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Flume Data Flow Model
Apache Flume is a distributed system for collecting and moving large amounts of streaming data from various sources to a centralized data store like HDFS or HBase. Flume has a flexible and reliable data flow model that allows different types of flows such as multi-hop, fan-in and fan-out. In this blog post, we will explain what these flows are and how they work in Flume.
Multi-hop flow: A multi-hop flow is a data flow where events travel through multiple agents before reaching the final destination. For example, you can have a web server that sends events to a Flume agent on the same machine, which then forwards them to another Flume agent on a different machine, which then writes them to HDFS. This way, you can create complex pipelines of data processing and aggregation using Flume.
Fan-in flow: A fan-in flow is a data flow where events from multiple sources are transferred through one channel to a single sink. For example, you can have multiple web servers that send events to a single Flume agent, which then writes them to HDFS. This way, you can consolidate data from different sources into one place using Flume.
Fan-out flow: A fan-out flow is a data flow where events from one source are transferred to multiple channels or sinks. For example, you can have one web server that sends events to a Flume agent, which then replicates them to multiple channels or multiplexes them based on some criteria. This way, you can distribute data to different destinations or perform selective filtering using Flume.
Conclusion: Apache Flume provides a powerful and flexible data flow model that supports various types of flows such as multi-hop, fan-in and fan-out. These flows enable users to create scalable and reliable data pipelines using Flume.
FAQs:
Q: What is the difference between replicating and multiplexing in fan-out flow?
A: Replicating means sending the same event to all the configured channels or sinks. Multiplexing means sending the event only to selected channels or sinks based on some information in the event header.
Q: How does Flume handle failures in data flow?
A: Flume uses transactions to ensure reliable delivery of events across agents and sinks. Each event has two transactions: one at the sender side and one at the receiver side. The event is removed from the sender channel only after it is successfully stored in the receiver channel or sink.
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