Big data and Hadoop framework

Name: Big data and Hadoop framework
Rating: 4.0 (510 reviews)

Big data applications, Hadoop Architecture , Data lake, data science and scientist, Demo

Last updated 6/2018

English

What you'll learn

2 sections • 14 lectures • 1h 12m total length

Big data Introduction5:33
1.2 Big data history5:33
1.3 Big data technologies3:14
1.4 Big data characteristics5:33
Explore the five big data characteristics—volume, velocity, variety, veracity, and value—and how cognitive big data, advanced analytics, and cloud computing enable real-time, contextual insights.
1.5 Big data Applications5:46
1.6 Data Lake4:43
Discover how a data lake acts as a centralized, scalable store for all data types, enabling dashboards, analytics, and machine learning with Hadoop and Spark.
1.7 Data science and Data scientist7:39

2.1 - Hadoop introduction6:17
Discover how the Hadoop open source framework stores and processes big data in distributed clusters, using a scalable distributed file system and the MapReduce processing model.
2.2 - HDFS-Overview6:20
2.3 - Hadoop Architecture
Explore the Hadoop architecture, including the master–slave NameNode and DataNodes, HDFS storage, and MapReduce with YARN for resource management and fault tolerance.
2.3a - Hadoop Architecture - assumptions and goals3:34
2.4 - Demo-Hadoop install - sw download verify integrity5:23
2.5 - Demo-Hadoop install - Java ssh configure5:56
Install and configure Hadoop by verifying the release, setting JAVA_HOME and HADOOP_HOME, enabling SSH passwordless login, and starting a standalone or pseudo-distributed cluster.
2.6 Demo hadoop access by browser6:35
Access Hadoop

FileSystem Java API and REST API.
HTTP browser and can also be used to browse the files of a HDFS instance.
HDFS can be mounted as part of the client’s local file system.
The NameNode and DataNode are pieces of software designed to run on
commodity machines. These machines typically run a GNU/Linux operating
system (OS).
File System (FS) Shell CLI to interact with the data in HDFS.
HDFS can be deployed on a wide range of machines.
A dedicated machine may run NameNode software and other nodes in the cluster runs an instance of the DataNode software.
The NameNode is the controller and repository for all HDFS metadata.

Basic computer knowledge, a bit of Java, database concepts and Linux operating system.

This course is focusing on Big data and Hadoop technologies, hands on demos,

Section 1 - Big data

1.1 Big data introduction

1.2 Big data history

1.3 Big data technologies

1.4 Big data characteristics

1.5 Big data Applications

1.6 Data Lake

1.7 Data Science and Data scientist

Section 2 - Hadoop

2.1 - Hadoop introduction

2.2 - HDFS-Overview

2.3 - Hadoop Architecture

2.3a - Hadoop Architecture - assumptions and goals

2.4 - Demo-Hadoop install - sw download verify integrity

2.5 - Demo-Hadoop install - Java ssh configure

2.6 - Demo hadoop access by browser

Anyone who is interested in learning Big data, Data analytics and Hadoop Framework