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MCOL-1829 Subquery with limited order by could potentially return onordered set.

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There were two code mistakes: Eq::operator() always returned true for
	any pair and Hasher::operator() always returned 0 as a key.
This commit is contained in:
Roman Nozdrin
2018-12-25 12:50:18 +03:00
parent 0584b114da
commit 35a17a87c4
4 changed files with 16 additions and 17 deletions
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21
dbcon/joblist/limitedorderby.cpp
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@@ -113,7 +113,6 @@ void LimitedOrderBy::processRow(const rowgroup::Row& row)
if (fOrderByQueue.size() < fStart + fCount)
{
copyRow(row, &fRow0);
//memcpy(fRow0.getData(), row.getData(), row.getSize());
OrderByRow newRow(fRow0, fRule);
fOrderByQueue.push(newRow);
@@ -121,8 +120,6 @@ void LimitedOrderBy::processRow(const rowgroup::Row& row)
if (fDistinct)
fDistinctMap->insert(fRow0.getPointer());
//fDistinctMap->insert(make_pair((fRow0.getData()+2), fRow0.getData()));
fRowGroup.incRowCount();
fRow0.nextRow();
@@ -150,23 +147,16 @@ void LimitedOrderBy::processRow(const rowgroup::Row& row)
{
OrderByRow swapRow = fOrderByQueue.top();
row1.setData(swapRow.fData);
fOrderByQueue.pop();
if (!fDistinct)
copyRow(row, &row1);
if (fDistinct)
{
copyRow(row, &row1);
//memcpy(swapRow.fData, row.getData(), row.getSize());
}
else
{
fDistinctMap->erase(row.getPointer());
copyRow(row, &row1);
fDistinctMap->erase(fOrderByQueue.top().fData);
fDistinctMap->insert(row1.getPointer());
//fDistinctMap->erase(fDistinctMap->find(row.getData() + 2));
//memcpy(swapRow.fData, row.getData(), row.getSize());
//fDistinctMap->insert(make_pair((swapRow.fData+2), swapRow.fData));
}
fOrderByQueue.pop();
fOrderByQueue.push(swapRow);
}
}
@@ -228,6 +218,7 @@ void LimitedOrderBy::finalize()
const OrderByRow& topRow = fOrderByQueue.top();
row1.setData(topRow.fData);
copyRow(row1, &fRow0);
//cerr << "LimitedOrderBy::finalize fRow0 " << fRow0.toString() << endl;
fRowGroup.incRowCount();
offset--;
fRow0.prevRow(rSize);

4
dbcon/joblist/tupleaggregatestep.cpp
View File

@@ -5554,6 +5554,8 @@ void TupleAggregateStep::threadedAggregateRowGroups(uint32_t threadID)
rowIn.copyField(distRow[j], k, multiDist->subAggregators()[j]->getGroupByCols()[k].get()->fInputColumnIndex);
}
// TBD This approach could potentiall
// put all values in on bucket.
bucketID = distRow[j].hash(hashLens[j] - 1) % fNumOfBuckets;
rowBucketVecs[bucketID][j].push_back(rowIn.getPointer());
rowIn.nextRow();
@@ -5572,6 +5574,8 @@ void TupleAggregateStep::threadedAggregateRowGroups(uint32_t threadID)
for (uint64_t i = 0; i < fRowGroupIns[threadID].getRowCount(); ++i)
{
// The key is the groupby columns, which are the leading columns.
// TBD This approach could potentiall
// put all values in on bucket.
int bucketID = rowIn.hash(hashLens[0] - 1) % fNumOfBuckets;
rowBucketVecs[bucketID][0].push_back(rowIn.getPointer());
rowIn.nextRow();