Using Flume: Flexible, Scalable, and Reliable Data Streaming

Using Flume: Flexible, Scalable, and Reliable Data Streaming

<div><p>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.</p><p><i>Using Flume</i> 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.</p><ul><li>Learn how Flume provides a steady rate of flow by acting as a buffer between data producers and consumers</li><li>Dive into key Flume components, including sources that accept data and sinks that write and deliver it</li><li>Write custom plugins to customize the way Flume receives, modifies, formats, and writes data</li><li>Explore APIs for sending data to Flume agents from your own applications</li><li>Plan and deploy Flume in a scalable and flexible way€"and monitor your cluster once it€s running</li></ul></div>