/*
* Druid - a distributed column store.
* Copyright (C) 2012, 2013 Metamarkets Group Inc.
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
package io.druid.query.timeseries;
import com.google.common.base.Function;
import com.metamx.common.guava.Sequence;
import io.druid.query.QueryRunnerHelper;
import io.druid.query.Result;
import io.druid.query.aggregation.Aggregator;
import io.druid.query.aggregation.AggregatorFactory;
import io.druid.segment.Cursor;
import io.druid.segment.SegmentMissingException;
import io.druid.segment.StorageAdapter;
import io.druid.segment.filter.Filters;
import java.util.List;
/**
*/
public class TimeseriesQueryEngine
{
public Sequence<Result<TimeseriesResultValue>> process(final TimeseriesQuery query, final StorageAdapter adapter)
{
if (adapter == null) {
throw new SegmentMissingException(
"Null storage adapter found. Probably trying to issue a query against a segment being memory unmapped."
);
}
return QueryRunnerHelper.makeCursorBasedQuery(
adapter,
query.getQuerySegmentSpec().getIntervals(),
Filters.convertDimensionFilters(query.getDimensionsFilter()),
query.getGranularity(),
new Function<Cursor, Result<TimeseriesResultValue>>()
{
private final List<AggregatorFactory> aggregatorSpecs = query.getAggregatorSpecs();
@Override
public Result<TimeseriesResultValue> apply(Cursor cursor)
{
Aggregator[] aggregators = QueryRunnerHelper.makeAggregators(cursor, aggregatorSpecs);
try {
while (!cursor.isDone()) {
for (Aggregator aggregator : aggregators) {
aggregator.aggregate();
}
cursor.advance();
}
TimeseriesResultBuilder bob = new TimeseriesResultBuilder(cursor.getTime());
for (Aggregator aggregator : aggregators) {
bob.addMetric(aggregator);
}
Result<TimeseriesResultValue> retVal = bob.build();
return retVal;
}
finally {
// cleanup
for (Aggregator agg : aggregators) {
agg.close();
}
}
}
}
);
}
}