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org.apache.hadoop.hive.ql.exec.vector.expressions.aggregates.VectorUDAFBloomFilterMerge Maven / Gradle / Ivy
/*
* 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.hadoop.hive.ql.exec.vector.expressions.aggregates;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.util.Arrays;
import org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.ColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorAggregationBufferRow;
import org.apache.hadoop.hive.ql.exec.vector.VectorAggregationDesc;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression;
import org.apache.hadoop.hive.ql.exec.vector.expressions.aggregates.VectorAggregateExpression.AggregationBuffer;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.plan.AggregationDesc;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.Mode;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.io.IOUtils;
import org.apache.hive.common.util.BloomKFilter;
public class VectorUDAFBloomFilterMerge extends VectorAggregateExpression {
private static final long serialVersionUID = 1L;
private long expectedEntries = -1;
transient private int aggBufferSize;
/**
* class for storing the current aggregate value.
*/
private static final class Aggregation implements AggregationBuffer {
private static final long serialVersionUID = 1L;
byte[] bfBytes;
public Aggregation(long expectedEntries) {
ByteArrayOutputStream bytesOut = null;
try {
BloomKFilter bf = new BloomKFilter(expectedEntries);
bytesOut = new ByteArrayOutputStream();
BloomKFilter.serialize(bytesOut, bf);
bfBytes = bytesOut.toByteArray();
} catch (Exception err) {
throw new IllegalArgumentException("Error creating aggregation buffer", err);
} finally {
IOUtils.closeStream(bytesOut);
}
}
@Override
public int getVariableSize() {
throw new UnsupportedOperationException();
}
@Override
public void reset() {
// Do not change the initial bytes which contain NumHashFunctions/NumBits!
Arrays.fill(bfBytes, BloomKFilter.START_OF_SERIALIZED_LONGS, bfBytes.length, (byte) 0);
}
}
// This constructor is used to momentarily create the object so match can be called.
public VectorUDAFBloomFilterMerge() {
super();
}
public VectorUDAFBloomFilterMerge(VectorAggregationDesc vecAggrDesc) {
super(vecAggrDesc);
init();
}
private void init() {
GenericUDAFBloomFilterEvaluator udafBloomFilter =
(GenericUDAFBloomFilterEvaluator) vecAggrDesc.getEvaluator();
expectedEntries = udafBloomFilter.getExpectedEntries();
aggBufferSize = -1;
}
@Override
public AggregationBuffer getNewAggregationBuffer() throws HiveException {
if (expectedEntries < 0) {
throw new IllegalStateException("expectedEntries not initialized");
}
return new Aggregation(expectedEntries);
}
@Override
public void aggregateInput(AggregationBuffer agg, VectorizedRowBatch batch)
throws HiveException {
inputExpression.evaluate(batch);
ColumnVector inputColumn = batch.cols[this.inputExpression.getOutputColumnNum()];
int batchSize = batch.size;
if (batchSize == 0) {
return;
}
Aggregation myagg = (Aggregation) agg;
if (inputColumn.isRepeating) {
if (inputColumn.noNulls || !inputColumn.isNull[0]) {
processValue(myagg, inputColumn, 0);
}
return;
}
if (!batch.selectedInUse && inputColumn.noNulls) {
iterateNoSelectionNoNulls(myagg, inputColumn, batchSize);
}
else if (!batch.selectedInUse) {
iterateNoSelectionHasNulls(myagg, inputColumn, batchSize);
}
else if (inputColumn.noNulls){
iterateSelectionNoNulls(myagg, inputColumn, batchSize, batch.selected);
}
else {
iterateSelectionHasNulls(myagg, inputColumn, batchSize, batch.selected);
}
}
private void iterateNoSelectionNoNulls(
Aggregation myagg,
ColumnVector inputColumn,
int batchSize) {
for (int i=0; i< batchSize; ++i) {
processValue(myagg, inputColumn, i);
}
}
private void iterateNoSelectionHasNulls(
Aggregation myagg,
ColumnVector inputColumn,
int batchSize) {
for (int i=0; i< batchSize; ++i) {
if (!inputColumn.isNull[i]) {
processValue(myagg, inputColumn, i);
}
}
}
private void iterateSelectionNoNulls(
Aggregation myagg,
ColumnVector inputColumn,
int batchSize,
int[] selected) {
for (int j=0; j< batchSize; ++j) {
int i = selected[j];
processValue(myagg, inputColumn, i);
}
}
private void iterateSelectionHasNulls(
Aggregation myagg,
ColumnVector inputColumn,
int batchSize,
int[] selected) {
for (int j=0; j< batchSize; ++j) {
int i = selected[j];
if (!inputColumn.isNull[i]) {
processValue(myagg, inputColumn, i);
}
}
}
@Override
public void aggregateInputSelection(
VectorAggregationBufferRow[] aggregationBufferSets, int aggregateIndex,
VectorizedRowBatch batch) throws HiveException {
int batchSize = batch.size;
if (batchSize == 0) {
return;
}
inputExpression.evaluate(batch);
ColumnVector inputColumn = batch.cols[this.inputExpression.getOutputColumnNum()];
if (inputColumn.noNulls) {
if (inputColumn.isRepeating) {
iterateNoNullsRepeatingWithAggregationSelection(
aggregationBufferSets, aggregateIndex,
inputColumn, batchSize);
} else {
if (batch.selectedInUse) {
iterateNoNullsSelectionWithAggregationSelection(
aggregationBufferSets, aggregateIndex,
inputColumn, batch.selected, batchSize);
} else {
iterateNoNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex,
inputColumn, batchSize);
}
}
} else {
if (inputColumn.isRepeating) {
if (!inputColumn.isNull[0]) {
iterateNoNullsRepeatingWithAggregationSelection(
aggregationBufferSets, aggregateIndex,
inputColumn, batchSize);
}
} else {
if (batch.selectedInUse) {
iterateHasNullsSelectionWithAggregationSelection(
aggregationBufferSets, aggregateIndex,
inputColumn, batchSize, batch.selected);
} else {
iterateHasNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex,
inputColumn, batchSize);
}
}
}
}
private void iterateNoNullsRepeatingWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregrateIndex,
ColumnVector inputColumn,
int batchSize) {
for (int i=0; i < batchSize; ++i) {
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregrateIndex,
i);
processValue(myagg, inputColumn, 0);
}
}
private void iterateNoNullsSelectionWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregrateIndex,
ColumnVector inputColumn,
int[] selection,
int batchSize) {
for (int i=0; i < batchSize; ++i) {
int row = selection[i];
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregrateIndex,
i);
processValue(myagg, inputColumn, row);
}
}
private void iterateNoNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregrateIndex,
ColumnVector inputColumn,
int batchSize) {
for (int i=0; i < batchSize; ++i) {
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregrateIndex,
i);
processValue(myagg, inputColumn, i);
}
}
private void iterateHasNullsSelectionWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregrateIndex,
ColumnVector inputColumn,
int batchSize,
int[] selection) {
for (int i=0; i < batchSize; ++i) {
int row = selection[i];
if (!inputColumn.isNull[row]) {
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregrateIndex,
i);
processValue(myagg, inputColumn, i);
}
}
}
private void iterateHasNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregrateIndex,
ColumnVector inputColumn,
int batchSize) {
for (int i=0; i < batchSize; ++i) {
if (!inputColumn.isNull[i]) {
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregrateIndex,
i);
processValue(myagg, inputColumn, i);
}
}
}
private Aggregation getCurrentAggregationBuffer(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregrateIndex,
int row) {
VectorAggregationBufferRow mySet = aggregationBufferSets[row];
Aggregation myagg = (Aggregation) mySet.getAggregationBuffer(aggregrateIndex);
return myagg;
}
@Override
public void reset(AggregationBuffer agg) throws HiveException {
agg.reset();
}
@Override
public long getAggregationBufferFixedSize() {
if (aggBufferSize < 0) {
// Not pretty, but we need a way to get the size
try {
Aggregation agg = (Aggregation) getNewAggregationBuffer();
aggBufferSize = agg.bfBytes.length;
} catch (Exception e) {
throw new RuntimeException("Unexpected error while creating AggregationBuffer", e);
}
}
return aggBufferSize;
}
void processValue(Aggregation myagg, ColumnVector columnVector, int i) {
// columnVector entry is byte array representing serialized BloomFilter.
// BloomFilter.mergeBloomFilterBytes() does a simple byte ORing
// which should be faster than deserialize/merge.
BytesColumnVector inputColumn = (BytesColumnVector) columnVector;
BloomKFilter.mergeBloomFilterBytes(myagg.bfBytes, 0, myagg.bfBytes.length,
inputColumn.vector[i], inputColumn.start[i], inputColumn.length[i]);
}
@Override
public boolean matches(String name, ColumnVector.Type inputColVectorType,
ColumnVector.Type outputColVectorType, Mode mode) {
/*
* Bloom filter merge input and output are BYTES.
*
* Just modes (PARTIAL2, FINAL).
*/
return
name.equals("bloom_filter") &&
inputColVectorType == ColumnVector.Type.BYTES &&
outputColVectorType == ColumnVector.Type.BYTES &&
(mode == Mode.PARTIAL2 || mode == Mode.FINAL);
}
@Override
public void assignRowColumn(VectorizedRowBatch batch, int batchIndex, int columnNum,
AggregationBuffer agg) throws HiveException {
BytesColumnVector outputColVector = (BytesColumnVector) batch.cols[columnNum];
outputColVector.isNull[batchIndex] = false;
Aggregation bfAgg = (Aggregation) agg;
outputColVector.setVal(batchIndex, bfAgg.bfBytes, 0, bfAgg.bfBytes.length);
}
}
