/**
* 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.udf.generic;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDFArgumentTypeException;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage.GenericUDAFAverageEvaluatorDouble;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage.GenericUDAFAverageEvaluatorDecimal;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFCorrelation.GenericUDAFCorrelationEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFCount.GenericUDAFCountEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFVariance.GenericUDAFVarianceEvaluator;
import org.apache.hadoop.hive.serde2.io.DoubleWritable;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector.PrimitiveCategory;
import org.apache.hadoop.hive.serde2.typeinfo.PrimitiveTypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo;
public class GenericUDAFBinarySetFunctions extends AbstractGenericUDAFResolver {
@Description(name = "regr_count", value = "_FUNC_(y,x) - returns the number of non-null pairs", extended = "The function takes as arguments any pair of numeric types and returns a long.\n"
+ "Any pair with a NULL is ignored.")
public static class RegrCount extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFCountEvaluator {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[0] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[0] });
}
}
}
@Description(name = "regr_sxx", value = "_FUNC_(y,x) - auxiliary analytic function", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " SUM(x*x)-SUM(x)*SUM(x)/N\n")
public static class RegrSXX extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFVarianceEvaluator {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[1] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[1] });
}
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
StdAgg myagg = (StdAgg) agg;
if (myagg.count == 0) {
return null;
} else {
DoubleWritable result = getResult();
result.set(myagg.variance);
return result;
}
}
}
}
@Description(name = "regr_syy", value = "_FUNC_(y,x) - auxiliary analytic function", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " SUM(y*y)-SUM(y)*SUM(y)/N\n")
public static class RegrSYY extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFVarianceEvaluator {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[0] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[0] });
}
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
StdAgg myagg = (StdAgg) agg;
if (myagg.count == 0) {
return null;
} else {
DoubleWritable result = getResult();
result.set(myagg.variance);
return result;
}
}
}
}
@Description(name = "regr_avgx", value = "_FUNC_(y,x) - evaluates the average of the independent variable", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " AVG(X)")
public static class RegrAvgX extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
if (((PrimitiveTypeInfo) parameters[1]).getPrimitiveCategory() == PrimitiveCategory.DECIMAL) {
return new EvaluatorDecimal();
} else {
return new EvaluatorDouble();
}
}
private static class EvaluatorDouble extends GenericUDAFAverageEvaluatorDouble {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[1] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[1] });
}
}
private static class EvaluatorDecimal extends GenericUDAFAverageEvaluatorDecimal {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[1] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[1] });
}
}
}
@Description(name = "regr_avgy", value = "_FUNC_(y,x) - evaluates the average of the dependent variable", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " AVG(Y)")
public static class RegrAvgY extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
if (((PrimitiveTypeInfo) parameters[0]).getPrimitiveCategory() == PrimitiveCategory.DECIMAL) {
return new EvaluatorDecimal();
} else {
return new EvaluatorDouble();
}
}
private static class EvaluatorDouble extends GenericUDAFAverageEvaluatorDouble {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[0] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[0] });
}
}
private static class EvaluatorDecimal extends GenericUDAFAverageEvaluatorDecimal {
@Override
public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException {
switch (m) {
case COMPLETE:
case PARTIAL1:
return super.init(m, new ObjectInspector[] { parameters[0] });
default:
return super.init(m, parameters);
}
}
@Override
public void iterate(AggregationBuffer agg, Object[] parameters) throws HiveException {
if (parameters[0] == null || parameters[1] == null)
return;
super.iterate(agg, new Object[] { parameters[0] });
}
}
}
@Description(name = "regr_slope", value = "_FUNC_(y,x) - returns the slope of the linear regression line", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "If N*SUM(x*x) = SUM(x)*SUM(x): NULL is returned (the fit would be a vertical).\n"
+ "Otherwise, it computes the following:\n"
+ " (N*SUM(x*y)-SUM(x)*SUM(y)) / (N*SUM(x*x)-SUM(x)*SUM(x))")
public static class RegrSlope extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFCorrelationEvaluator {
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
StdAgg myagg = (StdAgg) agg;
if (myagg.count < 2 || myagg.xvar == 0.0d) {
return null;
} else {
getResult().set(myagg.covar / myagg.xvar);
return getResult();
}
}
}
}
@Description(name = "regr_r2", value = "_FUNC_(y,x) - returns the coefficient of determination (also called R-squared or goodness of fit) for the regression line.", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "If N*SUM(x*x) = SUM(x)*SUM(x): NULL is returned.\n"
+ "If N*SUM(y*y) = SUM(y)*SUM(y): 1 is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " POWER( N*SUM(x*y)-SUM(x)*SUM(y) ,2) / ( (N*SUM(x*x)-SUM(x)*SUM(x)) * (N*SUM(y*y)-SUM(y)*SUM(y)) )")
public static class RegrR2 extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFCorrelationEvaluator {
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
StdAgg myagg = (StdAgg) agg;
if (myagg.count < 2 || myagg.xvar == 0.0d) {
return null;
}
DoubleWritable result = getResult();
if (myagg.yvar == 0.0d) {
result.set(1.0d);
} else {
result.set(myagg.covar * myagg.covar / myagg.xvar / myagg.yvar);
}
return result;
}
}
}
@Description(name = "regr_sxy", value = "_FUNC_(y,x) - return a value that can be used to evaluate the statistical validity of a regression model.", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "If N*SUM(x*x) = SUM(x)*SUM(x): NULL is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " SUM(x*y)-SUM(x)*SUM(y)/N")
public static class RegrSXY extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFCorrelationEvaluator {
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
StdAgg myagg = (StdAgg) agg;
if (myagg.count == 0) {
return null;
}
DoubleWritable result = getResult();
result.set(myagg.covar);
return result;
}
}
}
@Description(name = "regr_intercept", value = "_FUNC_(y,x) - returns the y-intercept of the regression line.", extended = "The function takes as arguments any pair of numeric types and returns a double.\n"
+ "Any pair with a NULL is ignored.\n"
+ "If applied to an empty set: NULL is returned.\n"
+ "If N*SUM(x*x) = SUM(x)*SUM(x): NULL is returned.\n"
+ "Otherwise, it computes the following:\n"
+ " ( SUM(y)*SUM(x*x)-SUM(X)*SUM(x*y) ) / ( N*SUM(x*x)-SUM(x)*SUM(x) )")
public static class RegrIntercept extends AbstractGenericUDAFResolver {
@Override
public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters) throws SemanticException {
checkArgumentTypes(parameters);
return new Evaluator();
}
private static class Evaluator extends GenericUDAFCorrelationEvaluator {
@Override
public Object terminate(AggregationBuffer agg) throws HiveException {
StdAgg myagg = (StdAgg) agg;
if (myagg.count == 0 || myagg.xvar == 0.0d) {
return null;
}
DoubleWritable result = getResult();
double slope = myagg.covar / myagg.xvar;
result.set(myagg.yavg - slope * myagg.xavg);
return result;
}
}
}
private static void checkArgumentTypes(TypeInfo[] parameters) throws UDFArgumentTypeException {
if (parameters.length != 2) {
throw new UDFArgumentTypeException(parameters.length - 1,
"Exactly two arguments are expected.");
}
if (parameters[0].getCategory() != ObjectInspector.Category.PRIMITIVE) {
throw new UDFArgumentTypeException(0, "Only primitive type arguments are accepted but "
+ parameters[0].getTypeName() + " is passed.");
}
if (parameters[1].getCategory() != ObjectInspector.Category.PRIMITIVE) {
throw new UDFArgumentTypeException(1, "Only primitive type arguments are accepted but "
+ parameters[1].getTypeName() + " is passed.");
}
if (!acceptedPrimitiveCategory(((PrimitiveTypeInfo) parameters[0]).getPrimitiveCategory())) {
throw new UDFArgumentTypeException(0, "Only numeric type arguments are accepted but "
+ parameters[0].getTypeName() + " is passed.");
}
if (!acceptedPrimitiveCategory(((PrimitiveTypeInfo) parameters[1]).getPrimitiveCategory())) {
throw new UDFArgumentTypeException(1, "Only numeric type arguments are accepted but "
+ parameters[1].getTypeName() + " is passed.");
}
}
private static boolean acceptedPrimitiveCategory(PrimitiveCategory primitiveCategory) {
switch (primitiveCategory) {
case BYTE:
case SHORT:
case INT:
case LONG:
case FLOAT:
case DOUBLE:
case TIMESTAMP:
case DECIMAL:
return true;
default:
return false;
}
}
}