1. BY: Mark Gruszecki

2.  What is a Recursive Query?  Definition(s) and Algorithm(s)  Optimization Techniques  Practical Issues  Impact of each Optimization  Conclusion

3. CREATE RECURSIVE VIEW R(d, i, j, v) AS ( SELECT 1, i, j, v FROM T UNION ALL SELECT d+1, R.i, T.j, R.v + T.v FROM R JOIN T ON R.j = T.i WHERE d < 8);

4.  Any kind of Hierarchical Data is more easily accessed using a Recursive Query.  For example, displaying Employees in an orginizational chart.

5.  A base table T is defined as T(i, j, v) with primary key (i, j) and v representing a numerical value.  Define the result table from a recursive query by R(d, i, j, v) with primary key (d, i, j).  The queries of interest are of the form  R[k] = T  T  T  …  T where  is the recursive query.  Let G = (V, E) be a directed graph with n vertices and m edges.  The algorithm to evaluate optimizations is:  R =

6. 1. Early evaluation of row select conditions. 2. Deleting Duplicate Rows. 3. Indexing base and result tables for efficient joins.

7.  Used on Queries of the form: SELECT i, j, v FROM R WHERE  Two Cases:  If the “WHERE” condition doesn’t participate in the JOIN condition of the recursion.  The “WHERE” condition is part of the JOIN in the recursion.

8.  Suppose we want to know which vertices of a graph are connected to a specific node (e.g. all dependants of a particular person).  What if G is complete, dense, sparse, or even a tree?  Queries are optimized by deleting duplicate rows at each step.

9.  Two Choices:  Index based on i and j.  Gives rise to an optimal Hash Join  Cannot uniquely identify rows  Index based on primary key of T and R  Can uniquely identify rows

10.  The possible size of a result table of a recursive query is |T| x |T| x … |T|.  In general, if there are n recursive steps and T has m entries, then there are m^n.

11.  Early Evaluation of Row Selection Conditions  Good in all cases  Deleting Duplicate Rows  Good in certain cases, but not necessary in all  Indexing Base and Result Tables for Efficient Joins  If G is highly connected, slight loss of performance (Hash Collisions).  Otherwise, this is the best optimization.

12.  Recursive Queries are an important tool to be exposed to when dealing with databases.  There are three types of optimizations of these queries discussed:  Early evaluation of row selections  Deleting duplicate rows  Indexing for more efficient joins  Every optimization is good, but some are more applicable in certain circumstances than others.

13.  Carlos Ordonez (2005) Optimizing Recursive Queries in SQL. Retrieved February 10, 2009 from IEEE Computer Science Digital Library  http://publib.boulder.ibm.com/infocenter/iseries/v5r4/index.jsp?topic=/rzajq/rzajqrcteexa mple.htm