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vec_to_weighted_mean_numeric.c
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Datum vec_to_weighted_mean_numeric_transfn(PG_FUNCTION_ARGS);
PG_FUNCTION_INFO_V1(vec_to_weighted_mean_numeric_transfn);
/**
* Returns an of n elements,
* which each element is the weighted mean of the values found in that position
* from all input arrays. The second parameter is an array of weights.
*
* by Paul A. Jungwirth
*/
Datum
vec_to_weighted_mean_numeric_transfn(PG_FUNCTION_ARGS)
{
Oid elemTypeId;
Oid elemWeightTypeId;
int16 elemTypeWidth;
int16 elemWeightTypeWidth;
bool elemTypeByValue;
bool elemWeightTypeByValue;
char elemTypeAlignmentCode;
char elemWeightTypeAlignmentCode;
int currentLength;
int currentWeightLength;
MemoryContext aggContext;
VecArrayBuildState *state = NULL;
ArrayType *currentArray;
ArrayType *currentWeightArray;
int arrayLength;
int arrayLengthWeight;
Datum *currentVals;
Datum *currentWeightVals;
bool *currentNulls;
bool *currentWeightNulls;
int i;
MemoryContext old;
if (!AggCheckCallContext(fcinfo, &aggContext)) {
elog(ERROR, "vec_to_weighted_mean_numeric_transfn called in non-aggregate context");
}
// PG_ARGISNULL tests for SQL NULL,
// but after the first pass we can have a
// value that is non-SQL-NULL but still is C NULL.
if (!PG_ARGISNULL(0)) {
state = (VecArrayBuildState *)PG_GETARG_POINTER(0);
}
if (PG_ARGISNULL(1) || PG_ARGISNULL(2)) {
// just return the current state unchanged (possibly still NULL)
PG_RETURN_POINTER(state);
}
currentArray = PG_GETARG_ARRAYTYPE_P(1);
currentWeightArray = PG_GETARG_ARRAYTYPE_P(2);
if (ARR_NDIM(currentArray) == 0) {
PG_RETURN_POINTER(state);
}
if (state == NULL) {
// Since we have our first not-null argument
// we can initialize the state to match its length.
elemTypeId = ARR_ELEMTYPE(currentArray);
elemWeightTypeId = ARR_ELEMTYPE(currentWeightArray);
if (ARR_NDIM(currentArray) != 1) {
ereport(ERROR, (errmsg("One-dimensional arrays are required")));
}
if (ARR_NDIM(currentWeightArray) != 1) {
ereport(ERROR, (errmsg("One-dimensional arrays are required for weights")));
}
arrayLength = (ARR_DIMS(currentArray))[0];
arrayLengthWeight = (ARR_DIMS(currentWeightArray))[0];
if (arrayLength != arrayLengthWeight) {
ereport(ERROR, (errmsg("All arrays must be the same length, but we got %d for values vs %d for weights", arrayLength, arrayLengthWeight)));
}
// Just start with all NULLs and let the comparisons below replace them:
state = initVecArrayResultWithNulls(elemTypeId, NUMERICOID, aggContext, arrayLength);
} else {
elemTypeId = state->inputElementType;
arrayLength = state->state.nelems;
elemWeightTypeId = ARR_ELEMTYPE(currentWeightArray);
}
get_typlenbyvalalign(elemTypeId, &elemTypeWidth, &elemTypeByValue, &elemTypeAlignmentCode);
deconstruct_array(currentArray, elemTypeId, elemTypeWidth, elemTypeByValue, elemTypeAlignmentCode,
¤tVals, ¤tNulls, ¤tLength);
if (currentLength != arrayLength) {
ereport(ERROR, (errmsg("All arrays must be the same length, but we got %d vs %d", currentLength, arrayLength)));
}
get_typlenbyvalalign(elemWeightTypeId, &elemWeightTypeWidth, &elemWeightTypeByValue, &elemWeightTypeAlignmentCode);
deconstruct_array(currentWeightArray, elemWeightTypeId, elemWeightTypeWidth, elemWeightTypeByValue, elemWeightTypeAlignmentCode,
¤tWeightVals, ¤tWeightNulls, ¤tWeightLength);
if (currentWeightLength != arrayLength) {
ereport(ERROR, (errmsg("All arrays must be the same length, but we got %d vs %d for weights", arrayLength, currentLength)));
}
old = MemoryContextSwitchTo(aggContext);
for (i = 0; i < arrayLength; i++) {
if (currentNulls[i] || currentWeightNulls[i]) {
// do nothing: nulls can't change the result.
} else if (state->state.dnulls[i]) {
state->state.dnulls[i] = false;
state->vecvalues[i].num = DatumGetNumeric(DirectFunctionCall2(
numeric_mul,
currentWeightVals[i],
currentVals[i]));
state->vectmpvalues[i].num = DatumGetNumericCopy(currentWeightVals[i]);
} else {
// Instead of performing sub/div/add numeric calculations each row,
// just add and complete later in final function.
// NUMERIC precision should be plenty.
#if PG_VERSION_NUM < 120000
state->vecvalues[i].num = DatumGetNumeric(DirectFunctionCall2(
numeric_add,
NumericGetDatum(state->vecvalues[i].num),
DirectFunctionCall2(
numeric_mul,
currentWeightVals[i],
currentVals[i])));
state->vectmpvalues[i].num = DatumGetNumeric(DirectFunctionCall2(
numeric_add,
NumericGetDatum(state->vectmpvalues[i].num),
currentWeightVals[i]));
#else
state->vecvalues[i].num = numeric_add_opt_error(
state->vecvalues[i].num,
numeric_mul_opt_error(
DatumGetNumeric(currentWeightVals[i]),
DatumGetNumeric(currentVals[i]),
NULL),
NULL);
state->vectmpvalues[i].num = numeric_add_opt_error(
state->vectmpvalues[i].num,
DatumGetNumeric(currentWeightVals[i]),
NULL);
#endif
}
}
MemoryContextSwitchTo(old);
PG_RETURN_POINTER(state);
}
Datum vec_to_weighted_mean_numeric_finalfn(PG_FUNCTION_ARGS);
PG_FUNCTION_INFO_V1(vec_to_weighted_mean_numeric_finalfn);
Datum
vec_to_weighted_mean_numeric_finalfn(PG_FUNCTION_ARGS)
{
Datum result;
VecArrayBuildState *state;
int dims[1];
int lbs[1];
int i;
Datum div;
Assert(AggCheckCallContext(fcinfo, NULL));
state = PG_ARGISNULL(0) ? NULL : (VecArrayBuildState *)PG_GETARG_POINTER(0);
if (state == NULL)
PG_RETURN_NULL();
// Convert from our pgnums to Datums:
for (i = 0; i < state->state.nelems; i++) {
if (state->state.dnulls[i]) continue;
#if PG_VERSION_NUM < 120000
div = DirectFunctionCall2(numeric_div, NumericGetDatum(state->vecvalues[i].num), NumericGetDatum(state->vectmpvalues[i].num));
#else
div = NumericGetDatum(numeric_div_opt_error(state->vecvalues[i].num, state->vectmpvalues[i].num, NULL));
#endif
state->state.dvalues[i] = div;
}
dims[0] = state->state.nelems;
lbs[0] = 1;
result = makeMdArrayResult(&state->state, 1, dims, lbs, CurrentMemoryContext, false);
PG_RETURN_DATUM(result);
}