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Abstract:
Numerous applications such as stock market or medical information systems
require that both historical and current data be logically integrated into a
temporal database. The underlying access method must support different forms of
“time-travel” queries, the migration of old record versions onto inexpensive
archive media, and high insertion and update rates. This paper presents an
access method for transaction-time temporal data, called the log-structured
history data access method (LHAM) that meets these demands. The basic principle
of LHAM is to partition the data into successive components based on the
timestamps of the record versions. Components are assigned to different levels
of a storage hierarchy, and incoming data is continuously migrated through the
hierarchy. The paper discusses the LHAM concepts, including concurrency control
and recovery, our full-fledged LHAM implementation, and experimental
performance results based on this implementation. A detailed comparison with
the TSB-tree, both analytically and based on experiments with real
implementations, shows that LHAM is highly superior in terms of insert
performance, while query performance is in almost all cases at least as good as
for the TSB-tree; in many cases it is much better.