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   * 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.db.guardrails;
  
  import java.nio.ByteBuffer;
  import java.util.List;
  
  import com.google.common.primitives.Floats;
  import org.junit.Test;
  
  import org.apache.cassandra.config.DataStorageSpec;
  import org.apache.cassandra.db.marshal.FloatType;
  import org.apache.cassandra.db.marshal.VectorType;
  import org.apache.cassandra.transport.messages.ResultMessage;
  
  import static org.apache.cassandra.config.DataStorageSpec.DataStorageUnit.BYTES;
  import static org.junit.Assert.assertEquals;
  
  /**
   * Tests the guardrails around the size of SAI vector terms
   *
   * @see Guardrails#saiVectorTermSize
   */
  public class GuardrailSaiVectorTermSizeTest extends ValueThresholdTester
  {
      private static final int WARN_THRESHOLD = 1024; // bytes
      private static final int FAIL_THRESHOLD = WARN_THRESHOLD * 4; // bytes
  
      public GuardrailSaiVectorTermSizeTest()
      {
          super(WARN_THRESHOLD + "B",
                FAIL_THRESHOLD + "B",
                Guardrails.saiVectorTermSize,
                Guardrails::setSaiVectorTermSizeThreshold,
                Guardrails::getSaiVectorTermSizeWarnThreshold,
                Guardrails::getSaiVectorTermSizeFailThreshold,
                bytes -> new DataStorageSpec.LongBytesBound(bytes, BYTES).toString(),
                size -> new DataStorageSpec.LongBytesBound(size).toBytes());
      }
  
      @Override
      protected int warnThreshold()
      {
          return WARN_THRESHOLD;
      }
  
      @Override
      protected int failThreshold()
      {
          return FAIL_THRESHOLD;
      }
  
      @Test
      public void testWarn() throws Throwable
      {
          int warnDimensions = warnThreshold() / 4; // 4 bytes per dimension
          List<Float> warnVector = Floats.asList(new float[warnDimensions + 1]);
  
          createTable(KEYSPACE, "CREATE TABLE %s (k int PRIMARY KEY, v vector<float, " + warnVector.size() + ">)");
          createIndex("CREATE INDEX ON %s(v) USING 'sai' WITH OPTIONS = {'similarity_function' : 'euclidean'}");
  
          VectorType<Float> vectorType = VectorType.getInstance(FloatType.instance, warnDimensions + 1);
          assertWarns(() -> execute("INSERT INTO %s (k, v) VALUES (0, ?)", vectorType.decompose(warnVector)),
                      "Value of column 'v' has size");
      }
  
      @Test
      public void testFail() throws Throwable
      {
          int failDimensions = failThreshold() / 4; // 4 bytes per dimension
          List<Float> failVector = Floats.asList(new float[failDimensions + 1]);
  
          createTable(KEYSPACE, "CREATE TABLE %s (k int PRIMARY KEY, v vector<float, " + failVector.size() + ">)");
          createIndex("CREATE INDEX ON %s(v) USING 'sai' WITH OPTIONS = {'similarity_function' : 'euclidean'}");
  
          VectorType<Float> vectorType = VectorType.getInstance(FloatType.instance, failDimensions + 1);
          assertFails(() -> execute("INSERT INTO %s (k, v) VALUES (0, ?)", vectorType.decompose(failVector)),
                      "Value of column 'v' has size");
      }
  
      @Test
      public void testWarningVectorOnBuild()
      {
          int warnDimensions = warnThreshold() / 4; // 4 bytes per dimension
          List<Float> largeVector = Floats.asList(new float[warnDimensions + 1]);
  
          createTable(KEYSPACE, "CREATE TABLE %s (k int PRIMARY KEY, v vector<float, " + largeVector.size() + ">)");
  
          VectorType<Float> vectorType = VectorType.getInstance(FloatType.instance, warnDimensions + 1);
          ByteBuffer vectorBytes = vectorType.decompose(largeVector);
          execute("INSERT INTO %s (k, v) VALUES (0, ?)", vectorBytes);
  
          createIndex("CREATE INDEX ON %s(v) USING 'sai' WITH OPTIONS = {'similarity_function' : 'euclidean'}");
  
          // verify that the large vector is written on initial index build
          assertEquals(((ResultMessage.Rows) execute("SELECT * FROM %s ORDER BY v ANN OF ? LIMIT 10", vectorBytes)).result.size(), 1);
      }
  
      @Test
      public void testFailingVectorOnBuild()
      {
          int failDimensions = failThreshold() / 4; // 4 bytes per dimension
          List<Float> oversizedVector = Floats.asList(new float[failDimensions + 1]);
  
          createTable(KEYSPACE, "CREATE TABLE %s (k int PRIMARY KEY, v vector<float, " + oversizedVector.size() + ">)");
  
          VectorType<Float> vectorType = VectorType.getInstance(FloatType.instance, failDimensions + 1);
          ByteBuffer vectorBytes = vectorType.decompose(oversizedVector);
          execute("INSERT INTO %s (k, v) VALUES (0, ?)", vectorBytes);
          
          createIndex("CREATE INDEX ON %s(v) USING 'sai' WITH OPTIONS = {'similarity_function' : 'euclidean'}");
  
          // verify that the oversized vector isn't written on initial index build
          assertEquals(((ResultMessage.Rows) execute("SELECT k, v FROM %s")).result.size(), 1);
          assertEquals(((ResultMessage.Rows) execute("SELECT * FROM %s ORDER BY v ANN OF ? LIMIT 10", vectorBytes)).result.size(), 0);
      }
  }
  