How does the Flume system operate?
The operating principle of the Flume system involves collecting data from sources (such as log files, sensors, message queues, etc.) and transferring it to destinations (such as Hadoop, HBase, and other storage systems).
Specifically, the Flume system includes the following components:
- Data Source: Responsible for collecting data from the source, which can be log files, network ports, message queues, etc. The source can be one or more, and Flume provides a variety of built-in source types.
- Channel: responsible for temporarily storing data collected from the source for subsequent processing and transmission. Channels can be queues in memory or files on disk.
- Sink is responsible for transferring data from the channel to the destination. The destination can be storage systems such as Hadoop cluster, HBase, Elasticsearch, or another Flume agent.
Below is the workflow of the Flume system:
- The data source sends data to the Source component.
- The Source component writes data to the Channel component.
- The Sink component retrieves data from the Channel component and transfers it to the destination.
The workings of the Flume system also involve the following important concepts:
- Agent: An independent running instance of Flume composed of Source, Channel, and Sink components.
- Event in Flume refers to a unit of data, consisting of the data itself and optional metadata.
- Flume Topology: A data flow pipeline consisting of multiple agents, used for achieving multi-level collection and transmission of data.
In summary, the Flume system operates by collecting data from a data source via the Source component, storing it temporarily in the Channel component, and finally transferring it to the destination through the Sink component. This process can be used to create complex data pipelines using a Flume topology composed of multiple Agents.
