diff options
Diffstat (limited to 'src/backend/utils/adt/array_selfuncs.c')
| -rw-r--r-- | src/backend/utils/adt/array_selfuncs.c | 20 |
1 files changed, 10 insertions, 10 deletions
diff --git a/src/backend/utils/adt/array_selfuncs.c b/src/backend/utils/adt/array_selfuncs.c index 20eb358a620..170a28a067c 100644 --- a/src/backend/utils/adt/array_selfuncs.c +++ b/src/backend/utils/adt/array_selfuncs.c @@ -524,7 +524,7 @@ mcelem_array_selec(ArrayType *array, TypeCacheEntry *typentry, /* * Estimate selectivity of "column @> const" and "column && const" based on - * most common element statistics. This estimation assumes element + * most common element statistics. This estimation assumes element * occurrences are independent. * * mcelem (of length nmcelem) and numbers (of length nnumbers) are from @@ -689,7 +689,7 @@ mcelem_array_contain_overlap_selec(Datum *mcelem, int nmcelem, * In the "column @> const" and "column && const" cases, we usually have a * "const" with low number of elements (otherwise we have selectivity close * to 0 or 1 respectively). That's why the effect of dependence related - * to distinct element count distribution is negligible there. In the + * to distinct element count distribution is negligible there. In the * "column <@ const" case, number of elements is usually high (otherwise we * have selectivity close to 0). That's why we should do a correction with * the array distinct element count distribution here. @@ -848,7 +848,7 @@ mcelem_array_contained_selec(Datum *mcelem, int nmcelem, /* * The presence of many distinct rare elements materially decreases * selectivity. Use the Poisson distribution to estimate the probability - * of a column value having zero occurrences of such elements. See above + * of a column value having zero occurrences of such elements. See above * for the definition of "rest". */ mult *= exp(-rest); @@ -856,7 +856,7 @@ mcelem_array_contained_selec(Datum *mcelem, int nmcelem, /*---------- * Using the distinct element count histogram requires * O(unique_nitems * (nmcelem + unique_nitems)) - * operations. Beyond a certain computational cost threshold, it's + * operations. Beyond a certain computational cost threshold, it's * reasonable to sacrifice accuracy for decreased planning time. We limit * the number of operations to EFFORT * nmcelem; since nmcelem is limited * by the column's statistics target, the work done is user-controllable. @@ -868,7 +868,7 @@ mcelem_array_contained_selec(Datum *mcelem, int nmcelem, * elements to start with, we'd have to remove any discarded elements' * frequencies from "mult", but since this is only an approximation * anyway, we don't bother with that. Therefore it's sufficient to qsort - * elem_selec[] and take the largest elements. (They will no longer match + * elem_selec[] and take the largest elements. (They will no longer match * up with the elements of array_data[], but we don't care.) *---------- */ @@ -878,7 +878,7 @@ mcelem_array_contained_selec(Datum *mcelem, int nmcelem, unique_nitems > EFFORT * nmcelem / (nmcelem + unique_nitems)) { /* - * Use the quadratic formula to solve for largest allowable N. We + * Use the quadratic formula to solve for largest allowable N. We * have A = 1, B = nmcelem, C = - EFFORT * nmcelem. */ double b = (double) nmcelem; @@ -953,7 +953,7 @@ calc_hist(const float4 *hist, int nhist, int n) /* * frac is a probability contribution for each interval between histogram - * values. We have nhist - 1 intervals, so contribution of each one will + * values. We have nhist - 1 intervals, so contribution of each one will * be 1 / (nhist - 1). */ frac = 1.0f / ((float) (nhist - 1)); @@ -1020,8 +1020,8 @@ calc_hist(const float4 *hist, int nhist, int n) * "rest" is the sum of the probabilities of all low-probability events not * included in p. * - * Imagine matrix M of size (n + 1) x (m + 1). Element M[i,j] denotes the - * probability that exactly j of first i events occur. Obviously M[0,0] = 1. + * Imagine matrix M of size (n + 1) x (m + 1). Element M[i,j] denotes the + * probability that exactly j of first i events occur. Obviously M[0,0] = 1. * For any constant j, each increment of i increases the probability iff the * event occurs. So, by the law of total probability: * M[i,j] = M[i - 1, j] * (1 - p[i]) + M[i - 1, j - 1] * p[i] @@ -1143,7 +1143,7 @@ floor_log2(uint32 n) /* * find_next_mcelem binary-searches a most common elements array, starting - * from *index, for the first member >= value. It saves the position of the + * from *index, for the first member >= value. It saves the position of the * match into *index and returns true if it's an exact match. (Note: we * assume the mcelem elements are distinct so there can't be more than one * exact match.) |