Managing Big Data in Clusters and Cloud Storage

In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need. By the end of the course, you will be able to • use different tools to browse existing databases and tables in big data systems; • use different tools to explore files in distributed big data filesystems and cloud storage; • create and manage big data databases and tables using Apache Hive and Apache Impala; and • describe and choose among different data types and file formats for big data systems. To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

• Orientation to Data in Clusters and Cloud Storage
• Defining Databases, Tables, and Columns
• Data Types and File Types
• Managing Datasets in Clusters and Cloud Storage
• Optimizing Hive and Impala (Honors)
• Honors (Optional)