Hadoop Developer Training

Hadoop Developer Training | GroNysa
Hadoop Developer Training | GroNysa

Hadoop Developer training course is designed to provide knowledge and skills to become a successful Hadoop developer, Hadoop administrator, Hadoop testing, and analytics and this is a comprehensive Hadoop Big Data training course designed by industry experts considering current industry job requirements to provide in-depth learning on big data and Hadoop Modules.

In-depth knowledge of concepts i.e. Hadoop Distributed File System, Hadoop Cluster – Single / Multi node, Hadoop 2.x, Flume, Sqoop, Map-Reduce, PIG, Hive, HBase, Spark,Zookeeper, Oozie etc.

 

Training Objectives of Hadoop Developer Training

  • Big Data & Hadoop concepts with HDFS and MapReduce framework& its Architecture
  • Setup Hadoop Cluster and write Complex MapReduce programs
  • Learn data loading / Ingestion techniques using Sqoop, Flume&HBase
  • Perform data analytics using Pig, Hive and YARN and scheduling jobs using Oozie
  • Understand Spark and its Ecosystem&Learn how to work in RDD in Spark
  • Work on a real life Project on Big Data Analytics

Course Information

  • Course Duration : 30 Hours
  • Training Timings : Week days 1-2 Hours per day (or) Weekends: 2-3 Hours per day
  • Training Method : Instructor Led Online Training
  • Study Material : Soft Copy

Prerequisite

As such, there are no pre-requisites for learning Hadoop, Knowledge of Core Java and SQL Basics will be beneficial, but certainly not a mandate.

Market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals.

Here are the few IT Professional, who are continuously enjoying the benefits moving into Big data domain:

  • Developers, Java Programmers and Architects
  • BI /ETL/DW professionals
  • Senior IT Professionals
  • Testing professionals
  • Mainframe professionals
  • Freshers


Course Content

What is Data Warehouse ?

• Data Warehouse Architecture

• Data Warehouse Vs Data Mart

• OLTP Vs OLAP

• Data Modeling
o Relational
o Dimensional
 Star Schema / Snowflake Schema

• Normalization
o Data Normalization
o Data De-Normalization

• Dimension Table
o Categories – Normal & Confirmed Dimension

o Slowly Changing Dimension – Type 1, Type 2 & Type 3

o Level & Hierarchy

• Fact Table
o Categories – Summary / Aggregations table
o Type
o Additive
o Semi-Additive
o Non-Additive

• Real Time Data ware housing – Change Data capture

• What is Business Intelligence?

What is Big Data ?

  • Limitations and Solutions of existing Data Analytics Architecture
  • Hadoop&Hadoop Features
  • Hadoop Ecosystem
  • Hadoop 2.x core components
  • Hadoop Storage: HDFS, Hadoop Processing: MapReduce Framework
  • Anatomy of File Write and Read Awareness
  • Hadoop 2.x Cluster Architecture – Federation and High Availability
  • Hadoop Cluster Modes
  • Common Hadoop Shell Commands
  • Hadoop 2.x Configuration Files
  • Hadoop Job Processes
  • MapReduce Job Execution
  • MapReduce Framework
  • Traditional way Vs MapReduce way
  • Hadoop 2.x MapReduce Architecture&Components
  • YARN Architecture, Components &Workflow
  • Anatomy of MapReduce Program
  • MapReduce Program
  • What is Sqoop ?
  • Sqoop Installations and Basics
  • Importing Data from RDBMS / MySQL to HDFS
  • Exporting Data from HDFS to RDBMS / MySQL
  • Parallelism
  • Importing data from RDBMS / MySQL to Hive
  • What is Flume ?
  • Flume Model and Goals
  • Features of Flume
  • What is Pig ?
  • MapReduce Vs Pig
  • Pig Use Cases
  • Programming Structure in Pig
  • Pig Running Modes
  • Pig Components
  • Pig Execution
  • Pig Data Types
  • Relational &Group Operators, File Loaders, Union &Joins, Diagnostic Operators& UDF
  • What is Hive ?
  • Hive Vs Pig
  • Hive Architecture and Components its Limitations
  • Metastore in Hive
  • Comparison with Traditional Database
  • Hive Data Types, Data Models,Partitions and Buckets
  • Hive Tables (Managed Tables and External Tables)
  • Importing, Querying Data & Managing Outputs
  • Hive Script & UDF
  • HBase Data Model
  • HBase Shell
  • HBase Client API
  • Data Loading Techniques
  • ZooKeeper Data Model
  • Zookeeper Service
  • Zookeeper
  • Data Handling
  • HBase Filters
  • What is Spark?
  • What is Spark Architecture & Components
  • Spark Algorithms-Iterative Algorithms, Graph Analysis, Machine Learning
  • Spark Core
  • Spark Libraries
  • Spark Demo
  • Towards the end of the course, you will work on a LIVE project where you will be using Sqoop, Flume, PIG, HIVE, Hbase, MapReduce& Spark to perform Big Data Analytics
  • You will use the industry-specific Big Data case studies that are included in our Big Data and Hadoop
  • You will gain in-depth experience in working with Hadoop & Big Data
  • Understand your sales pipeline and uncover what can lead to successful sales opportunities and better anticipate performance gap
  • Review product-related information like Cost, Revenue, Price, etc. across Years and Ordering Method. This dataset could also be used in the Explore feature to better understand the hidden trends & patterns
  • Data Sets


Reviews

Amitesh

Enjoyed the learning and the instructor was of great help. Must say SAP BPC training was fruitful and will surely help me in my current job.

SAP BPC

5.0
2017-09-03T10:39:19+00:00

SAP BPC

Enjoyed the learning and the instructor was of great help. Must say SAP BPC training was fruitful and will surely help me in my current job.

Vivek

SAP GTS trainer was really good. He had the command on the subject and explained the concept well. I will surely recommend anyone who want to learn SAP GTS to gronysa.

SAP GTS

5.0
2017-09-04T06:51:45+00:00

SAP GTS

SAP GTS trainer was really good. He had the command on the subject and explained the concept well. I will surely recommend anyone who want to learn SAP GTS to gronysa.
5.0
2


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