywords.
  • the data table is a Hadoop JOB association table
  • the Hadoop JOB association table is written by using a Hadoop statement and a SQL statement, and is saved in a corresponding database, and the Hadoop JOB association table is used.
  • the table name is written into the corresponding shell script.
  • the Hadoop JOB association table needs to be identified, the table name in the shell script is extracted first, that is, which JOB association tables are involved in the script, and the JOB associations are identified. Whether the type of the table belongs to the source table or the target table.
  • the source table refers to the table inside Hadoop and the table of the external relational database.
  • the string of the source table has spaces or newlines before and after the string, and the table name is followed by the from keyword;
  • the target table refers to Write mode is divided into insert target table and overlay target table, such as insert into tableA, this is the insert target table, insert overwrite tableB, this is the overlay target table,
  • the preset document can be the default database In the data table, for example, capture keywords and their related content from the script of the JOB association table, and record the captured content into a temporary file, which is done at the hdfs level of Hadoop, and then in the temporary file The result is loaded into the Hive table of the Hadoop.
  • the data in the Hive table is output to the specified preset Oracle database through the Sqoop method. Specifically, the data information is output to the pre-established data in the preset Oracle database. In the table.
  • the user can store a pre-established data table with data information and form an Oracle Pkg (Oracle packaging, Oracle package file). If the data table is needed for optimization, only the Oracle Pkg needs to be optimized.
  • the embodiment of the present application further provides a Shell-based data table extraction terminal, where the terminal 100 includes: an identification unit 101, an extraction unit 102, a classification unit 103, The acquisition unit 104.
  • the identification unit 101 is configured to identify a data table in the shell script.
  • the extracting unit 102 is configured to extract a table name of the data table.
  • the classification unit 103 is configured to classify the data table according to the extracted table name, wherein the data table includes a source table and a target table.
  • the obtaining unit 104 is configured to acquire data information corresponding to different types of data tables, and output the acquired different types of data information into the same preset document.
  • the embodiment of the present application identifies the data table in the shell script, extracts the table name of the data table, and classifies the data table according to the extracted table name, where the data table includes the source table and the target.
  • the data information corresponding to different types of data tables is obtained, and the obtained different types of data information are output to the same preset document.
  • the improved data table extraction method of the application of the present application does not require manual and cumbersome search for each script-related data table, greatly simplifies the collation and update process, and can save a lot of human resources.
  • the classification unit 103 includes:
  • the determining unit 1031 is configured to determine a character string corresponding to the data table table name.
  • the classification subunit 1032 is configured to classify the data table according to the character string.
  • the obtaining unit 104 includes:
  • the first execution unit 1041 is configured to divide the source table into an internal source table and an external source table.
  • the first obtaining subunit 1042 is configured to acquire data information corresponding to the internal source table and the external source table.
  • the first output unit 1043 is configured to output the acquired data information into the preset document.
  • the obtaining unit 104 includes:
  • the second execution unit 1044 is configured to divide the target table into an insertion target table and an overlay target table.
  • the second obtaining subunit 1045 is configured to acquire data information corresponding to the insertion target table and the coverage target table.
  • the second output unit 1046 is configured to output the acquired data information into the preset document.
  • the embodiment of the present application further provides a data table extraction terminal based on a shell, where the terminal 200 includes: a traversing unit 201, a positioning unit 202, and an identifying unit 203.
  • the extracting unit 204, the classifying unit 205, and the obtaining unit 206 are included in the terminal 200 .
  • the traversing unit 201 is configured to traverse the shell script according to a preset keyword.
  • the locating unit 202 is configured to locate the data table in the shell script according to the result of the traversal.
  • the identification unit 203 is configured to identify a data table in the shell script.
  • the extracting unit 204 is configured to extract a table name of the data table.
  • the classification unit 205 is configured to classify the data table according to the extracted table name, wherein the data table includes a source table and a target table.
  • the obtaining unit 206 is configured to acquire data information corresponding to different types of data tables, and output the acquired different types of data information into the same preset document.
  • the above Shell-based data table extraction terminal can be implemented in the form of a computer program that can be run on a device as shown in FIG.
  • FIG. 11 is a schematic structural diagram of a Shell-based data table extraction device according to the present application.
  • the device may be a terminal or a server, wherein the terminal may be a communication device such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, and a wearable device.
  • the server can be a standalone server or a server cluster consisting of multiple servers.
  • the computer device 500 includes a processor 502, a non-volatile storage medium 503, an internal memory 504, and a network interface 505 connected by a system bus 501.
  • the non-volatile storage medium 503 of the computer device 500 can store an operating system 5031 and a computer program 5032.
  • the processor 502 can be caused to execute a shell-based data table extraction method.
  • the processor 502 of the computer device 500 is used to provide computing and control capabilities to support the operation of the entire computer device 500.
  • the internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503, which when executed by the processor, causes the processor 502 to perform a shell-based data table extraction method.
  • the network interface 505 of the computer device 500 is used to perform network communications, such as sending assigned tasks and the like. It will be understood by those skilled in the art that the structure shown in FIG.
  • 11 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied.
  • the specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • the processor 502 performs the following operations:
  • the processor 502 also performs the following operations:
  • the data table in the shell script is located according to the result of the traversal.
  • the classifying the data table according to the extracted table name comprises:
  • the data table is classified according to the character string.
  • the acquiring data information corresponding to different types of data tables, and outputting the acquired different types of data information to the same preset document includes:
  • the acquired data information is output to a preset document.
  • the acquiring data information corresponding to different types of data tables, and outputting the acquired different types of data information to the same preset document includes:
  • the acquired data information is output to a preset document.
  • the embodiment of the Shell-based data table extraction device shown in FIG. 11 does not constitute a limitation on the specific configuration of the Shell-based data table extraction device.
  • the Shell-based data table The extraction device may include more or fewer components than illustrated, or some components may be combined, or different component arrangements.
  • the Shell-based data table extraction device includes only the memory and the processor. In such an embodiment, the structure and function of the memory and the processor are consistent with the embodiment shown in FIG. Narration.
  • the application provides a computer readable storage medium storing one or more computer programs, the one or more computer programs being executable by one or more processors to implement the above-described shell-based Data table extraction method.
  • the foregoing storage medium of the present application includes: a magnetic disk, an optical disk, a read-only memory (ROM), and the like, which can store various program codes.
  • the units in all the embodiments of the present application may be implemented by a general-purpose integrated circuit, such as a CPU (Central Processing Unit), or by an ASIC (Application Specific Integrated Circuit).
  • a general-purpose integrated circuit such as a CPU (Central Processing Unit), or by an ASIC (Application Specific Integrated Circuit).
  • the steps in the method for extracting the data table based on the Shell in the embodiment of the present application may be sequentially adjusted, merged, and deleted according to actual needs.
  • the unit in the terminal based on the data table of the Shell may be merged, divided, and deleted according to actual needs.

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Abstract

L'invention concerne un procédé d'extraction de données basé sur shell, un terminal, un dispositif et un support de stockage Le procédé consiste à : identifier des tables de données dans un script Shell ; extraire les noms des tables de données ; classer les tables de données selon les noms de tables extraits, les tables de données comprenant une table source et une table cible ; et obtenir des informations de données correspondant à différents types de tables de données, puis générer les différents types de données obtenus dans le même document prédéfini. En utilisant le procédé d'extraction de table de données amélioré de l'invention, il n'est pas nécessaire d'effectuer une recherche manuelle et complexe des tables de données associées à chaque script, les processus de tri et de mise à jour sont simplifiés au maximum et une grande quantité de ressources de main-d'œuvre peut être économisée.
PCT/CN2018/101880 2018-02-24 2018-08-23 Procédé d'extraction de données basé sur shell, terminal, dispositif et support de stockage WO2019161645A1 (fr)

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CN201810196485.4A CN108536745B (zh) 2018-02-24 2018-03-09 基于Shell的数据表提取方法、终端、设备及存储介质
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CN116578651A (zh) * 2023-07-12 2023-08-11 北京集度科技有限公司 数据表结构同步方法、系统及设备
CN116578651B (zh) * 2023-07-12 2023-11-17 北京集度科技有限公司 数据表结构同步方法、系统及设备

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