基于触发器的实时增量提取支持数据仓库

C. R. Valêncio, Matheus Henrique Marioto, G. F. D. Zafalon, J. M. Machado, J. C. Momente
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引用次数: 16

摘要

如今,大型公司需要来自不同来源的集成数据,这导致为此目的使用数据仓库体系结构。为了绕过与使用计算资源来处理大量数据相关的问题,可以使用零延迟的ETL(提取、转换和加载)技术,该技术通过不断处理小数据负载来工作。零延迟ETL的提取技术包括使用日志、触发器、物化视图和时间戳。本文提出了一种能够通过触发器执行此任务的结构,并开发了一种用于自动生成SQL(结构化查询语言)代码来创建这些触发器的工具,此外还展示了其性能并将其与其他技术进行了比较。所述方法与提取所选信息的部分相关,因为它允许将传统和实时ETL技术结合起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real Time Delta Extraction Based on Triggers to Support Data Warehousing
Nowadays large corporations require integrated data from diverse sources, leading to the use of data warehouse architectures for this purpose. To bypass problems related to the use of computational resources to process large volumes of data, an ETL (Extract, Transform and Load) technique with zero latency can be used, that works by constantly processing small data loads. Among the extraction techniques of the zero latency ETL are the use of logs, triggers, materialized views and timestamps. This paper proposes a structure capable of performing this task by means of triggers and a tool developed for the automatic generation of the SQL (Structured Query Language) code to create these trigger, besides showing its performance and comparing it to other techniques. Said method is relevant for the extraction of portions of selected information as it permits to combine conventional and real time ETL techniques.
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