co.cask.cdap.etl.batch.mapreduce.TransformRunner Maven / Gradle / Ivy

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/*
 * Copyright © 2016 Cask Data, Inc.
 *
 * Licensed 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 co.cask.cdap.etl.batch.mapreduce;

import co.cask.cdap.api.data.schema.Schema;
import co.cask.cdap.api.dataset.lib.KeyValue;
import co.cask.cdap.api.mapreduce.MapReduceTaskContext;
import co.cask.cdap.api.metrics.Metrics;
import co.cask.cdap.etl.api.InvalidEntry;
import co.cask.cdap.etl.api.Transform;
import co.cask.cdap.etl.api.batch.BatchAggregator;
import co.cask.cdap.etl.api.batch.BatchJoiner;
import co.cask.cdap.etl.batch.BatchPhaseSpec;
import co.cask.cdap.etl.batch.PipelinePluginInstantiator;
import co.cask.cdap.etl.batch.TransformExecutorFactory;
import co.cask.cdap.etl.common.Constants;
import co.cask.cdap.etl.common.Destroyables;
import co.cask.cdap.etl.common.PipelinePhase;
import co.cask.cdap.etl.common.SetMultimapCodec;
import co.cask.cdap.etl.common.TransformExecutor;
import co.cask.cdap.etl.common.TransformResponse;
import co.cask.cdap.etl.planner.StageInfo;
import co.cask.cdap.internal.io.SchemaTypeAdapter;
import com.google.common.base.Preconditions;
import com.google.common.collect.ImmutableSet;
import com.google.common.collect.SetMultimap;
import com.google.gson.Gson;
import com.google.gson.GsonBuilder;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.Mapper;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.Collection;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Map;
import java.util.Set;

/**
 * Initializes a TransformExecutor and runs transforms. This is used in both the mapper and reducer since they
 * do mostly the same thing, except the mapper needs to write to an aggregator or to sinks, whereas the reducer
 * needs to read from an aggregator and write to sinks.
 *
 * @param    the type of key to send into the transform executor
 * @param  the type of value to send into the transform executor
 */
public class TransformRunner {
  private static final Logger LOG = LoggerFactory.getLogger(TransformRunner.class);
  private static final Gson GSON = new GsonBuilder()
    .registerTypeAdapter(Schema.class, new SchemaTypeAdapter())
    .registerTypeAdapter(SetMultimap.class, new SetMultimapCodec<>())
    .create();
  private final Set transformsWithoutErrorDataset;
  private final Map> transformErrorSinkMap;
  private final TransformExecutor> transformExecutor;
  private final OutputWriter outputWriter;

  public TransformRunner(MapReduceTaskContext context,
                         Metrics metrics) throws Exception {
    JobContext jobContext = context.getHadoopContext();
    Configuration hConf = jobContext.getConfiguration();

    // figure out whether we are writing to a single output or to multiple outputs
    Map properties = context.getSpecification().getProperties();
    BatchPhaseSpec phaseSpec = GSON.fromJson(properties.get(Constants.PIPELINEID), BatchPhaseSpec.class);
    this.outputWriter = getSinkWriter(context, phaseSpec.getPhase(), hConf);

    // instantiate and initialize all transformations and setup the TransformExecutor
    PipelinePluginInstantiator pluginInstantiator = new PipelinePluginInstantiator(context, phaseSpec);
    // stage name -> runtime args for that stage
    Map> runtimeArgs = GSON.fromJson(
      hConf.get(ETLMapReduce.RUNTIME_ARGS_KEY), ETLMapReduce.RUNTIME_ARGS_TYPE);

    // input alias name -> stage name mapping
    Map inputAliasToStage = GSON.fromJson(hConf.get(ETLMapReduce.INPUT_ALIAS_KEY),
                                                          ETLMapReduce.INPUT_ALIAS_TYPE);
    String inputAliasName = context.getInputName();
    // inputAliasName can be null (in case of reducers)
    String sourceStage = (inputAliasName != null) ? inputAliasToStage.get(inputAliasName) : null;

    PipelinePhase phase = phaseSpec.getPhase();
    Set reducers = phase.getStagesOfType(BatchAggregator.PLUGIN_TYPE, BatchJoiner.PLUGIN_TYPE);
    if (!reducers.isEmpty()) {
      String reducerName = reducers.iterator().next().getName();
      // if we're in the mapper, get the part of the pipeline starting from sources and ending at aggregator
      if (jobContext instanceof Mapper.Context) {
        phase = phase.subsetTo(ImmutableSet.of(reducerName));
      } else {
        // if we're in the reducer, get the part of the pipeline starting from the aggregator and ending at sinks
        phase = phase.subsetFrom(ImmutableSet.of(reducerName));
      }
    }

    TransformExecutorFactory> transformExecutorFactory =
      new MapReduceTransformExecutorFactory<>(context, pluginInstantiator, metrics, runtimeArgs, sourceStage);
    this.transformExecutor = transformExecutorFactory.create(phase);

    // setup error dataset information
    this.transformsWithoutErrorDataset = new HashSet<>();
    this.transformErrorSinkMap = new HashMap<>();
    for (StageInfo transformInfo : phaseSpec.getPhase().getStagesOfType(Transform.PLUGIN_TYPE)) {
      String errorDatasetName = transformInfo.getErrorDatasetName();
      if (errorDatasetName != null) {
        transformErrorSinkMap.put(transformInfo.getName(), new ErrorOutputWriter<>(context, errorDatasetName));
      }
    }
  }

  // this is needed because we need to write to the context differently depending on the number of outputs
  private OutputWriter getSinkWriter(MapReduceTaskContext context,
                                                     PipelinePhase pipelinePhase,
                                                     Configuration hConf) {
    Set reducers = pipelinePhase.getStagesOfType(BatchAggregator.PLUGIN_TYPE, BatchJoiner.PLUGIN_TYPE);
    JobContext hadoopContext = context.getHadoopContext();
    if (!reducers.isEmpty() && hadoopContext instanceof Mapper.Context) {
        return new SingleOutputWriter<>(context);
    }

    String sinkOutputsStr = hConf.get(ETLMapReduce.SINK_OUTPUTS_KEY);

    // should never happen, this is set in initialize
    Preconditions.checkNotNull(sinkOutputsStr, "Sink outputs not found in Hadoop conf.");
    Map sinkOutputs = GSON.fromJson(sinkOutputsStr, ETLMapReduce.SINK_OUTPUTS_TYPE);
    return hasSingleOutput(pipelinePhase.getStagesOfType(Transform.PLUGIN_TYPE), sinkOutputs) ?
      new SingleOutputWriter<>(context) : new MultiOutputWriter<>(context, sinkOutputs);
  }

  private boolean hasSingleOutput(Set transformInfos, Map sinkOutputs) {
    // if there are any error datasets, we know we have at least one sink, and one error dataset
    for (StageInfo info : transformInfos) {
      if (info.getErrorDatasetName() != null) {
        return false;
      }
    }
    // if no error datasets, check if we have more than one sink
    Set allOutputs = new HashSet<>();

    for (SinkOutput sinkOutput : sinkOutputs.values()) {
      if (sinkOutput.getErrorDatasetName() != null) {
        return false;
      }
      allOutputs.addAll(sinkOutput.getSinkOutputs());
    }
    return allOutputs.size() == 1;
  }

  public void transform(KEY key, VALUE value) throws Exception {
    KeyValue input = new KeyValue<>(key, value);
    TransformResponse transformResponse = transformExecutor.runOneIteration(input);
    for (Map.Entry> transformedEntry : transformResponse.getSinksResults().entrySet()) {
      for (Object transformedRecord : transformedEntry.getValue()) {
        outputWriter.write(transformedEntry.getKey(), (KeyValue) transformedRecord);
      }
    }

    for (Map.Entry>> errorEntry :
      transformResponse.getMapTransformIdToErrorEmitter().entrySet()) {

      // this check is used to make sure we don't log the same warning multiple times,
      // but only log it once.
      if (transformsWithoutErrorDataset.contains(errorEntry.getKey())) {
        continue;
      }
      if (!errorEntry.getValue().isEmpty()) {
        if (!transformErrorSinkMap.containsKey(errorEntry.getKey())) {
          LOG.warn("Transform : {} has error records, but does not have a error dataset configured.",
                   errorEntry.getKey());
          transformsWithoutErrorDataset.add(errorEntry.getKey());
        } else {
          transformErrorSinkMap.get(errorEntry.getKey()).write(errorEntry.getValue());
        }
      }
    }
    transformExecutor.resetEmitter();
  }

  public void destroy() {
    Destroyables.destroyQuietly(transformExecutor);
  }
}