  We approximate analytic queries on streaming data with a weighted reservoir
sampling. For a stream of tuples of a Datawarehouse we show how to approximate
some OLAP queries. For a stream of graph edges from a Social Network, we
approximate the communities as the large connected components of the edges in
the reservoir. We show that for a model of random graphs which follow a power
law degree distribution, the community detection algorithm is a good
approximation. Given two streams of graph edges from two Sources, we define the
{\em Community Correlation} as the fraction of the nodes in communities in both
streams. Although we do not store the edges of the streams, we can approximate
the Community Correlation and define the {\em Integration of two streams}. We
illustrate this approach with Twitter streams, associated with TV programs.
