Apache Hadoop is the most popular and powerful big data
tool. Hadoop provides the world's most reliable storage layer HDFS, a batch
engine MapReduce and a resource
management layer YARN . Some of the most
important features that make this tool the most suitable for processing large
volumes of data are:
Open source : Apache Hadoop is an open source project. It
means that your code can be modified according to the business requirements.
Distributed processing : As data is stored distributed in
HDFS throughout the cluster, the data is processed in parallel in a cluster of
nodes.
Fault tolerance : This is one of the most important features
of Hadoop. By default, 3 replicas of each block are stored in the cluster in
Hadoop and can also be changed according to the requirement. Then, if any node
falls, the data from that node can be easily retrieved from other nodes with
the help of this feature. Nodes or tasks failures are automatically recovered
by the framework. This is how Hadoop is fault tolerant.
Reliability : Due to the replication of data in the cluster,
data is stored reliably in the machine cluster despite machine failures. If
your machine shuts down, your data will also be stored reliably due to this
feature of Hadoop.
High availability : The data is highly available and
accessible despite hardware failure due to multiple copies of the data. If a
machine or some hardware fails, the data can be accessed from another route.
Scalability : Hadoop is highly scalable in the way you can
easily add new hardware to the nodes. This feature of Hadoop also provides
horizontal scalability, which means that new nodes can be added on the fly
without any downtime.
Economy : Apache Hadoop is not very expensive, since it runs
on a group of basic hardware. We do not need any specialized machine for this.
Hadoop also offers great cost savings, as it is very easy to add more nodes on
the fly. Therefore, if the requirement increases, you can also increase the
nodes without any downtime and without requiring much prior planning.
Easy to use : Without the need for the client to deal with
distributed computing, the framework takes care of everything. So this feature
of Hadoop is easy to use.
Data location : This is a unique feature of Hadoop that made
it easy to handle Big Data. Hadoop works with the principle of data locality
that states that calculations move to data instead of data to calculations.
When a client sends the MapReduce algorithm, this algorithm moves to the data
in the cluster instead of taking the data to the location where the algorithm
is sent and then processing them.
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