Working with Amazon Redshift
SPL-17 Version 4.2.3
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This lab provides an overview of Amazon Redshift. In this lab, you will launch and work with an Amazon Redshift cluster to analyze USA Domestic flight data.
Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
Amazon Redshift delivers fast query and I/O performance for virtually any size dataset by using columnar storage technology and parallelizing and distributing queries across multiple nodes. We’ve made Amazon Redshift easy to use by automating most of the common administrative tasks associated with provisioning, configuring, monitoring, backing up, and securing a data warehouse.
By the end of this lab, you will be able to:
- Launch an Amazon Redshift cluster
- Connect to Amazon Redshift by using SQL client software
- Load data from Amazon S3 into Amazon Redshift
- Query data from Amazon Redshift
- Monitor Amazon Redshift performance
To successfully complete this lab, you should be familiar with basic concepts of databases and SQL.
Notice the lab properties below the lab title:
- setup - The estimated time to set up the lab environment
- access - The time the lab will run before automatically shutting down
- completion - The estimated time the lab should take to complete
- At the top of your screen, launch your lab by clicking
If you are prompted for a token, use the one distributed to you (or credits you have purchased).
A status bar shows the progress of the lab environment creation process. The AWS Management Console is accessible during lab resource creation, but your AWS resources may not be fully available until the process is complete.
- Open your lab by clicking
This will automatically log you into the AWS Management Console.
Please do not change the Region unless instructed.
Common login errors
Error : Federated login credentials
If you see this message:
- Close the browser tab to return to your initial lab window
- Wait a few seconds
- Click again
You should now be able to access the AWS Management Console.
Error: You must first log out
If you see the message, You must first log out before logging into a different AWS account:
- Click click here
- Close your browser tab to return to your initial Qwiklabs window
- Click again
Task 1: Launch your Amazon Redshift Cluster
You will now launch an Amazon Redshift cluster, which starts your very own database for use in this lab.
- Wait until the lab status at the top of this page shows Lab Running.
This indicates that required resources are available for your lab.
In the AWS Management Console, on the Services menu, click Amazon Redshift.
Click Launch cluster.
Configure the following settings:
- Cluster identifier:
- Database name:
- Database port:
- Master user name:
- Master user password:
- Confirm password: Enter the same password again
For Node type, select dc2.large.
This lab uses the dc2.large node size, which has 160GB of storage per node. You will be using a single node for this lab, but the type and number of nodes in a Redshift cluster can be changed at any time to provide extra storage and faster data processing.
- Click Continue.
You wll be presented with a configuration page.
- Configure the following, leaving other settings at their default value:
- Choose a VPC: Select the VPC that is not the Default VPC
- VPC security groups: Redshift Security Group
- Available IAM roles: Redshift-Role
If you cannot see the Redshift Security Group, confirm that you have changed the VPC.
These settings define the network and security configurations for the Redshift cluster.
Review the settings, then click Launch cluster (you might need to scroll down to see it).
In the left navigation pane, click Clusters to view your Clusters.
Click the lab link to view your cluster details.
Your cluster can take up to 5 minutes to launch.
While you are waiting, please continue reading the next section.
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