Shekhar, ShashiLu, Chang-tienChawla, Sanjay2020-09-022020-09-021999-08-06https://hdl.handle.net/11299/215386A Join Index is a data structure used for processing join queries in databases. Join indices usepre-computation techniques to speed up online query processing and are useful for data-sets which are updated infrequently. The cost of join computation using a join-index with limited buffer space depends primarily on the page-access sequence used to fetch the pages of the base relations. Given the join-index, we introduce a suite of methods based on clustering to compute the joins. We derive upper-bounds on the lengths of the page-access sequences. Experimental results with Sequoia 2000 data sets show that the clustering method outperforms the existing methods based on sorting and online-clustering heuristics.en-USReport