Query processing in data intensive applications

A couple of research topics related to query processing in data intensive software programs are shown within this thesis. The first one relates to database concurrency control in mobile computing settings and the other relates to operator scheduling in data stream systems. In the research which linked to database concurrency management mechanism, experiments are executed to evaluate the suggested concurrency control algorithm called Read-Write Set Test for broadcast transaction.

In contrast, two different operator scheduling algorithms for data stream systems are unveiled in the research. In mobile computing environments, there is an implicit presumption that the server is able to broadcast regular data to cellular clients. Unless there is a special algorithm to address data broadcasting in a consistent and well-timed manner, this presumption is probably not valid. In the work, data broadcasting at the hosting server is formulated like a broadcast transaction that reads the full database in a very consistent way before broadcasting info to the mobile users in a broadcast cycle.

This problem is not simple as the broadcast transaction creates high interference to normal update transactions at the host. Some algorithms suggested by prior reports on reading the entire databases could be candidate solutions. However, those algorithms such as Shade Test possess some inadequacies in handling update transactions correctly. Recently, an algorithm called Read-Write Set Test is proposed to correct the loophole. Within this study, a series of simulation experiments are carried out to judge the efficiency of RWST for broadcast transaction over a wide range of system workloads. In data stream systems, the arrival pattern of data streams is bursty and unstable. In case a device cannot handle query processing tuples in an efficient manner, the computer may get into an overloaded state and might lead to many backlogged tuples waiting for processing. In the area of data stream systems, there are many investigations on the subject of query or operator scheduling. They mainly concentrate on how to minimize memory usage, reduce tuple delay, and boost output rate.

In these investigations, the objectives are concentrated on researching the need for system parameters in operator scheduling and enhancing the productivity and effectiveness of query processing and operator processes by scheduling query operators to an ideal sequence. Even there are numerous researches making use of static factors in operator scheduling, dynamic factor may be important to operator scheduling. So in this research, dynamic factors are considered. Besides, instead of scheduling operators in an individual query as assumed in conventional approaches, new algorithms are designed to schedule all operators as a whole for all query procesing in a system. Two new scheduling algorithms are presented in this research. They are Memory Monitoring (MM) and Data Stream Grouping (DSG). MM utilizes one of the system parameters – memory usage to calculate and allocate priority values to operators. MM helps to demonstrate the efficiency of using dynamic factors in operator scheduling. On the other hand, popular static factors (operator selectivity – s and processing time – t) are used in DSG to do operator scheduling in multiple-query multiple-data-stream environment….

Source: City University of Hong Kong

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