A Queriable Repository for HST Telemetry Data, a Case Study in using Data Warehousing for Science and Engineering
Joseph A. Pollizzi, K. Lezon · ASPC · 1998
The Hubble Space Telescope (HST) generates on the order of 7,000 telemetry values, many of which are sampled at 1Hz, and with several hundred parameters being sampled at 40Hz. Such data volumes would quickly tax even the largest of processing facilities. Yet the ability to access the telemetry data in a variety of ways, and in particular, using ad hoc (i.e., no a priori fixed) queries, is essential to assuring the long term viability and usefulness of this instrument. As part of the recent NASA initiative to re-engineer HST’s ground control systems, a concept arose to apply newly available data warehousing technologies to this problem. The Space Telescope Science Institute was engaged to develop a pilot to investigate the technology and to create a proof-of-concept testbed that could be demonstrated and evaluated for operational use. This paper describes this effort and its results. 1. HST as a Telemetry Source The Hubble Space Telescope (HST) is well a known source of significant and substantial amounts of Astronomy data. Less known, however, is that the HST is also one of the most highly instrumented non-manned platforms ever launched. Over 6,000 telemetry points are monitored on the HST. These “monitors” cover practically every aspect of the platform and of the various instrument environmental and state conditions. In addition to routine study and problem analysis, we use telemetry to look for long term trends in how the platform is behaving. By carefully studying such trends, we hope to uncover potential problems before they arise. In this way, we plan to extend the scientific utility of this unique instrument as far as possible through its planned lifetime (now scheduled through to 2010). 1.1. Complications in Querying Telemetry Values Since telemetry values are sampled at widely different rates, looking for a “causeeffect” relationship between monitors can rarely be found by identifying time matches between records. Rather, the queries tend to look for overlapping time windows when the monitors acquire some state. We have coined the term, “Fuzzy Query” to describe this kind of query. Using a stylized SQL, a fuzzy query typically appears as: