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Big Data with Hadoop Developer Online Training
50.3%
Course Overview
The Big data is nothing more than large volume of data. It has been around for around two decades. Big data is large amount of data owned by a company, obtained and manipulated through some new techniques in order to produce valuable format in the best way possible.
In order to store and process big data an open-source framework Hadoop 3.0 can be used. Hadoop can process big data in a distributed environment across clusters of computers using simple programming models. Hadoop can scale up from single servers to hundreads of machines, each will offer local computation and storage. Our training in Big Data with Hadoop will teach you the concept of Big Data and will practically show how you can use Hadoop framework in distributed environment.
Course Start Dates
| Strat Date | Time | Days | Duration | Location |
Pre-requisites
Target Audience
On-site training for Corporate
Course Content
Big Data with Hadoop Developer
- Explain Hadoop 3.0 and YARN
- Explain how HDFS Federation works in Hadoop 3.0
- Explain the various tools and frameworks in the Hadoop 3.0 ecosystem
- Use the Hadoop cbrent to input data into HDFS
- Using HDFS commands
- Distributed systemsPreview
- Big Data Use Cases
- Explain the architecture of MapReduce
- Run a MapReduce job on Hadoop
- Monitor a MapReduce job
- Write a Pig script to explore and transform data in HDFS
- Define advanced Pig relations
- Use Pig to apply structure to unstructured Big Data
- Invoke a Pig User-Defined Function
- Compute Quantiles with Pig
- Explore data with Pig
- Spbrt a dataset with Pig
- Join datasets with Pig
- UsePig to prepare data for Hive
- Write a Hive query
- Understand how Hive tables are defined and implemented
- Use Hive to run SQL-brke queries to perform data analysis
- Perform a multi-table select in Hive
- Design a proper schema for Hive
- Explain the uses and purpose of HCatalog
- Use HCatalog with Pig and Hive
- Computing ngrams with Hive
- Analyzing Big Data with Hive
- Understanding MapReduce in Hive
- Joining datasets with Hive
- Streaming data with Hive and Python
- Use Sqoop to transfer data between Hadoop and a relational database
- Using Sqoop to transfer data between HDFS and a RDBMS
- Using HCatalog with Pig
- Define a workflow using Oozie
- Hive – Data ETL
- Importing data to Excel
- Using Spark to Analyse the Risk Factor
- Using Pig to Analyse Risk Factor
- Compute Driver Risk Factor
Rajan – :
The course was very useful, covering a wide range of topics and examples for Hadoop. there were plenty of helpful exercises to practice what was learnt throughout the course. the course was flexible allowing you to tailor the course to your specific needs. dr. Raj is very helpful and available for support following the course.