/**
* Add a value to this aggregate.
*
* @param database the database
* @param distinct if the calculation should be distinct
* @param v the value
*/
void add(Database database, boolean distinct, Value v) {
if (aggregateType == Aggregate.SELECTIVITY) {
count++;
if (distinctHashes == null) {
distinctHashes = new IntIntHashMap();
}
int size = distinctHashes.size();
if (size > Constants.SELECTIVITY_DISTINCT_COUNT) {
distinctHashes = new IntIntHashMap();
m2 += size;
}
int hash = v.hashCode();
// the value -1 is not supported
distinctHashes.put(hash, 1);
return;
} else if (aggregateType == Aggregate.COUNT_ALL) {
count++;
return;
} else if (aggregateType == Aggregate.HISTOGRAM) {
if (distinctValues == null) {
distinctValues = ValueHashMap.newInstance();
}
AggregateData a = distinctValues.get(v);
if (a == null) {
if (distinctValues.size() < Constants.SELECTIVITY_DISTINCT_COUNT) {
a = new AggregateData(Aggregate.HISTOGRAM, dataType);
distinctValues.put(v, a);
}
}
if (a != null) {
a.count++;
}
return;
}
if (v == ValueNull.INSTANCE) {
return;
}
count++;
if (distinct) {
if (distinctValues == null) {
distinctValues = ValueHashMap.newInstance();
}
distinctValues.put(v, this);
return;
}
switch (aggregateType) {
case Aggregate.COUNT:
case Aggregate.HISTOGRAM:
return;
case Aggregate.SUM:
if (value == null) {
value = v.convertTo(dataType);
} else {
v = v.convertTo(value.getType());
value = value.add(v);
}
break;
case Aggregate.AVG:
if (value == null) {
value = v.convertTo(DataType.getAddProofType(dataType));
} else {
v = v.convertTo(value.getType());
value = value.add(v);
}
break;
case Aggregate.MIN:
if (value == null || database.compare(v, value) < 0) {
value = v;
}
break;
case Aggregate.MAX:
if (value == null || database.compare(v, value) > 0) {
value = v;
}
break;
case Aggregate.GROUP_CONCAT:
{
if (list == null) {
list = New.arrayList();
}
list.add(v);
break;
}
case Aggregate.STDDEV_POP:
case Aggregate.STDDEV_SAMP:
case Aggregate.VAR_POP:
case Aggregate.VAR_SAMP:
{
// Using Welford's method, see also
// http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
// http://www.johndcook.com/standard_deviation.html
double x = v.getDouble();
if (count == 1) {
mean = x;
m2 = 0;
} else {
double delta = x - mean;
mean += delta / count;
m2 += delta * (x - mean);
}
break;
}
case Aggregate.BOOL_AND:
v = v.convertTo(Value.BOOLEAN);
if (value == null) {
value = v;
} else {
value =
ValueBoolean.get(value.getBoolean().booleanValue() && v.getBoolean().booleanValue());
}
break;
case Aggregate.BOOL_OR:
v = v.convertTo(Value.BOOLEAN);
if (value == null) {
value = v;
} else {
value =
ValueBoolean.get(value.getBoolean().booleanValue() || v.getBoolean().booleanValue());
}
break;
default:
DbException.throwInternalError("type=" + aggregateType);
}
}
/**
* Get the aggregate result.
*
* @param database the database
* @param distinct if distinct is used
* @return the value
*/
Value getValue(Database database, boolean distinct) {
if (distinct) {
count = 0;
groupDistinct(database);
}
Value v = null;
switch (aggregateType) {
case Aggregate.SELECTIVITY:
{
int s = 0;
if (count == 0) {
s = 0;
} else {
m2 += distinctHashes.size();
m2 = 100 * m2 / count;
s = (int) m2;
s = s <= 0 ? 1 : s > 100 ? 100 : s;
}
v = ValueInt.get(s);
break;
}
case Aggregate.COUNT:
case Aggregate.COUNT_ALL:
v = ValueLong.get(count);
break;
case Aggregate.SUM:
case Aggregate.MIN:
case Aggregate.MAX:
case Aggregate.BOOL_OR:
case Aggregate.BOOL_AND:
v = value;
break;
case Aggregate.AVG:
if (value != null) {
v = divide(value, count);
}
break;
case Aggregate.GROUP_CONCAT:
return null;
case Aggregate.STDDEV_POP:
{
if (count < 1) {
return ValueNull.INSTANCE;
}
v = ValueDouble.get(Math.sqrt(m2 / count));
break;
}
case Aggregate.STDDEV_SAMP:
{
if (count < 2) {
return ValueNull.INSTANCE;
}
v = ValueDouble.get(Math.sqrt(m2 / (count - 1)));
break;
}
case Aggregate.VAR_POP:
{
if (count < 1) {
return ValueNull.INSTANCE;
}
v = ValueDouble.get(m2 / count);
break;
}
case Aggregate.VAR_SAMP:
{
if (count < 2) {
return ValueNull.INSTANCE;
}
v = ValueDouble.get(m2 / (count - 1));
break;
}
case Aggregate.HISTOGRAM:
ValueArray[] values = new ValueArray[distinctValues.size()];
int i = 0;
for (Value dv : distinctValues.keys()) {
AggregateData d = distinctValues.get(dv);
values[i] = ValueArray.get(new Value[] {dv, ValueLong.get(d.count)});
i++;
}
final CompareMode compareMode = database.getCompareMode();
Arrays.sort(
values,
new Comparator<ValueArray>() {
public int compare(ValueArray v1, ValueArray v2) {
Value a1 = v1.getList()[0];
Value a2 = v2.getList()[0];
return a1.compareTo(a2, compareMode);
}
});
v = ValueArray.get(values);
break;
default:
DbException.throwInternalError("type=" + aggregateType);
}
return v == null ? ValueNull.INSTANCE : v.convertTo(dataType);
}