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Recommendation data extracting method based on Windows timed tasks

A technology for timed tasks and data extraction, applied in relational databases, database models, structured data retrieval, etc., can solve problems such as low DBLINK concurrency efficiency, DBLINK connections are not released, etc., to achieve stable and reliable operation, ensure operation, and facilitate configuration changes. Effect

Inactive Publication Date: 2016-07-13
INSPUR QILU SOFTWARE IND
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0018] Solve the problem that the DBLINK connection is not released sometimes;
[0019] Solve the problem of low concurrency efficiency of DBLINK;
[0021] Solve other unknown problems of DBLINK

Method used

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  • Recommendation data extracting method based on Windows timed tasks

Examples

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Embodiment 1

[0037] Such as figure 1 As shown, a proposed data extraction method based on Windows timing tasks, the method is a date-based incremental extraction method, developed based on the JAVA language, using JDBC to connect to the database, stable and reliable operation, flexible and convenient configuration, The log can be added freely, which is convenient for error tracking. The execution code of the extraction tool is called in the MAIN function, and the BAT script is written, which is called cyclically through the timing task that comes with Windows, and the calling time and cycle can be changed at will.

[0038] JDBC (JavaDataBaseConnectivity, java database connection) is a Java API for executing SQL statements, which can provide unified access to various relational databases. It consists of a set of classes and interfaces written in the Java language.

Embodiment 2

[0040] On the basis of Embodiment 1, the method described in this embodiment adds log4j log processing, and the JAVA-JDBC method can be used to add log information by itself, so as to facilitate error tracking.

Embodiment 3

[0042] On the basis of Embodiment 2, the method described in this embodiment provides a database configuration file, and the database configuration information is placed in a property file to facilitate modification of the connection configuration.

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Abstract

The invention discloses a recommendation data extracting method based on Windows timed tasks. The recommendation data extracting method is an increment extraction method based on dates and is developed on the basis of a JAVA language, database connection is performed in a JDBC mode, extracting tool execution codes are called in MAIN functions, a BAT script is made, and circulation calling is implemented through the timed tasks of Windows. According to the method disclosed by the invention, a JAVA-JDBC mode is adopted for compiling, and due to the characteristics of the JAVA language, constraint of an operation system is avoided, and relatively stable and reliable operation can be achieved; database configuration information is placed in a property file, thus facilitating configuration modification; due to log treatment, error messages can be conveniently tracked; due to the timed tasks of the system, reliable and uninterrupted operation can be ensured.

Description

technical field [0001] The invention relates to the technical field of software, in particular to a method for extracting suggested data based on Windows timing tasks. Background technique [0002] Data extraction is the process of extracting data from a data source. [0003] In practical applications, relational databases are mostly used as data sources. There are generally several ways to extract data from the database: [0004] Full extraction: [0005] Full extraction is similar to data migration or data replication. It extracts the data of the table or view in the data source from the database intact and converts it into a format that can be recognized by its own ETL tool. Full extraction is relatively simple. [0006] Incremental extraction: [0007] Incremental extraction refers to the extraction of newly added, modified, and deleted data in tables to be extracted in the database since the last extraction. During the use of ETL. Incremental extraction is more w...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/44G06F17/30
CPCG06F8/315G06F16/284
Inventor 宫志方杨培强
Owner INSPUR QILU SOFTWARE IND
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