如何天青DocumentDB规模有多大？而且，我需要担心吗？ [英] How does Azure DocumentDB scale? And do I need to worry about it?
问题描述
我已经得到了的outgrowing SQL Azure的应用程序 - 这个价格，我愿意付出，无论如何 - 我兴趣调查天青DocumentDB。在preVIEW显然具有明显的可扩展性限制（如描述
I've got an application that's outgrowing SQL Azure - at the price I'm willing to pay, at any rate - and I'm interested in investigating Azure DocumentDB. The preview clearly has distinct scalability limits (as described here, for instance), but I think I could probably get away with those for the preview period, provided I'm using it correctly.
因此，这里是我有问题。我怎么需要设计我的应用程序能够利用Azure的DocumentDB的内置可扩展性？举例来说，我知道，与天青表的存储 - 这便宜，但<击>可怕高度有限的选择 - 你需要在结构两步层次所有的数据：PartitionKey和RowKey。只要你这样做（这是在真实世界中的应用以及亲近不可能的），ATS（据我所知）四处移动分区在幕后，从机器到机器，让你得到近乎无限的可扩展性。真棒，你从来没有去想它。
So here's the question I've got. How do I need to design my application to take advantage of the built-in scalability of the Azure DocumentDB? For instance, I know that with Azure Table Storage - that cheap but awful highly limited alternative - you need to structure all your data in a two-step hierarchy: PartitionKey and RowKey. Provided you do that (which is nigh well impossible in a real-world application), ATS (as I understand it) moves partitions around behind the scenes, from machine to machine, so that you get near-infinite scalability. Awesome, and you never have to think about it.
与SQL Server扩展很显然要复杂得多 - 你需要设计自己的分片系统，处理找出有问题的碎片坐在哪个服务器，等等。可能的，而且做对相当可扩展性，但复杂和痛苦的。
Scaling out with SQL Server is obviously much more complicated - you need to design your own sharding system, deal with figuring out which server the shard in question sits on, and so forth. Possible, and done right quite scalable, but complex and painful.
那么，如何与DocumentDB可扩展性的工作？它有望任意扩展性，但如何做幕后的存储引擎的工作？我看到它数据库，每个数据库可以有珍藏的一些数，等等。但如何做它的可扩展性的任意地图，这些其他概念？如果我有一个包含数亿行的SQL表，我该怎么得到我需要的，如果我把所有这些数据转化为一个集合的可扩展性？或者，我需要手动š$ P $垫它横跨多个集合，分片不知何故？或跨多个数据库的？或者是莫名其妙DocumentDB足够聪明，从多台机器上凝聚了高性能的方式查询，没有我不必去想任何呢？还是...？
So how does scalability work with DocumentDB? It promises arbitrary scalability, but how does the storage engine work behind the scenes? I see that it has "Databases", and each database can have some number of "Collections", and so forth. But how does its arbitrary scalability map to these other concepts? If I have a SQL table that contains hundreds of millions of rows, am I going to get the scalability I need if I put all this data into one collection? Or do I need to manually spread it across multiple collections, sharded somehow? Or across multiple DB's? Or is DocumentDB somehow smart enough to coalesce queries in a performant way from across multiple machines, without me having to think about any of it? Or...?
我一直在四处寻找，并没有发现对如何处理这个任何指导。非常有兴趣在别人发现或者什么MS建议。
I've been looking around, and haven't yet found any guidance on how to approach this. Very interested in what other people have found or what MS recommends.
推荐答案
更新：截至2016年4月的，DocumentDB不断推出的分区收集它允许你向外扩展，并利用服务器端的分区。
Update: As of April 2016, DocumentDB has introduced the concept of a partitioned collection which allows you scale-out and take advantage of server-side partitioning.
一个单一的数据库DocumentDB实际上可以扩展到文档存储通过集合划分无限量的（换句话说，你可以通过添加更多的集合向外扩展）。
A single DocumentDB database can scale practically to an unlimited amount of document storage partitioned by collections (in other words, you can scale out by adding more collections).
每个集合提供10 GB的存储空间，和吞吐量的变化量（基于性能级别）。集合还提供了文档存储和查询执行范围;并且也是其中包含的所有文件的交易领域。
Each collection provides 10 GB of storage, and an variable amount of throughput (based on performance level). A collection also provides the scope for document storage and query execution; and is also the transaction domain for all the documents contained within it.
来源： http://azure.microsoft.com/en -us /文档/文章/ documentdb-管理/
下面是一个<一个href=\"http://blogs.msdn.com/b/documentdb/archive/2014/12/03/scaling-a-multi-tenant-application-with-azure-documentdb.aspx\"相对=nofollow>链接到一个博客帖子我对上一DocumentDB多租户应用程序扩展和数据分区中写道。
Here's a link to a blog post I wrote on scaling and partitioning data for a multi-tenant application on DocumentDB.
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