Managing peer database transactions

今天的教育、科学、商业和政府所依赖的许多数据源已经产生了越来越多的异构、网络化和以各种格式存储的大量数据。我们过去的工作有助于建立关系数据库网络（称为对等数据库，或简称为对等数据库），使如此巨大的数据量可供共享。对等数据库使用对等（P2P）网络共享数据。P2P网络是点对点的通信基础设施，用于在共享数据之前建立熟人。确保以语义上有意义的方式跨异构边界共享数据一直是我们研究的核心。 在与他人的合作中，我们已经产生了一个原型对等数据库管理系统（PDBMS），使用所谓的映射表来解决异构性问题。映射表是数据值之间以及不同对等点上的模式元素之间的对应关系。使用映射表，PDBMS通常与远程对等体建立熟人，使用源自熟人对等体的数据回答查询，并将本地更新传播到远程对等体。我们的研究计划有两个主要目标，这是设计先进的交易模型的PDBMS设置，并实现这些交易模型的顶部我们现有的PDBMS基础设施。由于PDBMS是类似于传统的多数据库系统中的本地数据源不集成，而是协调，我们仔细研究了传统的多数据库系统提出的事务模型，并放宽了许多假设，以及我们添加新的更适合的PDBMS设置。我们处理的主要问题是本地对等事务之间的关系，后者的一致性，并发控制和恢复在大量的同行。 我们的目标是使面向最终用户的互联网数据共享的愿景成为可能。用户只需要关注他们的本地数据，而与远程对等体的互操作性的复杂性将在系统级尽可能自动地处理。

Many of the data sources upon which today's education, science, business, and government depend have been generating increasingly heterogeneous, networked, and vast amounts of data stored in a variety of formats. Our past work has contributed to building networks of relational databases (called peer databases, or simply peers) that make such a gigantic amount of data available for sharing. Peer databases share data using a peer-to-peer (P2P) network. A P2P network is point-to-point communication infrastructure which is used by peers to establish acquaintances prior to sharing data. Ensuring data sharing across heterogeneous boundaries in a semantically meaningful way has been at the core of our research. In collaroration with others, we have produced a prototype peer database management system (PDBMS) that uses the so-called mapping tables to solve the heterogeneity problem. Mapping tables are correspondences between data values as well as between schema elements at different peers. Using mapping tables, a PDBMS typically establishes acquaintances with remote peers, answers queries using data originating in acquainted peers, and propagate local updates to remote peers. Our research program has two main objectives which are to design advanced transaction models for the PDBMS setting, and to implement these transaction models on top our existing PDBMS infrastructure. Since PDBMSs are similar to traditional multidatabase systems in which the local data sources are not integrated, but rather coordinated, we closely examine the transaction models proposed for traditional multidatabase systems and relax many of their assumptions, as well as we add new ones that are more suitable for the PDBMS setting. The main issues we deal with are the relationship among local peer transactions, the consistency of the latter, concurrency control and recovery across a large amount of peers. We aim at making the vision of end-user oriented Internet data sharing possible. Users will only need to focus on their local data while the intricacies of the interoperability with remote peers will be handled as automatically as possible at the system level.