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update t1 set n2 = n1; commit; create index t1_i1 on t1(ind_pad,n1,n2) pctfree 91 ; create table driver as select rownum id, ind_pad, n1, n2 from ( select distinct ind_pad, n1, n2 from t1 )

TIP: The Search, Search Sender, Search Recipient, and Search Subject commands work on SMS messages, E-mail, MMS anything in your messages inbox! Sometimes, you have many messages from one particular sender, and you want to see only the list of your communication with that particular individual. 1. From the messages list, scroll to any message from or to the person you wish to search and press the Menu key. Select Search Recipient or Search Sender. Only the list of messages sent by or sent to that particular person (in this case, Martin) is now displayed. Now that you only see messages to or from Martin, it is easy to scroll up or down and quickly find the message you are seeking.

public: // PlayerMove implements a player making a play. // Return true if the game is over. bool PlayerMove() { bool gameOver = false; bool moveComplete = false; while (! moveComplete) { try { List<Tile^>^ workingTiles = GetWorkingTiles(); array<Tile^, 2>^ workingBoard = GetWorkingBoard(); PrintBoard(); Console::WriteLine("{0}'s turn.", players[playerNum]->Name); players[playerNum]->PrintPlayerTiles(); PlayType playType = GetPlayType(); if ( playType == PlayType::Pass) { moveComplete = Pass(workingTiles); if (moveComplete) { // The pass was completed. pass_count++; // If everyone passes and the bag is empty, the game ends. if (pass_count == nPlayer && bag->Count == 0) { gameOver = true; } return gameOver; } else { // The pass was cancelled, restart play. continue; } } int row, col; if (! GetPlayStartPosition(row, col)) continue; if (! GetTilesForPlay(row, col, playType, workingTiles, workingBoard)) continue;

; alter table driver add constraint d_pk primary key(id); -select t1.small_vc from t1 where and and ; select /*+ ordered use_nl(t1) index(t1 t1_i1) */ t1.small_vc from driver d, t1 where and and and ; d.id t1.ind_pad t1.n1 t1.n2 = = = = 5 d.ind_pad d.n1 d.n2 t1.ind_pad = rpad('x',40) t1.n1 = 0 t1.n2 = 4 Collect statistics using dbms_stats here

2. 3.

In the baseline test, there are 625 different combinations for the pair (n1, n2) in table t1, so the driver table has 625 rows, but in the special test case where we copy n2 into n1, the driver table has 25 rows. Since there are 10,000 rows in t1, and the (n1, n2) combinations are randomly distributed, we can assume that there are 16 rows (10,000 / 625) per pair of values in the baseline test, and 400 rows (10,000 / 25) in the modified test. Because of the primary key constraint on the driver table, the optimizer knows that the first predicate (d.id = 5) in the second query will result in precisely one row being identified in the driver table. To emphasize the degree of variation from the standard formula, the first query we test is a single table indexed access into t1. According to the standard nested loop join formula, it is the cost from this operation that should be multiplied by the cardinality from the driving table when we switch to the two-table join. The plan we get from this single-table query is as follows: Execution Plan (9.2.0.6 autotrace) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=14 Card=16 Bytes=928) 1 0 TABLE ACCESS (BY INDEX ROWID) OF 'T1' (Cost=14 Card=16 Bytes=928) 2 1 INDEX (RANGE SCAN) OF 'T1_I1' (NON-UNIQUE) (Cost=4 Card=16)

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