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@@ -0,0 +1,39 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 org.apache.druid.query;

/**
* Serialization medium of the query results on the broker. It is currently used to communicate the result's format between
* the main query processing walker and the individual toolchests while materializing subquery's rows
*/
public enum ResultSerializationMode
{
/**
* Materialize the inner results as rows
*/
ROWS,

/**
* Materialize the inner results as frames
*/
FRAMES;

public static final String CTX_SERIALIZATION_PARAMETER = "serialization";
}
Original file line number Diff line number Diff line change
Expand Up @@ -23,24 +23,30 @@
import com.google.common.base.Function;
import com.google.common.base.Functions;
import com.google.common.collect.ImmutableMap;
import org.apache.druid.error.DruidException;
import org.apache.druid.frame.allocation.MemoryAllocatorFactory;
import org.apache.druid.java.util.common.guava.Sequence;
import org.apache.druid.java.util.common.guava.Sequences;
import org.apache.druid.query.DefaultQueryMetrics;
import org.apache.druid.query.FrameSignaturePair;
import org.apache.druid.query.QueryMetrics;
import org.apache.druid.query.QueryPlus;
import org.apache.druid.query.QueryRunner;
import org.apache.druid.query.QueryToolChest;
import org.apache.druid.query.ResultSerializationMode;
import org.apache.druid.query.aggregation.MetricManipulationFn;
import org.apache.druid.query.context.ResponseContext;
import org.apache.druid.query.rowsandcols.RowsAndColumns;
import org.apache.druid.query.rowsandcols.column.Column;
import org.apache.druid.query.rowsandcols.column.ColumnAccessor;
import org.apache.druid.query.rowsandcols.column.NullColumn;
import org.apache.druid.query.rowsandcols.semantic.FrameMaker;
import org.apache.druid.segment.column.ColumnType;
import org.apache.druid.segment.column.RowSignature;

import java.util.ArrayList;
import java.util.List;
import java.util.Optional;
import java.util.function.Supplier;

public class WindowOperatorQueryQueryToolChest extends QueryToolChest<RowsAndColumns, WindowOperatorQuery>
Expand All @@ -50,7 +56,7 @@ public class WindowOperatorQueryQueryToolChest extends QueryToolChest<RowsAndCol
@SuppressWarnings("unchecked")
public QueryRunner<RowsAndColumns> mergeResults(QueryRunner<RowsAndColumns> runner)
{
return new RowsAndColumnsUnravelingQueryRunner(
return new RowsAndColumnsSerializingQueryRunner(
(queryPlus, responseContext) -> {
final WindowOperatorQuery query = (WindowOperatorQuery) queryPlus.getQuery();
final List<OperatorFactory> opFactories = query.getOperators();
Expand All @@ -61,7 +67,7 @@ public QueryRunner<RowsAndColumns> mergeResults(QueryRunner<RowsAndColumns> runn
Supplier<Operator> opSupplier = () -> {
Operator retVal = new SequenceOperator(
runner.run(
queryPlus.withQuery(query.withOperators(new ArrayList<OperatorFactory>())),
queryPlus.withQuery(query.withOperators(new ArrayList<>())),
responseContext
)
);
Expand Down Expand Up @@ -112,16 +118,29 @@ public Sequence<Object[]> resultsAsArrays(
Sequence<RowsAndColumns> resultSequence
)
{
// Dark magic; see RowsAndColumnsUnravelingQueryRunner.
// Dark magic; see RowsAndColumnsSerializingQueryRunner.
return (Sequence) resultSequence;
}

@Override
@SuppressWarnings({"unchecked", "rawtypes"})
public Optional<Sequence<FrameSignaturePair>> resultsAsFrames(
Comment thread
kgyrtkirk marked this conversation as resolved.
WindowOperatorQuery query,
Sequence<RowsAndColumns> resultSequence,
MemoryAllocatorFactory memoryAllocatorFactory,
boolean useNestedForUnknownTypes
)
{
// see RowsAndColumnsSerializingQueryRunner
return Optional.of((Sequence) resultSequence);
}

/**
* This class exists to unravel the RowsAndColumns that are used in this query and make it the return Sequence
* actually be a Sequence of rows. This is relatively broken in a number of regards, the most obvious of which
* is that it is going to run counter to the stated class on the Generic of the QueryToolChest. That is, the
* code makes it look like you are getting a Sequence of RowsAndColumns, but, by using this, the query will
* actually ultimately produce a Sequence of Object[]. This works because of type Erasure in Java (it's all Object
* This class exists to serialize the RowsAndColumns that are used in this query and make it the return Sequence
* actually be a Sequence of rows or frames, as the query requires.
* This is relatively broken in a number of regards, the most obvious of which is that it is going to run counter to the stated class on the Generic of the QueryToolChest.
* That is, the code makes it look like you are getting a Sequence of RowsAndColumns, but, by using this, the query will
* actually ultimately produce a Sequence of Object[] or Frames. This works because of type Erasure in Java (it's all Object
* at the end of the day).
* <p>
* While it might seem like this will break all sorts of things, the Generic type is actually there more as a type
Expand All @@ -132,12 +151,12 @@ public Sequence<Object[]> resultsAsArrays(
* Not our proudest moment, but we use the tools available to us.
*/
@SuppressWarnings({"unchecked", "rawtypes"})
private static class RowsAndColumnsUnravelingQueryRunner implements QueryRunner
private static class RowsAndColumnsSerializingQueryRunner implements QueryRunner
{

private final QueryRunner<RowsAndColumns> baseQueryRunner;

private RowsAndColumnsUnravelingQueryRunner(
private RowsAndColumnsSerializingQueryRunner(
QueryRunner<RowsAndColumns> baseQueryRunner
)
{
Expand All @@ -158,42 +177,77 @@ public Sequence run(
queryPlus.withQuery(query.withOverriddenContext(ImmutableMap.of("unravel", false))),
responseContext
);
final ResultSerializationMode serializationMode = query.context().getEnum(
ResultSerializationMode.CTX_SERIALIZATION_PARAMETER,
ResultSerializationMode.class,
ResultSerializationMode.ROWS
);
switch (serializationMode) {
case ROWS:
return asRows(baseSequence, query);
case FRAMES:
return asFrames(baseSequence);
default:
throw DruidException.defensive("Serialization mode[%s] not supported", serializationMode);
}
}

final RowSignature rowSignature = query.getRowSignature();
return baseSequence.flatMap(
rac -> {
List<Object[]> results = new ArrayList<>(rac.numRows());

ColumnAccessor[] accessors = new ColumnAccessor[rowSignature.size()];
int index = 0;
for (String columnName : rowSignature.getColumnNames()) {
final Column column = rac.findColumn(columnName);
if (column == null) {
final ColumnType columnType = rowSignature
.getColumnType(columnName)
.orElse(ColumnType.UNKNOWN_COMPLEX);

accessors[index] = new NullColumn.Accessor(columnType, rac.numRows());
} else {
accessors[index] = column.toAccessor();
}
++index;
}
return baseQueryRunner.run(queryPlus, responseContext);
}

for (int i = 0; i < rac.numRows(); ++i) {
Object[] objArr = new Object[accessors.length];
for (int j = 0; j < accessors.length; j++) {
objArr[j] = accessors[j].getObject(i);
}
results.add(objArr);
/**
* Translates Sequence of RACs to a Sequence of Object[]
*/
private static Sequence asRows(final Sequence<RowsAndColumns> baseSequence, final WindowOperatorQuery query)
{
final RowSignature rowSignature = query.getRowSignature();
return baseSequence.flatMap(
rac -> {
List<Object[]> results = new ArrayList<>(rac.numRows());

ColumnAccessor[] accessors = new ColumnAccessor[rowSignature.size()];
int index = 0;
for (String columnName : rowSignature.getColumnNames()) {
final Column column = rac.findColumn(columnName);
if (column == null) {
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I feel like this should not happen at all - could it be an exception instead?

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Druid has a lot of places where the absence of a column is treated as all nulls, so leaving it as is is a less risky proposition. Can this happen if one of the segments doesn't contain a row, while the others do?

That said, this portion has been refactored as-is from the pre-existing code. I'll leave it to you to decide if this is applicable or not.

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around here it seems like we already had that in the signature; but if the rac doesn't know about that column I think its already inconsistent for some reason; it might be due to some other issue...

That said, this portion has been refactored as-is from the pre-existing code. I'll leave it to you to decide if this is applicable or not.

if we could add an exception and all tests pass I think we are better of with that 🤞

final ColumnType columnType = rowSignature
.getColumnType(columnName)
.orElse(ColumnType.UNKNOWN_COMPLEX);

accessors[index] = new NullColumn.Accessor(columnType, rac.numRows());
} else {
accessors[index] = column.toAccessor();
}
++index;
}

return Sequences.simple(results);
for (int i = 0; i < rac.numRows(); ++i) {
Object[] objArr = new Object[accessors.length];
for (int j = 0; j < accessors.length; j++) {
objArr[j] = accessors[j].getObject(i);
}
results.add(objArr);
}
);
}

return baseQueryRunner.run(queryPlus, responseContext);
return Sequences.simple(results);
}
);
}

/**
* Translates a sequence of RACs to a Sequence of Frames
*/
private static Sequence asFrames(final Sequence<RowsAndColumns> baseSequence)
{
return baseSequence.map(
rac -> {
FrameMaker frameMaker = FrameMaker.fromRAC(rac);
return new FrameSignaturePair(
frameMaker.toColumnBasedFrame(),
frameMaker.computeSignature()
);
Comment on lines +244 to +248
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just a note
I feel like this part might not perform that well if it processes very small racs; like 1-2 rows
for example the toColumnBasedFrame allocates a 200MB area for producing the frame...

we could possibly improve on this later by adding an operator which could compact smaller racs into bigger ones or something.

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Yeah, we could have a recombining operator at the end that basically exists to recombine things based on whatever input boundaries would have existed. We should be able to make this "magically" happen, if it's not already then it's just a question of what the stacktrace looks like and which concrete RAC classes are involved.

}
);
}
}
}
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