/**
 * 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.apex.benchmark;

import org.apache.hadoop.conf.Configuration;

import com.datatorrent.api.Context.PortContext;
import com.datatorrent.api.DAG;
import com.datatorrent.api.DAG.Locality;
import com.datatorrent.api.StreamingApplication;
import com.datatorrent.api.annotation.ApplicationAnnotation;

/**
 * Performance Demo Application:
 * <p>
 * This demo demonstrates the performance of Datatorrent platform.
 * Performance is measured by the number of events processed per second and latency.
 * Performance varies depending on container memory, CPU and network I/O.
 * The demo can be used to check how the performance varies with stream locality.
 *
 * Stream locality decides how the operators are deployed:
 * ThreadLocal - the operators are deployed within the same thread.
 * ContainerLocal -the operators are deployed as separate threads within the process.
 * NodeLocal- the operators are deployed as separate processes on a machine.
 * RackLocal - the operators are deployed on different nodes of the same rack.
 * NoLocality - lets the engine decide how to best deploy the operator.
 *
 * Note:  NodeLocal and RackLocal are preferences that can be specified to Hadoop ResourceManager.
 * It is not guaranteed that the operators will be deployed as requested.
 * ResourceManager makes the call depending on resource availability.
 *
 * Refer to demos/docs/PerformanceDemo.md for more details.
 *
 * </p>
 *
 * @since 0.9.0
 */

@ApplicationAnnotation(name = "PerformanceBenchmarkingApp")
public abstract class Benchmark
{
  abstract static class AbstractApplication implements StreamingApplication
  {
    public static final int QUEUE_CAPACITY = 32 * 1024;

    @Override
    public void populateDAG(DAG dag, Configuration conf)
    {
      RandomWordInputModule wordGenerator = dag.addOperator("wordGenerator", RandomWordInputModule.class);
      dag.getMeta(wordGenerator).getMeta(wordGenerator.output).getAttributes()
          .put(PortContext.QUEUE_CAPACITY, QUEUE_CAPACITY);

      WordCountOperator<byte[]> counter = dag.addOperator("counter", new WordCountOperator<byte[]>());
      dag.getMeta(counter).getMeta(counter.input).getAttributes().put(PortContext.QUEUE_CAPACITY, QUEUE_CAPACITY);

      dag.addStream("Generator2Counter", wordGenerator.output, counter.input).setLocality(getLocality());
    }

    public abstract Locality getLocality();
  }

  /**
   * Let the engine decide how to best place the 2 operators.
   */
  @ApplicationAnnotation(name = "PerformanceBenchmarkNoLocality")
  public static class NoLocality extends AbstractApplication
  {
    @Override
    public Locality getLocality()
    {
      return null;
    }

  }

  /**
   * Place the 2 operators so that they are in the same Rack.
   * The operators are requested to be deployed on different machines.
   */
  @ApplicationAnnotation(name = "PerformanceBenchmarkRackLocal")
  public static class RackLocal extends AbstractApplication
  {
    @Override
    public Locality getLocality()
    {
      return Locality.RACK_LOCAL;
    }

  }

  /**
   * Place the 2 operators so that they are in the same node.
   * The operators are requested to be deployed as different processes within the same machine.
   */
  @ApplicationAnnotation(name = "PerformanceBenchmarkNodeLocal")
  public static class NodeLocal extends AbstractApplication
  {
    @Override
    public Locality getLocality()
    {
      return Locality.NODE_LOCAL;
    }

  }

  /**
   * Place the 2 operators so that they are in the same container.
   * The operators are deployed as different threads in the same process.
   */
  @ApplicationAnnotation(name = "PerformanceBenchmarkContainerLocal")
  public static class ContainerLocal extends AbstractApplication
  {
    @Override
    public Locality getLocality()
    {
      return Locality.CONTAINER_LOCAL;
    }

  }

  /**
   * Place the 2 operators so that they are in the same thread.
   */
  @ApplicationAnnotation(name = "PerformanceBenchmarkThreadLocal")
  public static class ThreadLocal extends AbstractApplication
  {
    @Override
    public Locality getLocality()
    {
      return Locality.THREAD_LOCAL;
    }

  }

}