The Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) is a neutral hydrogen survey (HI) that is running on the Australian SKA Pathfinder (ASKAP), a precursor telescope for the Square Kilometre Array (SKA). The goal of WALLABY is to use ASKAP's powerful wide-field phased array feed technology to observe three quarters of the entire sky at the 21 cm neutral hydrogen line with an angular resolution of 30 arcseconds. Post-processing activities at the Australian SKA Regional Centre (AusSRC), Canadian Initiative for Radio Astronomy Data Analysis (CIRADA) and Spanish SKA Regional Centre prototype (SPSRC) will then produce publicly available advanced data products in the form of source catalogues, kinematic models and image cutouts, respectively. These advanced data products will be generated locally at each site and distributed across the network. Over the course of the full survey we expect to replicate data up to 10 MB per source detection, which could imply an ingestion of tens of GB to be consolidated in the other locations near real time. Here, we explore the use of an asymmetric database replication model and strategy, using PostgreSQL as the engine and Bucardo as the asynchronous replication service to enable robust multi-source pools operations with data products from WALLABY. This work would serve to evaluate this type of data distribution solution across globally distributed sites. Furthermore, a set of benchmarks have been developed to confirm that the deployed model is sufficient for future scalability and remote collaboration needs.
翻译:Widefield ASKAP L-band Legacy All-sky Blind survey (WALLABY) 是一项中性氢勘测(HI)项目,运行于澳大利亚SKA Pathfinder (ASKAP)天文望远镜,该望远镜是SKA的前置阵列。WALLABY旨在使用ASKAP强大的宽视场相干阵列技术,在21厘米中性氢线上观测整个天空的四分之三,达到30角秒的角分辨率。在澳大利亚SKA区域中心(AusSRC)、加拿大射电天文数据分析倡议(CIRADA)和西班牙SKA区域中心原型(SPSCR),进行的后处理活动将生成在源目录、动力学模型和图像切片方面的高级数据产品,并公开提供。这些高级数据产品将在每个站点本地产生并在网络上分发。在整个调查过程中,我们预计每个源检测将复制高达10 MB的数据,这可能意味着需要凝聚数十GB的数据来实现几乎实时处理。在这里,我们探讨了非对称数据库复制模型和策略的应用,使用PostgreSQL作为引擎和Bucardo作为异步复制服务,以使WALLABY的数据产品能从源池中提供稳健的多源操作。此项工作旨在评估这种数据分发解决方案在全球分布的站点上的应用效果。此外,我们还开发了一组基准测试,以确认所部署的模型对未来的可扩展性和远程协作需求是足够的。