Data streams are long, relatively unstructured sequences of characters that contain information such as electronic mail or a tape backup of various documents and reports created in an office. A conceptual framework is presented, using relational algebra and relational databases, within which data streams may be queried. As information is extracted from the data streams, it is put into a relational database that may be queried in the usual manner. The database schema evolves as the user's knowledge of the content of the data stream changes. Operators are defined in terms of relational algebra that can be used to extract data from a specially defined relation that contains all or part of the data stream. This approach to querying data streams permits the integration of unstructured data with structured data. The operators defined extend the functionality of relational algebra in much the same way that the join does relative to the basic operators select, project, union, difference, and Cartesian product.>

An analytic formula for the delay due to two-phase locking is developed in terms of mean values for the input parameters using an open queuing network model in equilibrium. The results of simulations, using various realistic probability distributions governing the number of locks that transactions request, are presented to validate the formula. Reasonably good accuracy is achieved for gamma distributions over a wide range of parameter settings. The simulations also provided evidence that the rate of deadlock, often disregarded in the literature, can be high in certain heavily utilized databases.>