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ray streaming api
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package io.ray.streaming.api.context;

import com.google.common.base.Preconditions;
import io.ray.api.Ray;
import io.ray.streaming.api.stream.StreamSink;
import io.ray.streaming.client.JobClient;
import io.ray.streaming.jobgraph.JobGraph;
import io.ray.streaming.jobgraph.JobGraphBuilder;
import io.ray.streaming.jobgraph.JobGraphOptimizer;
import io.ray.streaming.util.Config;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.ServiceLoader;
import java.util.concurrent.atomic.AtomicInteger;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/** Encapsulate the context information of a streaming Job. */
public class StreamingContext implements Serializable {

  private static final Logger LOG = LoggerFactory.getLogger(StreamingContext.class);

  private transient AtomicInteger idGenerator;

  /** The sinks of this streaming job. */
  private List streamSinks;

  /** The user custom streaming job configuration. */
  private Map jobConfig;

  /** The logic plan. */
  private JobGraph jobGraph;

  private StreamingContext() {
    this.idGenerator = new AtomicInteger(0);
    this.streamSinks = new ArrayList<>();
    this.jobConfig = new HashMap<>();
  }

  public static StreamingContext buildContext() {
    return new StreamingContext();
  }

  /** Construct job DAG, and execute the job. */
  public void execute(String jobName) {
    JobGraphBuilder jobGraphBuilder = new JobGraphBuilder(this.streamSinks, jobName);
    JobGraph originalJobGraph = jobGraphBuilder.build();
    this.jobGraph = new JobGraphOptimizer(originalJobGraph).optimize();
    jobGraph.printJobGraph();
    LOG.info("JobGraph digraph\n{}", jobGraph.generateDigraph());

    if (!Ray.isInitialized()) {
      if (Config.MEMORY_CHANNEL.equalsIgnoreCase(jobConfig.get(Config.CHANNEL_TYPE))) {
        ClusterStarter.startCluster(true);
        LOG.info("Created local cluster for job {}.", jobName);
      } else {
        ClusterStarter.startCluster(false);
        LOG.info("Created multi process cluster for job {}.", jobName);
      }
      Runtime.getRuntime().addShutdownHook(new Thread(StreamingContext.this::stop));
    } else {
      LOG.info("Reuse existing cluster.");
    }

    ServiceLoader serviceLoader = ServiceLoader.load(JobClient.class);
    Iterator iterator = serviceLoader.iterator();
    Preconditions.checkArgument(
        iterator.hasNext(), "No JobClient implementation has been provided.");
    JobClient jobClient = iterator.next();
    jobClient.submit(jobGraph, jobConfig);
  }

  public int generateId() {
    return this.idGenerator.incrementAndGet();
  }

  public void addSink(StreamSink streamSink) {
    streamSinks.add(streamSink);
  }

  public List getStreamSinks() {
    return streamSinks;
  }

  public void withConfig(Map jobConfig) {
    this.jobConfig = jobConfig;
  }

  public void stop() {
    if (Ray.isInitialized()) {
      ClusterStarter.stopCluster();
    }
  }
}