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Apply just the simple filtering predicates and do a Cartesian join with the resulting rows. We have 400 rows extracted from table t1, and 200 rows extracted from t2, so the Cartesian join is 80,000 rows. But there is one more predicate to apply to reduce that 80,000 rows down to the final result set, the predicate that represents the join condition. To apply this predicate, we look at it in two different ways, namely: t2.join1 = :unknown_value or :unknown_value = t1.join1 Then we simply pick whichever one of these two conditions is the most selective. And, as you learned in 3, the selectivity of column = :bind_variable is either the density or 1/ num_distinct. If there are multiple conditions, we simply apply the rules (which we also saw in 3) for combining predicates allowing for the special sanity checks introduced by 10g and the answer drops out. I d like to thank Benoit Dageville of Oracle Corporation for giving me this insight in a conversation we had at Oracle World 2004. I ve found it a very helpful way to visualize some of the effects of different conditions.

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// spaceTypeColors tell us how to draw the tiles when displaying the // board at the console. static initonly array<ConsoleColor>^ spaceTypeColors = { ConsoleColor::Gray, ConsoleColor::Cyan, ConsoleColor::Red, ConsoleColor::Blue, ConsoleColor::DarkRed, ConsoleColor::Red }; // the gameboard representing all played tiles array<Tile^, 2>^ gameBoard; // the bag, containing the tiles that have not yet been drawn List<Tile^>^ bag; // an array of the amount of each tile static initonly array<int>^ tilePopulation = gcnew array<int> { 2, 9, 2, 2, 4, 12, 2, 3, 2, 9, 1, 1, 4, 2, 6, 8, 2, 1, 6, 4, 6, 4, 2, 2, 1, 2, 1 }; int nPlayer; // the number of players in this game int playerNum; // the current player int moveNum; // count of the number of moves Random^ random; // a random number generator bool gameOver; // set to true when a condition results in the end of the game bool endBonus; // true at the end of the game when a player uses up all of // his or her tiles

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If you are still working with 8i, the formulae supplied by MetaLink for join selectivity and join cardinality are correct, although the note could be enhanced to point out that The selectivity formula simply has to be repeated across all columns of an N-column join. A single join predicate involving an unbounded range-based test uses a fixed 5% selectivity. A single join predicate involving a bounded (between) range-based test uses a fixed 0.25% selectivity. The join selectivity formula in a multitable join always uses the base table selectivity from the table that is explicitly named in the predicate (which is not necessarily the selectivity that was used in calculating the previous intermediate result). This means that you can make a legal textual change to rearrange the joins between tables, and find that the computed cardinality has changed. When you move from 8i to 9i, the basic formulae supplied by MetaLink still work in many cases, but there is an alternative strategy for handling nulls, which caters to them in the join

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