The role of Storm in Java big data processing

Storm is a distributed framework for processing real-time data streams. Its architecture is based on a publish-subscribe model, including Spouts that read data and publish it into the topology, and Bolts that process the data. In practice, Storm can be used to calculate real-time website traffic: // Create Spouts and Bolts to process website traffic and calculate the average number of requests // Use StormSubmitter to submit topology Storm is a powerful framework that is very suitable for processing real-time data flows.

The role of Storm in Java big data processing

Introduction
Apache Storm is a A distributed real-time stream processing framework for processing large streams of real-time data generated by applications, sensors, or other sources. It is known for its high throughput, low latency, and fault tolerance.

Architecture
Storm is based on a publish-subscribe model, where the data publisher is called a Spout and the subscriber is called a Bolt. Spouts read data from the data source and publish it into the Storm topology, while Bolts process the received data and possibly generate output as needed.

Practical Case
Consider an example where website traffic needs to be calculated in real time. We can use Storm to create a topology to achieve this goal:

// Spout类
class WebsiteTrafficSpout extends SpoutBase {
  private final AtomicInteger count = new AtomicInteger();

  @Override
  public void nextTuple() {
    emit(new Values("website", count.incrementAndGet()));
  }
}

// Bolt类
class WebsiteTrafficBolt extends BaseBasicBolt {
  private final Histogram histogram = new Histogram();

  @Override
  public void execute(Tuple input, BasicOutputCollector collector) {
    String website = input.getStringByField("website");
    int count = input.getIntegerByField("count");
    histogram.update(count);
    collector.emit(new Values("website", website, histogram.getMean())); 
  }
}

Topology Configuration
Use the StormSubmitter class to create and submit the topology:

StormSubmitter.submitTopology("website-traffic-topology", new Config(), 
   new TopologyBuilder()
       .setSpout("traffic-spout", new WebsiteTrafficSpout(), 1)
       .setBolt("traffic-bolt", new WebsiteTrafficBolt(), 1)
       .shuffleGrouping("traffic-spout", "traffic-bolt")
       .createTopology());

After starting the topology, It will continuously process website traffic data and generate the average number of requests per second through Bolt in real time.

Conclusion
Storm is a powerful framework that is ideal for processing real-time data streams. Its distributed architecture, low latency, and fault tolerance make it ideal for big data processing and analysis.

The above is the detailed content of The role of Storm in Java big data processing. For more information, please follow other related articles on the PHP Chinese website!