Hadoop Backup and Recovery Solutions
Hadoop offers distributed processing of large datasets across clusters and is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. It enables computing solutions that are scalable, cost-effective, flexible, and fault tolerant to back up very large data sets from hardware failures.
Starting off with the basics of Hadoop administration, this book becomes increasingly exciting with the best strategies of backing up distributed storage databases.
You will gradually learn about the backup and recovery principles, discover the common failure points in Hadoop, and facts about backing up Hive metadata. A deep dive into the interesting world of Apache HBase will show you different ways of backing up data and will compare them. Going forward, you'll learn the methods of defining recovery strategies for various causes of failures, failover recoveries, corruption, working drives, and metadata. Also covered are the concepts of Hadoop matrix and MapReduce. Finally, you'll explore troubleshooting strategies and techniques to resolve failures.
|Course Length||6 hours 10 minutes|
|Date Of Publication||27 Jul 2015|
|Understanding the backup and recovery philosophies|
|Knowing the necessity of backing up Hadoop|
|Determining backup areas – what should I back up?|
|Is taking backup enough?|