package storm.starter;
import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.LocalDRPC;
import backtype.storm.StormSubmitter;
import backtype.storm.coordination.BatchOutputCollector;
import backtype.storm.coordination.CoordinatedBolt.FinishedCallback;
import backtype.storm.drpc.LinearDRPCTopologyBuilder;
import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.IRichBolt;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.topology.base.BaseBatchBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;
import java.util.Arrays;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
/**
* This is a good example of doing complex Distributed RPC on top of Storm. This
* program creates a topology that can compute the reach for any URL on Twitter
* in realtime by parallelizing the whole computation.
*
* Reach is the number of unique people exposed to a URL on Twitter. To compute reach,
* you have to get all the people who tweeted the URL, get all the followers of all those people,
* unique that set of followers, and then count the unique set. It's an intense computation
* that can involve thousands of database calls and tens of millions of follower records.
*
* This Storm topology does every piece of that computation in parallel, turning what would be a
* computation that takes minutes on a single machine into one that takes just a couple seconds.
*
* For the purposes of demonstration, this topology replaces the use of actual DBs with
* in-memory hashmaps.
*
* See https://github.com/nathanmarz/storm/wiki/Distributed-RPC for more information on Distributed RPC.
*/
public class ReachTopology {
public static Map<String, List<String>> TWEETERS_DB = new HashMap<String, List<String>>() {{
put("foo.com/blog/1", Arrays.asList("sally", "bob", "tim", "george", "nathan"));
put("engineering.twitter.com/blog/5", Arrays.asList("adam", "david", "sally", "nathan"));
put("tech.backtype.com/blog/123", Arrays.asList("tim", "mike", "john"));
}};
public static Map<String, List<String>> FOLLOWERS_DB = new HashMap<String, List<String>>() {{
put("sally", Arrays.asList("bob", "tim", "alice", "adam", "jim", "chris", "jai"));
put("bob", Arrays.asList("sally", "nathan", "jim", "mary", "david", "vivian"));
put("tim", Arrays.asList("alex"));
put("nathan", Arrays.asList("sally", "bob", "adam", "harry", "chris", "vivian", "emily", "jordan"));
put("adam", Arrays.asList("david", "carissa"));
put("mike", Arrays.asList("john", "bob"));
put("john", Arrays.asList("alice", "nathan", "jim", "mike", "bob"));
}};
public static class GetTweeters extends BaseBasicBolt {
@Override
public void execute(Tuple tuple, BasicOutputCollector collector) {
Object id = tuple.getValue(0);
String url = tuple.getString(1);
List<String> tweeters = TWEETERS_DB.get(url);
if(tweeters!=null) {
for(String tweeter: tweeters) {
collector.emit(new Values(id, tweeter));
}
}
}
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "tweeter"));
}
}
public static class GetFollowers extends BaseBasicBolt {
@Override
public void execute(Tuple tuple, BasicOutputCollector collector) {
Object id = tuple.getValue(0);
String tweeter = tuple.getString(1);
List<String> followers = FOLLOWERS_DB.get(tweeter);
if(followers!=null) {
for(String follower: followers) {
collector.emit(new Values(id, follower));
}
}
}
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "follower"));
}
}
public static class PartialUniquer extends BaseBatchBolt {
BatchOutputCollector _collector;
Object _id;
Set<String> _followers = new HashSet<String>();
@Override
public void prepare(Map conf, TopologyContext context, BatchOutputCollector collector, Object id) {
_collector = collector;
_id = id;
}
@Override
public void execute(Tuple tuple) {
_followers.add(tuple.getString(1));
}
@Override
public void finishBatch() {
_collector.emit(new Values(_id, _followers.size()));
}
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "partial-count"));
}
}
public static class CountAggregator extends BaseBatchBolt {
BatchOutputCollector _collector;
Object _id;
int _count = 0;
@Override
public void prepare(Map conf, TopologyContext context, BatchOutputCollector collector, Object id) {
_collector = collector;
_id = id;
}
@Override
public void execute(Tuple tuple) {
_count+=tuple.getInteger(1);
}
@Override
public void finishBatch() {
_collector.emit(new Values(_id, _count));
}
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "reach"));
}
}
public static LinearDRPCTopologyBuilder construct() {
LinearDRPCTopologyBuilder builder = new LinearDRPCTopologyBuilder("reach");
builder.addBolt(new GetTweeters(), 4);
builder.addBolt(new GetFollowers(), 12)
.shuffleGrouping();
builder.addBolt(new PartialUniquer(), 6)
.fieldsGrouping(new Fields("id", "follower"));
builder.addBolt(new CountAggregator(), 3)
.fieldsGrouping(new Fields("id"));
return builder;
}
public static void main(String[] args) throws Exception {
LinearDRPCTopologyBuilder builder = construct();
Config conf = new Config();
if(args==null || args.length==0) {
conf.setMaxTaskParallelism(3);
LocalDRPC drpc = new LocalDRPC();
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("reach-drpc", conf, builder.createLocalTopology(drpc));
String[] urlsToTry = new String[] { "foo.com/blog/1", "engineering.twitter.com/blog/5", "notaurl.com"};
for(String url: urlsToTry) {
System.out.println("Reach of " + url + ": " + drpc.execute("reach", url));
}
cluster.shutdown();
drpc.shutdown();
} else {
conf.setNumWorkers(6);
StormSubmitter.submitTopology(args[0], conf, builder.createRemoteTopology());
}
}
}