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抽取模型是我们为仪表板准备数据时的另一种选择。
顾名思义，抽取模型是把目标数据库的数据在建模时抽取并缓存下来，查询时取用缓存数据并返回结果。
相对于直连模型来说，抽取模型可以构建跨数据源的数据模型，以更加完整的业务建模取代简单的物理模型。
并且抽取模式可以根据不同的需求指定不同刷新频率，适合数据量非常大的场景。
例如，一家公司有许多不同类型的数据，如产品数据、销售数据、员工数据等保存在不同的数据库表中。甚至这些数据可能来自不同的软件模型，比如来自 ERP 系统的销售数据、来自 OA 系统的员工数据、来自 CRM 系统的生产数据。
而所有这些系统都部署在不同类型的数据库中，有些是Oracle， 有些是 SQL Server， 最后需要构建一个数据模型， 并将其显示在一个仪表板中。其中产品数据、员工信息等不需要每天缓存，但对于销售数据则需要高频缓存， 比如每10分钟一次。此时就需要支持缓存，并在表级别上用不同的频率刷新数据。