Introduction To Apache Flume

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Introduction To Apache Flume

 

What is Flume?

Apache Flume is a tool/service/data ingestion mechanism for collecting aggregating and transporting large amounts of streaming data such as log files, events (etc...) from various sources to a centralized data store.

Flume is a highly reliable, distributed, and configurable tool. It is principally designed to copy streaming data (log data) from various web servers to HDFS.

Assume an e-commerce web application wants to analyze the customer behavior from a particular region. To do so, they would need to move the available log data into Hadoop for analysis. Here, Apache Flume comes to our rescue.

Flume is used to move the log data generated by application servers into HDFS at a higher speed.

Advantages of Flume:-

·       Using Apache Flume we can store the data into any of the centralized stores (HBase, HDFS).

·        When the rate of incoming data exceeds the rate at which data can be written to the destination, Flume acts as a mediator between data producers and the centralized stores and provides a steady flow of data between them.

·        Flume provides the feature of contextual routing.

·        The transactions in Flume are channel-based where two transactions (one sender and one receiver) are maintained for each message. It guarantees reliable message delivery.

·  Flume is reliable, fault tolerant, scalable, manageable, and customizable.

Features of Flume:-

·        Flume ingests log data from multiple web servers into a centralized store (HDFS, HBase) efficiently.

·        Using Flume, we can get the data from multiple servers immediately into Hadoop.

·        Along with the log files, Flume is also used to import huge volumes of event data produced by social networking sites like Facebook and Twitter, and e-commerce websites like Amazon and Flipkart.

·        Flume supports a large set of sources and destinations types.

·  Flume supports multi-hop flows, fan-in fan-out flows, contextual routing, etc.

·        Flume can be scaled horizontally.