/*
* Copyright © 2014 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.internal.app.runtime.spark;
import co.cask.cdap.api.spark.Spark;
import co.cask.cdap.api.spark.SparkSpecification;
import co.cask.cdap.app.ApplicationSpecification;
import co.cask.cdap.app.program.Program;
import co.cask.cdap.app.runtime.Arguments;
import co.cask.cdap.app.runtime.ProgramController;
import co.cask.cdap.app.runtime.ProgramOptions;
import co.cask.cdap.app.runtime.ProgramRunner;
import co.cask.cdap.common.conf.CConfiguration;
import co.cask.cdap.common.lang.InstantiatorFactory;
import co.cask.cdap.common.logging.LoggingContextAccessor;
import co.cask.cdap.common.metrics.MetricsCollectionService;
import co.cask.cdap.data2.dataset2.DatasetFramework;
import co.cask.cdap.internal.app.runtime.ProgramOptionConstants;
import co.cask.cdap.proto.ProgramType;
import co.cask.tephra.TransactionSystemClient;
import com.google.common.base.Preconditions;
import com.google.common.base.Throwables;
import com.google.common.reflect.TypeToken;
import com.google.common.util.concurrent.Service;
import com.google.inject.Inject;
import org.apache.hadoop.conf.Configuration;
import org.apache.twill.api.RunId;
import org.apache.twill.discovery.DiscoveryServiceClient;
import org.apache.twill.filesystem.LocationFactory;
import org.apache.twill.internal.RunIds;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Runs {@link Spark} programs
*/
public class SparkProgramRunner implements ProgramRunner {
private static final Logger LOG = LoggerFactory.getLogger(SparkProgramRunner.class);
private final DatasetFramework datasetFramework;
private final Configuration hConf;
private final CConfiguration cConf;
private final MetricsCollectionService metricsCollectionService;
private final TransactionSystemClient txSystemClient;
private final LocationFactory locationFactory;
private final DiscoveryServiceClient discoveryServiceClient;
@Inject
public SparkProgramRunner(DatasetFramework datasetFramework, CConfiguration cConf,
MetricsCollectionService metricsCollectionService, Configuration hConf,
TransactionSystemClient txSystemClient, LocationFactory locationFactory,
DiscoveryServiceClient discoveryServiceClient) {
this.hConf = hConf;
this.datasetFramework = datasetFramework;
this.cConf = cConf;
this.metricsCollectionService = metricsCollectionService;
this.locationFactory = locationFactory;
this.txSystemClient = txSystemClient;
this.discoveryServiceClient = discoveryServiceClient;
}
@Override
public ProgramController run(Program program, ProgramOptions options) {
// Extract and verify parameters
final ApplicationSpecification appSpec = program.getSpecification();
Preconditions.checkNotNull(appSpec, "Missing application specification.");
ProgramType processorType = program.getType();
Preconditions.checkNotNull(processorType, "Missing processor type.");
Preconditions.checkArgument(processorType == ProgramType.SPARK, "Only Spark process type is supported.");
final SparkSpecification spec = appSpec.getSpark().get(program.getName());
Preconditions.checkNotNull(spec, "Missing SparkSpecification for %s", program.getName());
// Optionally get runId. If the spark started by other program (e.g. Workflow), it inherit the runId.
Arguments arguments = options.getArguments();
RunId runId = arguments.hasOption(ProgramOptionConstants.RUN_ID) ? RunIds.fromString(arguments.getOption
(ProgramOptionConstants.RUN_ID)) : RunIds.generate();
long logicalStartTime = arguments.hasOption(ProgramOptionConstants.LOGICAL_START_TIME)
? Long.parseLong(arguments.getOption(ProgramOptionConstants.LOGICAL_START_TIME)) : System.currentTimeMillis();
String workflowBatch = arguments.getOption(ProgramOptionConstants.WORKFLOW_BATCH);
Spark spark;
try {
spark = new InstantiatorFactory(false).get(TypeToken.of(program.<Spark>getMainClass())).create();
} catch (Exception e) {
LOG.error("Failed to instantiate Spark class for {}", spec.getClassName(), e);
throw Throwables.propagate(e);
}
final BasicSparkContext context = new BasicSparkContext(program, runId, options.getUserArguments(),
program.getSpecification().getDatasets().keySet(), spec,
logicalStartTime, workflowBatch,
metricsCollectionService, datasetFramework, cConf,
discoveryServiceClient);
LoggingContextAccessor.setLoggingContext(context.getLoggingContext());
Service sparkRuntimeService = new SparkRuntimeService(cConf, hConf, spark, spec, context,
program.getJarLocation(), locationFactory,
txSystemClient);
ProgramController controller = new SparkProgramController(sparkRuntimeService, context);
LOG.info("Starting Spark Job: {}", context.toString());
sparkRuntimeService.start();
return controller;
}
}