/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.ignite.ml.math.impls.vector; import org.apache.ignite.ml.math.Matrix; import org.apache.ignite.ml.math.Vector; import org.apache.ignite.ml.math.impls.storage.vector.SparseLocalOffHeapVectorStorage; /** * Implementation for {@link Vector} assuming sparse logic and local offheap JVM storage. * It is suitable for data sets where local, non-distributed execution is satisfactory and on-heap JVM storage * is not enough to keep the entire data set. * <p>See also: <a href="https://en.wikipedia.org/wiki/Sparse_array">Wikipedia article</a>.</p> */ public class SparseLocalOffHeapVector extends AbstractVector { /** * @param crd Vector cardinality. */ public SparseLocalOffHeapVector(int crd) { setStorage(new SparseLocalOffHeapVectorStorage(crd)); } /** {@inheritDoc} */ @Override public Vector like(int crd) { return new SparseLocalOffHeapVector(crd); } /** {@inheritDoc} */ @Override public Matrix likeMatrix(int rows, int cols) { return null; } }