Benefits and limitations of bigtable.
BigTable的优点和限制。
BigTable is not a relational database.
BigTable不是一个关系型的数据库。
Figure 4 shows the upload form for bigtable.
图4显示的是针对Bigtable实现的上传表单。
That class handles all our Bigtable-related calls.
该类将处理所有与Bigtable相关的调用。
Exporting data from BigTable is even more problematic.
从BigTable导出数据更成问题。
To provide some structure to all that data, Google USES BigTable.
为了给全部这些数据提供一些结构，Google使用了大表。
Now we have a new schema that will allow us to store our feed using Bigtable.
现在具备了允许使用Bigtable存储提要的新模式。
Here, you're looking for the affiliation of the authors of the Bigtable paper.
这里，您将寻找这篇Bigtable论文的作者的从属关系。
In fact, both Bigtable and relational databases use the blob type to store binaries.
事实上，Bigtable和关系数据库都使用blob数据类型来存储二进制文件。
HBase and Bigtable promote a new way of thinking about the data-processing pipeline.
HBase和Bigtable提出了一种关于数据处理管道的新的思维方式。
HBase is a key value store akin to BigTable which stores data in Hadoop's DFS file system.
HBase是类似BigTable的键值存储模型，将数据存储于Hadoop的DFS文件系统。
Google's BigTable has also been studied by the community even though it is not open source.
而Google的BigTable尽管并不开源，也得到了社区的广泛研究。
By querying a feed from Bigtable, we are really just using Bigtable as another caching layer.
通过查询Bigtable中的提要，实际上使用了Bigtable作为另一个缓存层。
The actual bytes of whatever was uploaded aren't stored in the bean as they were in Bigtable.
所上传的实际字节并没有像Bigtable一样存储在这个Bean中。
In both cases, the native storage will not be used and the objects will be stored in Bigtable instead.
在这两种情况下，将不会使用自带的存储方式，取而代之的是将对象保存在Bigtable中。
Bigtable is a distributed storage system for managing structured data (see Resources for more information).
Bigtable是用于管理结构化数据的分布式存储系统(有关更多信息，请参阅参考资料)。
Listing 6 shows how you populate the articles table with information about the Bigtable journal article.
清单6显示如何使用关于Bigtable期刊文章的信息填充articles表。
For user services and entries, we are using a DB class for querying Bigtable. This class is shown below.
对于用户服务和条目，我们将使用db类查询Bigtable。
The largest BigTable instance manages about 6 petabytes of data spread across thousands of machines, Dean said.
Dean说，大表管理的最大一个数据表格有6petabytes大小，覆盖上千台机器。
Given that, Todd Outlines some other principles to keep in mind for an optimized use of BigTable storage system.
在以上论述的基础上，Todd针对优化使用BigTable存储系统总结了若干必须牢记的原则。
Then we'll work through the servlet implementation, which consists of three abstract methods customized for Bigtable.
然后我们将完成Servlet实现，它是由三个专门为Bigtable定制的抽象方法组成的。
Difficulty importing and exporting data: Another major issue with BigTable is the inability to import and export data.
导入和导出数据的难题：BigTable的另一个主要问题是无法导入和导出数据。
Unlike Bigtable, SimpleDB doesn't care what you name each item and in fact, it doesn't provide you with a key generator.
不同于Bigtable,SimpleDB不在乎您为每个项目如何命名，事实上，它不会为您提供一个主键生成器。
Google's BigTable is a proven technology for producing scalable applications, however, and you can build on top of that.
Google的BigTable是一种已经经过检验的技术，可用来生成可伸缩的应用程序，然而，您还可以在此基础上进行构建。
We do not want that, so we will make greater use of the GAE's data-modeling and Bigtable features to improve performance.
这并不是我们想要的结果，因此将更多地使用GAE的数据建模和Bigtable特性来提高性能。
BigTable is now used by over sixty Google products and projects as the platform for storing and retrieving structured data.
目前，BigTable正在为Google六十多种产品和项目提供存储和结构化数据获取的支撑平台。
The reason that we chose open source is because we felt that an open source implementation of Bigtable would be inevitable.
我们选择开源的理由是我们觉得注定会出现一个Bigtable的开源实现。
This makes use of the GAE's user's API to look up the user object based on the E-mail, then querying Bigtable for the account.
这将使用GAE的用户的API根据电子邮件查找user对象，然后查询Bigtable查找帐户。
Google engineers claim that the response time of data queries in BigTable is only determined by the size of the result dataset.
Google工程师宣称BigTable中数据查询的响应时间只根据结果数据集的大小确定。
We can now focus on seeing how each of the GAE storage options interacts with the application workflow, starting with Bigtable.
我们现在可以关注于GAE存储方法是如何与应用程序工作流程进行交互的，我们首先从Bigtable开始。
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