Duration
5 days
Overview
In this Big Data analytics training participants will gain practical skill set on Hadoop in detail, including its core and ecosystem components and targeting the data extraction and analysis process. This course focuses on case study approach for learning various tools and completely industry relevant training and a great blend of analytics and technology. After the completion of this course, you will be able to:
- Knowing Hadoop Storage
- Drawing BigData ideas using Hadoop
- Work on the concepts of HDFS and MapReduce framework.
- Learn data loading techniques
- Integration os Spark wnd SCALA
- Peform Spark queries and data generation.
- Perform data analytics using Spark
- Implement Spark SQL queries to perform several computations.
Target Audience
Individuals from both IT and non IT who want to understand the Hadoop system and frameworks for data extraction and analysis with concept unerstanding of Hadoop ecosystem, and use it to store, analyze, and data at scale.
Prerequisites
All participants must be familiar with Windows / Linux command line will be very helpful.
Course Outline
Introduction and Understanding Big Data
- What is Big Data
- Definition
- The Network System and Tick Bandwidth
- LAN and WAN Data flow
- Data packet and block
- Server Clustering
The Hadoop & Ecosystem Installation
- Install Hadoop
- Hadoop Overview and History
- The Ecosystem
Hadoop core components- HDFS
- HDFS: What it is, and how it works
- Install the Sample dataset into HDFS using the UI
- Install the Sample dataset into HDFS using the command line.
Hadoop core components- Mapreduce (YARN)
- MapReduce: What it is, and how it works
- How MapReduce distributes processing
Hadoop Data Analysis Tools: Hadoop Spark and SCALA
- Why Spark?
- Why Spark with SCALA ?
- Installation and commissioning of Spark and SCALA
- The Spark and SCALA
- Function
- Type Class
- Pattern Matching
- Functional Programming
- Build-in Effects
- Working with the Spark APIs
- The Resilient Distributed Dataset (RDD)?
- Working with Dataframe
- Dataset and Spark
- SparkSQL
- Processing Streaming Data
- ETL and ELT processing
Programme scope, delivery arrangements and suitability are confirmed during enquiry.