public double?EstSelectivity(string op, Value val)
{
int whichValue(Value val)
=> Array.IndexOf(values_, val);
if (!new List <String>()
{
"=", ">", ">=", "<", "<="
}.Contains(op))
{
return(null);
}
if (op == "=")
{
int which = whichValue(val);
if (which == -1)
{
return(otherfreq_);
}
return(freqs_[which]);
}
double selectivity = calcTotalFreq(val, op);
Estimator.validateSelectivity(selectivity);
return(selectivity);
}
public double EstSelectivity(string op, Value val)
{
if (!new List <String>()
{
"=", ">", ">=", "<", "<="
}.Contains(op))
{
return(StatConst.sel_one);
}
int which = whichValue(val);
if (which == -1)
{
return(StatConst.sel_zero);
}
double selectivity = 0.0;
switch (op)
{
case "=":
selectivity = freqs_[which];
break;
case ">":
case ">=":
int start = which;
for (int i = start; i < nvalues_; i++)
{
selectivity += freqs_[i];
}
break;
case "<":
case "<=":
int end = which;
for (int i = 0; i <= end; i++)
{
selectivity += freqs_[i];
}
break;
}
if (selectivity == 0)
{
selectivity = StatConst.sel_zero;
}
Estimator.validateSelectivity(selectivity);
return(selectivity);
}
public double EstSelectivity(string op, Value val)
{
double selectivity = StatConst.sel_one;
if (!new List <String>()
{
"=", ">", ">=", "<", "<="
}.Contains(op))
{
return(selectivity);
}
int which = whichBucket(val);
switch (op)
{
case "=":
selectivity = 1.0 / (nbuckets_ * distincts_[which]);
break;
case ">":
case ">=":
selectivity = 1.0 * (nbuckets_ - which) / nbuckets_;
break;
case "<":
case "<=":
selectivity = 1.0 * which / nbuckets_;
break;
}
if (selectivity == 0)
{
selectivity = StatConst.sel_zero;
}
Estimator.validateSelectivity(selectivity);
return(selectivity);
}
public double EstSelectivity(string op, Value val)
{
var selectivity = StatConst.one_;
if (op == "like")
{
selectivity = EstLikeSelectivity(val);
}
else if (!new List <String>()
{
"=", ">", ">=", "<", "<="
}.Contains(op))
{
selectivity = StatConst.one_;
}
else
{
if (mcv_ is null)
{
if (hist_ is null)
{
selectivity = StatConst.one_;
}
else if (op == "=") // unique
{
selectivity = 1.0 / n_rows_;
}
else
{
selectivity = hist_.EstSelectivity(op, val) ?? StatConst.one_;
}
}
else
{
if (op == "=")
{
selectivity = mcv_.EstSelectivity(op, val) ?? StatConst.one_;
}
else
{
var mcvest = mcv_.EstSelectivity(op, val);
var histest = hist_?.EstSelectivity(op, val);
if (mcvest is null)
{
// only use histgram if avaliable
selectivity = hist_ is null ? StatConst.one_ : (histest ?? StatConst.one_);
}
else
{
if (histest is null)
{
selectivity = (double)mcvest;
}
else
{
selectivity = (double)mcvest + ((1 - mcv_.totalfreq_) * ((double)histest));
}
}
}
}
}
Estimator.validateSelectivity(selectivity);
return(selectivity);
}
public double?EstSelectivity(string op, Value val)
{
// return the selectivity respect to only the histogram
double selectivity = StatConst.one_;
Debug.Assert(new List <String>()
{
">", ">=", "<", "<="
}.Contains(op));
int which = whichBucketLargerThan(val);
switch (op)
{
case ">":
case ">=":
if (which == 0)
{
selectivity = 1.0;
}
else if (which == nbuckets_ + 1)
{
selectivity = 0.0;
}
else
{
var basefraction = nbuckets_ - which;
var deltadjust = 0.0;
// for non-string data, we can further adjust within the bucket fraction by assuming
// data are continuous within the bucket
if (!(val is string))
{
deltadjust = 1.0 - getFraction(buckets_[which - 1], buckets_[which], val);
}
selectivity = (basefraction + deltadjust) / nbuckets_;
}
break;
case "<":
case "<=":
if (which == 0)
{
selectivity = 0.0;
}
else if (which == nbuckets_ + 1)
{
selectivity = 1.0;
}
else
{
var basefraction = which;
var deltadjust = 0.0;
if (!(val is string))
{
deltadjust = 1.0 - getFraction(buckets_[which - 1], buckets_[which], val);
}
selectivity = (basefraction - deltadjust) / nbuckets_;
}
break;
}
Estimator.validateSelectivity(selectivity);
return(selectivity);
}