下面是在麒麟V10服务器上编译安装Storm的详细过程的完整攻略:
准备工作
在开始之前,需要做好以下准备:
- 安装Java Development Kit(JDK):Storm是用Java编写的,需要JDK才能进行编译和执行。在麒麟V10服务器上,可以通过以下命令安装JDK:
sudo apt-get install default-jdk
- 安装Maven:Storm的编译需要使用Maven进行依赖管理。在麒麟V10服务器上,可以通过以下命令安装Maven:
sudo apt-get install maven
下载和编译Storm
-
下载Storm:可以从Storm官网(https://storm.apache.org/downloads.html)下载最新版本的Storm。下载完成后,解压缩到任意目录。
-
编译Storm:进入Storm源代码目录,执行以下命令进行编译:
mvn clean install -DskipTests=true
上述命令会将Storm的所有依赖包下载到本地,编译生成Storm的jar包,并安装到本地的Maven仓库中。
运行Storm
在编译完成后,可以通过以下命令来启动Storm:
bin/storm nimbus # 启动Nimbus节点
bin/storm supervisor # 启动Supervisor节点
bin/storm ui # 启动Storm Web UI
此时,可以在浏览器中访问http://localhost:8080来访问Storm的Web UI。
示例:使用Storm进行单词计数
下面是使用Storm进行单词计数的示例,包含Topology定义和代码实现:
Topology定义
public class WordCountTopology {
public static void main(String[] args) throws Exception {
TopologyBuilder builder = new TopologyBuilder();
builder.setSpout("spout", new RandomSentenceSpout(), 5);
builder.setBolt("split", new SplitSentenceBolt(), 8).shuffleGrouping("spout");
builder.setBolt("count", new CountBolt(), 12).fieldsGrouping("split", new Fields("word"));
Config conf = new Config();
conf.setDebug(true);
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("word-count", conf, builder.createTopology());
Utils.sleep(10000);
cluster.killTopology("word-count");
cluster.shutdown();
}
}
上述代码定义了一个拓扑结构,包含三个组件:spout、split和count。其中,spout组件用来产生随机的句子;split组件将句子拆分为单词;count组件将每个单词的计数汇总。
代码实现
- 创建RandomSentenceSpout类,用来产生随机的句子:
```java
public class RandomSentenceSpout extends BaseRichSpout {
private SpoutOutputCollector collector;
private Random rand;
public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {
this.collector = collector;
this.rand = new Random();
}
public void nextTuple() {
Utils.sleep(100);
String[] sentences = new String[]{
"the cow jumped over the moon",
"an apple a day keeps the doctor away",
"four score and seven years ago",
"snow white and the seven dwarfs",
"i am at two with nature"
};
String sentence = sentences[rand.nextInt(sentences.length)];
collector.emit(new Values(sentence));
}
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("sentence"));
}
}
```
- 创建SplitSentenceBolt类,用来将句子拆分为单词:
```java
public class SplitSentenceBolt extends BaseRichBolt {
private OutputCollector collector;
public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
this.collector = collector;
}
public void execute(Tuple tuple) {
String sentence = tuple.getStringByField("sentence");
String[] words = sentence.split(" ");
for (String word : words) {
collector.emit(new Values(word));
}
}
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("word"));
}
}
```
- 创建CountBolt类,用来汇总每个单词的计数:
```java
public class CountBolt extends BaseRichBolt {
private OutputCollector collector;
private Map
public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
this.collector = collector;
}
public void execute(Tuple tuple) {
String word = tuple.getStringByField("word");
int count = 0;
if (counts.containsKey(word)) {
count = counts.get(word);
}
count++;
counts.put(word, count);
collector.emit(new Values(word, count));
}
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("word", "count"));
}
}
```
完成上述代码后,运行WordCountTopology类即可启动单词计数拓扑,可以在Storm的Web UI中查看拓扑的运行状态和结果。
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