apache flume data flow
The data flow in Apache Flume involves the movement of data from sources to channels and from channels to sinks. The overall flow can be summarized as follows:
Ingestion: Data is ingested by Flume sources from external sources, such as log files, event streams, or message queues.
Pre-processing: The data may be processed and enriched by Flume interceptors before it is forwarded to the channels. Interceptors can be used to modify, filter, or transform data.
Buffering: The data is then stored in the channels, which serve as a buffer. Channels provide a reliable and fault-tolerant mechanism for storing data before it is sent to the destination.
Routing: The data is routed from the channels to the appropriate sink(s) based on the routing rules defined by the user. Routing rules can be based on various criteria, such as the data source, data type, and content.
Delivery: The data is finally delivered to the destination data store, such as HDFS or HBase, by the Flume sinks. Flume supports multiple sinks that can be used to transfer data to various destinations. The choice of sink depends on the nature of the data and the specific requirements of the use case.
Post-processing: The data may be further processed or analyzed by downstream applications or tools, such as Apache Spark or Apache Hive.