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If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this book shows you how Apache HBase can fulfill your needs. As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Many IT executives are asking pointed questions about HBase. This book provides meaningful answers, whether you’re evaluating this non-relational database or planning to put it into practice right away.

  • Discover how tight integration with Hadoop makes scalability with HBase easier
  • Distribute large datasets across an inexpensive cluster of commodity servers
  • Access HBase with native Java clients, or with gateway servers providing REST, Avro, or Thrift APIs
  • Get details on HBase’s architecture, including the storage format, write-ahead log, background processes, and more
  • Integrate HBase with Hadoop's MapReduce framework for massively parallelized data processing jobs
  • Learn how to tune clusters, design schemas, copy tables, import bulk data, decommission nodes, and many other tasks

 About the Author

Lars George has been involved with Hadoop and HBase since 2007 and became a full HBase committer in 2009. He has spoken at many Hadoop User Group meetings and conferences such as ApacheCon, FOSDEM, QCon, or Hadoop World and Hadoop Summit. He also started the Munich OpenHUG meetings. Lars worked for Cloudera, as the EMEA Chief Architect, acting as a liaison between the Cloudera professional services team and customers as well as partners in and around Europe, building the next data driven solutions. Starting 2016 he is a co-founding partner of OpenCore, a Hadoop and emerging data technologies advisory firm
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