XML publishing and enhanced data type support in cross-server distributed queries.
在跨服务器的分布式查询中支持XML发布和增强的数据类型。
You can have distributed queries inside the using clause that access databases on more than one server instance.
可在访问处于多个服务器实例中的数据库的子句中包含分布式查询。
Additional data types that can be used in cross-server distributed queries to built-in non-opaque SQL data types. They are.
从跨服务器分布式操作中可以使用的其他数据类型，扩展到内置的non - opaqueSQL数据类型。
The distinct data types must have exactly the same hierarchy and casts defined in all databases participating in the distributed queries.
在参与分布式查询的所有数据库中，各种数据类型必须定义有相同的层次结构和类型转换。
Users of a federated database system can pose distributed queries over data stored anywhere in the federated system, regardless of its location or the SQL dialect of the data source.
联邦数据库系统的用户可以对存储在联邦系统中任意位置的数据进行分布式查询，不管自己的位置在哪里，也不管数据源使用的是哪种SQL方言。
Before we describe the different types of queries and operations that you can perform on your federated system, we would like to first provide an overview of how a distributed query is processed.
在描述对联邦系统执行的不同类型的查询和操作之前，我们首先对分布式查询的处理过程作一个概述。
A JCache (JSR 107) interface to Memcache to provide fast, temporary distributed storage for caching queries and calculations.
一个通向Memcache的JCache (JSR 107)接口，提供快速、临时的分布式存储，用于缓存查询和计算。
If a good partitioning key is chosen, the data will be evenly distributed across the nodes, and for most, if not all, queries, the partitioning key will uniquely identify the node containing the data.
如果选定一个好的分区键，那么数据会均匀地分布在所有节点，对于大多数情况都是如此，如果不是这样，请进行查询，分区键将惟一地标识包含数据的节点。
These interfaces allow neither SQL queries nor stored procedures that use objects on both sources. Figure 1 shows a diagram of such a distributed application.
这些接口不允许SQL查询或存储过程同时使用多个数据源上的对象。
This paper used algorithm of minimum spanning tree to realized multi-join queries of distributed database and provided analyzing method.
本文用最小生成树算法实现了分布式数据库中的多元连接查询，并进行了算法的分析与设计。
But in DHT based P2P networks, similar documents are distributed randomly among peers with their data identifiers consistently hashed, which poses challenge on complex queries.
但是，在基于DHT的P 2 P网络中，内容相似的文档，其数据标识通过一致性哈希散列，均匀随机分布在节点空间中，不利于复杂查询的进行。
But in DHT based P2P networks, similar documents are distributed randomly among peers with their data identifiers consistently hashed, which poses challenge on complex queries.
但是，在基于DHT的P 2 P网络中，内容相似的文档，其数据标识通过一致性哈希散列，均匀随机分布在节点空间中，不利于复杂查询的进行。
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