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* Licensed to the Apache Software Foundation (ASF) under one
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* 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
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package org.apache.drill.exec.physical.impl.statistics;
// Library implementing HLL algorithm to derive approximate #distinct values(NDV). Please refer:
// 'HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm.' Flajolet et. al.
import com.clearspring.analytics.stream.cardinality.HyperLogLog;
import java.io.ByteArrayInputStream;
import java.io.DataInputStream;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import org.apache.drill.common.types.TypeProtos;
import org.apache.drill.exec.ExecConstants;
import org.apache.drill.exec.server.options.OptionManager;
import org.apache.drill.exec.vector.NullableVarBinaryVector;
import org.apache.drill.exec.vector.ValueVector;
import org.apache.drill.exec.vector.complex.MapVector;
import org.apache.drill.metastore.statistics.Statistic;
public class HLLMergedStatistic extends AbstractMergedStatistic {
private Map<String, HyperLogLog> hllHolder;
private long accuracy;
public HLLMergedStatistic () {
this.hllHolder = new HashMap<>();
state = State.INIT;
}
@Override
public void initialize(String inputName, double samplePercent) {
super.initialize(Statistic.HLL_MERGE, inputName, samplePercent);
state = State.CONFIG;
}
@Override
public String getName() {
return name;
}
@Override
public String getInput() {
return inputName;
}
@Override
public void merge(MapVector input) {
// Check the input is a Map Vector
assert (input.getField().getType().getMinorType() == TypeProtos.MinorType.MAP);
for (ValueVector vv : input) {
String colName = vv.getField().getName();
HyperLogLog colHLLHolder = null;
if (hllHolder.get(colName) != null) {
colHLLHolder = hllHolder.get(colName);
}
NullableVarBinaryVector hllVector = (NullableVarBinaryVector) vv;
NullableVarBinaryVector.Accessor accessor = hllVector.getAccessor();
try {
if (!accessor.isNull(0)) {
ByteArrayInputStream bais = new ByteArrayInputStream(accessor.get(0), 0, vv.getBufferSize());
HyperLogLog other = HyperLogLog.Builder.build(new DataInputStream(bais));
if (colHLLHolder != null) {
colHLLHolder.addAll(other);
hllHolder.put(colName, colHLLHolder);
} else {
hllHolder.put(colName, other);
}
}
} catch (Exception ex) {
//TODO: Catch IOException/CardinalityMergeException
//TODO: logger
}
}
}
public HyperLogLog getStat(String colName) {
if (state != State.COMPLETE) {
throw new IllegalStateException(String.format("Statistic `%s` has not completed merging statistics",
name));
}
return hllHolder.get(colName);
}
@Override
public void setOutput(MapVector output) {
// Check the input is a Map Vector
assert (output.getField().getType().getMinorType() == TypeProtos.MinorType.MAP);
// Dependencies have been configured correctly
assert (state == State.MERGE);
for (ValueVector outMapCol : output) {
String colName = outMapCol.getField().getName();
HyperLogLog colHLLHolder = hllHolder.get(colName);
NullableVarBinaryVector vv = (NullableVarBinaryVector) outMapCol;
vv.allocateNewSafe();
try {
if (colHLLHolder != null) {
vv.getMutator().setSafe(0, colHLLHolder.getBytes(),
0, colHLLHolder.getBytes().length);
} else {
vv.getMutator().setNull(0);
}
} catch (IOException ex) {
// TODO: logger
}
}
state = State.COMPLETE;
}
public void configure(OptionManager optionsManager) {
assert (state == State.CONFIG);
accuracy = optionsManager.getLong(ExecConstants.HLL_ACCURACY);
// Now config complete - moving to MERGE state
state = State.MERGE;
}
}