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co.cask.cdap.etl.batch.mapreduce.TransformRunner Maven / Gradle / Ivy
/*
* 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.batch.InputContext;
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.batch.BatchAggregator;
import co.cask.cdap.etl.api.batch.BatchJoiner;
import co.cask.cdap.etl.batch.BatchPhaseSpec;
import co.cask.cdap.etl.batch.PipeTransformExecutor;
import co.cask.cdap.etl.batch.PipelinePluginInstantiator;
import co.cask.cdap.etl.batch.connector.MultiConnectorFactory;
import co.cask.cdap.etl.common.BasicArguments;
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.spec.StageSpec;
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 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 Gson GSON = new GsonBuilder()
.registerTypeAdapter(Schema.class, new SchemaTypeAdapter())
.registerTypeAdapter(SetMultimap.class, new SetMultimapCodec<>())
.create();
private final PipeTransformExecutor> 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, metrics, phaseSpec, new MultiConnectorFactory());
// 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);
InputContext inputContext = context.getInputContext();
// inputContext can be null (in case of reducers)
String sourceStage = (inputContext != null) ? inputAliasToStage.get(inputContext.getInputName()) : 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));
}
}
MapReduceTransformExecutorFactory> transformExecutorFactory =
new MapReduceTransformExecutorFactory<>(context, pluginInstantiator, metrics,
new BasicArguments(context.getWorkflowToken(), runtimeArgs),
sourceStage, phaseSpec.getNumOfRecordsPreview(),
phaseSpec.pipelineContainsCondition());
this.transformExecutor = transformExecutorFactory.create(phase, outputWriter);
}
// 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(sinkOutputs) ?
new SingleOutputWriter<>(context) : new MultiOutputWriter<>(context, sinkOutputs);
}
private boolean hasSingleOutput(Map sinkOutputs) {
// if no error datasets, check if we have more than one sink
Set allOutputs = new HashSet<>();
for (SinkOutput sinkOutput : sinkOutputs.values()) {
allOutputs.addAll(sinkOutput.getSinkOutputs());
}
return allOutputs.size() == 1;
}
public void transform(KEY key, VALUE value) throws Exception {
KeyValue input = new KeyValue<>(key, value);
transformExecutor.runOneIteration(input);
}
public void destroy() {
Destroyables.destroyQuietly(transformExecutor);
}
}