Abstract: Instead of executing a plurality of submitted transactions separately, each data item to be processed by the plurality of submitted transactions is retrieved only once, update operations of the plurality of transactions are executed consecutively on the retrieved data item in main memory, and only the last updated result is written in a database once. Two-phase locking technique and timestamp technique are used for multi-operation processing providing concurrency control of transactions in order to execute multiple synthetic transactions concurrently.

Abstract: A query processing system of a database using multi-operation processing includes a task retrieval unit for retrieving relational algebra as tasks from a query tree, a unit for dividing retrieved tasks into groups for each relation of database, a synthetic relational operation unit for creating a synthetic relational operation by collecting tasks having common sub-expression for the grouped tasks into sub-groups and creating a task of a synthetic relational operation for each sub-group, wherein when there is a plurality of tasks of join operation in the grouped tasks, the synthetic relational operation unit further divides the grouped tasks into sub-groups for each common sub-expression of join operation, collects a plurality of tasks of the join operation into a sub-group, and creates a single task of a synthetic join operation by using logical union to concatenate each task of the join operation collected in the sub-group.

Abstract: Instead of executing a plurality of submitted transactions separately, each data item to be processed by the plurality of submitted transactions is retrieved only once, update operations of the plurality of transactions are executed consecutively on the retrieved data item in main memory, and only the last updated result is written in a database once. Two-phase locking technique and timestamp technique are used for multi-operation processing providing concurrency control of transactions in order to execute multiple synthetic transactions concurrently.

Abstract: When queries written in SQL are converted into query trees by the query optimizer (S1102). The query processor finds tasks to be processed directly from the query trees (S1104), and if the next tasks performing operation on processing results of the tasks that can be processed directly are project operation, the query processor retrieves both the tasks that can be processed directly and the tasks of the project operation, and combines these tasks to create tasks that combined relational operations (S1106). The query processor checks whether there is any group in the group queue collecting tasks that access the same relation (S1108). If a group is found, the query processor adds these tasks into the group (S1112). Otherwise, the query processor creates a new group for these tasks, adds these tasks into the group, and insert the group into the group queue. The query processor further collects the tasks having common sub-expression into sub-groups (S1116).