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Modify prefix_selectivity() so that it will never estimate the selectivity
of the generated range condition var >= 'foo' AND var < 'fop' as being less than what eqsel() would estimate for var = 'foo'. This is intuitively reasonable and it gets rid of the need for some entirely ad-hoc coding we formerly used to reject bogus estimates. The basic problem here is that if the prefix is more than a few characters long, the two boundary values are too close together to be distinguishable by comparison to the column histogram, resulting in a selectivity estimate of zero, which is often not very sane. Change motivated by an example from Peter Eisentraut. Arguably this is a bug fix, but I'll refrain from back-patching it for the moment.
This commit is contained in:
Tom Lane
parent
6f10eb2111
commit
422495d0da
@ -15,7 +15,7 @@
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*
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*
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* IDENTIFICATION
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* $PostgreSQL: pgsql/src/backend/utils/adt/selfuncs.c,v 1.243 2008/01/01 19:45:52 momjian Exp $
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* $PostgreSQL: pgsql/src/backend/utils/adt/selfuncs.c,v 1.244 2008/03/08 22:41:38 tgl Exp $
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*
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*-------------------------------------------------------------------------
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*/
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@ -103,6 +103,12 @@
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#include "utils/syscache.h"
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static double var_eq_const(VariableStatData *vardata, Oid operator,
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Datum constval, bool constisnull,
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bool varonleft);
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static double var_eq_non_const(VariableStatData *vardata, Oid operator,
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Node *other,
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bool varonleft);
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static double ineq_histogram_selectivity(VariableStatData *vardata,
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FmgrInfo *opproc, bool isgt,
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Datum constval, Oid consttype);
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@ -156,10 +162,6 @@ eqsel(PG_FUNCTION_ARGS)
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VariableStatData vardata;
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Node *other;
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bool varonleft;
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Datum *values;
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int nvalues;
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float4 *numbers;
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int nnumbers;
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double selec;
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/*
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@ -171,148 +173,203 @@ eqsel(PG_FUNCTION_ARGS)
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PG_RETURN_FLOAT8(DEFAULT_EQ_SEL);
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/*
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* If the something is a NULL constant, assume operator is strict and
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* We can do a lot better if the something is a constant. (Note: the
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* Const might result from estimation rather than being a simple constant
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* in the query.)
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*/
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if (IsA(other, Const))
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selec = var_eq_const(&vardata, operator,
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((Const *) other)->constvalue,
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((Const *) other)->constisnull,
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varonleft);
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else
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selec = var_eq_non_const(&vardata, operator, other,
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varonleft);
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ReleaseVariableStats(vardata);
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PG_RETURN_FLOAT8((float8) selec);
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}
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/*
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* var_eq_const --- eqsel for var = const case
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*
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* This is split out so that some other estimation functions can use it.
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*/
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static double
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var_eq_const(VariableStatData *vardata, Oid operator,
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Datum constval, bool constisnull,
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bool varonleft)
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{
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double selec;
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/*
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* If the constant is NULL, assume operator is strict and
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* return zero, ie, operator will never return TRUE.
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*/
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if (IsA(other, Const) &&
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((Const *) other)->constisnull)
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{
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ReleaseVariableStats(vardata);
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PG_RETURN_FLOAT8(0.0);
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}
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if (constisnull)
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return 0.0;
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if (HeapTupleIsValid(vardata.statsTuple))
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if (HeapTupleIsValid(vardata->statsTuple))
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{
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Form_pg_statistic stats;
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Datum *values;
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int nvalues;
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float4 *numbers;
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int nnumbers;
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bool match = false;
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int i;
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stats = (Form_pg_statistic) GETSTRUCT(vardata.statsTuple);
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stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);
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if (IsA(other, Const))
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/*
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* Is the constant "=" to any of the column's most common values?
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* (Although the given operator may not really be "=", we will
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* assume that seeing whether it returns TRUE is an appropriate
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* test. If you don't like this, maybe you shouldn't be using
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* eqsel for your operator...)
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*/
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if (get_attstatsslot(vardata->statsTuple,
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vardata->atttype, vardata->atttypmod,
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STATISTIC_KIND_MCV, InvalidOid,
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&values, &nvalues,
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&numbers, &nnumbers))
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{
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/* Variable is being compared to a known non-null constant */
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Datum constval = ((Const *) other)->constvalue;
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bool match = false;
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int i;
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FmgrInfo eqproc;
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/*
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* Is the constant "=" to any of the column's most common values?
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* (Although the given operator may not really be "=", we will
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* assume that seeing whether it returns TRUE is an appropriate
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* test. If you don't like this, maybe you shouldn't be using
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* eqsel for your operator...)
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*/
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if (get_attstatsslot(vardata.statsTuple,
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vardata.atttype, vardata.atttypmod,
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STATISTIC_KIND_MCV, InvalidOid,
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&values, &nvalues,
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&numbers, &nnumbers))
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fmgr_info(get_opcode(operator), &eqproc);
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for (i = 0; i < nvalues; i++)
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{
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FmgrInfo eqproc;
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fmgr_info(get_opcode(operator), &eqproc);
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for (i = 0; i < nvalues; i++)
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{
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/* be careful to apply operator right way 'round */
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if (varonleft)
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match = DatumGetBool(FunctionCall2(&eqproc,
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values[i],
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constval));
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else
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match = DatumGetBool(FunctionCall2(&eqproc,
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constval,
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values[i]));
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if (match)
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break;
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}
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/* be careful to apply operator right way 'round */
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if (varonleft)
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match = DatumGetBool(FunctionCall2(&eqproc,
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values[i],
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constval));
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else
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match = DatumGetBool(FunctionCall2(&eqproc,
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constval,
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values[i]));
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if (match)
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break;
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}
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else
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{
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/* no most-common-value info available */
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values = NULL;
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numbers = NULL;
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i = nvalues = nnumbers = 0;
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}
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if (match)
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{
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/*
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* Constant is "=" to this common value. We know selectivity
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* exactly (or as exactly as ANALYZE could calculate it,
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* anyway).
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*/
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selec = numbers[i];
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}
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else
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{
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/*
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* Comparison is against a constant that is neither NULL nor
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* any of the common values. Its selectivity cannot be more
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* than this:
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*/
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double sumcommon = 0.0;
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double otherdistinct;
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for (i = 0; i < nnumbers; i++)
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sumcommon += numbers[i];
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selec = 1.0 - sumcommon - stats->stanullfrac;
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CLAMP_PROBABILITY(selec);
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/*
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* and in fact it's probably a good deal less. We approximate
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* that all the not-common values share this remaining
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* fraction equally, so we divide by the number of other
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* distinct values.
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*/
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otherdistinct = get_variable_numdistinct(&vardata)
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- nnumbers;
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if (otherdistinct > 1)
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selec /= otherdistinct;
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/*
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* Another cross-check: selectivity shouldn't be estimated as
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* more than the least common "most common value".
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*/
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if (nnumbers > 0 && selec > numbers[nnumbers - 1])
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selec = numbers[nnumbers - 1];
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}
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free_attstatsslot(vardata.atttype, values, nvalues,
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numbers, nnumbers);
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}
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else
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{
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double ndistinct;
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/* no most-common-value info available */
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values = NULL;
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numbers = NULL;
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i = nvalues = nnumbers = 0;
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}
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if (match)
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{
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/*
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* Constant is "=" to this common value. We know selectivity
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* exactly (or as exactly as ANALYZE could calculate it,
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* anyway).
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*/
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selec = numbers[i];
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}
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else
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{
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/*
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* Comparison is against a constant that is neither NULL nor
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* any of the common values. Its selectivity cannot be more
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* than this:
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*/
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double sumcommon = 0.0;
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double otherdistinct;
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for (i = 0; i < nnumbers; i++)
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sumcommon += numbers[i];
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selec = 1.0 - sumcommon - stats->stanullfrac;
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CLAMP_PROBABILITY(selec);
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/*
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* Search is for a value that we do not know a priori, but we will
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* assume it is not NULL. Estimate the selectivity as non-null
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* fraction divided by number of distinct values, so that we get a
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* result averaged over all possible values whether common or
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* uncommon. (Essentially, we are assuming that the not-yet-known
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* comparison value is equally likely to be any of the possible
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* values, regardless of their frequency in the table. Is that a
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* good idea?)
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* and in fact it's probably a good deal less. We approximate
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* that all the not-common values share this remaining
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* fraction equally, so we divide by the number of other
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* distinct values.
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*/
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selec = 1.0 - stats->stanullfrac;
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ndistinct = get_variable_numdistinct(&vardata);
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if (ndistinct > 1)
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selec /= ndistinct;
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otherdistinct = get_variable_numdistinct(vardata) - nnumbers;
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if (otherdistinct > 1)
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selec /= otherdistinct;
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/*
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* Cross-check: selectivity should never be estimated as more than
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* the most common value's.
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* Another cross-check: selectivity shouldn't be estimated as
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* more than the least common "most common value".
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*/
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if (get_attstatsslot(vardata.statsTuple,
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vardata.atttype, vardata.atttypmod,
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STATISTIC_KIND_MCV, InvalidOid,
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NULL, NULL,
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&numbers, &nnumbers))
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{
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if (nnumbers > 0 && selec > numbers[0])
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selec = numbers[0];
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free_attstatsslot(vardata.atttype, NULL, 0, numbers, nnumbers);
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}
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if (nnumbers > 0 && selec > numbers[nnumbers - 1])
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selec = numbers[nnumbers - 1];
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}
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free_attstatsslot(vardata->atttype, values, nvalues,
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numbers, nnumbers);
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}
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else
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{
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/*
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* No ANALYZE stats available, so make a guess using estimated number
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* of distinct values and assuming they are equally common. (The guess
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* is unlikely to be very good, but we do know a few special cases.)
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*/
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selec = 1.0 / get_variable_numdistinct(vardata);
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}
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/* result should be in range, but make sure... */
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CLAMP_PROBABILITY(selec);
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return selec;
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}
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/*
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* var_eq_non_const --- eqsel for var = something-other-than-const case
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*/
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static double
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var_eq_non_const(VariableStatData *vardata, Oid operator,
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Node *other,
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bool varonleft)
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{
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double selec;
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if (HeapTupleIsValid(vardata->statsTuple))
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{
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Form_pg_statistic stats;
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double ndistinct;
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float4 *numbers;
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int nnumbers;
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stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);
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/*
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* Search is for a value that we do not know a priori, but we will
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* assume it is not NULL. Estimate the selectivity as non-null
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* fraction divided by number of distinct values, so that we get a
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* result averaged over all possible values whether common or
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* uncommon. (Essentially, we are assuming that the not-yet-known
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* comparison value is equally likely to be any of the possible
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* values, regardless of their frequency in the table. Is that a
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* good idea?)
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*/
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selec = 1.0 - stats->stanullfrac;
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ndistinct = get_variable_numdistinct(vardata);
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if (ndistinct > 1)
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selec /= ndistinct;
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/*
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* Cross-check: selectivity should never be estimated as more than
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* the most common value's.
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*/
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if (get_attstatsslot(vardata->statsTuple,
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vardata->atttype, vardata->atttypmod,
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STATISTIC_KIND_MCV, InvalidOid,
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NULL, NULL,
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&numbers, &nnumbers))
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{
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if (nnumbers > 0 && selec > numbers[0])
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selec = numbers[0];
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free_attstatsslot(vardata->atttype, NULL, 0, numbers, nnumbers);
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}
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}
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else
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@ -322,15 +379,13 @@ eqsel(PG_FUNCTION_ARGS)
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* of distinct values and assuming they are equally common. (The guess
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* is unlikely to be very good, but we do know a few special cases.)
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*/
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selec = 1.0 / get_variable_numdistinct(&vardata);
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selec = 1.0 / get_variable_numdistinct(vardata);
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}
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ReleaseVariableStats(vardata);
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/* result should be in range, but make sure... */
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CLAMP_PROBABILITY(selec);
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PG_RETURN_FLOAT8((float8) selec);
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return selec;
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}
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/*
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@ -1047,16 +1102,11 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype, bool negate)
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*/
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Oid eqopr = get_opfamily_member(opfamily, vartype, vartype,
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BTEqualStrategyNumber);
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List *eqargs;
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if (eqopr == InvalidOid)
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elog(ERROR, "no = operator for opfamily %u", opfamily);
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eqargs = list_make2(variable, prefix);
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result = DatumGetFloat8(DirectFunctionCall4(eqsel,
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PointerGetDatum(root),
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ObjectIdGetDatum(eqopr),
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PointerGetDatum(eqargs),
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Int32GetDatum(varRelid)));
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result = var_eq_const(&vardata, eqopr, prefix->constvalue,
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false, true);
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}
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else
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{
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@ -4430,6 +4480,7 @@ prefix_selectivity(VariableStatData *vardata,
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Oid cmpopr;
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FmgrInfo opproc;
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Const *greaterstrcon;
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Selectivity eq_sel;
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cmpopr = get_opfamily_member(opfamily, vartype, vartype,
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BTGreaterEqualStrategyNumber);
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@ -4444,7 +4495,7 @@ prefix_selectivity(VariableStatData *vardata,
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if (prefixsel <= 0.0)
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{
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/* No histogram is present ... return a suitable default estimate */
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return 0.005;
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return DEFAULT_MATCH_SEL;
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}
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/*-------
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@ -4452,17 +4503,17 @@ prefix_selectivity(VariableStatData *vardata,
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* "x < greaterstr".
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*-------
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*/
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cmpopr = get_opfamily_member(opfamily, vartype, vartype,
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BTLessStrategyNumber);
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if (cmpopr == InvalidOid)
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elog(ERROR, "no < operator for opfamily %u", opfamily);
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fmgr_info(get_opcode(cmpopr), &opproc);
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greaterstrcon = make_greater_string(prefixcon, &opproc);
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if (greaterstrcon)
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{
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Selectivity topsel;
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cmpopr = get_opfamily_member(opfamily, vartype, vartype,
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BTLessStrategyNumber);
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if (cmpopr == InvalidOid)
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elog(ERROR, "no < operator for opfamily %u", opfamily);
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fmgr_info(get_opcode(cmpopr), &opproc);
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topsel = ineq_histogram_selectivity(vardata, &opproc, false,
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greaterstrcon->constvalue,
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greaterstrcon->consttype);
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@ -4477,16 +4528,30 @@ prefix_selectivity(VariableStatData *vardata,
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* doesn't count those anyway.
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*/
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prefixsel = topsel + prefixsel - 1.0;
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/*
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* A zero or negative prefixsel should be converted into a small
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* positive value; we probably are dealing with a very tight range and
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* got a bogus result due to roundoff errors.
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*/
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if (prefixsel <= 0.0)
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prefixsel = 1.0e-10;
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}
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/*
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* If the prefix is long then the two bounding values might be too
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* close together for the histogram to distinguish them usefully,
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* resulting in a zero estimate (plus or minus roundoff error).
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* To avoid returning a ridiculously small estimate, compute the
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* estimated selectivity for "variable = 'foo'", and clamp to that.
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* (Obviously, the resultant estimate should be at least that.)
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*
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* We apply this even if we couldn't make a greater string. That case
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* suggests that the prefix is near the maximum possible, and thus
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* probably off the end of the histogram, and thus we probably got a
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* very small estimate from the >= condition; so we still need to clamp.
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*/
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cmpopr = get_opfamily_member(opfamily, vartype, vartype,
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BTEqualStrategyNumber);
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if (cmpopr == InvalidOid)
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elog(ERROR, "no = operator for opfamily %u", opfamily);
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eq_sel = var_eq_const(vardata, cmpopr, prefixcon->constvalue,
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false, true);
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prefixsel = Max(prefixsel, eq_sel);
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return prefixsel;
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}
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