Hadoop is the first public made available open-source in 2011. Hadoop has undergone various changes in three different versions. In this blog, we have focused mainly on the Features and Enhancement in the new Hadoop 3.0. Its release is predicted to be successful in mid-2018. Hadoop Training in Chennai is the best place to make you magnify your skill and knowledge over Hadoop.
What is more in the new version of the tiny toy?
The scope of Apache Hadoop 3 has overcome the previous version with thousands of features and enhancement, new bug fixes. The features sneak peek to boost the enterprise by making it flexible and powerful. Hadoop 3 is the best version.
Why Hadoop 3?
As Java 7 ended its life in 2017, revising of Java 8 was mandatory along with Hadoop release so that it would support security fixes with Oracle. Hadoop 2.0 was difficult for developers to handle shell script. When compared to Hadoop 3.0, the previous versions of Hadoop didn’t reach the maximum level of fault tolerance as it offers multiple NameNodes.
What’s brand new in Hadoop 3.0?
Listed below are the new features in Hadoop 3.0
- Support for Erasure Coding in HDFS
In the upcoming years, Hadoop 3 will play an important role in data and datacenter hardware for erasure in coding. Erasure Coding which is a 50-year-old technique to recover data stored in metadata. It is likely an advanced RAID technique when a hard disk fails. With the support of this Hadoop 3, the disk usage will be half cut. This new feature will save Hadoop developers to reduce the size of Hadoop cluster to half and store double the amount of data. - MapReduce Task Level Native Optimization
The next new feature is the implementation of the map helping to improve the performance of shuffle intensive jobs. - Hadoop 3.0 the More Powerful YARN
The next feature is the way YARN works and support. It was introduced in Hadoop 2 to make clusters efficiently. At the same time in Hadoop 3 it is coming with multiple enhancements in the following areas:
Hadoop 3.0 would manage resources and services from beyond the scope of a Hadoop Cluster
It supports long-running services to consolidate infrastructure - Minimum Runtime Version for Hadoop 3.0 is JDK 8
Hadoop 3.0 has upgraded its version to support Java 8. As a Hadoop user, start to improve the JDK 8 to make the improvement more flexible in Hadoop 3.0. - Addition of new default ports & the change in Default Ports
To avoid bind errors in other applications the default ports DataNode, NameNode, KMS, and Secondary NameNode has been moved to Linux. The new feature has been introduced to magnify the reliability of large Hadoop clusters. - Support for Multiple NameNodes to maximize Fault Tolerance
To run with high configure levels this feature supports business-critical deployments. In Hadoop 2.0 fault tolerance was limited by a single active NameNode, whereas in 3.0 it has been addressed to enhance the fault tolerance in HDFS. Big Data Hadoop Training Online will make you clear with all the features in Hadoop 3.0. - Hadoop Shell Script Rewrite
The shell scripts in Hadoop are rewritten in Hadoop 3.0. This is to address the standing bugs and to enhance the functionality and documentation. This is mainly to make difference for Hadoop users. Big Data Training in Bangalorewill help you to learn the features of big data.
The introduction to the features and enhancement in Hadoop 3.0 has made the tech world to turn to it. Enroll with FITA Academy for Big Data Hadoop Training Chennai!