用的是ShuffleGrouping分组方式，并行度设置为3
这是跑下来的结果
参考代码StormTopologyShufferGrouping.java
package yehua.storm;
import java.util.Map;
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.StormSubmitter;
import org.apache.storm.generated.AlreadyAliveException;
import org.apache.storm.generated.AuthorizationException;
import org.apache.storm.generated.InvalidTopologyException;
import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.topology.base.BaseRichBolt;
import org.apache.storm.topology.base.BaseRichSpout;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;
import org.apache.storm.utils.Utils;
/**
* shufferGrouping
* 没有特殊情况下，就使用这个分组方式，可以保证负载均衡，工作中最常用的
* @author yehua
*
*/
public class StormTopologyShufferGrouping {
public static class MySpout extends BaseRichSpout{
private Map conf;
private TopologyContext context;
private SpoutOutputCollector collector;
// @Override
public void open(Map conf, TopologyContext context,
SpoutOutputCollector collector) {
this.conf = conf;
this.collector = collector;
this.context = context;
}
int num = 0;
//@Override
public void nextTuple() {
num++;
System.out.println("spout:"+num);
this.collector.emit(new Values(num));
Utils.sleep(1000);
}
//@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("num"));
}
}
public static class MyBolt extends BaseRichBolt{
private Map stormConf;
private TopologyContext context;
private OutputCollector collector;
// @Override
public void prepare(Map stormConf, TopologyContext context,
OutputCollector collector) {
this.stormConf = stormConf;
this.context = context;
this.collector = collector;
}
//@Override
public void execute(Tuple input) {
Integer num = input.getIntegerByField("num");
System.err.println("thread:"+Thread.currentThread().getId()+",num="+num);
}
//@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
}
}
public static void main(String[] args) {
TopologyBuilder topologyBuilder = new TopologyBuilder();
String spout_id = MySpout.class.getSimpleName();
String bolt_id = MyBolt.class.getSimpleName();
topologyBuilder.setSpout(spout_id, new MySpout());
topologyBuilder.setBolt(bolt_id, new MyBolt(),3).shuffleGrouping(spout_id);
Config config = new Config();
String topology_name = StormTopologyShufferGrouping.class.getSimpleName();
if(args.length==0){
//在本地运行
LocalCluster localCluster = new LocalCluster();
localCluster.submitTopology(topology_name, config, topologyBuilder.createTopology());
}else{
//在集群运行
try {
StormSubmitter.submitTopology(topology_name, config, topologyBuilder.createTopology());
} catch (AlreadyAliveException e) {
e.printStackTrace();
} catch (InvalidTopologyException e) {
e.printStackTrace();
} catch (AuthorizationException e) {
e.printStackTrace();
}
}
}
}
用fieldsGrouping方法
按奇偶数分组（也就是按字段分组）
从跑出来的结果看出来，一个线程处理奇数的一个线程处理偶数的
参考代码StormTopologyFieldsGrouping.java
1 package yehua.storm;
2
3 import java.util.Map;
4
5 import org.apache.storm.Config;
6 import org.apache.storm.LocalCluster;
7 import org.apache.storm.StormSubmitter;
8 import org.apache.storm.generated.AlreadyAliveException;
9 import org.apache.storm.generated.AuthorizationException;
10 import org.apache.storm.generated.InvalidTopologyException;
11 import org.apache.storm.spout.SpoutOutputCollector;
12 import org.apache.storm.task.OutputCollector;
13 import org.apache.storm.task.TopologyContext;
14 import org.apache.storm.topology.OutputFieldsDeclarer;
15 import org.apache.storm.topology.TopologyBuilder;
16 import org.apache.storm.topology.base.BaseRichBolt;
17 import org.apache.storm.topology.base.BaseRichSpout;
18 import org.apache.storm.tuple.Fields;
19 import org.apache.storm.tuple.Tuple;
20 import org.apache.storm.tuple.Values;
21 import org.apache.storm.utils.Utils;
22
23 /**
24 * FieldsGrouping
25 * 字段分组
26 * @author yehua
27 *
28 */
29
30 public class StormTopologyFieldsGrouping {
31
32 public static class MySpout extends BaseRichSpout{
33 private Map conf;
34 private TopologyContext context;
35 private SpoutOutputCollector collector;
36 //@Override
37 public void open(Map conf, TopologyContext context,
38 SpoutOutputCollector collector) {
39 this.conf = conf;
40 this.collector = collector;
41 this.context = context;
42 }
43
44 int num = 0;
45 //@Override
46 public void nextTuple() {
47 num++;
48 System.out.println("spout:"+num);
49 this.collector.emit(new Values(num,num%2));
50 Utils.sleep(1000);
51 }
52
53 //@Override
54 public void declareOutputFields(OutputFieldsDeclarer declarer) {
55 declarer.declare(new Fields("num","flag"));
56 }
57
58 }
59
60
61
62 public static class MyBolt extends BaseRichBolt{
63
64 private Map stormConf;
65 private TopologyContext context;
66 private OutputCollector collector;
67 //@Override
68 public void prepare(Map stormConf, TopologyContext context,
69 OutputCollector collector) {
70 this.stormConf = stormConf;
71 this.context = context;
72 this.collector = collector;
73 }
74
75 //@Override
76 public void execute(Tuple input) {
77 Integer num = input.getIntegerByField("num");
78 System.err.println("thread:"+Thread.currentThread().getId()+",num="+num);
79 }
80
81 //@Override
82 public void declareOutputFields(OutputFieldsDeclarer declarer) {
83
84 }
85
86 }
87
88
89
90 public static void main(String[] args) {
91 TopologyBuilder topologyBuilder = new TopologyBuilder();
92 String spout_id = MySpout.class.getSimpleName();
93 String bolt_id = MyBolt.class.getSimpleName();
94
95 topologyBuilder.setSpout(spout_id, new MySpout());
96 //注意：字段分组一定可以保证相同分组的数据进入同一个线程处理
97 topologyBuilder.setBolt(bolt_id, new MyBolt(),2).fieldsGrouping(spout_id, new Fields("flag"));
98
99
100 Config config = new Config();
101 String topology_name = StormTopologyFieldsGrouping.class.getSimpleName();
102 if(args.length==0){
103 //在本地运行
104 LocalCluster localCluster = new LocalCluster();
105 localCluster.submitTopology(topology_name, config, topologyBuilder.createTopology());
106 }else{
107 //在集群运行
108 try {
109 StormSubmitter.submitTopology(topology_name, config, topologyBuilder.createTopology());
110 } catch (AlreadyAliveException e) {
111 e.printStackTrace();
112 } catch (InvalidTopologyException e) {
113 e.printStackTrace();
114 } catch (AuthorizationException e) {
115 e.printStackTrace();
116 }
117 }
118
119 }
120
121 }
这里补充一下，比如说有两类数据3个线程的时候
我们再看看运行结果，发现只有两个线程干活了
还有一种情况，只有一个线程的情况，还是两类数据
从运行结果看出来，所有话一个进程干完了
allGrouping方法
运行结果：spout每发一条数据三个进程都接收到了（基本没什么应用场景）
参考代码StormTopologyAllGrouping.java
1 package yehua.storm;
2
3 import java.util.Map;
4
5 import org.apache.storm.Config;
6 import org.apache.storm.LocalCluster;
7 import org.apache.storm.StormSubmitter;
8 import org.apache.storm.generated.AlreadyAliveException;
9 import org.apache.storm.generated.AuthorizationException;
10 import org.apache.storm.generated.InvalidTopologyException;
11 import org.apache.storm.spout.SpoutOutputCollector;
12 import org.apache.storm.task.OutputCollector;
13 import org.apache.storm.task.TopologyContext;
14 import org.apache.storm.topology.OutputFieldsDeclarer;
15 import org.apache.storm.topology.TopologyBuilder;
16 import org.apache.storm.topology.base.BaseRichBolt;
17 import org.apache.storm.topology.base.BaseRichSpout;
18 import org.apache.storm.tuple.Fields;
19 import org.apache.storm.tuple.Tuple;
20 import org.apache.storm.tuple.Values;
21 import org.apache.storm.utils.Utils;
22
23 /**
24 * AllGrouping
25 * 广播分组
26 * @author yehua
27 *
28 */
29
30 public class StormTopologyAllGrouping {
31
32 public static class MySpout extends BaseRichSpout{
33 private Map conf;
34 private TopologyContext context;
35 private SpoutOutputCollector collector;
36 //@Override
37 public void open(Map conf, TopologyContext context,
38 SpoutOutputCollector collector) {
39 this.conf = conf;
40 this.collector = collector;
41 this.context = context;
42 }
43
44 int num = 0;
45 //@Override
46 public void nextTuple() {
47 num++;
48 System.out.println("spout:"+num);
49 this.collector.emit(new Values(num));
50 Utils.sleep(1000);
51 }
52
53 //@Override
54 public void declareOutputFields(OutputFieldsDeclarer declarer) {
55 declarer.declare(new Fields("num"));
56 }
57
58 }
59
60
61
62 public static class MyBolt extends BaseRichBolt{
63
64 private Map stormConf;
65 private TopologyContext context;
66 private OutputCollector collector;
67 //@Override
68 public void prepare(Map stormConf, TopologyContext context,
69 OutputCollector collector) {
70 this.stormConf = stormConf;
71 this.context = context;
72 this.collector = collector;
73 }
74
75 //@Override
76 public void execute(Tuple input) {
77 Integer num = input.getIntegerByField("num");
78 System.err.println("thread:"+Thread.currentThread().getId()+",num="+num);
79 }
80
81 //@Override
82 public void declareOutputFields(OutputFieldsDeclarer declarer) {
83
84 }
85
86 }
87
88
89
90 public static void main(String[] args) {
91 TopologyBuilder topologyBuilder = new TopologyBuilder();
92 String spout_id = MySpout.class.getSimpleName();
93 String bolt_id = MyBolt.class.getSimpleName();
94
95 topologyBuilder.setSpout(spout_id, new MySpout());
96 topologyBuilder.setBolt(bolt_id, new MyBolt(),3).allGrouping(spout_id);
97
98
99 Config config = new Config();
100 String topology_name = StormTopologyAllGrouping.class.getSimpleName();
101 if(args.length==0){
102 //在本地运行
103 LocalCluster localCluster = new LocalCluster();
104 localCluster.submitTopology(topology_name, config, topologyBuilder.createTopology());
105 }else{
106 //在集群运行
107 try {
108 StormSubmitter.submitTopology(topology_name, config, topologyBuilder.createTopology());
109 } catch (AlreadyAliveException e) {
110 e.printStackTrace();
111 } catch (InvalidTopologyException e) {
112 e.printStackTrace();
113 } catch (AuthorizationException e) {
114 e.printStackTrace();
115 }
116 }
117
118 }
119
120 }
LocalOrShufferGrouping方法
spout只会给同一个主机的线程发送数据（图中的线程1），也就是在同一个线程里会被发送数据，这样做的好处就是在同一个进程里发送数据效率搞，不用跨主机传输
但是当数据量太大的时候，线程1处理不了的时候就麻烦了，所以在实际工作中不建议这样做。
这里用的是3个线程（3个bolt），2个进程(2个worker)
从运行的结果我们可以看出来，只有一个线程在接收数据
还有一种情况，如果本地没有线程的时候，他就跟ShufferGrouping的效果一样的
参考代码StormTopologyLocalOrShufferGrouping.java
1 package yehua.storm;
2
3 import java.util.Map;
4
5 import org.apache.storm.Config;
6 import org.apache.storm.LocalCluster;
7 import org.apache.storm.StormSubmitter;
8 import org.apache.storm.generated.AlreadyAliveException;
9 import org.apache.storm.generated.AuthorizationException;
10 import org.apache.storm.generated.InvalidTopologyException;
11 import org.apache.storm.spout.SpoutOutputCollector;
12 import org.apache.storm.task.OutputCollector;
13 import org.apache.storm.task.TopologyContext;
14 import org.apache.storm.topology.OutputFieldsDeclarer;
15 import org.apache.storm.topology.TopologyBuilder;
16 import org.apache.storm.topology.base.BaseRichBolt;
17 import org.apache.storm.topology.base.BaseRichSpout;
18 import org.apache.storm.tuple.Fields;
19 import org.apache.storm.tuple.Tuple;
20 import org.apache.storm.tuple.Values;
21 import org.apache.storm.utils.Utils;
22
23 /**
24 * LocalAllshufferGrouping
25 * @author yehua
26 *
27 */
28
29 public class StormTopologyLocalOrShufferGrouping {
30
31 public static class MySpout extends BaseRichSpout{
32 private Map conf;
33 private TopologyContext context;
34 private SpoutOutputCollector collector;
35 //@Override
36 public void open(Map conf, TopologyContext context,
37 SpoutOutputCollector collector) {
38 this.conf = conf;
39 this.collector = collector;
40 this.context = context;
41 }
42
43 int num = 0;
44 //@Override
45 public void nextTuple() {
46 num++;
47 System.out.println("spout:"+num);
48 this.collector.emit(new Values(num));
49 Utils.sleep(1000);
50 }
51
52 //@Override
53 public void declareOutputFields(OutputFieldsDeclarer declarer) {
54 declarer.declare(new Fields("num"));
55 }
56
57 }
58
59
60
61 public static class MyBolt extends BaseRichBolt{
62
63 private Map stormConf;
64 private TopologyContext context;
65 private OutputCollector collector;
66 //@Override
67 public void prepare(Map stormConf, TopologyContext context,
68 OutputCollector collector) {
69 this.stormConf = stormConf;
70 this.context = context;
71 this.collector = collector;
72 }
73
74 //@Override
75 public void execute(Tuple input) {
76 Integer num = input.getIntegerByField("num");
77 System.err.println("thread:"+Thread.currentThread().getId()+",num="+num);
78 }
79
80 //@Override
81 public void declareOutputFields(OutputFieldsDeclarer declarer) {
82
83 }
84
85 }
86
87
88
89 public static void main(String[] args) {
90 TopologyBuilder topologyBuilder = new TopologyBuilder();
91 String spout_id = MySpout.class.getSimpleName();
92 String bolt_id = MyBolt.class.getSimpleName();
93
94 topologyBuilder.setSpout(spout_id, new MySpout());
95 topologyBuilder.setBolt(bolt_id, new MyBolt(),3).localOrShuffleGrouping(spout_id);
96
97
98 Config config = new Config();
99 config.setNumWorkers(2);
100 String topology_name = StormTopologyLocalOrShufferGrouping.class.getSimpleName();
101 if(args.length==0){
102 //在本地运行
103 LocalCluster localCluster = new LocalCluster();
104 localCluster.submitTopology(topology_name, config, topologyBuilder.createTopology());
105 }else{
106 //在集群运行
107 try {
108 StormSubmitter.submitTopology(topology_name, config, topologyBuilder.createTopology());
109 } catch (AlreadyAliveException e) {
110 e.printStackTrace();
111 } catch (InvalidTopologyException e) {
112 e.printStackTrace();
113 } catch (AuthorizationException e) {
114 e.printStackTrace();
115 }
116 }
117
118 }
119
120 }