Big data,Cassandra,AWS,Mysql,MariaDB,Linux for Beginners

Name: Big data,Cassandra,AWS,Mysql,MariaDB,Linux for Beginners
Rating: 3.6 (34 reviews)

Hands on experience for MySQL,MariaDB,Cassandra,Nosql and Big data ( Hadoop ) on AWS cloud and advance your career.

Created byTheo W.

Last updated 8/2016

English

What you'll learn

Learn about AWS | Amazon Elastic Compute Cloud (EC2), Security group, launch instance, access to it
Learn about basic MySQL and NoSQL(Cassandra) syntax
Learn about how to create one of the leading NoSQL DB, Cassandra cluster on AWS
Learn about High Available MySQL cluster with NDB engine
Learn about how to create MariaDB Galera cluster for true master-master , fault tolerant RDBMS on AWS
Learn about how to create instances( for databases) on different available zones on a cloud for true fault tolerant
Learn about how to connect between MariaDB(RDBMS) with Cassandra(NoSQL) storage
Learn about how to load balance for database servers
Learn about how to create a Hadoop cluster and do map-reduce jobs

Course content

7 sections • 38 lectures • 3h 56m total length

Introduction8:24

Create a MariaDB Galera Cluster with three Ubuntu servers 1st part8:08
Create a MariaDB Galera Cluster with three Ubuntu servers 2nd part6:51
Hands on experience Lab 3
Create AWS VPC Peering connection. Five steps( step 1,2,3)9:45
Create AWS VPC Peering connection. Five steps( step 4,5)10:05
Learn to create AWS VPC peering connections across VPCs, grant permissions, accept requests, and update route tables with VPC IDs and IP ranges in steps 4 and 5.
Create a MGC on different availability zones for a true fault tolerance-(A)10:49
Create a MGC on different availability zones for a true fault tolerance-(B)9:59
Secure AWS instance access4:05
Secure AWS instance access by restricting ssh to your ip via security group rules. Find your ip, add it to the ssh rule, and enable access only when needed.
Hands on experience Lab 4
Connect between MariaDB and Cassandra14:04

Create a Mysql Cluster with 4 machines on the cloud on AWS 1st part (Management)9:03
Create a four-machine MySQL cluster on AWS, focusing on management, security groups, port configuration, and setting up cluster members and API clients for communication.
Create a Mysql Cluster with 4 machines on the cloud on AWS 2nd part( Data nodes)4:37
Create a Mysql Cluster with 4 machines on the cloud on AWS 3rd (sql node)8:21
Hands on experience Lab 6
MySQL : Create a database5:35
Learn how to create a database in MySQL with the NDB cluster engine, switch to the database, and access, update, and query tables using basic SQL commands.
MySQL : Create a Table4:26
MySQL : Describe a table1:51
MySQL : Pattern matching1:17
MySQL : Insert Data, Retrieve Data, Check tables9:05
Learn how to insert and retrieve data in MySQL, define primary keys with auto_increment, set defaults, and inspect tables using describe and show columns in a car dealer example.
MySQL : Comparison Operators & logical operators3:02
MySQL : Order By1:22
MySQL : Limit By1:00
MySQL : Distinct, Count, Name As2:00
MySQL : Update a row and Delete a row1:55
MySQL : Rename a Table1:01
MySQL : Drop a table0:26
MySQL : Drop a database0:49

Create a Single Node Hadoop Cluster part 111:45
Create a Single Node Hadoop Cluster part 210:51
Set up a single-node Hadoop cluster by generating and securing SSH keys, configuring environments, starting Hadoop, creating HDFS directories, and verifying the name node status in the browser.
Create a Single Node Hadoop Cluster part 3 And run a map reduce job14:00
Create a single node Hadoop cluster and run a MapReduce job to count word occurrences in a book, transferring files from local to a server and displaying results.
Hands on experience Lab 7

Requirements

A passion to learn
A passion to advance your career
A passion for success
Need Internet access since most of these classes will be deployed on AWS
A computer/Laptop with any OS (Windows, Ubuntu, Mac OS, etc)

Description

By 2020, there will be a lot of shortage for data scientists and analytic professionals. The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise. This course gives you what you need to get started for data scientists, system administrator, devOps. You will be able to create MySQL cluster that uses ndb storage engine, create MariaDB Galera cluster, create Cassandra cluster, and also you will be able to create a hadoop cluster. You will be able to load balance for your databases using Ha-proxy. You will be able to deploy all of these on AWS cloud with Amazon Elastic Compute Cloud (EC2). You will get reinforced by hands on experience with an assignemt on every section. Furthermore, you will also be able to map between MariaDB with Cassandra, so you can use both RDBMS and NoSQL all together for your needs. You can advance your career with this course, save thousands of dollars that you spend otherwise, and make it easier to land a job.

Who this course is for:

Anyone new to database
Anyone who would like to become a Web developer, Database developer, System Administrator
Anyone who doesn't have enough time, but want to learn practical things by doing it
This is for anyone who haven't had any experience, but would like to get started for various databases and hands on experience with them
If you / your company wants to know about what databases out on the market and would like to try and save a lot of time with these videos

Big data,Cassandra,AWS,Mysql,MariaDB,Linux for Beginners

What you'll learn

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Course content

Course Introduction1 lecture • 8min

AWS(Amazon Web Services) EC2 . AWS account, instance, access4 lectures • 14min

Create a Cassandra cluster on commodity hardwares for scalability3 lectures • 25min

MariaDB Galera Cluster8 lectures • 1hr 14min

Haproxy (High available proxy ) load balance3 lectures • 23min

Mysql cluster16 lectures • 56min

Hadoop Single node cluster3 lectures • 37min

Requirements

Description

Who this course is for: