Tag: about Hadoop online training

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Hadoop Online Training Institute In Hyderabad

Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

This brief tutorial provides a quick introduction to Big Data, MapReduce algorithm, and Hadoop Distributed File System.

Audience

This tutorial has been prepared for professionals aspiring to learn the basics of Big Data Analytics using Hadoop Framework and become a Hadoop Developer. Software Professionals, Analytics Professionals, and ETL developers are the key beneficiaries of this course.

Prerequisites

Before you start proceeding with this tutorial, we assume that you have prior exposure to Core Java, database concepts, and any of the Linux operating system flavors.

Future Q Technologies recognized as No.1 Hadoop Training Center in Hyderabad

We are providing Hadoop Online Training in Hyderabad. We are one of best Institute to provide Best High Quality Hadoop online training all over India. If you are staying in Hyderabad, Bangalore, Chennai, Pune, Delhi, USA, UK, Australia, and Singapore etc. and unable to attend regular class room training programs then contact our training institute for information on online training.

For more details on Hadoop Online Training please call to +91 9581111796 / 9581111896, or drop a mail to: online@futureqtech.com

 

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Big Data Hadoop Certification Training in Hyderabad, India

What skills will you learn with our Big Data Hadoop Certification Training?

Big Data Hadoop training in Hyderabad will enable you to master the concepts of the Hadoop framework and its deployment in a cluster environment. You will learn to:

Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark with this Hadoop course.

  • Understand Hadoop Distributed File System (HDFS) and YARN architecture, and learn how to work with them for storage and resource management
  • Understand MapReduce and its characteristics and assimilate advanced MapReduce concepts
  • Ingest data using Sqoop and Flume
  • Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
  • Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
  • Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
  • Understand and work with HBase, its architecture and data storage, and learn the difference between HBase and RDBMS
  • Gain a working knowledge of Pig and its components
  • Do functional programming in Spark, and implement and build Spark applications
  • Understand resilient distribution datasets (RDD) in detail
  • Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
  • Understand the common use cases of Spark and various interactive algorithms
  • Learn Spark SQL, creating, transforming, and querying data frames
  • Prepare for Cloudera CCA175 Big Data certification