Application of Recursive Query on Structured Query Language Server

The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done correctly.Structured query language(SQL)is a database language and is used to manipulate data.In Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its disadvantages.Common table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive CTE.Hierarchical data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive CTEs.The recursive query is illustrated and implemented on some simple hierarchical data.In addition,one business case study is brought forward and the solution using recursive query based on CTE is shown.At the same time,stored procedures are programmed to do the recursion in SQL.Test results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax.

Magic Sets Revisited

This paper distinguishes among three kinds of linear recursions: canonical strongly linear recursion (CSLR), non-interdependent linear recursion (NILR) and interdependent linear recurstion (ILR) and presents an optimal algorithm for each. First, for the CSLRs, the magic-set method is refined in such a way that queries can be evaluated efficiently. Then, for the NILRS and ILRs, the concept of query dependency graphs is introduced to partition the rules of a program into a set of CSLRs and the computation is elaborated so that the oplimization for CSLRs can also be applied.

Counting and Topological Order

The counting method is a simple and efficient method for processing linear recursive datalog queries. Its time complexity is bounded by O(n.e), where n and e denote the numbers of nodes and edges, respectively, in the graph representing the input relations. In this paper, the concepts of heritage appearance function and heritage selection function are introduced, and an evaluation algorithm based on the computation of such functions in topological order is developed. This new algorithm requires only linear time in the case of non-cyclic data.

Graph Traversal and Top-Down Evaluation of Logic Queries

In this paper, an optimal method to handle cyclic and acyclic data relations in the linear recursive queries is proposed. High efficiency is achieved by integrating graph traversal mechanisms into a top-down evaluation. In such a way the subsumption checks and the identification of cyclic data can be done very efficielltly First, based on the subsumption checks, the search space can be reduced drastically by avoiding any redundant expansion operation. In fact, in the case of non-cyclic data, the proposed algorithm requires only linear time for evaluating a linear recursive query. On the other hand, in the case of cyclic data, by using the technique for isolating strongly connected components a lot of answers can be generated directly in terms of the intermediate results and the relevant path information instead of evaluating them by performing algebraic operations. Since the cost of generating an answer is much less than that of evaluating an answer by algebraic operations, the time consumption for cyclic data can be reduced by an order of magnitude or more.