基于开源的ATLAS状态数据管理系统实施经验
Experience with the Open Source based implementation for ATLAS Conditions Data Management System
摘要：
在高能物理实验中，数据通常被看作是除事件数据本身之外的重建所需的所有数据。这包括各种缓慢发展的数据，如探测器对准、校准和鲁棒性，以及来自探测器控制系统的数据。此外，每个条件数据对象都与有效性时间间隔和版本相关联。除此之外，通常对标记条件数据对象的集合很有用。这些问题已经被调查和数据模型已被提出，并用于不同的实现基于商业DBMS，无论是在欧洲核子研究中心和BaBar实验。ATLAS复杂触发器的特殊情况需要在线访问校准和对齐数据，这带来了新的挑战，必须使用灵活且可定制的解决方案来满足这些挑战。受到ATLAS挑战的激励，我们开发了一种基于开源RDBMS的替代实现。几个问题进行了调查土地将在本文中描述：-最好的方式来映射的条件数据模型到关系数据库的概念，考虑到什么是预见到的最频繁的查询。- 最适合解决可伸缩性问题的集群模型。- 进行了广泛的测试，并将进行描述。这些测试非常有希望的结果吸引了HEP社区的关注，并推动了进一步的发展。
英文摘要：
Conditions Data in high energy physics experiments is frequently seen as every data needed for reconstruction besides the event data itself. This includes all sorts of slowly evolving data like detector alignment, calibration and robustness, and data from detector control system. Also, every Conditions Data Object is associated with a time interval of validity and a version. Besides that, quite often is useful to tag collections of Conditions Data Objects altogether. These issues have already been investigated and a data model has been proposed and used for different implementations based in commercial DBMSs, both at CERN and for the BaBar experiment. The special case of the ATLAS complex trigger that requires online access to calibration and alignment data poses new challenges that have to be met using a flexible and customizable solution more in the line of Open Source components. Motivated by the ATLAS challenges we have developed an alternative implementation, based in an Open Source RDBMS. Several issues were investigated land will be described in this paper: -The best way to map the conditions data model into the relational database concept considering what are foreseen as the most frequent queries. -The clustering model best suited to address the scalability problem. -Extensive tests were performed and will be described. The very promising results from these tests are attracting the attention from the HEP community and driving further developments.
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