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/*
* 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.drill.exec.planner.fragment;
import org.apache.commons.lang3.tuple.Pair;
import org.apache.drill.common.util.function.CheckedConsumer;
import org.apache.drill.exec.ops.QueryContext;
import org.apache.drill.exec.physical.PhysicalOperatorSetupException;
import org.apache.drill.exec.physical.base.PhysicalOperator;
import org.apache.drill.exec.planner.cost.NodeResource;
import org.apache.drill.exec.proto.CoordinationProtos.DrillbitEndpoint;
import java.util.Map;
import java.util.HashMap;
import java.util.Collection;
import java.util.Set;
import java.util.List;
import java.util.ArrayList;
import java.util.function.BiFunction;
import java.util.stream.Collectors;
/**
* Paralellizer specialized for managing resources for a query based on Queues. This parallelizer
* does not deal with increase/decrease of the parallelization of a query plan based on the current
* cluster state. However, the memory assignment for each operator, minor fragment and major
* fragment is based on the cluster state and provided queue configuration.
*/
public class QueueQueryParallelizer extends SimpleParallelizer {
private final boolean planHasMemory;
private final QueryContext queryContext;
private final Map<DrillbitEndpoint, Map<PhysicalOperator, Long>> operators;
public QueueQueryParallelizer(boolean memoryPlanning, QueryContext queryContext) {
super(queryContext);
this.planHasMemory = memoryPlanning;
this.queryContext = queryContext;
this.operators = new HashMap<>();
}
// return the memory computed for a physical operator on a drillbitendpoint.
public BiFunction<DrillbitEndpoint, PhysicalOperator, Long> getMemory() {
return (endpoint, operator) -> {
if (planHasMemory) {
return operators.get(endpoint).get(operator);
}
else {
return operator.getMaxAllocation();
}
};
}
/**
* Function called by the SimpleParallelizer to adjust the memory post parallelization.
* The overall logic is to traverse the fragment tree and call the MemoryCalculator on
* each major fragment. Once the memory is computed, resource requirement are accumulated
* per drillbit.
*
* The total resource requirements are used to select a queue. If the selected queue's
* resource limit is more/less than the query's requirement than the memory will be re-adjusted.
*
* @param planningSet context of the fragments.
* @param roots root fragments.
* @param activeEndpoints currently active endpoints.
* @throws PhysicalOperatorSetupException
*/
public void adjustMemory(PlanningSet planningSet, Set<Wrapper> roots,
Collection<DrillbitEndpoint> activeEndpoints) throws PhysicalOperatorSetupException {
if (planHasMemory) {
return;
}
// total node resources for the query plan maintained per drillbit.
final Map<DrillbitEndpoint, NodeResource> totalNodeResources =
activeEndpoints.stream().collect(Collectors.toMap(x ->x,
x -> NodeResource.create()));
// list of the physical operators and their memory requirements per drillbit.
final Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>> operators =
activeEndpoints.stream().collect(Collectors.toMap(x -> x,
x -> new ArrayList<>()));
for (Wrapper wrapper : roots) {
traverse(wrapper, CheckedConsumer.throwingConsumerWrapper((Wrapper fragment) -> {
MemoryCalculator calculator = new MemoryCalculator(planningSet, queryContext);
fragment.getNode().getRoot().accept(calculator, fragment);
NodeResource.merge(totalNodeResources, fragment.getResourceMap());
operators.entrySet()
.stream()
.forEach((entry) -> entry.getValue()
.addAll(calculator.getBufferedOperators(entry.getKey())));
}));
}
//queryrm.selectQueue( pass the max node Resource) returns queue configuration.
Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>> memoryAdjustedOperators = ensureOperatorMemoryWithinLimits(operators, totalNodeResources, 10);
memoryAdjustedOperators.entrySet().stream().forEach((x) -> {
Map<PhysicalOperator, Long> memoryPerOperator = x.getValue().stream()
.collect(Collectors.toMap(operatorLongPair -> operatorLongPair.getLeft(),
operatorLongPair -> operatorLongPair.getRight(),
(mem_1, mem_2) -> (mem_1 + mem_2)));
this.operators.put(x.getKey(), memoryPerOperator);
});
}
/**
* Helper method to adjust the memory for the buffered operators.
* @param memoryPerOperator list of physical operators per drillbit
* @param nodeResourceMap resources per drillbit.
* @param nodeLimit permissible node limit.
* @return list of operators which contain adjusted memory limits.
*/
private Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>>
ensureOperatorMemoryWithinLimits(Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>> memoryPerOperator,
Map<DrillbitEndpoint, NodeResource> nodeResourceMap, int nodeLimit) {
// Get the physical operators which are above the node memory limit.
Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>> onlyMemoryAboveLimitOperators = new HashMap<>();
memoryPerOperator.entrySet().stream().forEach((entry) -> {
onlyMemoryAboveLimitOperators.putIfAbsent(entry.getKey(), new ArrayList<>());
if (nodeResourceMap.get(entry.getKey()).getMemory() > nodeLimit) {
onlyMemoryAboveLimitOperators.get(entry.getKey()).addAll(entry.getValue());
}
});
// Compute the total memory required by the physical operators on the drillbits which are above node limit.
// Then use the total memory to adjust the memory requirement based on the permissible node limit.
Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>> memoryAdjustedDrillbits = new HashMap<>();
onlyMemoryAboveLimitOperators.entrySet().stream().forEach(
entry -> {
Long totalMemory = entry.getValue().stream().mapToLong(Pair::getValue).sum();
List<Pair<PhysicalOperator, Long>> adjustedMemory = entry.getValue().stream().map(operatorMemory -> {
// formula to adjust the memory is (optimalMemory / totalMemory(this is for all the operators)) * permissible_node_limit.
return Pair.of(operatorMemory.getKey(), (long) Math.ceil(operatorMemory.getValue()/totalMemory * nodeLimit));
}).collect(Collectors.toList());
memoryAdjustedDrillbits.put(entry.getKey(), adjustedMemory);
}
);
// Get all the operations on drillbits which were adjusted for memory and merge them with operators which are not
// adjusted for memory.
Map<DrillbitEndpoint, List<Pair<PhysicalOperator, Long>>> allDrillbits = new HashMap<>();
memoryPerOperator.entrySet().stream().filter((entry) -> !memoryAdjustedDrillbits.containsKey(entry.getKey())).forEach(
operatorMemory -> {
allDrillbits.put(operatorMemory.getKey(), operatorMemory.getValue());
}
);
memoryAdjustedDrillbits.entrySet().stream().forEach(
operatorMemory -> {
allDrillbits.put(operatorMemory.getKey(), operatorMemory.getValue());
}
);
// At this point allDrillbits contains the operators on all drillbits. The memory also is adjusted based on the nodeLimit and
// the ratio of their requirements.
return allDrillbits;
}
}
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