content: /*
   * 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.cassandra.index.sai.disk.v1.vector;
  
  import org.jctools.maps.NonBlockingHashMapLong;
  
  public class ConcurrentVectorValues implements RamAwareVectorValues
  {
      private final int dimensions;
      private final NonBlockingHashMapLong<float[]> values = new NonBlockingHashMapLong<>();
  
      public ConcurrentVectorValues(int dimensions)
      {
          this.dimensions = dimensions;
      }
  
      @Override
      public int size()
      {
          return values.size();
      }
  
      @Override
      public int dimension()
      {
          return dimensions;
      }
  
      @Override
      public float[] vectorValue(int i)
      {
          return values.get(i);
      }
  
      /** return approximate bytes used by the new vector */
      public long add(int ordinal, float[] vector)
      {
          values.put(ordinal, vector);
          return RamEstimation.concurrentHashMapRamUsed(1) + oneVectorBytesUsed();
      }
  
      @Override
      public boolean isValueShared()
      {
          return false;
      }
  
      @Override
      public ConcurrentVectorValues copy()
      {
          // no actual copy required because we always return distinct float[] for distinct vector ordinals
          return this;
      }
  
      private long oneVectorBytesUsed()
      {
          return Integer.BYTES + Integer.BYTES + (long) dimension() * Float.BYTES;
      }
  }
  