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SQL中Dataverse虚拟表之三种延迟模式
SapotaCorp · 2026-05-24 · via DEV Community

虚拟表使Dataverse得以呈现存于他处之数据——SQL Server、Cosmos DB、REST API——而无需将其复制入Dataverse。用户所见之体验,与寻常表格无异:视图、表单、查询、关联。其根本检索,每读必越网线,至外部之源。

纸面观之,其引人之趣昭然:无同步之弊,无重复之扰,恒保其新。然实践之中,迟滞之性乃决其是否合乎用。今列三式,凡议虚拟之表者,必以之较之,并陈其规。

虚拟之表者何(虚拟之表者非何)

虚拟之表于Dataverse中,其定义在:

  • 一虚拟之实体(表之式)
  • 虚拟实体提供者(为Dataverse与外部数据源之桥梁)
  • 元数据映射(外部数据源之列名与类型至Dataverse视图)

当用户开启虚拟表之视图时,Dataverse即唤此提供者。提供者询外部数据源。结果回传,乃呈现之。

至要者:

  • 无数据存于Dataverse。虛表不存一行。
  • 与原表之關係有制。可自原表查虛表;不可有匯總,亦不可有涉虛表之複雜跨表查詢。
  • 無審計,無欄級安全,無重複檢測。依賴存於Dataverse之功能皆不適用。

吾所行之标尺

未尝定于虚案,先设三境以测之。

  1. 单行检索:依主键取一行。"启详单。"
  2. 列表视:以滤器取50行。"载活跃订单之默认视。"
  3. 集成写入及回读:原表行即得创建,与虚表相系;表单立时显合数据。

量端至端迟滞,自Power平台主调至应答可呈。目:

  • 单行索:五百毫秒以下
  • 列视:一千二百毫秒以下
  • 写入及回读:二秒以下

虚拟表之后有 SQL Server,属地区域

此为 Azure 区域内 Dataverse 环境同地托管之 SQL Server 数据库之典型基准,常态负载下:

  • 单行检索:150-300毫秒(佳)
  • 列表视之:400-900毫秒(佳)
  • 写入并回读:800-1500毫秒(尚可,可运作)

主导之费,乃网络往返加SQL查询之计划。同址SQL于多数情境中表现尚可。

此法可行之时:索购物史,引据数据,其本源在库;作报类观,数据浩繁,复之非宜。

范式二:虚拟之案后,有 REST API,经由互联网路由之

API寓于客户之基构或第三方之服务,非共址:

  • 单行检索:800-1500毫秒(微弱)
  • 列视:2000-5000毫秒(劣)
  • 写及回读:3000-6000毫秒(失二秒之限)

API之呼增每呼基线迟滞300-800毫秒。列五十行需多后端查询者,积速甚速。

此法不效时:凡用户目之所及,一时显五十行以上者。逐表索骥可行;视窗载入则不然。

此法可行时:低频场景,用户可忍加载之旋,所引数据鲜变,可纵力缓存。

模式三:虚表配供端缓存

巧思之设:于数据宇宙与外源间,置一缓存(Redis,Cosmos DB 配时效,或 SQL Server 充缓存之表)。虚拟实体之供,取自缓存;别一之程,恒使缓存新自真源。

  • 单行索检:八十至百五十毫秒(优)
  • 列观之览:二百至五百毫秒(优)
  • 写而复读:四百至八百毫秒(良)

权衡:缓存引致陈旧。 backing source 中更改之行列,或需秒至分钟,视缓存刷新之策而定,方显于 Dataverse。

此模式得效之时:读量高而写量低,用户可容短暂陈旧。多见于报章引用之数据境。

当此模式繁复时:缓存今为独立系统,以监之、使无效、令其老。增操作之面.

择虚拟表之前,有三问.

  1. 数据几何?

不满十万行,且增缓:但录之入本Dataverse表,经数据流。得平台全备之能,无性能之患。

逾千萬行,或迅疾增長:虛擬表格漸顯其美。藏十萬行於Dataverse,耗容量費。

其间:审度他二者之问而决之。

  1. 数据更迭几何?

变故鲜有(参考数据、史册):土生土长之表,以数据流周期同步,已足矣。虚拟之表,于汝无益。

更迭频仍(如运行时数据、实时交易、物联网遥测):若源支持,虚拟表或可适宜;否则,需同步加缓存之模式。

  1. 人何以与之交?

游目观览,深入探赜(列视,详表):若迟滞可容,依式一或式三,虚拟之表可用。

批量操作(大规模编辑、导入、跨数百万行进行报告查询):虚拟表非宜。外源将遭重击;数据域将超时。

查找字段目标(原生表引用虚拟表之行):可行,然任何导航将中断汇总与计算列。

去年吾辈所为之比试

有客欲其SQL Server之十五万行订单史,得见于Dynamics Sales之界面。议其三策:

  • 尽录十五万行于Dataverse:耗Dataverse之容量,月更其同步,滞数据至二十四时。
  • 设虛表,直通SQL:实时数据,无存储之费,每视之迟滞四百至九百毫秒。
  • 虚拟表配以Cosmos DB缓存:近实时数据(缓存TTL三十秒),读取迅捷(150-300毫秒),然增操作之繁复.

吾等于UAT环境克隆中,试三法。一法之费,仅Dataverse存储计年十二千。二法之观,峰时犹滞(SQL争用)。三法则胜于价与效。

唯有一忌:择三则需投运以养缓存。吾辈筑监控之台,复于其上设缓存预热之序。客户内人继之,九载未尝有恙。

吾辈不荐虚席之时

有三境,吾等导客远离虚表:

  • 重写之境。虛表供應者必須實現創/改/刪,而排錯供應端交易語義之難,遠甚於排錯尋常之增刪改查。
  • 需求特徵,欲求虛擬世界本然之行為。欄級安全、審計、警報、重複檢測、業務流程流轉——此諸者,皆不適於虛表。
  • 参考数据量稀少。不满五千行,但可直抄。所省工程之工,值容量之费。

虚拟表乃专应规模与数据新度之器。然于多数"别处已有旧数据"之境,非首择之策。数据宜抄,除非有特异之由。