ETLator -一个脚本ETL框架

Miran Radonic, I. Mekterović
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引用次数: 5

摘要

ETL(提取转换加载)过程是数据提取、转换和加载到数据仓库(DW)中的行业标准术语。ETL过程是数据仓库实现中最需要资源的过程,通常必须在数据仓库的持续时间内进行发展和维护。为了促进ETL过程的开发和维护,已经开发了许多ETL工具,这些工具具有图形用户界面和各种内置功能(并行性、日志记录、丰富的转换库、文档生成等)。这种GUI ETL工具的缺点是,开发大量使用鼠标操作,很少编写编程代码,这对一些开发人员来说是不自然的,特别是对于许多相似的、重复的任务。在本文中,我们提出了另一种方法——基于Python脚本语言的ETL框架“ETLator”,其中ETL任务通过编写Python代码来定义。ETLator实现了各种典型的ETL转换,并允许用户简单有效地定义具有多个源和并行任务的复杂ETL任务,同时充分利用Python的灵活性。ETLator还提供日志记录功能,并可以通过生成数据流图像来记录ETL任务。在一个测试用例中,我们展示了ETLator简化了ETL开发,并与GUI方法相抗衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ETLator - a scripting ETL framework
ETL (Extract Transform Load) process is the industry standard term for data extraction, transformation and loading into the Data Warehouse (DW). ETL process is the most resource demanding process in DW implementation and typically has to be evolved and maintained for the duration of the DW. To facilitate the development and maintenance of ETL processes many ETL tools have been developed featuring Graphical User Interfaces and various built-in functionalities (parallelism, logging, rich transformation libraries, documentation generation, etc.). The downside of such GUI ETL tools is that development is carried out heavily using mouse operations and less by writing programming code, which feels unnatural for some developers, especially with many similar, repetitive tasks. In this paper we present an alternative approach - an ETL framework “ETLator” based on Python scripting language where ETL tasks are defined by writing Python code. ETLator implements various typical ETL transformations and allows the user to simply and efficiently define complex ETL tasks with multiple sources and parallel tasks whilst leveraging full flexibility of Python. ETLator also provides logging and can document ETL tasks by generating data flow images. On a test case we show that ETLator simplifies ETL development and rivals the GUI approach.
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