We
present an innovative approach to replication management, called freshness-aware
scheduling (FAS). The intention of freshness-aware scheduling is to trade query
performance for freshness of data. Consequently, FAS introduces a new quality-ofservice
parameter that allows queries to specify an explicit freshness limit for the
data accessed. If some queries agree to be evaluated on older data, update propagation
can be interleaved with query processing more efficiently. This results in an
overall better system performance and only a minimal slowdown of both queries
and updates. In particular, it enables clients to request and access up-to-date data.
The remainder of this chapter is organised as follows: In the next two sections, we
will first present a scalable infrastructure for an unified OLTP/OLAP database cluster
and discuss physical data design alternatives for cluster-based online decision support
systems. The subsequent two sections introduce query routing and freshness-aware
scheduling, and also discuss related work. Both techniques have been prototypically
implemented as part of the PowerDB project at ETH Zurich and in the Evaluation
section, we report on the results of a comprehensive performance evaluation with
our prototype system. The last section concludes the chapter.
Towards an Unified Architecture for
OLTP.and.
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