  This paper proposes a method for semiparametric regression analysis of
large-scale data which are distributed over multiple hosts. This enables
modeling of nonlinear relationships and both the batch approach, where analysis
starts after all data have been collected, and the real-time setting are
addressed. The methodology is extended to operate in evolving environments,
where it can no longer be assumed that model parameters remain constant over
time. Two areas of application for the methodology are presented: regression
modeling when there are multiple data owners and regression modeling within the
MapReduce framework. A website, realtime-semiparametric-regression.net,
illustrates the use of the proposed method on United States domestic airline
data in real-time.
