Logs are the source of stress in most of the companies. Today logs were necessary for many of the companies. Logs were painful to the operations team, as they occupy a large amount of space. There logs were present rarely on the disk. The Big companies usually wing up the log and process it and store in a repository other than disk for effective retrieval to both operations team and developers. This frustrates the both developers and operations team, as they were not present at their current location, to access them at the time of necessary. To overcome this problem, Apache Flume was designed.

Apache Flume:

Apache Flume is a tool designed for efficiently collecting large amounts of streaming data in a Hadoop Distributed File System (HDFS) in a distributed environment. This tool was designed to address the problems of both developers and operations team, by providing a tool, where they can push logs from application servers to various repositories via high configurable agent. A flume agent is responsible for intake of huge amount of data from different resources like Syslog, netcat and JMs . Data passed by a flume agent is passed to a sink using a commonly used distributed file systems like Hadoop. Multiple flume agents were connected together by connecting the source of one agent to the sink of another .

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The Work Flow of flume is depends upon the two components.
1. The master acts like reliable configuration service which is used by nodes for retrieving their configuration
2. The configuration of a particular node is changes dynamically by the master, when the configuration of a node changes.

A node in Hadoop flume is generally a connector, which is responsible for transfer of data between source and sink. The characteristic and role of Flume node is determined by the behavior of Source and sink. If none of the requirements match then, they can define their own by writing the code as per their requirements. A flume node can be configured with the help of Sink detector.

Architecture:

The architecture of flume tool is simple. It contains 3 important roles:

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Source : It is responsible for the data coming into the Queue /File.

Sink:  It is responsible for data out flow of the Queue / File.

Channel: It is responsible for the connection between sources and sinks.

Workflow :    The work Flow of Flume is described with the help of following diagram

Before going to know about the data flow, lets discuss the following concepts:

Log Data :  The  data  will be coming from various data resources like  application servers , cloud Servers and  enterprise servers  need s to be analyzed  . The produced data will be in the form of log file and events.  The data in the log file is known as log data.

 Flume is a framework, which is used to move data into HDFS . In  general , log servers  generates events and logs and  these servers have flume agents running on them. These  Flume agents is responsible  for  receiving of  data from data generators.

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 A  Collector is a intermediate node , where the data   from multiple data sources is collected .  Like  multiple agents, they can be multiple collectors. All the data in collectors will be stored in a centralized store called HDFS.

Features:
  •  It is a tool to scale data in environments with minimum of 5 machines to thousands    of machines.
  •   It is stream oriented, fault tolerant and linearly scalable.
  •   It provides low latency and high through put
  •   It provides the ease of extensibility.
  •  Along with log files, Flume is also used to import data from Social Media sites like  Facebook, Twitter
  •   It intakes the data from multiple sources and stores efficiently.

Recommended Audience :

Software developers

ETL  developers

Project Managers

Team Lead’s

Business Analyst

Prerequisites :   Prerequisite for learning Big Data Hadoop .Its good to have a knowledge on  some  OOPs Concepts . But it is not mandatory . Trainers of  OnlineITGuru  will teach you if you don’t have a knowledge on  those OOPs Concepts

Become a Master in    Flume   from OnlineITGuru Experts  through Big Data Hadoop online  training in Bangalore

 
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