deletions | additions       diff --git a/section_Challenegs_in_Bushy_Trees__.tex b/section_Challenegs_in_Bushy_Trees__.tex  index ba8c029..463b2fa 100644  --- a/section_Challenegs_in_Bushy_Trees__.tex  +++ b/section_Challenegs_in_Bushy_Trees__.tex 
...
Therefore the number of possible permutations are $S(N)*N!$. Unlike left-deep tree case, estimating the cost for all the possible bushy trees is computationally infeasible for moderately large N. Therefore it is required to come with a heuristic to select set of permutations for cost computations.Some heuristics considered are  \textbf{QUIKPICK-1000} \textit{QUIKPICK-1000}  Here we build pseudo-random joining trees . This approach can build trees very fast and  due to this nature we can build large number of trees and choose 1000 cheapest plans. While being simple and fast this approach may fail to come up with reasonable optimized plan.  \textbf{Greedy \textit{Greedy  Operator Order(GOO)} GOO maintains a set of join trees, each of which initially consists of one base relation. The algorithm then combines the pair of join trees with the lowest cost to a single join tree.This approach is capable of building join orders fast enough. Advantage of this approach is due to the evaluation of intermediate results. [L. Fegaras. A new heuristic for optimizing large queries. In  DEXA, pages 726–735, 1998.] have shown the superiority of this approach compared with others