A stream processing approach for temporal query processing and optimization is discussed. Given properly sorted data, the implementation of temporal joins and semijoins as stream processors can be very effective. Also discussed are the tradeoffs among sort orders, the amount of local workspace, and multiple scans over input streams; in particular, the authors are interested in the effect of sort ordering on the local workspace. They present stream processing algorithms for various temporal joins and semijoins, and their workspace requirements for various data sort orderings. Finally, it is shown how semantic query optimization can play an important and natural role in optimization of temporal queries.< &gt;