Examples with IntDoubleSortedVectorStorage com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage used on opensource projects

Example 11 with IntDoubleSortedVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage in project angel by Tencent.

the class MixedBinaryOutNonZAExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntFloatVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        float[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntDoubleVector part : parts) {
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[k];
            double[] newValues = resPart.getValues();
            if (part.isDense()) {
                double[] partValue = part.getStorage().getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i + base;
                    newValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                    for (int i = 0; i < part.getDim(); i++) {
                        resPart.set(i, op.apply(0, v2Values[i + base]));
                    }
                    ObjectIterator<Int2DoubleMap.Entry> iter = part.getStorage().entryIterator();
                    while (iter.hasNext()) {
                        Int2DoubleMap.Entry entry = iter.next();
                        int idx = entry.getIntKey();
                        resPart.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx + base]));
                    }
                } else {
                    for (int i = 0; i < newValues.length; i++) {
                        if (part.getStorage().hasKey(i)) {
                            resPart.set(i, op.apply(part.get(i), v2Values[i + base]));
                        } else {
                            resPart.set(i, op.apply(0, v2Values[i + base]));
                        }
                    }
                }
            } else {
                // sorted
                if (op.isKeepStorage()) {
                    int dim = part.getDim();
                    int[] resIndices = resPart.getIndices();
                    double[] resValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int i = 0; i < dim; i++) {
                        resIndices[i] = i;
                        resValues[i] = op.apply(0, v2Values[i + base]);
                    }
                    int size = part.size();
                    for (int i = 0; i < size; i++) {
                        int idx = partIndices[i];
                        resValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                    }
                } else {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            newValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            newValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < newValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                newValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                newValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                }
            }
            base += part.getDim();
            k++;
        }
    } else {
        if (v2.isSparse()) {
            if (!op.isKeepStorage()) {
                for (int i = 0; i < parts.length; i++) {
                    if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                        resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                    }
                }
            }
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2FloatMap.Entry entry = iter.next();
                int gidx = entry.getIntKey();
                int pidx = (int) (gidx / subDim);
                int subidx = gidx % subDim;
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getFloatValue()));
            }
        } else {
            // sorted
            if (!op.isKeepStorage()) {
                for (int i = 0; i < parts.length; i++) {
                    if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                        resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                    }
                }
            }
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                int gidx = v2Indices[i];
                int pidx = (int) (gidx / subDim);
                int subidx = gidx % subDim;
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
            }
        }
    }
    IntDoubleVector[] res = new IntDoubleVector[parts.length];
    int i = 0;
    for (IntDoubleVector part : parts) {
        res[i] = new IntDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntDoubleVectorStorage) resParts[i]);
        i++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 12 with IntDoubleSortedVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntLongVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        long[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntDoubleVector part : parts) {
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[k];
            if (part.isDense()) {
                double[] partValue = part.getStorage().getValues();
                double[] resPartValues = resPart.getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i + base;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                double[] resPartValues = resPart.getValues();
                if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                    for (int i = 0; i < part.getDim(); i++) {
                        resPart.set(i, op.apply(0, v2Values[i + base]));
                    }
                    ObjectIterator<Int2DoubleMap.Entry> iter = part.getStorage().entryIterator();
                    while (iter.hasNext()) {
                        Int2DoubleMap.Entry entry = iter.next();
                        int idx = entry.getIntKey();
                        resPart.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx + base]));
                    }
                } else {
                    for (int i = 0; i < resPartValues.length; i++) {
                        if (part.getStorage().hasKey(i)) {
                            resPart.set(i, op.apply(part.get(i), v2Values[i + base]));
                        } else {
                            resPart.set(i, op.apply(0, v2Values[i + base]));
                        }
                    }
                }
            } else {
                // sorted
                int[] resPartIndices = resPart.getIndices();
                double[] resPartValues = resPart.getValues();
                if (op.isKeepStorage()) {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            resPartIndices[i] = i;
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                } else {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                }
            }
            base += part.getDim();
            k++;
        }
    } else {
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                    resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        for (int i = 0; i < v1.getDim(); i++) {
            int pidx = (int) (i / subDim);
            int subidx = i % subDim;
            if (v2.getStorage().hasKey(i)) {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
            } else {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
            }
        }
    }
    IntDoubleVector[] res = new IntDoubleVector[parts.length];
    int i = 0;
    for (IntDoubleVector part : parts) {
        res[i] = new IntDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 13 with IntDoubleSortedVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntDummyVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (!op.isKeepStorage()) {
        for (int i = 0; i < parts.length; i++) {
            if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        int subidx = i % subDim;
        ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
    }
    IntDoubleVector[] res = new IntDoubleVector[parts.length];
    int i = 0;
    for (IntDoubleVector part : parts) {
        res[i] = new IntDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 14 with IntDoubleSortedVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage in project angel by Tencent.

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(IntDoubleVector v1, IntFloatVector v2, Binary op) {
    IntDoubleVectorStorage newStorage = (IntDoubleVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isDense() && v2.isDense()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        float[] v2Values = v2.getStorage().getValues();
        for (int idx = 0; idx < resValues.length; idx++) {
            resValues[idx] = op.apply(v1Values[idx], v2Values[idx]);
        }
    } else if (v1.isDense() && v2.isSparse()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2FloatMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            resValues[idx] = op.apply(v1Values[idx], entry.getFloatValue());
        }
    } else if (v1.isDense() && v2.isSorted()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        int[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        int size = v2.size();
        for (int i = 0; i < size; i++) {
            int idx = v2Indices[i];
            resValues[idx] = op.apply(v1Values[idx], v2Values[i]);
        }
    } else if (v1.isSparse() && v2.isDense()) {
        if (op.isKeepStorage()) {
            int dim = v1.getDim();
            float[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < dim; i++) {
                    newStorage.set(i, op.apply(0, v2Values[i]));
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx]));
                }
            } else {
                for (int i = 0; i < dim; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        newStorage.set(i, op.apply(v1.get(i), v2Values[i]));
                    } else {
                        newStorage.set(i, op.apply(0, v2Values[i]));
                    }
                }
            }
        } else {
            double[] resValues = newStorage.getValues();
            float[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
                }
            } else {
                for (int i = 0; i < resValues.length; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
        }
    } else if (v1.isSorted() && v2.isDense()) {
        if (op.isKeepStorage()) {
            int dim = v1.getDim();
            int[] resIndices = newStorage.getIndices();
            double[] resValues = newStorage.getValues();
            float[] v2Values = v2.getStorage().getValues();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            for (int i = 0; i < dim; i++) {
                resIndices[i] = i;
                resValues[i] = op.apply(0, v2Values[i]);
            }
            int size = v1.size();
            for (int i = 0; i < size; i++) {
                int idx = v1Indices[i];
                resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
            }
        } else {
            double[] resValues = newStorage.getValues();
            float[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
                }
            } else {
                IntDoubleVectorStorage v1Storage = v1.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v1Storage.hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
        }
    } else if (v1.isSparse() && v2.isSparse()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2FloatMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss dense storage is more efficient
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            ObjectIterator<Int2FloatMap.Entry> iter2 = v2.getStorage().entryIterator();
            while (iter2.hasNext()) {
                Int2FloatMap.Entry entry = iter2.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                // no rehashor one onle rehash is required, nothing to optimization
                ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
                }
            } else {
                // multi-rehash
                ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2DoubleMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                ObjectIterator<Int2FloatMap.Entry> iter2 = v2.getStorage().entryIterator();
                while (iter2.hasNext()) {
                    Int2FloatMap.Entry entry = iter2.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
                }
            }
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2.size(); i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            int size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                int[] v2Indices = v2.getStorage().getIndices();
                float[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < v2.size(); i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            } else {
                ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2DoubleMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                int[] v2Indices = v2.getStorage().getIndices();
                float[] v2Values = v2.getStorage().getValues();
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                int[] v1Indices = v1.getStorage().getIndices();
                int[] idxiter = v2.getStorage().indexIterator().toIntArray();
                int[] indices = new int[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                IntAVLTreeSet avl = new IntAVLTreeSet(indices);
                IntBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    int idx = iter.nextInt();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getFloatValue()));
                }
            }
        } else {
            if (op.isKeepStorage()) {
                int[] v1Indices = v1.getStorage().getIndices();
                int[] idxiter = v2.getStorage().indexIterator().toIntArray();
                int[] indices = new int[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                IntAVLTreeSet avl = new IntAVLTreeSet(indices);
                IntBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    int idx = iter.nextInt();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getFloatValue()));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        int v1Pointor = 0;
        int v2Pointor = 0;
        int size1 = v1.size();
        int size2 = v2.size();
        int[] v1Indices = v1.getStorage().getIndices();
        double[] v1Values = v1.getStorage().getValues();
        int[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        if ((size1 + size2) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                // sorted
                int[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int global = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        global++;
                        v1Pointor++;
                        v2Pointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = v1Values[v1Pointor];
                        global++;
                        v1Pointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[global] = v2Indices[v2Pointor];
                        resValues[global] = op.apply(0, v2Values[v2Pointor]);
                        global++;
                        v2Pointor++;
                    }
                }
            } else {
                // dense
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        } else {
            if (op.isKeepStorage()) {
                int[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int globalPointor = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[globalPointor] = v1Indices[v1Pointor];
                        resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        v1Pointor++;
                        v2Pointor++;
                        globalPointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[globalPointor] = v1Indices[v1Pointor];
                        resValues[globalPointor] = v1Values[v1Pointor];
                        v1Pointor++;
                        globalPointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[globalPointor] = v2Indices[v2Pointor];
                        resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                        v2Pointor++;
                        globalPointor++;
                    }
                }
            } else {
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}

Example 15 with IntDoubleSortedVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage in project angel by Tencent.

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(IntDoubleVector v1, IntLongVector v2, Binary op) {
    IntDoubleVectorStorage newStorage = (IntDoubleVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isDense() && v2.isDense()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        long[] v2Values = v2.getStorage().getValues();
        for (int idx = 0; idx < resValues.length; idx++) {
            resValues[idx] = op.apply(v1Values[idx], v2Values[idx]);
        }
    } else if (v1.isDense() && v2.isSparse()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2LongMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            resValues[idx] = op.apply(v1Values[idx], entry.getLongValue());
        }
    } else if (v1.isDense() && v2.isSorted()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        int[] v2Indices = v2.getStorage().getIndices();
        long[] v2Values = v2.getStorage().getValues();
        int size = v2.size();
        for (int i = 0; i < size; i++) {
            int idx = v2Indices[i];
            resValues[idx] = op.apply(v1Values[idx], v2Values[i]);
        }
    } else if (v1.isSparse() && v2.isDense()) {
        if (op.isKeepStorage()) {
            int dim = v1.getDim();
            long[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < dim; i++) {
                    newStorage.set(i, op.apply(0, v2Values[i]));
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx]));
                }
            } else {
                for (int i = 0; i < dim; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        newStorage.set(i, op.apply(v1.get(i), v2Values[i]));
                    } else {
                        newStorage.set(i, op.apply(0, v2Values[i]));
                    }
                }
            }
        } else {
            double[] resValues = newStorage.getValues();
            long[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
                }
            } else {
                for (int i = 0; i < resValues.length; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
        }
    } else if (v1.isSorted() && v2.isDense()) {
        if (op.isKeepStorage()) {
            int dim = v1.getDim();
            int[] resIndices = newStorage.getIndices();
            double[] resValues = newStorage.getValues();
            long[] v2Values = v2.getStorage().getValues();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            for (int i = 0; i < dim; i++) {
                resIndices[i] = i;
                resValues[i] = op.apply(0, v2Values[i]);
            }
            int size = v1.size();
            for (int i = 0; i < size; i++) {
                int idx = v1Indices[i];
                resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
            }
        } else {
            double[] resValues = newStorage.getValues();
            long[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
                }
            } else {
                IntDoubleVectorStorage v1Storage = v1.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v1Storage.hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
        }
    } else if (v1.isSparse() && v2.isSparse()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss dense storage is more efficient
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            ObjectIterator<Int2LongMap.Entry> iter2 = v2.getStorage().entryIterator();
            while (iter2.hasNext()) {
                Int2LongMap.Entry entry = iter2.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                // no rehashor one onle rehash is required, nothing to optimization
                ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
                }
            } else {
                // multi-rehash
                ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2DoubleMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                ObjectIterator<Int2LongMap.Entry> iter2 = v2.getStorage().entryIterator();
                while (iter2.hasNext()) {
                    Int2LongMap.Entry entry = iter2.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
                }
            }
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            int[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2.size(); i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            int[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            int size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                int[] v2Indices = v2.getStorage().getIndices();
                long[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < v2.size(); i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            } else {
                ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2DoubleMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                int[] v2Indices = v2.getStorage().getIndices();
                long[] v2Values = v2.getStorage().getValues();
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                int[] v1Indices = v1.getStorage().getIndices();
                int[] idxiter = v2.getStorage().indexIterator().toIntArray();
                int[] indices = new int[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                IntAVLTreeSet avl = new IntAVLTreeSet(indices);
                IntBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    int idx = iter.nextInt();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getLongValue()));
                }
            }
        } else {
            if (op.isKeepStorage()) {
                int[] v1Indices = v1.getStorage().getIndices();
                int[] idxiter = v2.getStorage().indexIterator().toIntArray();
                int[] indices = new int[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                IntAVLTreeSet avl = new IntAVLTreeSet(indices);
                IntBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    int idx = iter.nextInt();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getLongValue()));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        int v1Pointor = 0;
        int v2Pointor = 0;
        int size1 = v1.size();
        int size2 = v2.size();
        int[] v1Indices = v1.getStorage().getIndices();
        double[] v1Values = v1.getStorage().getValues();
        int[] v2Indices = v2.getStorage().getIndices();
        long[] v2Values = v2.getStorage().getValues();
        if ((size1 + size2) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                // sorted
                int[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int global = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        global++;
                        v1Pointor++;
                        v2Pointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = v1Values[v1Pointor];
                        global++;
                        v1Pointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[global] = v2Indices[v2Pointor];
                        resValues[global] = op.apply(0, v2Values[v2Pointor]);
                        global++;
                        v2Pointor++;
                    }
                }
            } else {
                // dense
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        } else {
            if (op.isKeepStorage()) {
                int[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int globalPointor = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[globalPointor] = v1Indices[v1Pointor];
                        resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        v1Pointor++;
                        v2Pointor++;
                        globalPointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[globalPointor] = v1Indices[v1Pointor];
                        resValues[globalPointor] = v1Values[v1Pointor];
                        v1Pointor++;
                        globalPointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[globalPointor] = v2Indices[v2Pointor];
                        resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                        v2Pointor++;
                        globalPointor++;
                    }
                }
            } else {
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}