Apache Storm in Twitter

Apache Storm is a free and open-source distributed stream processing computation framework used for processing big data in real-time. Twitter is one of the companies that first adopted Apache Storm to process their big data at scale.

What is Storm and How Does it Work?

Apache Storm is a real-time distributed computing system, which processes data streams in parallel across a cluster of machines in a fault-tolerant way. It is designed to be scalable, meaning that it can process and analyze large amounts of data, and it is able to handle high throughput and low latency streaming data.

Storm uses a stream processing model, where data is processed in a continuous stream of events. It supports many different data sources, such as Apache Kafka, Twitter Streaming API, and more.

Storm Topologies

Storm processing takes place in a network of nodes called a topology, which is made up of spouts and bolts. A spout is a source of data, and a bolt processes that data.

A Storm topology is described as a graph, where nodes represent spouts and bolts, and the edges represent the streams of data flowing between them. A topology can be created and deployed on a Storm cluster, where it can process streaming data in real-time.

Storm Components

One of the major components of Apache Storm is Nimbus, which is a master node that is responsible for distributing code and configuration data to the worker nodes in the cluster. The worker nodes are responsible for executing the spouts and bolts that make up the topology.

Storm has a rich set of features, including:

• Scalability: Storm can process high volumes of data by scaling out across a cluster of machines.
• Fault-tolerance: Storm is designed to be fault-tolerant, where the processing of data can continue even if a node fails.
• Real-time processing: Storm is able to process streams of data in real-time, allowing for low latency processing.
• Flexible processing: Storm supports a variety of data sources and can process both batch and real-time data.

Twitter's Use of Storm

Twitter uses Apache Storm for a variety of use cases, such as real-time analytics, processing and indexing tweets, and building infrastructure for Twitter's ad system.

Twitter's use of Storm is an example of how big data technologies can be used to analyze and process large volumes of data in real-time. Apache Storm is a powerful tool for processing streaming data and can help companies like Twitter gain insights from their data in real-time.

Conclusion

Apache Storm has become a cornerstone of big data processing and is a popular choice for companies that need to process large volumes of data in real-time. Twitter's use of Storm is a testament to the flexibility and power of the framework, and how it can be used to process and analyze large amounts of data in real-time.