Efficient Indexing of Compressed Time-series Data
ServiceNow Computer Science, 2019-20
Liaison(s): James Capaldo ’92, Magaly Drant, Thejaka Kanewala, Meg Sharkey, Vincent Seguin
Advisor(s): Geoff Kuenning
Students(s): Garrett Cheadle, Alanna DeMuro, Levente Papp, Neeta Rao (PM-F), Cassie Rossi (PM-S)
The ServiceNow 2019–2020 Clinic team has designed a long-term storage database for time-series data. Incoming data is compressed when added to the long-term storage database, and therefore the data is stored in irregularly sized segments. The team has developed an efficient indexing strategy to access compressed blocks of time-series data in the database.