Temporal view self-maintenance

View self-maintenance refers to maintaining materialized views without accessing base data. Self-maintenance is particularly useful in data warehousing settings, where base data comes from sources that may be inaccessible. Self-maintenance has been studied for nontemporalviews, but is even more important when a warehouse stores temporal views over the history of source data, since the source history needed to perform view maintenance may no longer exist. This paper tackles the self-maintenance problem for temporal views. We show how to derive auxiliary data to be stored at the warehouse so that the warehouse views and auxiliary data can be maintained without accessing the sources. The temporal view self-maintenance problem is considerably harder than the nontemporal case because a temporal view may need to be maintained not only when source data is modified but also as time advances, and these two dimensions of change interact in subtle ways. We also seek to minimize the amount of auxiliary data required, taking into account different source capabilities and update constraints that are common in temporal warehousing scenarios. While our framework and algorithms are presented using a true temporal data model, our results apply directly to the ad-hoc temporal support (i.e., timestamp attributes in the standard relational model) commonly found in data warehouses today.

Duke Scholars

Author Jun Yang Computer Science