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QuestDB is High Performance Time Series Database
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* | | | | | | |/ _ \/ __| __| | | | _ \
* | |_| | |_| | __/\__ \ |_| |_| | |_) |
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*
* Copyright (c) 2014-2019 Appsicle
* Copyright (c) 2019-2020 QuestDB
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
******************************************************************************/
package io.questdb.cairo;
import io.questdb.cairo.sql.DataFrame;
import io.questdb.std.LongList;
public class IntervalFwdDataFrameCursor extends AbstractIntervalDataFrameCursor {
/**
* Cursor for data frames that chronologically intersect collection of intervals.
* Data frame low and high row will be within intervals inclusive of edges. Intervals
* themselves are pairs of microsecond time.
*
* @param intervals pairs of microsecond interval values, as in "low" and "high" inclusive of
* edges.
* @param timestampIndex index of timestamp column in the readr that is used by this cursor
*/
public IntervalFwdDataFrameCursor(LongList intervals, int timestampIndex) {
super(intervals, timestampIndex);
}
@Override
public DataFrame next() {
// order of logical operations is important
// we are not calculating partition rages when intervals are empty
while (intervalsLo < intervalsHi && partitionLo < partitionHi) {
// We don't need to worry about column tops and null column because we
// are working with timestamp. Timestamp column cannot be added to existing table.
long rowCount = reader.openPartition(partitionLo);
if (rowCount > 0) {
final ReadOnlyColumn column = reader.getColumn(TableReader.getPrimaryColumnIndex(reader.getColumnBase(partitionLo), timestampIndex));
final long intervalLo = intervals.getQuick(intervalsLo * 2);
final long intervalHi = intervals.getQuick(intervalsLo * 2 + 1);
final long partitionTimestampLo = column.getLong(0);
// interval is wholly above partition, skip interval
if (partitionTimestampLo > intervalHi) {
intervalsLo++;
continue;
}
final long partitionTimestampHi = column.getLong((rowCount - 1) * 8);
// interval is wholly below partition, skip partition
if (partitionTimestampHi < intervalLo) {
partitionLimit = 0;
partitionLo++;
continue;
}
// calculate intersection
long lo;
if (partitionTimestampLo == intervalLo) {
lo = 0;
} else {
lo = search(column, intervalLo, partitionLimit, rowCount, AbstractIntervalDataFrameCursor.SCAN_UP);
if (lo < 0) {
lo = -lo - 1;
}
}
long hi = search(column, intervalHi, lo, rowCount, AbstractIntervalDataFrameCursor.SCAN_DOWN);
if (hi < 0) {
hi = -hi - 1;
} else {
// We have direct hit. Interval is inclusive of edges and we have to
// bump to high bound because it is non-inclusive
hi++;
}
if (lo < hi) {
dataFrame.partitionIndex = partitionLo;
dataFrame.rowLo = lo;
dataFrame.rowHi = hi;
// we do have whole partition of fragment?
if (hi == rowCount) {
// whole partition, will need to skip to next one
partitionLimit = 0;
partitionLo++;
} else {
// only fragment, need to skip to next interval
partitionLimit = hi;
intervalsLo++;
}
return dataFrame;
}
// interval yielded empty data frame
partitionLimit = hi;
intervalsLo++;
} else {
// partition was empty, just skip to next
partitionLo++;
}
}
return null;
}
@Override
public long size() {
return -1;
}
@Override
public void toTop() {
super.toTop();
partitionLimit = 0;
}
}
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