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How can you get your data from frontend servers to Hadoop in near real time? With this complete reference guide, you'll learn Flume's rich set of features for collecting, aggregating, and writing large amounts of streaming data to the Hadoop Distributed File System (HDFS), Apache HBase, SolrCloud, Elastic Search, and other systems.
Using Flume shows operations engineers how to configure, deploy, and monitor a Flume cluster, and teaches developers how to write Flume plugins and custom components for their specific use-cases. You'll learn about Flume's design and implementation, as well as various features that make it highly scalable, flexible, and reliable. Code examples and exercises are available on GitHub.
Hari Shreedharan is a PMC Member and Committer on the Apache Flume Project. As a PMC member, he is involved in making decisions on the direction of the project. Hari is also a Software Engineer at Cloudera where he works on Apache Flume and Apache Sqoop. He also ensures that customers can successfully deploy and manage Flume and Sqoop on their clusters, by helping them resolve any issues they are facing. Hari completed his Bachelors from Malaviya National Institute of Technology, Jaipur, India and his Masters in Computer Science from Cornell University in 2010.
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Take 20% off your first order
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