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Overview
Comment:Do not try to use STAT2 to refine the row estimate of a query that uses a unique or nearly-unique index.
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SHA1: efffc49baf38698ed3de05d16b4261bf405d42d7
User & Date: drh 2011-07-13 18:31:10.999
Context
2011-07-15
13:43
In os_unix.c, check if the ESTALE macro is defined before using it. (check-in: 87017410f2 user: dan tags: trunk)
2011-07-13
18:31
Do not try to use STAT2 to refine the row estimate of a query that uses a unique or nearly-unique index. (check-in: efffc49baf user: drh tags: trunk)
16:03
Added the SQLITE_FCNTL_WIN32_AV_RETRY file control for configuring the retry counts and delays in the windows VFS. (check-in: 7aaf0a6ae1 user: drh tags: trunk)
Changes
Unified Diff Ignore Whitespace Patch
Changes to src/where.c.
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    nRow = (double)(aiRowEst[nEq] * nInMul);
    if( bInEst && nRow*2>aiRowEst[0] ){
      nRow = aiRowEst[0]/2;
      nInMul = (int)(nRow / aiRowEst[nEq]);
    }

#ifdef SQLITE_ENABLE_STAT2
    /* If the constraint is of the form x=VALUE and histogram

    ** data is available for column x, then it might be possible
    ** to get a better estimate on the number of rows based on
    ** VALUE and how common that value is according to the histogram.
    */
    if( nRow>(double)1 && nEq==1 && pFirstTerm!=0 ){
      if( pFirstTerm->eOperator & (WO_EQ|WO_ISNULL) ){
        testcase( pFirstTerm->eOperator==WO_EQ );
        testcase( pFirstTerm->eOperator==WO_ISNULL );
        whereEqualScanEst(pParse, pProbe, pFirstTerm->pExpr->pRight, &nRow);
      }else if( pFirstTerm->eOperator==WO_IN && bInEst==0 ){
        whereInScanEst(pParse, pProbe, pFirstTerm->pExpr->x.pList, &nRow);
      }







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    nRow = (double)(aiRowEst[nEq] * nInMul);
    if( bInEst && nRow*2>aiRowEst[0] ){
      nRow = aiRowEst[0]/2;
      nInMul = (int)(nRow / aiRowEst[nEq]);
    }

#ifdef SQLITE_ENABLE_STAT2
    /* If the constraint is of the form x=VALUE or x IN (E1,E2,...)
    ** and we do not think that values of x are unique and if histogram
    ** data is available for column x, then it might be possible
    ** to get a better estimate on the number of rows based on
    ** VALUE and how common that value is according to the histogram.
    */
    if( nRow>(double)1 && nEq==1 && pFirstTerm!=0 && aiRowEst[1]>1 ){
      if( pFirstTerm->eOperator & (WO_EQ|WO_ISNULL) ){
        testcase( pFirstTerm->eOperator==WO_EQ );
        testcase( pFirstTerm->eOperator==WO_ISNULL );
        whereEqualScanEst(pParse, pProbe, pFirstTerm->pExpr->pRight, &nRow);
      }else if( pFirstTerm->eOperator==WO_IN && bInEst==0 ){
        whereInScanEst(pParse, pProbe, pFirstTerm->pExpr->x.pList, &nRow);
      }