src/main/java/org/apache/sysds/runtime/compress/colgroup/ColGroupDDCFOR.java - systemds - Git at Google

 /*
  * 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.sysds.runtime.compress.colgroup;

 import java.io.DataInput;
 import java.io.DataOutput;
 import java.io.IOException;
 import java.util.Arrays;

 import org.apache.commons.lang.NotImplementedException;
 import org.apache.sysds.runtime.DMLRuntimeException;
 import org.apache.sysds.runtime.compress.colgroup.dictionary.ADictionary;
 import org.apache.sysds.runtime.compress.colgroup.dictionary.DictionaryFactory;
 import org.apache.sysds.runtime.compress.colgroup.dictionary.MatrixBlockDictionary;
 import org.apache.sysds.runtime.compress.colgroup.indexes.ColIndexFactory;
 import org.apache.sysds.runtime.compress.colgroup.indexes.IColIndex;
 import org.apache.sysds.runtime.compress.colgroup.mapping.AMapToData;
 import org.apache.sysds.runtime.compress.colgroup.mapping.MapToFactory;
 import org.apache.sysds.runtime.compress.colgroup.scheme.ICLAScheme;
 import org.apache.sysds.runtime.compress.cost.ComputationCostEstimator;
 import org.apache.sysds.runtime.compress.estim.CompressedSizeInfoColGroup;
 import org.apache.sysds.runtime.compress.estim.EstimationFactors;
 import org.apache.sysds.runtime.compress.estim.encoding.EncodingFactory;
 import org.apache.sysds.runtime.compress.estim.encoding.IEncode;
 import org.apache.sysds.runtime.functionobjects.Builtin;
 import org.apache.sysds.runtime.functionobjects.Divide;
 import org.apache.sysds.runtime.functionobjects.Minus;
 import org.apache.sysds.runtime.functionobjects.Multiply;
 import org.apache.sysds.runtime.functionobjects.Plus;
 import org.apache.sysds.runtime.instructions.cp.CM_COV_Object;
 import org.apache.sysds.runtime.matrix.data.MatrixBlock;
 import org.apache.sysds.runtime.matrix.operators.BinaryOperator;
 import org.apache.sysds.runtime.matrix.operators.CMOperator;
 import org.apache.sysds.runtime.matrix.operators.ScalarOperator;
 import org.apache.sysds.runtime.matrix.operators.UnaryOperator;

 /**
  * Class to encapsulate information about a column group that is encoded with dense dictionary encoding (DDC).
  */
 public class ColGroupDDCFOR extends AMorphingMMColGroup implements IFrameOfReferenceGroup {
 	private static final long serialVersionUID = -5769772089913918987L;

 	/** Pointers to row indexes in the dictionary */
 	protected final AMapToData _data;

 	/** Reference values in this column group */
 	protected final double[] _reference;

 	private ColGroupDDCFOR(IColIndex colIndexes, ADictionary dict, double[] reference, AMapToData data,
 		int[] cachedCounts) {
 		super(colIndexes, dict, cachedCounts);
 		_data = data;
 		_reference = reference;
 	}

 	public static AColGroup create(IColIndex colIndexes, ADictionary dict, AMapToData data, int[] cachedCounts,
 		double[] reference) {
 		final boolean allZero = ColGroupUtils.allZero(reference);
 		if(dict == null && allZero)
 			return new ColGroupEmpty(colIndexes);
 		else if(dict == null)
 			return ColGroupConst.create(colIndexes, reference);
 		else if(data.getUnique() == 1)
 			return ColGroupConst.create(colIndexes,
 				dict.binOpRight(new BinaryOperator(Plus.getPlusFnObject()), reference));
 		else if(allZero)
 			return ColGroupDDC.create(colIndexes, dict, data, cachedCounts);
 		else
 			return new ColGroupDDCFOR(colIndexes, dict, reference, data, cachedCounts);
 	}

 	public static AColGroup sparsifyFOR(ColGroupDDC g) {
 		// It is assumed whoever call this does not use an empty Dictionary in g.
 		final int nCol = g.getColIndices().size();
 		final MatrixBlockDictionary mbd = g._dict.getMBDict(nCol);
 		if(mbd != null) {

 			final MatrixBlock mb = mbd.getMatrixBlock();

 			final double[] ref = ColGroupUtils.extractMostCommonValueInColumns(mb);
 			if(ref != null) {
 				MatrixBlockDictionary mDict = mbd.binOpRight(new BinaryOperator(Minus.getMinusFnObject()), ref);
 				return create(g.getColIndices(), mDict, g._data, g.getCachedCounts(), ref);
 			}
 			else
 				return g;
 		}
 		else {
 			throw new NotImplementedException("The dictionary was empty... highly unlikely");
 		}
 	}

 	public CompressionType getCompType() {
 		return CompressionType.DDCFOR;
 	}

 	@Override
 	public double getIdx(int r, int colIdx) {
 		return _dict.getValue(_data.getIndex(r), colIdx, _colIndexes.size()) + _reference[colIdx];
 	}

 	@Override
 	protected void computeRowSums(double[] c, int rl, int ru, double[] preAgg) {
 		for(int rix = rl; rix < ru; rix++)
 			c[rix] += preAgg[_data.getIndex(rix)];
 	}

 	@Override
 	protected void computeRowMxx(double[] c, Builtin builtin, int rl, int ru, double[] preAgg) {
 		for(int i = rl; i < ru; i++)
 			c[i] = builtin.execute(c[i], preAgg[_data.getIndex(i)]);
 	}

 	@Override
 	public int[] getCounts(int[] counts) {
 		return _data.getCounts(counts);
 	}

 	@Override
 	public ColGroupType getColGroupType() {
 		return ColGroupType.DDCFOR;
 	}

 	@Override
 	public long estimateInMemorySize() {
 		long size = super.estimateInMemorySize();
 		size += _data.getInMemorySize();
 		size += 8 * _colIndexes.size();
 		return size;
 	}

 	@Override
 	public AColGroup scalarOperation(ScalarOperator op) {
 		final double[] newRef = new double[_reference.length];
 		for(int i = 0; i < _reference.length; i++)
 			newRef[i] = op.executeScalar(_reference[i]);
 		if(op.fn instanceof Plus || op.fn instanceof Minus)
 			return create(_colIndexes, _dict, _data, getCachedCounts(), newRef);
 		else if(op.fn instanceof Multiply || op.fn instanceof Divide) {
 			final ADictionary newDict = _dict.applyScalarOp(op);
 			return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 		}
 		else {
 			final ADictionary newDict = _dict.applyScalarOpWithReference(op, _reference, newRef);
 			return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 		}
 	}

 	@Override
 	public AColGroup unaryOperation(UnaryOperator op) {
 		final double[] newRef = ColGroupUtils.unaryOperator(op, _reference);
 		final ADictionary newDict = _dict.applyUnaryOpWithReference(op, _reference, newRef);
 		return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 	}

 	@Override
 	public AColGroup binaryRowOpLeft(BinaryOperator op, double[] v, boolean isRowSafe) {
 		final double[] newRef = new double[_reference.length];
 		for(int i = 0; i < _reference.length; i++)
 			newRef[i] = op.fn.execute(v[_colIndexes.get(i)], _reference[i]);

 		if(op.fn instanceof Plus || op.fn instanceof Minus) // only edit reference
 			return create(_colIndexes, _dict, _data, getCachedCounts(), newRef);
 		else if(op.fn instanceof Multiply || op.fn instanceof Divide) {
 			// possible to simply process on dict and keep reference
 			final ADictionary newDict = _dict.binOpLeft(op, v, _colIndexes);
 			return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 		}
 		else { // have to apply reference while processing
 			final ADictionary newDict = _dict.binOpLeftWithReference(op, v, _colIndexes, _reference, newRef);
 			return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 		}
 	}

 	@Override
 	public AColGroup binaryRowOpRight(BinaryOperator op, double[] v, boolean isRowSafe) {
 		final double[] newRef = new double[_reference.length];
 		for(int i = 0; i < _reference.length; i++)
 			newRef[i] = op.fn.execute(_reference[i], v[_colIndexes.get(i)]);

 		if(op.fn instanceof Plus || op.fn instanceof Minus)// only edit reference
 			return create(_colIndexes, _dict, _data, getCachedCounts(), newRef);
 		else if(op.fn instanceof Multiply || op.fn instanceof Divide) {
 			// possible to simply process on dict and keep reference
 			final ADictionary newDict = _dict.binOpRight(op, v, _colIndexes);
 			return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 		}
 		else { // have to apply reference while processing
 			final ADictionary newDict = _dict.binOpRightWithReference(op, v, _colIndexes, _reference, newRef);
 			return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
 		}
 	}

 	@Override
 	public void write(DataOutput out) throws IOException {
 		super.write(out);
 		_data.write(out);
 		for(double d : _reference)
 			out.writeDouble(d);
 	}

 	public static ColGroupDDCFOR read(DataInput in) throws IOException {
 		IColIndex cols = ColIndexFactory.read(in);
 		ADictionary dict = DictionaryFactory.read(in);
 		AMapToData data = MapToFactory.readIn(in);
 		double[] ref = ColGroupIO.readDoubleArray(cols.size(), in);
 		return new ColGroupDDCFOR(cols, dict, ref, data, null);
 	}

 	@Override
 	public long getExactSizeOnDisk() {
 		long ret = super.getExactSizeOnDisk();
 		ret += _data.getExactSizeOnDisk();
 		ret += 8 * _colIndexes.size(); // reference values.
 		return ret;
 	}

 	@Override
 	public double getCost(ComputationCostEstimator e, int nRows) {
 		final int nVals = getNumValues();
 		final int nCols = getNumCols();
 		return e.getCost(nRows, nRows, nCols, nVals, _dict.getSparsity());
 	}

 	@Override
 	public AColGroup replace(double pattern, double replace) {
 		final ADictionary newDict = _dict.replaceWithReference(pattern, replace, _reference);
 		boolean patternInReference = false;
 		for(double d : _reference)
 			if(pattern == d) {
 				patternInReference = true;
 				break;
 			}
 		if(patternInReference) {
 			double[] nRef = new double[_reference.length];
 			for(int i = 0; i < _reference.length; i++)
 				if(pattern == _reference[i])
 					nRef[i] = replace;
 				else
 					nRef[i] = _reference[i];

 			return create(_colIndexes, newDict, _data, getCachedCounts(), nRef);
 		}
 		else
 			return create(_colIndexes, newDict, _data, getCachedCounts(), _reference);

 	}

 	@Override
 	protected double computeMxx(double c, Builtin builtin) {
 		return _dict.aggregateWithReference(c, builtin, _reference, false);
 	}

 	@Override
 	protected void computeColMxx(double[] c, Builtin builtin) {
 		_dict.aggregateColsWithReference(c, builtin, _colIndexes, _reference, false);
 	}

 	@Override
 	protected void computeSum(double[] c, int nRows) {
 		// trick, use normal sum
 		super.computeSum(c, nRows);
 		// and add all sum of reference multiplied with nrows.
 		final double refSum = ColGroupUtils.refSum(_reference);
 		c[0] += refSum * nRows;
 	}

 	@Override
 	public void computeColSums(double[] c, int nRows) {
 		// trick, use normal sum
 		super.computeColSums(c, nRows);
 		// and add reference multiplied with number of rows.
 		for(int i = 0; i < _colIndexes.size(); i++)
 			c[_colIndexes.get(i)] += _reference[i] * nRows;
 	}

 	@Override
 	protected void computeSumSq(double[] c, int nRows) {
 		c[0] += _dict.sumSqWithReference(getCounts(), _reference);
 	}

 	@Override
 	protected void computeColSumsSq(double[] c, int nRows) {
 		_dict.colSumSqWithReference(c, getCounts(), _colIndexes, _reference);
 	}

 	@Override
 	protected double[] preAggSumRows() {
 		return _dict.sumAllRowsToDoubleWithReference(_reference);
 	}

 	@Override
 	protected double[] preAggSumSqRows() {
 		return _dict.sumAllRowsToDoubleSqWithReference(_reference);
 	}

 	@Override
 	protected double[] preAggProductRows() {
 		return _dict.productAllRowsToDoubleWithReference(_reference);
 	}

 	@Override
 	protected double[] preAggBuiltinRows(Builtin builtin) {
 		return _dict.aggregateRowsWithReference(builtin, _reference);
 	}

 	@Override
 	protected void computeProduct(double[] c, int nRows) {
 		_dict.productWithReference(c, getCounts(), _reference, 0);
 	}

 	@Override
 	protected void computeRowProduct(double[] c, int rl, int ru, double[] preAgg) {
 		for(int rix = rl; rix < ru; rix++)
 			c[rix] *= preAgg[_data.getIndex(rix)];
 	}

 	@Override
 	protected void computeColProduct(double[] c, int nRows) {
 		_dict.colProductWithReference(c, getCounts(), _colIndexes, _reference);
 	}

 	@Override
 	protected AColGroup sliceMultiColumns(int idStart, int idEnd, IColIndex outputCols) {
 		ADictionary retDict = _dict.sliceOutColumnRange(idStart, idEnd, _colIndexes.size());
 		final double[] newDef = new double[idEnd - idStart];
 		for(int i = idStart, j = 0; i < idEnd; i++, j++)
 			newDef[j] = _reference[i];
 		return create(outputCols, retDict, _data, getCounts(), newDef);
 	}

 	@Override
 	protected AColGroup sliceSingleColumn(int idx) {
 		final IColIndex retIndexes = ColIndexFactory.create(1);
 		if(_colIndexes.size() == 1) // early abort, only single column already.
 			return create(retIndexes, _dict, _data, getCounts(), _reference);
 		final double[] newDef = new double[] {_reference[idx]};
 		final ADictionary retDict = _dict.sliceOutColumnRange(idx, idx + 1, _colIndexes.size());
 		return create(retIndexes, retDict, _data, getCounts(), newDef);

 	}

 	@Override
 	public boolean containsValue(double pattern) {

 		if(Double.isNaN(pattern) || Double.isInfinite(pattern))
 			return ColGroupUtils.containsInfOrNan(pattern, _reference) || _dict.containsValue(pattern);
 		else
 			return _dict.containsValueWithReference(pattern, _reference);
 	}

 	@Override
 	public long getNumberNonZeros(int nRows) {
 		// to be safe just assume the worst fully dense for DDCFOR
 		return (long) _colIndexes.size() * nRows;
 	}

 	@Override
 	public AColGroup extractCommon(double[] constV) {
 		for(int i = 0; i < _colIndexes.size(); i++)
 			constV[_colIndexes.get(i)] += _reference[i];
 		return ColGroupDDC.create(_colIndexes, _dict, _data, getCounts());
 	}

 	@Override
 	public AColGroup rexpandCols(int max, boolean ignore, boolean cast, int nRows) {
 		final int def = (int) _reference[0];
 		ADictionary d = _dict.rexpandColsWithReference(max, ignore, cast, def);

 		if(d == null) {
 			if(def <= 0 || def > max)
 				return ColGroupEmpty.create(max);
 			else {
 				double[] retDef = new double[max];
 				retDef[((int) def) - 1] = 1;
 				return ColGroupConst.create(retDef);
 			}
 		}
 		else {
 			IColIndex outCols = ColIndexFactory.create(max);
 			if(def <= 0) {
 				if(ignore)
 					return ColGroupDDC.create(outCols, d, _data, getCachedCounts());
 				else
 					throw new DMLRuntimeException("Invalid content of zero in rexpand");
 			}
 			else if(def > max)
 				return ColGroupDDC.create(outCols, d, _data, getCachedCounts());
 			else {
 				double[] retDef = new double[max];
 				retDef[((int) def) - 1] = 1;
 				return ColGroupDDCFOR.create(outCols, d, _data, getCachedCounts(), retDef);
 			}
 		}

 	}

 	@Override
 	public CM_COV_Object centralMoment(CMOperator op, int nRows) {
 		// should be guaranteed to be one column therefore only one reference value.
 		CM_COV_Object ret = _dict.centralMomentWithReference(op.fn, getCounts(), _reference[0], nRows);
 		return ret;
 	}

 	@Override
 	public double[] getCommon() {
 		return _reference;
 	}

 	@Override
 	protected AColGroup allocateRightMultiplicationCommon(double[] common, IColIndex colIndexes, ADictionary preAgg) {
 		return create(colIndexes, preAgg, _data, getCachedCounts(), common);
 	}

 	@Override
 	public AColGroup sliceRows(int rl, int ru) {
 		AMapToData sliceMap = _data.slice(rl, ru);
 		return new ColGroupDDCFOR(_colIndexes, _dict, _reference, sliceMap, null);
 	}

 	@Override
 	protected AColGroup copyAndSet(IColIndex colIndexes, ADictionary newDictionary) {
 		return create(colIndexes, newDictionary, _data, getCachedCounts(), _reference);
 	}

 	@Override
 	public AColGroup append(AColGroup g) {
 		if(g instanceof ColGroupDDCFOR && g.getColIndices().equals(_colIndexes)) {
 			ColGroupDDCFOR gDDC = (ColGroupDDCFOR) g;
 			if(Arrays.equals(_reference, gDDC._reference) && gDDC._dict.equals(_dict)) {
 				AMapToData nd = _data.append(gDDC._data);
 				return create(_colIndexes, _dict, nd, null, _reference);
 			}
 		}
 		return null;
 	}

 	@Override
 	public AColGroup appendNInternal(AColGroup[] g) {
 		return null;
 	}

 	@Override
 	public ICLAScheme getCompressionScheme() {
 		return null;
 	}

 	@Override
 	public AColGroup recompress() {
 		return this;
 	}

 	@Override
 	public CompressedSizeInfoColGroup getCompressionInfo(int nRow) {
 		IEncode enc = getEncoding();
 		EstimationFactors ef = new EstimationFactors(getNumValues(), _data.size(), _data.size(), _dict.getSparsity());
 		return new CompressedSizeInfoColGroup(_colIndexes, ef, estimateInMemorySize(), getCompType(), enc);
 	}

 	@Override
 	public IEncode getEncoding() {
 		return EncodingFactory.create(_data);
 	}

 	@Override
 	public boolean sameIndexStructure(AColGroupCompressed that) {
 		return that instanceof ColGroupDDCFOR && ((ColGroupDDCFOR) that)._data == _data;
 	}

 	@Override
 	protected AColGroup fixColIndexes(IColIndex newColIndex, int[] reordering) {
 		throw new NotImplementedException();
 	}

 	@Override
 	public String toString() {
 		StringBuilder sb = new StringBuilder();
 		sb.append(super.toString());
 		sb.append(String.format("\n%15s ", "Data: "));
 		sb.append(_data);
 		sb.append(String.format("\n%15s", "Reference:"));
 		sb.append(Arrays.toString(_reference));
 		return sb.toString();
 	}
 }
	/*
	* 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.sysds.runtime.compress.colgroup;

	import java.io.DataInput;
	import java.io.DataOutput;
	import java.io.IOException;
	import java.util.Arrays;

	import org.apache.commons.lang.NotImplementedException;
	import org.apache.sysds.runtime.DMLRuntimeException;
	import org.apache.sysds.runtime.compress.colgroup.dictionary.ADictionary;
	import org.apache.sysds.runtime.compress.colgroup.dictionary.DictionaryFactory;
	import org.apache.sysds.runtime.compress.colgroup.dictionary.MatrixBlockDictionary;
	import org.apache.sysds.runtime.compress.colgroup.indexes.ColIndexFactory;
	import org.apache.sysds.runtime.compress.colgroup.indexes.IColIndex;
	import org.apache.sysds.runtime.compress.colgroup.mapping.AMapToData;
	import org.apache.sysds.runtime.compress.colgroup.mapping.MapToFactory;
	import org.apache.sysds.runtime.compress.colgroup.scheme.ICLAScheme;
	import org.apache.sysds.runtime.compress.cost.ComputationCostEstimator;
	import org.apache.sysds.runtime.compress.estim.CompressedSizeInfoColGroup;
	import org.apache.sysds.runtime.compress.estim.EstimationFactors;
	import org.apache.sysds.runtime.compress.estim.encoding.EncodingFactory;
	import org.apache.sysds.runtime.compress.estim.encoding.IEncode;
	import org.apache.sysds.runtime.functionobjects.Builtin;
	import org.apache.sysds.runtime.functionobjects.Divide;
	import org.apache.sysds.runtime.functionobjects.Minus;
	import org.apache.sysds.runtime.functionobjects.Multiply;
	import org.apache.sysds.runtime.functionobjects.Plus;
	import org.apache.sysds.runtime.instructions.cp.CM_COV_Object;
	import org.apache.sysds.runtime.matrix.data.MatrixBlock;
	import org.apache.sysds.runtime.matrix.operators.BinaryOperator;
	import org.apache.sysds.runtime.matrix.operators.CMOperator;
	import org.apache.sysds.runtime.matrix.operators.ScalarOperator;
	import org.apache.sysds.runtime.matrix.operators.UnaryOperator;

	/**
	* Class to encapsulate information about a column group that is encoded with dense dictionary encoding (DDC).
	*/
	public class ColGroupDDCFOR extends AMorphingMMColGroup implements IFrameOfReferenceGroup {
	private static final long serialVersionUID = -5769772089913918987L;

	/** Pointers to row indexes in the dictionary */
	protected final AMapToData _data;

	/** Reference values in this column group */
	protected final double[] _reference;

	private ColGroupDDCFOR(IColIndex colIndexes, ADictionary dict, double[] reference, AMapToData data,
	int[] cachedCounts) {
	super(colIndexes, dict, cachedCounts);
	_data = data;
	_reference = reference;
	}

	public static AColGroup create(IColIndex colIndexes, ADictionary dict, AMapToData data, int[] cachedCounts,
	double[] reference) {
	final boolean allZero = ColGroupUtils.allZero(reference);
	if(dict == null && allZero)
	return new ColGroupEmpty(colIndexes);
	else if(dict == null)
	return ColGroupConst.create(colIndexes, reference);
	else if(data.getUnique() == 1)
	return ColGroupConst.create(colIndexes,
	dict.binOpRight(new BinaryOperator(Plus.getPlusFnObject()), reference));
	else if(allZero)
	return ColGroupDDC.create(colIndexes, dict, data, cachedCounts);
	else
	return new ColGroupDDCFOR(colIndexes, dict, reference, data, cachedCounts);
	}

	public static AColGroup sparsifyFOR(ColGroupDDC g) {
	// It is assumed whoever call this does not use an empty Dictionary in g.
	final int nCol = g.getColIndices().size();
	final MatrixBlockDictionary mbd = g._dict.getMBDict(nCol);
	if(mbd != null) {

	final MatrixBlock mb = mbd.getMatrixBlock();

	final double[] ref = ColGroupUtils.extractMostCommonValueInColumns(mb);
	if(ref != null) {
	MatrixBlockDictionary mDict = mbd.binOpRight(new BinaryOperator(Minus.getMinusFnObject()), ref);
	return create(g.getColIndices(), mDict, g._data, g.getCachedCounts(), ref);
	}
	else
	return g;
	}
	else {
	throw new NotImplementedException("The dictionary was empty... highly unlikely");
	}
	}

	public CompressionType getCompType() {
	return CompressionType.DDCFOR;
	}

	@Override
	public double getIdx(int r, int colIdx) {
	return _dict.getValue(_data.getIndex(r), colIdx, _colIndexes.size()) + _reference[colIdx];
	}

	@Override
	protected void computeRowSums(double[] c, int rl, int ru, double[] preAgg) {
	for(int rix = rl; rix < ru; rix++)
	c[rix] += preAgg[_data.getIndex(rix)];
	}

	@Override
	protected void computeRowMxx(double[] c, Builtin builtin, int rl, int ru, double[] preAgg) {
	for(int i = rl; i < ru; i++)
	c[i] = builtin.execute(c[i], preAgg[_data.getIndex(i)]);
	}

	@Override
	public int[] getCounts(int[] counts) {
	return _data.getCounts(counts);
	}

	@Override
	public ColGroupType getColGroupType() {
	return ColGroupType.DDCFOR;
	}

	@Override
	public long estimateInMemorySize() {
	long size = super.estimateInMemorySize();
	size += _data.getInMemorySize();
	size += 8 * _colIndexes.size();
	return size;
	}

	@Override
	public AColGroup scalarOperation(ScalarOperator op) {
	final double[] newRef = new double[_reference.length];
	for(int i = 0; i < _reference.length; i++)
	newRef[i] = op.executeScalar(_reference[i]);
	if(op.fn instanceof Plus \|\| op.fn instanceof Minus)
	return create(_colIndexes, _dict, _data, getCachedCounts(), newRef);
	else if(op.fn instanceof Multiply \|\| op.fn instanceof Divide) {
	final ADictionary newDict = _dict.applyScalarOp(op);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}
	else {
	final ADictionary newDict = _dict.applyScalarOpWithReference(op, _reference, newRef);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}
	}

	@Override
	public AColGroup unaryOperation(UnaryOperator op) {
	final double[] newRef = ColGroupUtils.unaryOperator(op, _reference);
	final ADictionary newDict = _dict.applyUnaryOpWithReference(op, _reference, newRef);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}

	@Override
	public AColGroup binaryRowOpLeft(BinaryOperator op, double[] v, boolean isRowSafe) {
	final double[] newRef = new double[_reference.length];
	for(int i = 0; i < _reference.length; i++)
	newRef[i] = op.fn.execute(v[_colIndexes.get(i)], _reference[i]);

	if(op.fn instanceof Plus \|\| op.fn instanceof Minus) // only edit reference
	return create(_colIndexes, _dict, _data, getCachedCounts(), newRef);
	else if(op.fn instanceof Multiply \|\| op.fn instanceof Divide) {
	// possible to simply process on dict and keep reference
	final ADictionary newDict = _dict.binOpLeft(op, v, _colIndexes);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}
	else { // have to apply reference while processing
	final ADictionary newDict = _dict.binOpLeftWithReference(op, v, _colIndexes, _reference, newRef);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}
	}

	@Override
	public AColGroup binaryRowOpRight(BinaryOperator op, double[] v, boolean isRowSafe) {
	final double[] newRef = new double[_reference.length];
	for(int i = 0; i < _reference.length; i++)
	newRef[i] = op.fn.execute(_reference[i], v[_colIndexes.get(i)]);

	if(op.fn instanceof Plus \|\| op.fn instanceof Minus)// only edit reference
	return create(_colIndexes, _dict, _data, getCachedCounts(), newRef);
	else if(op.fn instanceof Multiply \|\| op.fn instanceof Divide) {
	// possible to simply process on dict and keep reference
	final ADictionary newDict = _dict.binOpRight(op, v, _colIndexes);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}
	else { // have to apply reference while processing
	final ADictionary newDict = _dict.binOpRightWithReference(op, v, _colIndexes, _reference, newRef);
	return create(_colIndexes, newDict, _data, getCachedCounts(), newRef);
	}
	}

	@Override
	public void write(DataOutput out) throws IOException {
	super.write(out);
	_data.write(out);
	for(double d : _reference)
	out.writeDouble(d);
	}

	public static ColGroupDDCFOR read(DataInput in) throws IOException {
	IColIndex cols = ColIndexFactory.read(in);
	ADictionary dict = DictionaryFactory.read(in);
	AMapToData data = MapToFactory.readIn(in);
	double[] ref = ColGroupIO.readDoubleArray(cols.size(), in);
	return new ColGroupDDCFOR(cols, dict, ref, data, null);
	}

	@Override
	public long getExactSizeOnDisk() {
	long ret = super.getExactSizeOnDisk();
	ret += _data.getExactSizeOnDisk();
	ret += 8 * _colIndexes.size(); // reference values.
	return ret;
	}

	@Override
	public double getCost(ComputationCostEstimator e, int nRows) {
	final int nVals = getNumValues();
	final int nCols = getNumCols();
	return e.getCost(nRows, nRows, nCols, nVals, _dict.getSparsity());
	}

	@Override
	public AColGroup replace(double pattern, double replace) {
	final ADictionary newDict = _dict.replaceWithReference(pattern, replace, _reference);
	boolean patternInReference = false;
	for(double d : _reference)
	if(pattern == d) {
	patternInReference = true;
	break;
	}
	if(patternInReference) {
	double[] nRef = new double[_reference.length];
	for(int i = 0; i < _reference.length; i++)
	if(pattern == _reference[i])
	nRef[i] = replace;
	else
	nRef[i] = _reference[i];

	return create(_colIndexes, newDict, _data, getCachedCounts(), nRef);
	}
	else
	return create(_colIndexes, newDict, _data, getCachedCounts(), _reference);

	}

	@Override
	protected double computeMxx(double c, Builtin builtin) {
	return _dict.aggregateWithReference(c, builtin, _reference, false);
	}

	@Override
	protected void computeColMxx(double[] c, Builtin builtin) {
	_dict.aggregateColsWithReference(c, builtin, _colIndexes, _reference, false);
	}

	@Override
	protected void computeSum(double[] c, int nRows) {
	// trick, use normal sum
	super.computeSum(c, nRows);
	// and add all sum of reference multiplied with nrows.
	final double refSum = ColGroupUtils.refSum(_reference);
	c[0] += refSum * nRows;
	}

	@Override
	public void computeColSums(double[] c, int nRows) {
	// trick, use normal sum
	super.computeColSums(c, nRows);
	// and add reference multiplied with number of rows.
	for(int i = 0; i < _colIndexes.size(); i++)
	c[_colIndexes.get(i)] += _reference[i] * nRows;
	}

	@Override
	protected void computeSumSq(double[] c, int nRows) {
	c[0] += _dict.sumSqWithReference(getCounts(), _reference);
	}

	@Override
	protected void computeColSumsSq(double[] c, int nRows) {
	_dict.colSumSqWithReference(c, getCounts(), _colIndexes, _reference);
	}

	@Override
	protected double[] preAggSumRows() {
	return _dict.sumAllRowsToDoubleWithReference(_reference);
	}

	@Override
	protected double[] preAggSumSqRows() {
	return _dict.sumAllRowsToDoubleSqWithReference(_reference);
	}

	@Override
	protected double[] preAggProductRows() {
	return _dict.productAllRowsToDoubleWithReference(_reference);
	}

	@Override
	protected double[] preAggBuiltinRows(Builtin builtin) {
	return _dict.aggregateRowsWithReference(builtin, _reference);
	}

	@Override
	protected void computeProduct(double[] c, int nRows) {
	_dict.productWithReference(c, getCounts(), _reference, 0);
	}

	@Override
	protected void computeRowProduct(double[] c, int rl, int ru, double[] preAgg) {
	for(int rix = rl; rix < ru; rix++)
	c[rix] *= preAgg[_data.getIndex(rix)];
	}

	@Override
	protected void computeColProduct(double[] c, int nRows) {
	_dict.colProductWithReference(c, getCounts(), _colIndexes, _reference);
	}

	@Override
	protected AColGroup sliceMultiColumns(int idStart, int idEnd, IColIndex outputCols) {
	ADictionary retDict = _dict.sliceOutColumnRange(idStart, idEnd, _colIndexes.size());
	final double[] newDef = new double[idEnd - idStart];
	for(int i = idStart, j = 0; i < idEnd; i++, j++)
	newDef[j] = _reference[i];
	return create(outputCols, retDict, _data, getCounts(), newDef);
	}

	@Override
	protected AColGroup sliceSingleColumn(int idx) {
	final IColIndex retIndexes = ColIndexFactory.create(1);
	if(_colIndexes.size() == 1) // early abort, only single column already.
	return create(retIndexes, _dict, _data, getCounts(), _reference);
	final double[] newDef = new double[] {_reference[idx]};
	final ADictionary retDict = _dict.sliceOutColumnRange(idx, idx + 1, _colIndexes.size());
	return create(retIndexes, retDict, _data, getCounts(), newDef);

	}

	@Override
	public boolean containsValue(double pattern) {

	if(Double.isNaN(pattern) \|\| Double.isInfinite(pattern))
	return ColGroupUtils.containsInfOrNan(pattern, _reference) \|\| _dict.containsValue(pattern);
	else
	return _dict.containsValueWithReference(pattern, _reference);
	}

	@Override
	public long getNumberNonZeros(int nRows) {
	// to be safe just assume the worst fully dense for DDCFOR
	return (long) _colIndexes.size() * nRows;
	}

	@Override
	public AColGroup extractCommon(double[] constV) {
	for(int i = 0; i < _colIndexes.size(); i++)
	constV[_colIndexes.get(i)] += _reference[i];
	return ColGroupDDC.create(_colIndexes, _dict, _data, getCounts());
	}

	@Override
	public AColGroup rexpandCols(int max, boolean ignore, boolean cast, int nRows) {
	final int def = (int) _reference[0];
	ADictionary d = _dict.rexpandColsWithReference(max, ignore, cast, def);

	if(d == null) {
	if(def <= 0 \|\| def > max)
	return ColGroupEmpty.create(max);
	else {
	double[] retDef = new double[max];
	retDef[((int) def) - 1] = 1;
	return ColGroupConst.create(retDef);
	}
	}
	else {
	IColIndex outCols = ColIndexFactory.create(max);
	if(def <= 0) {
	if(ignore)
	return ColGroupDDC.create(outCols, d, _data, getCachedCounts());
	else
	throw new DMLRuntimeException("Invalid content of zero in rexpand");
	}
	else if(def > max)
	return ColGroupDDC.create(outCols, d, _data, getCachedCounts());
	else {
	double[] retDef = new double[max];
	retDef[((int) def) - 1] = 1;
	return ColGroupDDCFOR.create(outCols, d, _data, getCachedCounts(), retDef);
	}
	}

	}

	@Override
	public CM_COV_Object centralMoment(CMOperator op, int nRows) {
	// should be guaranteed to be one column therefore only one reference value.
	CM_COV_Object ret = _dict.centralMomentWithReference(op.fn, getCounts(), _reference[0], nRows);
	return ret;
	}

	@Override
	public double[] getCommon() {
	return _reference;
	}

	@Override
	protected AColGroup allocateRightMultiplicationCommon(double[] common, IColIndex colIndexes, ADictionary preAgg) {
	return create(colIndexes, preAgg, _data, getCachedCounts(), common);
	}

	@Override
	public AColGroup sliceRows(int rl, int ru) {
	AMapToData sliceMap = _data.slice(rl, ru);
	return new ColGroupDDCFOR(_colIndexes, _dict, _reference, sliceMap, null);
	}

	@Override
	protected AColGroup copyAndSet(IColIndex colIndexes, ADictionary newDictionary) {
	return create(colIndexes, newDictionary, _data, getCachedCounts(), _reference);
	}

	@Override
	public AColGroup append(AColGroup g) {
	if(g instanceof ColGroupDDCFOR && g.getColIndices().equals(_colIndexes)) {
	ColGroupDDCFOR gDDC = (ColGroupDDCFOR) g;
	if(Arrays.equals(_reference, gDDC._reference) && gDDC._dict.equals(_dict)) {
	AMapToData nd = _data.append(gDDC._data);
	return create(_colIndexes, _dict, nd, null, _reference);
	}
	}
	return null;
	}

	@Override
	public AColGroup appendNInternal(AColGroup[] g) {
	return null;
	}

	@Override
	public ICLAScheme getCompressionScheme() {
	return null;
	}

	@Override
	public AColGroup recompress() {
	return this;
	}

	@Override
	public CompressedSizeInfoColGroup getCompressionInfo(int nRow) {
	IEncode enc = getEncoding();
	EstimationFactors ef = new EstimationFactors(getNumValues(), _data.size(), _data.size(), _dict.getSparsity());
	return new CompressedSizeInfoColGroup(_colIndexes, ef, estimateInMemorySize(), getCompType(), enc);
	}

	@Override
	public IEncode getEncoding() {
	return EncodingFactory.create(_data);
	}

	@Override
	public boolean sameIndexStructure(AColGroupCompressed that) {
	return that instanceof ColGroupDDCFOR && ((ColGroupDDCFOR) that)._data == _data;
	}

	@Override
	protected AColGroup fixColIndexes(IColIndex newColIndex, int[] reordering) {
	throw new NotImplementedException();
	}

	@Override
	public String toString() {
	StringBuilder sb = new StringBuilder();
	sb.append(super.toString());
	sb.append(String.format("\n%15s ", "Data: "));
	sb.append(_data);
	sb.append(String.format("\n%15s", "Reference:"));
	sb.append(Arrays.toString(_reference));
	return sb.toString();
	}
	}