Hadoop Training

Intellipaat Big Data Hadoop course helps you master Big Data Hadoop and Spark to get ready for the Cloudera CCA Spark and Hadoop Developer Certification (CCA175) exam as well as master Hadoop Administration with 14 real-time industry-oriented case-study projects. In this Big Data training, you will master MapReduce, Hive, Pig, Sqoop, Oozie and Flume and work with Amazon EC2 for cluster setup, Spark framework and RDD, Scala and Spark SQL, Machine Learning using Spark, Spark Streaming, etc.

It is a comprehensive Hadoop Big Data course designed by industry experts considering current industry job requirements to help you learn Big Data Hadoop and Spark modules. This is an industry-recognized Big Data Hadoop certification course that is a combination of the course in Hadoop developer, Hadoop administrator, Hadoop testing and analytics with Apache Spark. This Cloudera Hadoop and Spark will prepare you to clear Cloudera CCA175 Big Data certification.

Hadoop is Open Source

Hadoop is an open-source project, which means its source code is available free of cost for inspection, modification, and analyses that allows enterprises to modify the code as per their requirements.

Hadoop cluster is Highly Scalable

Hadoop cluster is scalable means we can add any number of nodes (horizontal scalable) or increase the hardware capacity of nodes (vertical scalable) to achieve high computation power. This provides horizontal as well as vertical scalability to the Hadoop framework.

Hadoop provides Fault Tolerance

Fault tolerance is the most important feature of Hadoop. HDFS in Hadoop 2 uses a replication mechanism to provide fault tolerance. It creates a replica of each block on the different machines depending on the replication factor (by default, it is 3). So if any machine in a cluster goes down, data can be accessed from the other machines containing a replica of the same data.

Hadoop provides High Availability

This feature of Hadoop ensures the high availability of the data, even in unfavorable conditions.Due to the fault tolerance feature of Hadoop, if any of the DataNodes goes down, the data is available to the user from different DataNodes containing a copy of the same data.

Hadoop is very Cost-Effective

Since the Hadoop cluster consists of nodes of commodity hardware that are inexpensive, thus provides a cost-effective solution for storing and processing big data. Being an open-source product, Hadoop doesn’t need any license.

Hadoop is Faster in Data Processing

Hadoop stores data in a distributed fashion, which allows data to be processed distributedly on a cluster of nodes. Thus it provides lightning-fast processing capability to the Hadoop framework.

Hadoop is based on Data Locality concept

Hadoop is popularly known for its data locality feature means moving computation logic to the data, rather than moving data to the computation logic. This features of Hadoop reduces the bandwidth utilization in a system.