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org.apache.hadoop.hive.ql.exec.vector.expressions.aggregates.gen.VectorUDAFStdPopLong 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.gen;
import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression;
import org.apache.hadoop.hive.ql.exec.vector.expressions.aggregates.VectorAggregateExpression;
import org.apache.hadoop.hive.ql.exec.vector.VectorAggregationBufferRow;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.plan.AggregationDesc;
import org.apache.hadoop.hive.ql.util.JavaDataModel;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.hive.serde2.io.DoubleWritable;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
/**
* VectorUDAFStdPopLong. Vectorized implementation for VARIANCE aggregates.
*/
@Description(name = "std,stddev,stddev_pop",
value = "_FUNC_(x) - Returns the standard deviation of a set of numbers (vectorized, long)")
public class VectorUDAFStdPopLong extends VectorAggregateExpression {
private static final long serialVersionUID = 1L;
/**
/* class for storing the current aggregate value.
*/
private static final class Aggregation implements AggregationBuffer {
private static final long serialVersionUID = 1L;
transient private double sum;
transient private long count;
transient private double variance;
/**
* Value is explicitly (re)initialized in reset() (despite the init() bellow...)
*/
transient private boolean isNull = true;
public void init() {
isNull = false;
sum = 0;
count = 0;
variance = 0;
}
@Override
public int getVariableSize() {
throw new UnsupportedOperationException();
}
@Override
public void reset () {
isNull = true;
sum = 0;
count = 0;
variance = 0;
}
}
private VectorExpression inputExpression;
transient private LongWritable resultCount;
transient private DoubleWritable resultSum;
transient private DoubleWritable resultVariance;
transient private Object[] partialResult;
transient private ObjectInspector soi;
public VectorUDAFStdPopLong(VectorExpression inputExpression) {
this();
this.inputExpression = inputExpression;
}
public VectorUDAFStdPopLong() {
super();
partialResult = new Object[3];
resultCount = new LongWritable();
resultSum = new DoubleWritable();
resultVariance = new DoubleWritable();
partialResult[0] = resultCount;
partialResult[1] = resultSum;
partialResult[2] = resultVariance;
initPartialResultInspector();
}
private void initPartialResultInspector() {
List foi = new ArrayList();
foi.add(PrimitiveObjectInspectorFactory.writableLongObjectInspector);
foi.add(PrimitiveObjectInspectorFactory.writableDoubleObjectInspector);
foi.add(PrimitiveObjectInspectorFactory.writableDoubleObjectInspector);
List fname = new ArrayList();
fname.add("count");
fname.add("sum");
fname.add("variance");
soi = ObjectInspectorFactory.getStandardStructObjectInspector(fname, foi);
}
private Aggregation getCurrentAggregationBuffer(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
int row) {
VectorAggregationBufferRow mySet = aggregationBufferSets[row];
Aggregation myagg = (Aggregation) mySet.getAggregationBuffer(aggregateIndex);
return myagg;
}
@Override
public void aggregateInputSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
VectorizedRowBatch batch) throws HiveException {
inputExpression.evaluate(batch);
LongColumnVector inputVector = (LongColumnVector)batch.
cols[this.inputExpression.getOutputColumn()];
int batchSize = batch.size;
if (batchSize == 0) {
return;
}
long[] vector = inputVector.vector;
if (inputVector.isRepeating) {
if (inputVector.noNulls || !inputVector.isNull[0]) {
iterateRepeatingNoNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex, vector[0], batchSize);
}
}
else if (!batch.selectedInUse && inputVector.noNulls) {
iterateNoSelectionNoNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex, vector, batchSize);
}
else if (!batch.selectedInUse) {
iterateNoSelectionHasNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex, vector, batchSize, inputVector.isNull);
}
else if (inputVector.noNulls){
iterateSelectionNoNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex, vector, batchSize, batch.selected);
}
else {
iterateSelectionHasNullsWithAggregationSelection(
aggregationBufferSets, aggregateIndex, vector, batchSize,
inputVector.isNull, batch.selected);
}
}
private void iterateRepeatingNoNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
double value,
int batchSize) {
for (int i=0; i 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
private void iterateSelectionHasNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
long[] vector,
int batchSize,
boolean[] isNull,
int[] selected) {
for (int j=0; j< batchSize; ++j) {
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregateIndex,
j);
int i = selected[j];
if (!isNull[i]) {
double value = vector[i];
if (myagg.isNull) {
myagg.init ();
}
myagg.sum += value;
myagg.count += 1;
if(myagg.count > 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
}
private void iterateSelectionNoNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
long[] vector,
int batchSize,
int[] selected) {
for (int i=0; i< batchSize; ++i) {
Aggregation myagg = getCurrentAggregationBuffer(
aggregationBufferSets,
aggregateIndex,
i);
double value = vector[selected[i]];
if (myagg.isNull) {
myagg.init ();
}
myagg.sum += value;
myagg.count += 1;
if(myagg.count > 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
private void iterateNoSelectionHasNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
long[] vector,
int batchSize,
boolean[] isNull) {
for(int i=0;i 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
}
private void iterateNoSelectionNoNullsWithAggregationSelection(
VectorAggregationBufferRow[] aggregationBufferSets,
int aggregateIndex,
long[] vector,
int batchSize) {
for (int i=0; i 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
@Override
public void aggregateInput(AggregationBuffer agg, VectorizedRowBatch batch)
throws HiveException {
inputExpression.evaluate(batch);
LongColumnVector inputVector = (LongColumnVector)batch.
cols[this.inputExpression.getOutputColumn()];
int batchSize = batch.size;
if (batchSize == 0) {
return;
}
Aggregation myagg = (Aggregation)agg;
long[] vector = inputVector.vector;
if (inputVector.isRepeating) {
if (inputVector.noNulls) {
iterateRepeatingNoNulls(myagg, vector[0], batchSize);
}
}
else if (!batch.selectedInUse && inputVector.noNulls) {
iterateNoSelectionNoNulls(myagg, vector, batchSize);
}
else if (!batch.selectedInUse) {
iterateNoSelectionHasNulls(myagg, vector, batchSize, inputVector.isNull);
}
else if (inputVector.noNulls){
iterateSelectionNoNulls(myagg, vector, batchSize, batch.selected);
}
else {
iterateSelectionHasNulls(myagg, vector, batchSize, inputVector.isNull, batch.selected);
}
}
private void iterateRepeatingNoNulls(
Aggregation myagg,
double value,
int batchSize) {
if (myagg.isNull) {
myagg.init ();
}
// TODO: conjure a formula w/o iterating
//
myagg.sum += value;
myagg.count += 1;
if(myagg.count > 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
// We pulled out i=0 so we can remove the count > 1 check in the loop
for (int i=1; i 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
}
private void iterateSelectionNoNulls(
Aggregation myagg,
long[] vector,
int batchSize,
int[] selected) {
if (myagg.isNull) {
myagg.init ();
}
double value = vector[selected[0]];
myagg.sum += value;
myagg.count += 1;
if(myagg.count > 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
// i=0 was pulled out to remove the count > 1 check in the loop
//
for (int i=1; i< batchSize; ++i) {
value = vector[selected[i]];
myagg.sum += value;
myagg.count += 1;
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
private void iterateNoSelectionHasNulls(
Aggregation myagg,
long[] vector,
int batchSize,
boolean[] isNull) {
for(int i=0;i 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
}
}
}
private void iterateNoSelectionNoNulls(
Aggregation myagg,
long[] vector,
int batchSize) {
if (myagg.isNull) {
myagg.init ();
}
double value = vector[0];
myagg.sum += value;
myagg.count += 1;
if(myagg.count > 1) {
double t = myagg.count*value - myagg.sum;
myagg.variance += (t*t) / ((double)myagg.count*(myagg.count-1));
}
// i=0 was pulled out to remove count > 1 check
for (int i=1; i
