Hadoop Online Training
Learn Hadoop online Training, proexcellency covers basic to advance level Hadoop training like Hadoop is an open-source framework that is utilized to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data. Instead of using one large computer to store and process the data, Hadoop offers clustering multiple computers to analyze massive datasets in parallel more quickly.
Proexcellency Teach you four main modules in Hadoop Online training:
Hadoop Distributed File System (HDFS) – A distributed file system that runs on
standard or low-end hardware. HDFS offers better data throughput than traditional
file systems, in addition to high fault tolerance and native support of large datasets.
Yet Another Resource Negotiator (YARN) – Controls and monitors cluster nodes and
resource usage. It schedules jobs and tasks.
MapReduce – A framework that enables programs do the parallel computation on
data. The map task takes input data and changes it into a dataset that can be
computed in key value pairs. The output of the map task is consumed by minimize
tasks to aggregate output and give the desired result.
Hadoop Common – Offers common Java libraries that can be used across all
modules.
How Hadoop Works
Hadoop makes it easier to utilize all the storage and processing capacity in mass
servers, and to execute distributed processes against huge amounts of data. Hadoop
offers the building blocks on which other services and applications can be built.
Applications that collect data in several formats can place data into the Hadoop
cluster by utilizing an API operation to connect to the NameNode. The NameNode
records the file directory structure and placement of “chunks” for each file,
duplicated across DataNodes.
The Hadoop ecosystem has grown remarkably over the years due to its extensibility.
Today, the Hadoop ecosystem includes many tools and applications to enable
collect, store, process, analyze, and manage big data.
Prerequisites: No prerequisites required but if you have basic understanding of Core Java and SQL it is an advantage.
Salary Package:
Hadoop Developer salary in India ranges between ₹ 3.6 Lakhs to ₹ 11.0 Lakhs per
annum.
An average Hadoop Developer salary is approximately of ₹ 5.5 Lakhs per annum.
Hadoop Developer salary in India with less than 2 years of experience to 6 years
ranges from ₹ 3.6 Lakhs to ₹ 11 Lakhs per annum.
CAREER:
The requirement for Big Data professionals is increasing with an advent of time. The
technology is already creating ample job opportunities for professionals. Below are the
individuals to whom Hadoop will be an added advantage.
Testing professionals
Mainframe professionals
Developers and Architects
Senior IT professionals
The ability to access, analyze and use humungous volumes of data through specific
technology is what is required by almost every organization. The Big Data job market is
growing at a robust pace and Hadoop provides lucrative job opportunities for an aspiring data scientist.
Proexcellency Teach you four main modules in Hadoop Online training:
Hadoop Distributed File System (HDFS) – A distributed file system that runs on
standard or low-end hardware. HDFS offers better data throughput than traditional
file systems, in addition to high fault tolerance and native support of large datasets.
Yet Another Resource Negotiator (YARN) – Controls and monitors cluster nodes and
resource usage. It schedules jobs and tasks.
MapReduce – A framework that enables programs do the parallel computation on
data. The map task takes input data and changes it into a dataset that can be
computed in key value pairs. The output of the map task is consumed by minimize
tasks to aggregate output and give the desired result.
Hadoop Common – Offers common Java libraries that can be used across all
modules.
How Hadoop Works
Hadoop makes it easier to utilize all the storage and processing capacity in mass
servers, and to execute distributed processes against huge amounts of data. Hadoop
offers the building blocks on which other services and applications can be built.
Applications that collect data in several formats can place data into the Hadoop
cluster by utilizing an API operation to connect to the NameNode. The NameNode
records the file directory structure and placement of “chunks” for each file,
duplicated across DataNodes.
The Hadoop ecosystem has grown remarkably over the years due to its extensibility.
Today, the Hadoop ecosystem includes many tools and applications to enable
collect, store, process, analyze, and manage big data.
Prerequisites: No prerequisites required but if you have basic understanding of Core Java and SQL it is an advantage.
Salary Package:
Hadoop Developer salary in India ranges between ₹ 3.6 Lakhs to ₹ 11.0 Lakhs per
annum.
An average Hadoop Developer salary is approximately of ₹ 5.5 Lakhs per annum.
Hadoop Developer salary in India with less than 2 years of experience to 6 years
ranges from ₹ 3.6 Lakhs to ₹ 11 Lakhs per annum.
CAREER:
The requirement for Big Data professionals is increasing with an advent of time. The
technology is already creating ample job opportunities for professionals. Below are the
individuals to whom Hadoop will be an added advantage.
Testing professionals
Mainframe professionals
Developers and Architects
Senior IT professionals
The ability to access, analyze and use humungous volumes of data through specific
technology is what is required by almost every organization. The Big Data job market is
growing at a robust pace and Hadoop provides lucrative job opportunities for an aspiring data scientist.
Duration
Duration
30-35 hrs