Analyze Big Data with Hadoop
SPL-166 - Version 1.0.7
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Amazon EMR is a managed service that makes it fast, easy, and cost-effective to run Apache Hadoop and Spark to process vast amounts of data. Amazon EMR also supports powerful and proven Hadoop tools such as Presto, Hive, Pig, HBase, and more.
In this lab, you will deploy a fully functional Hadoop cluster, ready to analyze log data in just a few minutes. You will start by launching an Amazon EMR cluster and then use a HiveQL script to process sample log data stored in an Amazon S3 bucket. HiveQL is a SQL-like scripting language for data warehousing and analysis. You can then use a similar setup to analyze your own log files.
This lab is based on the Analyze Big Data with Hadoop project.
By the end of this lab, you will be able to:
- Launch a fully functional Hadoop cluster using Amazon EMR
- Define the schema and create a table for sample log data stored in Amazon S3
- Analyze the data using a HiveQL script and write the results back to Amazon S3
- Download and view the results on your computer
- IT Experience: Prior experience with Hadoop is recommended, but not required, to complete this lab
- AWS Experience: Basic familiarity with Amazon S3 and Amazon EC2 key pairs is suggested, but not required, to complete this project
The lab will take approximately 20 minutes to complete.
- At the top of your screen, launch your lab by clicking
This will start the process of provisioning your lab resources. An estimated amount of time to provision your lab resources will be displayed. You must wait for your resources to be provisioned before continuing.
If you are prompted for a token, use the one distributed to you (or credits you have purchased).
- Open your lab by clicking
This will automatically log you into the AWS Management Console.
Please do not change the Region unless instructed.
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You should now be able to access the AWS Management Console.
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