Design and implement a series of Flume agents to send streamed data into Hadoop
Apache Flume is a distributed, reliable, and available service used to efficiently collect, aggregate, and move large amounts of log data. It is used to stream logs from application servers to HDFS for ad hoc analysis.
This book starts with an architectural overview of Flume and its logical components. It explores channels, sinks, and sink processors, followed by sources and channels. By the end of this book, you will be fully equipped to construct a series of Flume agents to dynamically transport your stream data and logs from your systems into Hadoop.
A step-by-step book that guides you through the architecture and components of Flume covering different approaches, which are then pulled together as a real-world, end-to-end use case, gradually going from the simplest to the most advanced features.
What You Will Learn
Understand the Flume architecture, and also how to download and install open source Flume from Apache
Follow along a detailed example of transporting weblogs in Near Real Time (NRT) to Kibana/Elasticsearch and archival in HDFS
Learn tips and tricks for transporting logs and data in your production environment
Understand and configure the Hadoop File System (HDFS) Sink
Use a morphline-backed Sink to feed data into Solr
Create redundant data flows using sink groups
Configure and use various sources to ingest data
Inspect data records and move them between multiple destinations based on payload content
Transform data en-route to Hadoop and monitor your data flows
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