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

Example 16 with LongLongVectorStorage

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

the class MixedBinaryOutZAExecutor method apply.

private static Vector apply(CompLongLongVector v1, LongIntVector v2, Binary op) {
    LongLongVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        ObjectIterator<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Long2IntMap.Entry entry = iter.next();
                long idx = entry.getLongKey();
                int pidx = (int) (idx / subDim);
                long subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getIntValue()));
                }
            }
        } else {
            long base = 0;
            for (int i = 0; i < parts.length; i++) {
                LongLongVector part = parts[i];
                LongLongVectorStorage resPart = (LongLongVectorStorage) resParts[i];
                if (part.isDense()) {
                    long[] partValues = part.getStorage().getValues();
                    long[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Long2LongMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Long2LongMap.Entry entry = piter.next();
                        long idx = entry.getLongKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getLongValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        long[] partIndices = part.getStorage().getIndices();
                        long[] partValues = part.getStorage().getValues();
                        long[] resPartIndices = resPart.getIndices();
                        long[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        long[] partIndices = part.getStorage().getIndices();
                        long[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    } else {
        // sorted
        if (v1.size() > v2.size()) {
            long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            long[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                long idx = v2Indices[i];
                int pidx = (int) (idx / subDim);
                long subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
                }
            }
        } else {
            long base = 0;
            for (int i = 0; i < parts.length; i++) {
                LongLongVector part = parts[i];
                LongLongVectorStorage resPart = (LongLongVectorStorage) resParts[i];
                if (part.isDense()) {
                    long[] partValues = part.getStorage().getValues();
                    long[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Long2LongMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Long2LongMap.Entry entry = piter.next();
                        long idx = entry.getLongKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getLongValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        long[] partIndices = part.getStorage().getIndices();
                        long[] partValues = part.getStorage().getValues();
                        long[] resPartIndices = resPart.getIndices();
                        long[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        long[] partIndices = part.getStorage().getIndices();
                        long[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    }
    LongLongVector[] res = new LongLongVector[parts.length];
    int i = 0;
    for (LongLongVector part : parts) {
        res[i] = new LongLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongLongVectorStorage) resParts[i]);
        i++;
    }
    return new CompLongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 17 with LongLongVectorStorage

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

the class MixedBinaryOutNonZAExecutor method apply.

private static Vector apply(CompLongLongVector v1, LongIntVector v2, Binary op) {
    LongLongVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof LongLongSortedVectorStorage) {
                    resParts[i] = new LongLongSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        ObjectIterator<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Long2IntMap.Entry entry = iter.next();
            long gidx = entry.getLongKey();
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getIntValue()));
        }
    } else {
        // sorted
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof LongLongSortedVectorStorage) {
                    resParts[i] = new LongLongSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        long[] v2Indices = v2.getStorage().getIndices();
        int[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            long gidx = v2Indices[i];
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
        }
    }
    LongLongVector[] res = new LongLongVector[parts.length];
    int i = 0;
    for (LongLongVector part : parts) {
        res[i] = new LongLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongLongVectorStorage) resParts[i]);
        i++;
    }
    return new CompLongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 18 with LongLongVectorStorage

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongLongVector v1, LongLongVector v2, Binary op) {
    LongLongVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongLongVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, 0));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongLongVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, 0));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = new LongLongSparseVectorStorage(v1.getDim());
            LongLongVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, 0));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            long[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            long[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                if (size1 != v1.getDim() && size2 != v2.getDim()) {
                    for (int i = 0; i < v1.getDim(); i++) {
                        resValues[i] = 0 / 0;
                    }
                }
            }
            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] = op.apply(v2Values[v2Pointor], 0);
                    v1Pointor++;
                    globalPointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resIndices[globalPointor] = v2Indices[v2Pointor];
                    resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                    globalPointor++;
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}

Example 19 with LongLongVectorStorage

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongFloatVector v1, LongLongVector v2, Binary op) {
    LongFloatVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongFloatVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0f, 0));
                }
            }
            res = new LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongFloatVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0f, 0));
                }
            }
            res = new LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongFloatVectorStorage newStorage = new LongFloatSparseVectorStorage(v1.getDim());
            LongFloatVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0f, 0));
                }
            }
            res = new LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongFloatVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            float[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            float[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Float.NaN;
                }
            }
            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] = op.apply(v2Values[v2Pointor], 0);
                    v1Pointor++;
                    globalPointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resIndices[globalPointor] = v2Indices[v2Pointor];
                    resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                    globalPointor++;
                }
            }
            res = new LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}

Example 20 with LongLongVectorStorage

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

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(LongLongVector v1, LongIntVector v2, Binary op) {
    LongLongVectorStorage newStorage = (LongLongVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isSparse() && v2.isSparse()) {
        long v1Size = v1.size();
        long 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<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Long2IntMap.Entry entry = iter.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getIntValue()));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss dense storage is more efficient
            ObjectIterator<Long2LongMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Long2LongMap.Entry entry = iter1.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, entry.getLongValue());
            }
            ObjectIterator<Long2IntMap.Entry> iter2 = v2.getStorage().entryIterator();
            while (iter2.hasNext()) {
                Long2IntMap.Entry entry = iter2.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getIntValue()));
            }
        } 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<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Long2IntMap.Entry entry = iter.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getIntValue()));
                }
            } else {
                // multi-rehash
                ObjectIterator<Long2LongMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Long2LongMap.Entry entry = iter1.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, entry.getLongValue());
                }
                ObjectIterator<Long2IntMap.Entry> iter2 = v2.getStorage().entryIterator();
                while (iter2.hasNext()) {
                    Long2IntMap.Entry entry = iter2.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getIntValue()));
                }
            }
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        long v1Size = v1.size();
        long 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
            long[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2.size(); i++) {
                long idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            ObjectIterator<Long2LongMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Long2LongMap.Entry entry = iter1.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, entry.getLongValue());
            }
            long[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            long size = v2.size();
            for (int i = 0; i < size; i++) {
                long 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) {
                long[] v2Indices = v2.getStorage().getIndices();
                int[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < v2.size(); i++) {
                    long idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            } else {
                ObjectIterator<Long2LongMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Long2LongMap.Entry entry = iter1.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, entry.getLongValue());
                }
                long[] v2Indices = v2.getStorage().getIndices();
                int[] v2Values = v2.getStorage().getValues();
                long size = v2.size();
                for (int i = 0; i < size; i++) {
                    long idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        long v1Size = v1.size();
        long v2Size = v2.size();
        if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                long[] v1Indices = v1.getStorage().getIndices();
                long[] idxiter = v2.getStorage().indexIterator().toLongArray();
                long[] indices = new long[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                LongAVLTreeSet avl = new LongAVLTreeSet(indices);
                LongBidirectionalIterator iter = avl.iterator();
                long[] values = new long[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    long idx = iter.nextLong();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new LongLongSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                long[] v1Indices = v1.getStorage().getIndices();
                long[] v1Values = v1.getStorage().getValues();
                long size = v1.size();
                for (int i = 0; i < size; i++) {
                    long idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Long2IntMap.Entry entry = iter.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getIntValue()));
                }
            }
        } else {
            if (op.isKeepStorage()) {
                long[] v1Indices = v1.getStorage().getIndices();
                long[] idxiter = v2.getStorage().indexIterator().toLongArray();
                long[] indices = new long[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                LongAVLTreeSet avl = new LongAVLTreeSet(indices);
                LongBidirectionalIterator iter = avl.iterator();
                long[] values = new long[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    long idx = iter.nextLong();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new LongLongSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                long[] v1Indices = v1.getStorage().getIndices();
                long[] v1Values = v1.getStorage().getValues();
                long size = v1.size();
                for (int i = 0; i < size; i++) {
                    long idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Long2IntMap.Entry entry = iter.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getIntValue()));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        int v1Pointor = 0;
        int v2Pointor = 0;
        long size1 = v1.size();
        long size2 = v2.size();
        long[] v1Indices = v1.getStorage().getIndices();
        long[] v1Values = v1.getStorage().getValues();
        long[] v2Indices = v2.getStorage().getIndices();
        int[] v2Values = v2.getStorage().getValues();
        if ((size1 + size2) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                // sorted
                long[] resIndices = newStorage.getIndices();
                long[] 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()) {
                long[] resIndices = newStorage.getIndices();
                long[] 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 LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}