apache flume introduction

Apache Flume is a distributed, reliable, and scalable system for collecting, aggregating, and moving large amounts of data from various sources to centralized data stores, such as Hadoop Distributed File System (HDFS), HBase, and Apache Solr.

Flume is designed to handle data streaming scenarios in which data needs to be collected continuously and moved to a centralized data store in a reliable and fault-tolerant manner. It achieves this by providing a flexible and extensible architecture that allows users to build custom data ingestion pipelines that fit their specific requirements.

Flume consists of three main components:

  1. Sources: A source is responsible for ingesting data from external sources and forwarding it to Flume channels. Flume provides a number of built-in sources, including HTTP, syslog, and netcat, as well as custom sources that can be developed using the Flume SDK.

  2. Channels: A channel is a buffer that stores incoming data before it is forwarded to the sinks. Flume supports different types of channels, such as memory channels and file channels, which provide different levels of durability and throughput.

  3. Sinks: A sink is responsible for delivering data from the channels to the destination data store. Flume provides a number of built-in sinks, including HDFS sink, HBase sink, and Solr sink, as well as custom sinks that can be developed using the Flume SDK.

Flume also provides a flexible and robust event routing mechanism that allows users to define complex routing rules for data flow within their data pipelines. This allows users to route data to different sinks based on various criteria, such as the data source, data type, and content.