/*
 * 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.beam.runners.flink.translation.functions;

import static org.apache.flink.util.Preconditions.checkArgument;

import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import org.apache.beam.runners.core.DoFnRunner;
import org.apache.beam.runners.core.DoFnRunners;
import org.apache.beam.runners.core.InMemoryStateInternals;
import org.apache.beam.runners.core.InMemoryTimerInternals;
import org.apache.beam.runners.core.StateInternals;
import org.apache.beam.runners.core.StateNamespace;
import org.apache.beam.runners.core.StateNamespaces;
import org.apache.beam.runners.core.TimerInternals;
import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
import org.apache.beam.runners.flink.FlinkPipelineOptions;
import org.apache.beam.runners.flink.metrics.DoFnRunnerWithMetricsUpdate;
import org.apache.beam.runners.flink.metrics.FlinkMetricContainer;
import org.apache.beam.runners.flink.translation.utils.FlinkClassloading;
import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.io.FileSystems;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.DoFnSchemaInformation;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.transforms.reflect.DoFnInvoker;
import org.apache.beam.sdk.transforms.reflect.DoFnInvokers;
import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.KV;
import org.apache.beam.sdk.values.PCollectionView;
import org.apache.beam.sdk.values.TupleTag;
import org.apache.beam.sdk.values.WindowingStrategy;
import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Lists;
import org.apache.flink.api.common.functions.RichGroupReduceFunction;
import org.apache.flink.api.common.functions.RuntimeContext;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.util.Collector;
import org.joda.time.Instant;

/** A {@link RichGroupReduceFunction} for stateful {@link ParDo} in Flink Batch Runner. */
public class FlinkStatefulDoFnFunction<K, V, OutputT>
    extends RichGroupReduceFunction<WindowedValue<KV<K, V>>, WindowedValue<OutputT>> {

  private final DoFn<KV<K, V>, OutputT> dofn;
  private String stepName;
  private final WindowingStrategy<?, ?> windowingStrategy;
  private final Map<PCollectionView<?>, WindowingStrategy<?, ?>> sideInputs;
  private final SerializablePipelineOptions serializedOptions;
  private final Map<TupleTag<?>, Integer> outputMap;
  private final TupleTag<OutputT> mainOutputTag;
  private final Coder<KV<K, V>> inputCoder;
  private final Map<TupleTag<?>, Coder<?>> outputCoderMap;
  private final DoFnSchemaInformation doFnSchemaInformation;
  private final Map<String, PCollectionView<?>> sideInputMapping;
  private transient DoFnInvoker doFnInvoker;

  public FlinkStatefulDoFnFunction(
      DoFn<KV<K, V>, OutputT> dofn,
      String stepName,
      WindowingStrategy<?, ?> windowingStrategy,
      Map<PCollectionView<?>, WindowingStrategy<?, ?>> sideInputs,
      PipelineOptions pipelineOptions,
      Map<TupleTag<?>, Integer> outputMap,
      TupleTag<OutputT> mainOutputTag,
      Coder<KV<K, V>> inputCoder,
      Map<TupleTag<?>, Coder<?>> outputCoderMap,
      DoFnSchemaInformation doFnSchemaInformation,
      Map<String, PCollectionView<?>> sideInputMapping) {

    this.dofn = dofn;
    this.stepName = stepName;
    this.windowingStrategy = windowingStrategy;
    this.sideInputs = sideInputs;
    this.serializedOptions = new SerializablePipelineOptions(pipelineOptions);
    this.outputMap = outputMap;
    this.mainOutputTag = mainOutputTag;
    this.inputCoder = inputCoder;
    this.outputCoderMap = outputCoderMap;
    this.doFnSchemaInformation = doFnSchemaInformation;
    this.sideInputMapping = sideInputMapping;
  }

  @Override
  public void reduce(
      Iterable<WindowedValue<KV<K, V>>> values, Collector<WindowedValue<OutputT>> out)
      throws Exception {
    RuntimeContext runtimeContext = getRuntimeContext();

    DoFnRunners.OutputManager outputManager;
    if (outputMap.size() == 1) {
      outputManager = new FlinkDoFnFunction.DoFnOutputManager(out);
    } else {
      // it has some additional Outputs
      outputManager = new FlinkDoFnFunction.MultiDoFnOutputManager((Collector) out, outputMap);
    }

    final Iterator<WindowedValue<KV<K, V>>> iterator = values.iterator();

    // get the first value, we need this for initializing the state internals with the key.
    // we are guaranteed to have a first value, otherwise reduce() would not have been called.
    WindowedValue<KV<K, V>> currentValue = iterator.next();
    final K key = currentValue.getValue().getKey();

    final InMemoryStateInternals<K> stateInternals = InMemoryStateInternals.forKey(key);

    // Used with Batch, we know that all the data is available for this key. We can't use the
    // timer manager from the context because it doesn't exist. So we create one and advance
    // time to the end after processing all elements.
    final InMemoryTimerInternals timerInternals = new InMemoryTimerInternals();
    timerInternals.advanceProcessingTime(Instant.now());
    timerInternals.advanceSynchronizedProcessingTime(Instant.now());

    List<TupleTag<?>> additionalOutputTags = Lists.newArrayList(outputMap.keySet());

    DoFnRunner<KV<K, V>, OutputT> doFnRunner =
        DoFnRunners.simpleRunner(
            serializedOptions.get(),
            dofn,
            new FlinkSideInputReader(sideInputs, runtimeContext),
            outputManager,
            mainOutputTag,
            additionalOutputTags,
            new FlinkNoOpStepContext() {
              @Override
              public StateInternals stateInternals() {
                return stateInternals;
              }

              @Override
              public TimerInternals timerInternals() {
                return timerInternals;
              }
            },
            inputCoder,
            outputCoderMap,
            windowingStrategy,
            doFnSchemaInformation,
            sideInputMapping);

    if ((serializedOptions.get().as(FlinkPipelineOptions.class)).getEnableMetrics()) {
      doFnRunner =
          new DoFnRunnerWithMetricsUpdate<>(
              stepName, doFnRunner, new FlinkMetricContainer(getRuntimeContext()));
    }

    doFnRunner.startBundle();

    doFnRunner.processElement(currentValue);
    while (iterator.hasNext()) {
      currentValue = iterator.next();
      doFnRunner.processElement(currentValue);
    }

    // Finish any pending windows by advancing the input watermark to infinity.
    timerInternals.advanceInputWatermark(BoundedWindow.TIMESTAMP_MAX_VALUE);

    // Finally, advance the processing time to infinity to fire any timers.
    timerInternals.advanceProcessingTime(BoundedWindow.TIMESTAMP_MAX_VALUE);
    timerInternals.advanceSynchronizedProcessingTime(BoundedWindow.TIMESTAMP_MAX_VALUE);

    fireEligibleTimers(timerInternals, doFnRunner);

    doFnRunner.finishBundle();
  }

  private void fireEligibleTimers(
      InMemoryTimerInternals timerInternals, DoFnRunner<KV<K, V>, OutputT> runner)
      throws Exception {

    while (true) {

      TimerInternals.TimerData timer;
      boolean hasFired = false;

      while ((timer = timerInternals.removeNextEventTimer()) != null) {
        hasFired = true;
        fireTimer(timer, runner);
      }
      while ((timer = timerInternals.removeNextProcessingTimer()) != null) {
        hasFired = true;
        fireTimer(timer, runner);
      }
      while ((timer = timerInternals.removeNextSynchronizedProcessingTimer()) != null) {
        hasFired = true;
        fireTimer(timer, runner);
      }
      if (!hasFired) {
        break;
      }
    }
  }

  private void fireTimer(TimerInternals.TimerData timer, DoFnRunner<KV<K, V>, OutputT> doFnRunner) {
    StateNamespace namespace = timer.getNamespace();
    checkArgument(namespace instanceof StateNamespaces.WindowNamespace);
    BoundedWindow window = ((StateNamespaces.WindowNamespace) namespace).getWindow();
    doFnRunner.onTimer(timer.getTimerId(), window, timer.getTimestamp(), timer.getDomain());
  }

  @Override
  public void open(Configuration parameters) {
    // Note that the SerializablePipelineOptions already initialize FileSystems in the readObject()
    // deserialization method. However, this is a hack, and we want to properly initialize the
    // options where they are needed.
    FileSystems.setDefaultPipelineOptions(serializedOptions.get());
    doFnInvoker = DoFnInvokers.tryInvokeSetupFor(dofn);
  }

  @Override
  public void close() throws Exception {
    try {
      Optional.ofNullable(doFnInvoker).ifPresent(DoFnInvoker::invokeTeardown);
    } finally {
      FlinkClassloading.deleteStaticCaches();
    }
  }
}